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You have a stockpile of data from a cloud data platform like Snowflake. Now, you’re ready to drive personalized marketing for your customers. But how do you translate the data from your CDW into actionable campaigns? Simple: with a CDP.

There are multiple ways companies use CDPs. Some install a packaged CDP and integrate their Snowflake data into the CDP, while others employ a composable CDP approach — essentially bringing the CDP to Snowflake. 

Companies can also choose a two-pronged approach with a reverse-ETL tool for data management, and then employ a campaign or marketing-focused CDP for activation. What's right for a given organization depends on factors we can use this article to explain.

But with 76% of customers preferring brands that personalize their marketing, you’ll be expected to segment diverse audiences and run complex omnichannel campaigns to meet these demands. The world is increasingly data-driven, and content delivery platforms can help us turn data into actionable insights. CDPs create harmony from disorganized data noise.

Let’s walk you through how you select a CDP — one that checks all the boxes without skimping on any must-have features, so you can breeze through complex data tasks while sparing yourself time for the other responsibilities on your to-do list.

The first step? Understanding your cloud data platform. Here’s why Snowflake has so many competitive CDP options, but only Simon is the one that fully integrates and connects with it.

Why Snowflake for CDPs?

Snowflake is popular, both with customers and CDPs, for a few key reasons:

• Snowflake is one of the biggest data platforms in the business, cloud-agnostic, and available for Azure, Google Cloud, and AWS. This gives it an edge in scalability. 
• Being cloud-based and with a real-time connection to a CDP means Snowflake won’t interfere with computer performance. It’s known for some of the fastest queries in the data warehouse business, and it’s uniquely aligned to power marketing use cases
• Snowflake is also airtight when it comes to security. It offers encryption in transit and at rest and grants access control to its users.

These reasons are why it’s one of the most highly recommended data platforms out there. And, coincidentally, these are all reasons Snowflake plays nicely with CDPs. 

CDPs are a natural match for a cloud data platform like Snowflake that is scalable and accessible for a diverse team with varying levels of technical know-how. Snowflake gives you real-time access to data from all the popular cloud platforms — then it’s a CDP’s job to unify and/or activate that data.

Choosing the right CDP for Snowflake

There’s no shortage of CDP options out there. The issue is finding one that will meet your specific needs with quick, no-fuss integration. Two huge considerations that factor into your decision are:

1. How much end-to-end marketing functionally do you need your CDP to support?
2. Do you care if it’s embedded into Snowflake?

Additionally, when you’re choosing a CDP, you’ll also need to consider:

• Your primary end user — is it your data engineers, your marketers, your customers? How about all three?
• Your primary use case — are you looking to organize, centralize, consolidate, move, route, or model your data?
• Building to last — is your CDP scalable and secure?

Let’s define these points and drill them down further to help you make an informed decision.

Key features to consider when choosing a CDP for Snowflake

Data ingestion and integration

CDPs are supposed to centralize data, right? How they do that depends on the product you choose. If you pick a CDP that won’t centralize all data from your stack, you may be stuck pulling information by hand out of your leftover tools. 

An incomplete dataset will leave you manually segmenting audiences or bouncing between tools to activate your campaigns. CDPs should ingest data from internal and external sources in real time; the flow of data should be active.

CDPs can integrate customer data in a few ways:

1. Data from multiple sources is consolidated into one warehouse — your CDW. This consolidated information is served up to you for takeout!
2. A CDP duplicates the data. While the data still exists at its source, it’s copied into your warehouse. This is beneficial if you have multiple tools that are using the same data, because they’ll both have copies. However, this method is messy if you have lots of data sources you need to consolidate!
3. Data is consolidated into your cloud data platform, but isn’t accessible until the end user makes a request. This means the data isn’t always accessible, but it can save you some money if you have large data sets and multiple sources.

Data segmentation and targeting

A good CDP makes your data actionable, but there are nearly endless ways to do that. CDPs can segment by:

• Demographic, such as age or income
• Behaviors, such as website visits or dwell time
• Transactions, such as subscription renewal history or types of product purchase
• Engagement history, such as email open rates
• Channels, such as social media or text
• Lifecycles, such as newbies or product superfans
• Predictive algorithms, like possible churners

And any number of custom rules that you get to dictate. Some CDPs can let you segment by all of these; others are more focused. Better yet, some CDPs like Simon will let you create segments without code, so they’re accessible to all of your teams.

Personalization and activation

If a CDP can help you segment and target your audiences, it’s likely got some recommendations for personalization and activation, too.

Many customer data platforms will let you personalize your messaging based on segmented audiences, so you can send newbies reminders about setting up their accounts or ask your superfans to leave product reviews. CDPs also incorporate generative AI and machine learning to help personalize the customer experience, even when it comes to predicting customer behavior.

With advanced personalization comes advanced activation. Once you’ve segmented audiences by account activity or subscription level, think about how you can engage them to upsell. CDPs can help you send an upsell nudge to an account that hit its monthly subscription cap or encourage a customer who hasn’t logged in over a month with an email reminder.

Analytics and reporting

It would be a shame if all your customer data went to waste in a warehouse. A CDP can wave a wand and whip that data into trend reports, campaign insights, and cutting-edge customer analytics — it will seem like magic.

CDPs can organize data without any of your heavy lifting. Expect a good platform to have a robust dashboard with filters that help you hone in on the metrics you need to do your job.

Scalability and security

We usually think about scalability when it’s too late. After all, we usually aren’t buying the flashiest subscription pan with the highest data cap right out of the gate, are we? But it’s important to know that your CDP can evolve with your company.

When you need a higher data volume, you have the option to up the limit. When you want to integrate a new data source, your CDP is compatible. Nobody has a course fully charted for the future of their business, but if you foresee changes in your data down the line, pick a CDP that’s scalable.

What’s more, security is another feature that we can take for granted. CDPs should ensure data encryption in transit and have access controls. Even more importantly, it should balance marketing team needs with customer privacy. Cloud data can be tricky; consider who owns the cloud security perimeter.

The top CDPs for Snowflake

Based on these criteria, we have some recommendations for CDPs that are a balance of these features and some that excel in their particular capabilities. Some don’t quite fall under the full capability of a CDP, but still help you collect and activate your customer data, which we’ve highlighted below. 

Here are some popular choices that are touted as essential Snowflake companions.

Best for data routing: Segment

If you’ve already done any hunting for a Snowflake CDP, you’ve probably heard of Twilio-owned Segment. Segment is a non-connected Snowflake CDP, but it’s flexible — for enterprises and SMBs, with customers in everything from healthcare to B2B to retail.

When you think about Segment, you probably think of the engineering and data teams that benefit from it. Segment excels at data routing, with a heavy emphasis on thorough documentation for ease of use. If you have a complex ecosystem that will require a thorough setup, Segment will work for you: it has over 450 integrations and is built for complexity.

The catch? Because it’s focused on data routing, it will not maintain Snowflake as your single source of truth, which can still result in disparate data silos.

Another option for data routing: mParticle

mParticle was built to solve a specific (and thorny) issue: engineering and data teams were struggling to integrate data throughout the enterprise. mParticle helps applications transfer data from one another.

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mParticle places great emphasis on data quality and governance. They want to ensure your data is clean and in compliance. If you’re tasked with the tricky ordeal of integrating data across applications, mParticle is worth a look.

Best rETL tool: Hightouch

Although you could argue Hightouch isn’t a “true” CDP, it has some big names in its portfolio: Spotify, PetSmart, and GitLab to name a few. You may notice that these are all enterprise companies, and they’re from diverse backgrounds.

Hightouch, founded by former Segment product leaders, has over 200 tools delivered into data engineers’ and data analysts’ hands. That data — assuming it is already well organized within the data warehouse — can then be further accessed by sales, marketing, and customer success teams’ tools for activation. How is it able to speak to this audience? Being a no-code solution certainly helps.

Hightouch’s features are full service, with action items that drive revenue as opposed to being a CDP that focuses on customer data cleaning and record-keeping.

What’s even bigger than its feature set is its number of integrations. Many customers seek out Hightouch because you need to get your cleaned and prepped Snowflake data sent into one or many of the tools in your current stack. 

Best for marketers: Simon Data

Excuse our humble bid. Simon’s value proposition says it all: it’s a CDP for customer marketers. Simon’s biggest differentiator is the priority given to activating data from a CDW so marketers can use it to run their campaigns. Simon emphasizes quick and robust onboarding so marketing teams can get the insights they need fast.

What’s more, we integrate with over 70 software tools (and are webhook-friendly!) and can help you activate Snowflake data from its platform. Simon Data is Snowflake’s powered by a partner of the year, so marketers can create and sync segments directly in their Snowflake instance. 

Best rETL for B2B SaaS teams: Census

Census is a reverse ETL with a lot of popular sources, and Snowflake is their bread and butter. What sets Census apart from other CDPs is their focus on building for sales and CS in addition to marketing and data teams. The fringe benefits of a CDP are obvious to these teams, but Census speaks directly to them in much of their messaging.

Census offers “Census Embedded,” their built-in rETL tool designed with developers in mind. According to their site, “Census Embedded enables you to instantly connect to 200+ SaaS tools and data sources, without the burden of managing pipelines and customer credentials.”

Check out CDP if you’re looking to put product-led growth into the hands of every team.

Choosing the best CDP for your business

Now that we’ve gone through some of the well-known names in the world of CDPs, how do you choose what’s right for your use case? You could go with the popular choice, or the least expensive, but selecting one that fits will go beyond that. You should think a few things through before you lock in on a CDP.

Define your specific needs and goals

First, define your organization's goals for implementing a CDP. What challenges are you hoping your CDP will help you overcome? Improving customer engagement, enhancing personalization, streamlining marketing efforts? Talk with your team about what they want and make a list. Then, review your options together.

Evaluate existing data infrastructure and Snowflake integration

How well do your existing systems integrate with Snowflake? 

Consider factors such as data formats, protocols, and synchronization capabilities. A CDP that seamlessly integrates with Snowflake ensures a unified and efficient data ecosystem, allowing you to leverage the full power of both platforms.

Consider your budget and future scalability needs

This is usually your biggest lever when purchasing any tool. You should already have a budget determined; some CDPs are a better price point for SMBs, while enterprise customers will typically pay more because their plan will need tailoring. 

Choose a CDP that will scale alongside your organization, accommodating larger data volumes without compromising your performance. Thankfully, many CDPs are ready to scale with you.

Conduct thorough research and platform comparison

Once you’ve gotten to this point, you’ve set a clear goal (or goals) for your dream CDP, know how airtight your existing Snowflake integrations are, and have your budget prepared. Now, you need to find the CDP that balances these priorities.

This is the fun part! Reading articles like this will help you decide on a CDP for Snowflake, but it’s not the full picture. Read customer reviews, take a look at each platform’s resources, and check forums or customer profiles for other peoples’ thoughts. 

Try to find case studies or testimonials from companies that look like yours — if your choice of CDP was able to help someone with a similar problem, they’ll probably work for you.

Request demos and trials

Once you’re ready, request demos or trials of your favorites. Narrow it down to just a few so that this more time-intensive stage doesn’t lead you down a lot of dead ends.

Once you’re here, you get to dig into a CDP’s feature set. Is it everything you dreamed? Is the query performance everything the company touted, is the UI accessible? Don’t box yourself into one choice here. Be sure to explore a few so you know if the grass is greener. You want to feel confident in your final decision.

Conclusion

This isn’t an easy decision. You have a vision of unlocking powerful data insights and driving successful marketing campaigns, but not every CDP you come across is right for these use cases, your team, or your company. CDPs have the power to benefit data analytics, software engineering, and customer marketing.

Take this guide under advisement and decide on a CDP as a group effort. If you need more information, check out our 2024 CDP Buyer’s Guide, which goes even further into depth on the selection process.

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By now, you’ve probably heard of cloud data warehouses and customer data platforms (CDPs). However, as the industry continues to evolve, and with over 150+ CDP tools out there, it’s difficult to understand how using these platforms together can personalize the customer experience.

Put simply, if your enterprise marketing team wants to:

1. Deliver the 1:1 experience customers crave
2. Consolidate and activate customer data
3. Drive more personalization and optimization, and be able to adapt customer workflows in real time
4. Use (or currently uses) Snowflake

…then Snowflake + Simon Data is the right solution for you!

We don’t need to tell you all that you’re sitting on a goldmine of rich, valuable customer data. You already know that. But, like an actual goldmine, it can be complicated to find and extract it — and for many of you, use that data for marketing purposes. Many companies still struggle with siloed data, and manual and messy data workflows—making it slow and difficult to use the data for marketing purposes. And with this messy data, the dream of becoming truly data-driven seems further away.

Why should marketers care about their Data Cloud?

‍Reason 1: It’s your single source of truth. You do not want “multiple” sources of truth. A single source of truth (SSOT) ensures that everyone in your organization is making decisions based on the same data. 

Snowflake captures all the data there is to know about a customer: website activity, purchases, channel engagements, and even customer support data. Having multiple sources of data is not efficient, and it’s not scalable.

_{“If everyone in the business is working in the same data instead of in their own siloed data, there will be better decisions made across the org.” - Luke Ambrosetti, Senior Partner Solutions Engineer at Snowflake}

Reason 2: You can use Snowflake data for marketing segmentation and activation. If you have your data activation layer within Snowflake, you’re preserving that SSOT.

If you take it out and replicate the data in another platform, you lose that SSOT because it leads to poor quality data, inconsistencies, bad decision-making, etc., and this also poses certain security and privacy risks.

Reason 3: Data security, governance, and compliance. Privacy regulations have exploded in recent years and for good reason. These new laws have set a precedent as to how businesses should handle customer data – correctly, respectfully, and with care.

Reason 4: With AI and ML being top-of-mind for enterprise marketing teams, cloud data platforms and CDPs use GenAI to help teams save time, streamline processes, and offer predictive analytics so you can get the most out of your data.

 _{“For AI/ML, both Simon and Snowflake can help you harness the power of AI. But when you’re thinking about AI, first solidify your data strategy. You need quality data for quality AI.” - Luke Ambrosetti}

Why should marketers care about a CDP?

A CDP unifies your customer data from all sources and all types, including online and offline, real-time events, from your cloud data warehouse, and other marketing engagement data. 

CDPs then create one single profile for each customer, enabling marketers to create highly sophisticated customer segments, which turn into highly personalized campaigns spanning multiple channels in some cases.  All of which help businesses drive revenue!

How Simon Data + Snowflake work together

Simon Data is a Snowflake-connected CDP. It is built on top of Snowflake, connects directly to your Snowflake instance, and enables marketing teams to activate that data directly from Snowflake. 

But what exactly does a connected CDP mean for marketing teams? There are several benefits over a traditional, non-connected Snowflake CDP. 

First, marketers can create the highly sophisticated segments you need for campaigns easily. Simon Data’s segment builder is self-serve and no-code, so you don’t need to know SQL, and you don’t need to ask your data or engineering team for that data. Your engineers get time back, and you can launch campaigns quickly. It’s a win-win!

Second, real-time data processing, which is extremely important for certain marketing campaigns, such as abandon cart campaigns. You want the event data in real time, so you can see exactly when and what a customer abandoned and follow up with them in real time to get them to purchase. 

_{“One of the cool things about using the Snowflake and Simon architecture is going beyond just customer data by having contextual data, and even meta data, too, which you can use for marketing purposes. It’s a huge benefit.”- Luke Ambrosetti}

With Simon + Snowflake, there will be no data replication, so the data remains in your single source of truth (in this case, in Snowflake), until it’s ready for activation. 

Other CDPs require data replication, which means now you have a second source of truth. Another added benefit of this is that you also inherit Snowflake’s security and governance.

The last significant benefit of Simon’s Snowflake-Connected CDP is that it's built for composability. You can use and integrate all of the existing tools you know and love like Braze, Iterable, Attentive, or Salesforce. 

Snowflake houses all of your customer data so you can use Simon Connected to develop all of those hyper-specific audiences that you need. 

With Simon’s seamless connection to Snowflake, you can easily access that customer data to build audience segments, and then sync those audiences and orchestrate your campaigns to all your marketing channels which we see on the left (such as SMS, email, paid, push, and more).

Simon’s Snowflake-Connected CDP also allows customers to leverage the core capabilities of a CDP, such as identity stitching, reporting, and other additional Simon SKUs — as well as ID+, Match+, and Predict.

What’s more, all of your campaign data from those channels get funneled back into your Snowflake Data Cloud for further analysis.

Check out our latest webinar to learn more. If you want to see Simon Data in action, book a demo today.

From personalized messaging and deals to curated product recommendations, today’s customers don’t just prefer a personalized experience when they interact with brands — they’ve come to expect it. 

And it isn’t only the customers who reap benefits from personalization. Businesses that deliver personalized customer experiences are rewarded by better open rates and click-through rates (email marketing), improved conversion rates, greater return on ad spend, and generally higher revenue generated by campaigns.  

But effectively delivering a targeted experience to your customers requires you to have enough high-quality data about them — and for that data to be actionable.

A customer data platform (CDP) like the Simon CDP, which sits on top of a cloud data warehouse (CDW) like Snowflake, can help. CDPs work by ingesting customer data from multiple sources and unifying that data into a single customer profile, which you can then use to power personalized campaigns. 

According to our research, leveraging a CDP leads to better segmentation and targeting, higher productivity and collaboration between teams, and easier cross-channel experimentation and execution. 

We can go on and on about the benefits implementing a CDP can have for your business. After all, it’s what we do! But instead of rambling, we thought we’d highlight how three of our actual clients — world-leading brands in the video, hospitality, and e-commerce industries — have leveraged the Simon CDP to increase conversions and revenue, boost productivity, and realize real cost savings. 

Vimeo increased trial conversions 300%

Vimeo, the popular video-sharing platform and YouTube alternative, embraces a freemium model common in the world of SaaS. Anyone can sign up for a free account, but accessing the platform’s most powerful and valuable tools requires a paid subscription. Converting free users into paid subscribers required Vimeo to make those free users aware of the features and benefits that a paid subscription offered. Enter the 7-day free trial, which allows users to try premium features at no cost. 

The free trial was Vimeo’s primary means of nurturing free users along with becoming paid subscribers. But the success of this strategy hinged on one key moment: A user completing their first video upload — which, for a variety of reasons, many users failed to do. 

To better nudge users to complete this critical action, Vimeo turned to the Simon CDP and Snowflake, which they used to:

• Understand the precise moment a user abandoned their video upload
• Build a dynamic, real-time segment of free users who abandoned their upload
• Design and execute an A/B test to determine the optimal time for sending an email nudging users to complete their upload

The results were astounding. Personalizing the timing of their email nudges resulted in a 300% increase in conversions to free trials — highlighting the power of incorporating customer data into your marketing efforts. 

Click here to learn more about how Vimeo designed and executed their test using Simon CDP. 

Travel + Leisure Co. added $350,000 in incremental revenue

Travel + Leisure Co., a world-leading hospitality business consisting of nearly 20 brands, had a problem. The company used multiple websites, call centers, digital marketing platforms, and other systems to service each of its brands — including Wyndham Destinations, Panorama, and Travel + Leisure Group. 

This created multiple data siloes that didn’t easily speak to each other, making it difficult for T+L to resolve a customer’s identity across brands, hampering their marketing efforts and ability to grow revenue. 

To put that valuable data to use, L+T knew that it would need to be centralized in a single location — ideally one with an easy-to-navigate interface. To make this happen, they turned to the Simon CDP. 

With the Simon CDP, Trust + Leisure Co. was able to completely transform their marketing efforts by:

• Empowering their marketing team to find and use customer data quickly and easily, regardless of where it originated, to put it to work.
• Simplifying the process of building customer segments that could be automatically updated in real-time.
• Facilitating the orchestration of highly personalized customer journeys across multiple channels.

As a result, T+L was able to implement more relevant vacation recommendations based on a customer’s transaction history, inventory, demographic information, and web activity. They were also able to conceive and deploy a custom metric — called the customer’s “Next Best Action” — that measured which actions a customer was most likely to take at any given moment in their journey. This score unlocked a level of personalization that T+L has never experienced before. 

Ultimately, leveraging the Simon CDP empowered Trust + Leisure Co. to realize $350,000 in incremental revenue per year, reduce technology costs by 30%, and double productivity. 

Click here for more details about how Trust + Leisure Co. deployed the Simon CDP to transform their marketing efforts. 

BARK nearly doubled revenue per user

Subscription pet food and supply company BARK knew that it was sitting on a gold mine of customers whose subscriptions had lapsed. With the right messaging and incentives, they believed that these customers could be reactivated. But, like Travel + Leisure Co., BARK had a data problem. 

Running reactivation campaigns required BARK to centralize from several disparate systems — including MixPanel, Recurly, Delighted, and its data warehouse — which it typically achieved with one-off database pulls. 

This was not only time-consuming and often unwieldy; it was also inefficient. Worse, it meant that retention and reactivation were sporadic events rather than an ongoing process. 

BARK’s solution? Using the Simon CDP, BARK created a customer segment of subscribers who had recently canceled their subscriptions. Then, they conducted many A/B tests to fine-tune messaging, timing, and promotional offers for their reactivation campaigns. 

They did all of this while keeping an eye on the downstream effects that discounting would have on long-term revenue, to ensure they weren’t setting the business up for trouble down the line. 

With the Simon CDP, BARK was able to nearly double revenue per user year over year, and increase campaign volume by 300%.

Click here to learn more about how BARK used the Simon CDP to reactivate lost customers.

Supercharge your marketing efforts with 1:1 personalization powered by Simon Data

Each of the three brands above used the Simon Data CDP in slightly different ways to achieve 1:1 personalization in their marketing campaigns — and saw real, significant results. 

Are you ready to unlock the true value of your customer data? The Simon CDP can help. Take a look at our CDP Buyer’s Guide to learn more about what to look for as you evaluate your options, or request a demo today to see how we can work together.

Twilio isn’t selling Segment and announced share buybacks. What does this mean for the CDP market? 

On Tuesday, Twilio announced it had completed an operational review of Segment and that it would retain the Segment business. The Board also approved an additional $2bn in share buybacks on top of the $1bn previously approved in 2023. 

Before I answer the titular question, let’s review some ancient (by CDP standards) and modern history of the Twilio / Segment relationship.  

On Nov. 2, 2020, Twilio announced the Segment acquisition:. $3.2bn in Class A TWLO stock, which closed that day at $292.13 per share (trading at publication in the high $50 per share range, roughly an 80% decline). By comparison, over the same time frame, the Nasdaq is up 36.8% and the S&P is up 46.4%. 

When Jerome Powell turned the lights on at the bar and the ZIRP tab closed, many growth companies took a beating; few have delivered worse value to shareholders since than Twilio. 

When announcing the acquisition, Twilio Co-Founder and then-CEO Jeff Lawson made it clear that the Segment acquisition was to be a part of a broader strategy for Twilio Engage: 

“Nearly every company is focused on acquiring, retaining, and growing their customer relationships through digital engagement. However, the biggest impediment to great digital engagement is the data silos that prevent companies from truly understanding their customers. With the addition of Segment, Twilio's Customer Engagement Platform now enables companies to both understand their customer and engage with them digitally -- the combination is key to building great digital experiences."

At the time, it seemed Twilio was making a push to compete with the customer engagement and marketing clouds, but as a kind of developer-first alternative. It’s also important to note that less than a year prior, Twilio acquired Sendgrid, a developer-first ESP (email service provider) or MTA (message transfer agent), depending on your level of industry hardo-ness. The puzzle pieces were coming together to form an undulating sea and a crepuscular sky, with only a big gap remaining on the horizon. 

What Twilio missed with Segment

The answer to this question comes down to a few important market trends that have shaped the CDP space over the past few years. 

1. In this puzzle analogy, the middle of the landscape is the most important (and Twilio Engage failed to deliver)
2. The CDP market clarified into different subcategories (and Segment lost its subcategory) 

The missing messy middle

In the acquisition press release, Twilio listed 6 capabilities they believed the acquisition would deliver for their clients: 

1. Unparalleled insight into the way customers interact across channels to create a single, unified view of the customer journey.
2. The ability to break down data silos to help businesses make their customer engagement more personalized, timely, and impactful across channels. 
3. Access to the world’s leading cloud communications platform to more effectively manage customer communications including SMS, Messaging, Voice, Video, Email, Internet of Things (IoT), and more.
4. A flexible API that allows developers to connect sources of customer data, such as web or mobile apps, with analytics tools, without having to write new code. 
5. A steady supply of quality, high-velocity first-party data that easily integrates into existing systems.
6. A single platform with views for the marketer, the contact center agent, the product teams and the developers that reveal data-driven insights to serve their individual needs. 

By “missing the middle” I mean two things. First, the solution needs to deliver on the capabilities teams need to power their customer experience (i.e. in between data collection and message delivery), and second, the tool needs to be usable by the people who power the customer experience, whether that’s CRM team or end-user marketing and marketing operations teams. 

While Segment has been a category leader in data collection and enabling developers to establish an events routing infrastructure, for example, this does not necessarily deliver for clients a “single, unified view of the customer journey.” Such requires complex identity resolution, data modeling, and a UI such that a non-technical CRM person can use it. 

Segment is a strong data infrastructure CDP, but was probably the wrong type of CDP to use in achieving the overall vision of Twilio Engage. 

CDP category evolution

As businesses, especially businesses within Segment’s ideal customer profile, undertook a data warehouse-centric approach to data management, Segment missed the wave. 

Developers, data teams, and the technical teams that support marketers over the past several years have begun a shift toward data warehouse centralization, often referred to as the “modern data stack” that Segment couldn’t pivot quickly enough to capitalize on. The beneficiaries of this have been former Segment engineers who left to found Hightouch and other reverse ETL/composable CDP vendors who fill the capability gaps Segment was once great at, but in a data warehouse-centric way. 

In Twilio’s operational review press release, the comment that addressing “Segment’s recent challenges” will require “delivering additional features to enhance data warehouse interoperability” is an admission of this. 

What this means for the CDP category

At this point, the poor horse has had enough. Composable CDPs are here to stay and Segment will likely deliver something to the market (per their comments) not unlike Blackberry deciding to ditch the keyboard finally. 

With a significant customer base, it’s possible to see a Composable Segment gaining market traction and regaining market share in the rETL category. 

It’s also entirely possible, and potentially more likely, that it does not. 

In a recent press release, Twilio mentions several times the importance of Segment as a differentiator for Communications customers and that a key point of focus going forward will be increasing “innovation velocity by delivering three products in 2024 that natively embed Segment into Communications, while also capitalizing on CustomerAI momentum.” 

So it seems Twilio may be doubling down on their failed Twilio Engage strategy and pushing Segment more as a value-add to their Communications customers than as a standalone product. 

Either way, the board has put their money where their mouth is and this next frontier will be critical for Twilio (which will also have to deal with activist pressure to split up the businesses). 

To this day, Segment represents the only real strategic exit for a CDP vendor in the history of the category. 

I bet that the all-in-one developer cloud vision that Twilio Engage promised is not going to be achieved (including by Twilio if that wasn’t clear at this point). The problems developers and data teams want to solve are too different from the problems CRM and marketing teams want to solve. 

Salesforce, as an example, is coming at this from the other angle (as a tool used by marketers that solves only marketing problems but is positioned as a Data Cloud) and failing equally as hard from the developer’s POV. 

So then what happens to the “messy middle” of CDPs that marketing teams use to solve data problems? As the category splits along ideological lines, there will continue to be winners and losers, and in light of an improved macro environment, this next frontier will put us all to the test. 

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What is customer segmentation?

Every customer journey is unique, and a one-size-fits-all approach won’t work for everyone. Today, consumers demand a 1:1 personalized customer experience from brands, and this is where customer segmentation is key to a marketing team’s success.

Customer segmentation is the organization of customers into specific groups based on common characteristics such as demographics and behaviors to deliver more relevant customer experiences. 

This segmentation process allows businesses to align their marketing strategies with customer interactions to better understand how to market more effectively to each group of customers.

How does customer segmentation work?

In a customer segmentation strategy, marketers create groups of customers according to how and why they purchase. Using segmentation, businesses can gain a deeper understanding of the needs and buying behaviors of their customer base and discover what is important to each segment.

Customer segmentation uses key differentiating factors to divide customers into different groups — the most common of which are customer demographics, geographical location, psychographic information, personality characteristics, and behavioral information. (We’ll look at each of these in more detail.) 

These smaller, more specific segments are then targeted with relevant messaging. Tailored marketing efforts improve campaign effectiveness with messaging that is more likely to lead to conversion.

Benefits of customer segmentation

A well-implemented customer segmentation strategy holds many benefits for businesses.

Fine-tuning your messaging

Messaging that directly relates to your customer base will grab their attention and cause them to engage with your brand more, increasing the chances of conversion. 

Customer segmentation helps you identify how to communicate with your customers in the most effective ways using the most effective means. The more relevant your messaging is to your customer’s needs, the higher their engagement will be with your products or services.

Improving the customer experience

Customer segmentation allows businesses to create new products and services that customers want and give them the experiences they are looking for. Personalized content and messaging matched to a particular customer segment can make those customers feel appreciated and understood. A customer segmentation strategy can tell you what emails customers want to receive, if they prefer to buy online or in-store, and even whether they prefer to interact with a chatbot or a real person for customer support.

Increasing your ROI

Segmenting customers allows you to create content and messaging that speaks directly to specific segments — helping you better understand how to turn prospects into customers and increase the purchasing frequency of existing customers. 

It can also highlight who your most valuable customers are. They might be high-income users who buy your more expensive products, or they could be more dependable long-time customers or subscribers. 

Narrowing down who your most profitable customers are can help you make the most of your marketing campaign budget to increase your ROI on marketing spend.

Four types of customer segmentation

The four most common types of customer segmentation models are demographic, psychographic, geographic, and behavioral.

Demographic segmentation

Demographic segmentation involves categorizing your target audience into segments based on information such as age, gender, income, and job title. In B2C marketing, this form of segmentation allows you to present personalized offers such as clothing recommendations based on age or gender.

 In B2B marketing, it allows you to target individuals based on pain points associated with their job title, for example. Examples of demographic information include the following:

• Age
• Gender
• Income
• Job title
• Religion
• Marital status

Psychographic segmentation

Why do people purchase your products or services? To find the answer to this question, you need to understand your customers’ needs, habits, and lifestyles.

Psychographic segmentation creates different customer groups based on psychological characteristics that influence their buying habits, such as personality, lifestyle, social status, political views, and interests. 

Psychographic data can be obtained from forums, social media activity, and purchase behavior, as well as through your own research, such as conducting surveys. Note: It’s more important than ever to use as much zero- and first-party data as you can instead of relying on third-party data.

Marketers often combine psychographic data with demographic data to create buyer personas.

Psychographic information can include these characteristics:

• Personality
• Lifestyle
• Social status
• Attitudes
• Activities
• Interests
• Opinions
• Habits
• Political views
• Hobbies

Geographic segmentation

Geographic segmentation divides customers based on the locations where they live or shop. Segmentation can be done by country, region, city, time zone, or other geographical factors such as cultural considerations, populations, and climate. 

The premise of geographic segmentation is that people in the same locations have similar needs, behavioral patterns, and customs. 

By understanding these needs, you can create more relevant marketing messaging so customers are more likely to buy. For example, local climate or customs can have an enormous influence on demand.

If you are a global brand, using geographic segmentation allows you to offer winter clothes to your customers in the north while sending swimwear offers to those in the tropics. Here are some examples of the information used for geographic segmentation:

• Location
• Climate
• Culture
• Population density
• Urban vs. suburban
• Language

Behavioral segmentation

Behavioral segmentation divides customers into different segments based on their behavioral patterns as they interact with your company. 

Behavioral data may be related to the customer lifecycle (e.g., buying a home), seasonal patterns (e.g., holiday shopping), or previous interactions with your business (e.g., purchase history or responses to marketing messaging). 

Using a behavioral segmentation approach, you can track specific behaviors such as opening an email, completing a purchase, cart abandonment, or raw data from clicks as the user moves around the business website. This information helps you gauge metrics such as customer retention, engagement, and experience. 

With this data, marketers can identify the most loyal and valuable customers, uncover roadblocks in the customer journey, and enhance the customer experience for new and existing customers. Behavioral segmentation can make use of the following information:

• Purchasing behavior
• Customer journey stage
• Customer loyalty
• Customer satisfaction
• Engagement level

Customer segmentation examples

Here are some examples of customer segmentation in action.

Using customer income to highlight products based on price point

Disposable income can influence which products customers purchase and how often they purchase. A demographic segmentation strategy that targets potential customers based on income can help you focus on customers who you know can afford your product, and prevent you from spending valuable marketing dollars on those unlikely to buy.

Recommending new items based on customer personality

Using psychographic segmentation, an online shoe store might discover that many of its customers who buy running shoes are environmentally conscious. The store could then target these customers by suggesting environmentally friendly shoe brands.

Showing different products depending on where the customer is based

Using geographic segmentation, an ecommerce store can display different products to customers based on where they live. This could mean displaying higher-end products to people living in more expensive areas such as New York or San Francisco, or, for global companies, showcasing winter gear to customers in North America in the fall while showing swimsuits to those in the southern hemisphere.

Distinguishing between first-time visitors, returning visitors, and existing customers

A behavioral segmentation process can help you tell the difference between first-time visitors to your website, those who have visited multiple times but never purchased, and actual customers, so you can market to each one specifically. 

You might offer a first-time visitor a site-wide discount coupon but send a returning visitor a coupon specific to an item they keep returning to the site to view. Existing customers could be invited to join your loyalty program.

Considering data and privacy laws when it comes to customer segmentation

In today’s world, the tightening of privacy laws around data significantly impacts how marketing teams can collect and use customer data. Additionally, consumers must also be able to trust brands with their data to feel comfortable buying from them.

To keep in line with government laws and remain ethical when it comes to customer data usage, consider using a cloud data platform or warehouse in your MarTech stack, which collects data in one place and keeps it secure.

Customer segmentation with a Customer Data Platform (CDP)

In this post we’ve looked at the basics of customer segmentation, what it means, and how it can benefit your business. But without a comprehensive customer data management solution, the process of collecting customer data, separating it, and segmenting it into usable categories can be long and complex. 

A customer data platform (CDP) ingests data from a cloud data platform like Snowflake and creates a unified database and comprehensive customer profiles for all your company’s data sources to give you a 360-degree view of your customers. Consolidated customer profiles allow marketers to create custom segments to increase personalization and tailor communications. 

CDPs can also ingest data from other platforms — such as customer relationship management (CRM) tools, data management platforms (DMPs), and multichannel marketing hubs (MMHs)—for greater audience segmentation and personalization.

Using AI-powered customer segmentation within a CDP

AI-powered customer segmentation is revolutionizing the way marketers understand their audiences. AI and machine learning algorithms are capable of going far beyond traditional demographics to analyze enormous datasets of customer behavior. 

They can identify intricate patterns, connections, and trends that would take humans much longer to uncover, if they could be found manually at all. This allows businesses to create highly specific customer segments based on shared behaviors, preferences, and purchase histories.

The precision unlocked by AI-powered tools makes marketing campaigns laser-focused. Marketers can use their CPD to understand the exact product features that resonate with a specific group, or quickly learn the type of messaging that will pique their interest. 

This level of targeting eliminates wasted resources on generic campaigns. AI segmentation helps to deliver the right messages to the right people at the right time, significantly increasing the chances of engagement and conversion.

Sign up for a demo to learn more about how Simon Data’s customer data management solutions can help you segment your customers and improve your messaging and customer experience.

Meal subscription services, skincare, flavored water, boxed water, the Twilight franchise resurgence, beige everything, and Stanley cups — what are the similarities between all of these trends?

Influencers — they are driving sales left and right. Why? According  to Forbes, “People like to buy products from people who they like and trust.“ 

It’s simple: consumers have a relationship with the people they’re watching online. For customers, they’re authentic and relatable, they’re storytelling and they’re building a sense of community. 

Combined with an algorithm that makes sure viewers see content that is targeted right at them based on multiple data points (more on that soon), it’s a magic recipe composed of empathy and intentional, data-based personalization.

Empathy is imperative in marketing

What exactly is customer empathy and why does it matter? Trust is important in relationship forming. Human psychology tells us that people want to feel intentionally connected. 

Dopamine is the name of the game. It’s a lot easier to click and buy (and return) without a second thought if you trust who you’re buying for and it feels customized to your needs and desires.

“Understanding is at the heart of empathy. It's the ability to put oneself in another person's shoes, to comprehend another person's ideas and feelings. But empathy isn't only about feelings. It all comes down to action. No two people will have identical experiences, sensations, or sentiments, but the goal is to get as near as possible by putting our prejudices aside and attempting to realize how others think and what their needs and desires are.” — Forbes

Beyond a positive (and in many ways, ethical) way to operate, there is a real return on investment (ROI) that comes from leading with empathy, which includes earning new customers, retaining and upselling existing customers, and preventing churn. 

Consider this customer research:

• 68% of customers expect brands to demonstrate empathy, but only 37% of customers say brands generally demonstrate empathy
• 68% of customers will spend more money with a brand that understands them and treats them like an individual
• 66% of customers expect companies to understand their unique needs and expectations, but only 34% of companies generally treat customers as unique individuals

Leading with empathy increases ROI, decreases customer churn, and increases brand loyalty by enabling you to:

1. Understand customer needs to address customer needs better and provide tailored solutions
2. Personalize customer experiences in a way that makes customers feel valued and understood
3. Communicate effectively to build trust between customers and your company. Transparent and honest communication during any issues or challenges can reassure customers and strengthen their connection with the brand
4. Resolve problems quickly and effectively by turning a potentially negative experience into a positive one, ultimately fostering customer loyalty
5. Adapt quickly to change so you can stay attuned to changing customer preferences and market trends, and remain relevant

Ultimately, it’s nice to be thought of, but it’s even nicer to be seen. People are struggling with inflation, housing, jobs, and grocery costs – they don’t want to be cold-called. They want a relationship. They want someone to see them, not just place them in a crowd of post-Covid era travelers. 

How can you do this without knowing your customer personally? Through data — but not just one point of data here and there. You need a whole view and it’s not without its challenges. Here’s where a Customer Data Platform (CDP) can help.

Your customer data: The empathy engine

What does it mean to be in a data-driven world? It means that data infuses our work, personal, and home lives — essentially, everything. 

Say you choose to order iced coffee instead of hot coffee. 

Why? Is it based on an experience? Your mood? The weather? The barista? The customer in front of you who ordered it? These data points helped you decide without you even thinking about it.

The same can be applied to customer marketing. For example, a popular pet service can send flowers when they track that their customer’s beloved pet has passed. In the case of customer marketing, this shows customer empathy.

But when a company sends a romantic Valentine’s Day message to someone who’s been traveling solo for years and has a household of one…. well, that message might have missed the mark. Sometimes an attempt to empathize ends up in an unsubscribe, simply because you don’t have the entire picture.

So how do you even begin to get this holistic view of a customer you don’t know personally, but wants you to behave like you do? 

Customer Data Platforms serve as the empathy engine for modern businesses. They go beyond mere data collection, unifying information from various sources to create this holistic view of individual customers, and this is what Simon Data does best. 

“Simon Data has been an incredible partner in helping The Farmer’s Dog deliver on our promise of simplifying pet care and nutrition. The platform and the team have been instrumental in powering our ability to deliver personalized, relevant information that communicates the value of our products, inspires people to try them, and most importantly, improves the lives of our customers and their canine loved ones.” - Adrian Evans, Director of Retention & Lifecycle at The Farmer's Dog

Having a holistic view of data also goes hand-in-hand with the increasing importance customers place on data privacy. First-party data collection, a hallmark of CDPs, not only complies with privacy concerns but also enhances customer trust. 

It's the foundation for creating rich customer profiles that extend beyond basic demographics. CDPs enable businesses to delve into website behavior, purchase history, social media interactions, and more. 

By doing so, they create a nuanced understanding of customers, uncovering not just what they buy but why they buy.

Remember: 76% of consumers want the companies they’ve done business with to remember who they are, and their history with the company.

The beauty lies in the granularity of these customer profiles. CDPs don't just stop at transactional data; they incorporate inferred preferences and emotional triggers and can even predict potential lifetime value. 

They help marketers take a deep dive into the psyche of their customers, turning data into actionable insights. Key performance indicators (KPIs) like customer lifetime value, retention rates, and brand advocacy can be tracked to assess the ROI of empathy-driven initiatives.

Putting empathy into action: CDP-powered strategies

CDPs enable personalized marketing messages, offers, and recommendations based on individual customer preferences and emotions. 

With a CDP, you can incorporate multiple data points to authentically empathize with your customer, get to know them, and consider their needs and circumstances dynamically. 

Let’s say you want to determine how best to communicate with customers likely to churn (so you don’t overtext them or miss them via email since you’re already at risk of losing them). No one likes to find out they missed a promo the day after a purchase or get message after message in a channel they don’t prefer.  

You can experiment with different communication channels, content, etc., to find what meets your customers’ wants day to day, not just with a top-level picture, and meet them right where they are. 

For example, you can use our Simon Predict Churn Prediction model to first segment a Journey to users who are likely to churn. You can first send an email that includes personalized product recommendations from the Simon Predict Product Recommendation model, then experiment with sending an email vs. SMS to see if you get any bites. 

Then, you can leverage that result data in the future to be sure you’re communicating with customers within their preferences (and not over-communicating in other channels) without ever having to send one survey asking if they prefer email or text. 

Take it a step further and be sure you’re only sending messages at a reasonable time in their timezone, consider any special days coming up, planned travel, etc. Consciously or subconsciously this empathy ensures your customer has a more personalized experience with you.

Simon provides:

• One-to-one personalization across all touchpoints

• The ability to orchestrate unique customer experiences with advanced segmentation, out-of-the-box predictive models, and other data enrichment tools.

As a bonus, you can even use our AI-powered Jinja generator to help you build no-code content that scripts all these data points in seconds for you.

“With Simon Data, we unlocked the ability to unify all of our customer data and cohesively orchestrate customer experience across our marketing channels. This allowed us to increase our sales by improving how we interact with our customers and enhancing our understanding of their needs.” — Ash Fisher, Head of Technology at ASOS

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Conclusion

Understanding customer needs, personalizing experiences, and effective communication foster trust and enhance brand loyalty. This empathetic approach is pivotal in navigating the complexities of a data-driven world – and the research shows your customers are asking for it! 

It’s time to shift from mere transactions to authentic relationships. By creating holistic customer profiles and orchestrating personalized strategies, Simon’s CDP not only helps you meet evolving expectations but also measurably impacts ROI. 

Are there risks from leading with empathy? Sure, but the better question is what are the risks if you don’t?

You may make a poor assumption or miss the mark here and there, but you can intentionally make positive choices by using well-rounded, data-driven campaigns and experiments to empathize more.  

And what’s more, you can use empathy to not only earn new customers, but you can win them back too with your authenticity and willingness to get to know them as the unique person they are.

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The sheer volume of disorganized customer data pouring in these days can make you feel like you're sinking fast. Does this sound familiar?

• Your sales and support teams rely on your CRM database OR on your data teams to access customer data
• Website behavior and interactions are tracked separately
• Loyalty programs generate yet another stream of customer info you can’t track

If this is the case and you’re feeling overwhelmed by these data silos, a customer data platform (CDP) might be your new best friend. CDPs pull all that fragmented customer information into one centralized powerhouse, transforming data chaos into powerful insights. 

Whether you’re in the market for a CDP or are considering making a switch, let's look into the critical features you'll need to find the perfect CDP solution for your needs.

Navigating the CDP landscape

A CDP is designed to break down data silos and create a unified, 360-degree view of each customer. In short, it’s a platform that makes sense of and helps you activate your data.

Here's a preview of some key benefits of using a CDP:

• Enhanced personalization: Offer laser-focused marketing tailored to individual preferences
• Optimized customer journeys: Guide customers seamlessly through every interaction with your brand
• Boosted ROI: make the most of your marketing dollars with targeted, data-driven campaigns

While most CDPs offer these benefits, picking the right one is about more than finding the one with every single bell and whistle. It's about aligning features with your unique business needs. 

Consider these questions:

1. What are your main goals? (increased customer personalization, increased repeat sales, higher CLTV, or improved ROAS)
2. What are your existing systems? (marketing automation, CRM, loyalty programs, etc.)
3. What kind of customer data do you deal with? (purchase history, preferences, and/or demographic data)

Unveiling the must-have CDP features

In our experience, here are the fundamental features that make CDPs tick for customer marketing teams:

Data unification and identity resolution: When combined with a Cloud Data Platform like Snowflake, your CDP should be gobbling your unified, real-time data and customer info from multiple sources – then transforming it into a single, accurate customer profile. This means matching and cleaning names, addresses, and more, linking it all back to individuals, even if they interact using different devices.

Granular customer segmentation: A CDP is your secret weapon for understanding customer groups. Imagine you can easily carve up your audience by behavior ("recent purchasers"), demographics ("women 25-35"), or even engagement ("clicked on last three sale emails"). That translates to hyper-personalized promotions and offers.

Customer journey orchestration: This is about visualizing your customers' ideal paths – from visiting your website to subscribing to your newsletter to making a purchase. Once you understand the journey, a CDP can optimize each step.

Omnichannel marketing activation: Consistent messaging builds trust! Use your CDP to drive relevant, personalized experiences across every channel – email, social media, websites, and even SMS.

Predictive analytics and insights: CDPs have a crystal ball of sorts. Artificial Intelligence (AI) and machine learning (ML) help predict customer behavior, spot potential churn risks, and suggest things like the most promising products to recommend based on past purchases — thus, personalizing the customer experience even more.

Real-time data ingestion and activation: Time is money in marketing. Your CDP needs to process data immediately to trigger relevant actions. Abandoned shopping cart? Boom, reminder email (and maybe a special discount!) in a flash.

Robust reporting and visualization: This is about understanding what's working and what's not. Your CDP should make it simple to see how campaigns perform, and then use this data to shape your future customer marketing strategy.

Integrations and openness: Your marketing tech stack doesn't live in a bubble. Look for a CDP with extensive API access that links seamlessly to your existing CRM, email tools, and more. The smooth flow of data both upstream and downstream is key.

Scalability and security: As your business grows, your data will too. A robust CDP sits on top of a Cloud Data Platform so that it scales effortlessly, storing and managing that customer info securely.

Privacy compliance and data governance: We can't skip this! Choose a CDP that prioritizes data privacy and meets compliance standards (GDPR, CCPA, etc.).

Bonus features for advanced use cases

Ready to level up? Here are some extra features beyond the basics to consider when searching for a CDP that could unlock next-level insights.

Artificial Intelligence and Machine Learning (AI/ML): AI-powered CDPs can do incredible things. Imagine predictive models that automatically identify your most likely-to-convert prospects or customers on the verge of churning. A good CDP might even recommend the "next best action" to guide your interactions.

Attribution modeling: This is the secret sauce for proving marketing ROI. An advanced CDP can connect a customer's interactions across touchpoints, helping you see which is driving the most sales and conversions. Finally, some justification for that clever social media campaign!

Customer feedback management: Customer surveys, testimonials, and reviews give you a goldmine of data. A good CDP can pull in feedback from every source, revealing how your customers really feel and where you can improve the journey.

Conclusion

The world of CDPs is vast and diverse. There's no single “best” option, but there is the right option for your unique needs. Don't be blinded by bells and whistles you may not use right away. 

Instead, you should:

1. Prioritize the essential features needed to tackle your biggest data challenges
2. Outline your current setup and goals to pinpoint the specific benefits a CDP will bring
3. Think about the future. Where do you want your marketing efforts to go, and how can a CDP help you get there?

Selecting a CDP is a worthwhile investment in data-driven decision-making and enhanced customer experience. When you find the perfect match, you'll have the foundation for marketing strategies that not only connect with your customers but deliver undeniable results.

Ready to continue your research? Check out these helpful resources:

• The CDP Buyer’s Guide
• How CDPs leverage Snowflake to create hyper-personalized customer experiences
• Building a Customer 360 with your CDP

Happy CDP hunting!

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Recently, Gartner released a Customer Data Platform Critical Capabilities assessment Magic Quadrant report. This report is less a milestone and more of a juncture in analyst coverage of what has been a confusing space to navigate for the better part of the past decade.

The CDP acronym has been used to describe hundreds of vendors, many of which serve different purposes and solve different problems. Categorizing all CDPs against the same set of dimensions is therefore not only an unenviable task but also arguably not useful for this particular category. 

Unlike other categories that Gartner and other analysts evaluate, CDPs have been used as a bit of a catch-all term to describe various software applications used to consolidate, transform, and activate customer data. The variety of tools used to deliver these capabilities not so roughly corresponds to the different strategies businesses use around data management.

In other words, categorizing CDPs against the same set of dimensions is a bit like categorizing all athletes, regardless of the sport they play, against the same set of dimensions.

Comparing Salesforce, Twilio, and Amperity against the same set of dimensions is like comparing Lebron James, Tom Brady, and Tiger Woods and rating them on their speed, vertical, and long jump distance. That comparison is probably being generous to Twilio and Amperity, and certainly Salesforce (Gartner’s above-and-beyond prize horse that won’t run on a track except its own and charges you rent for the stable it occupies). 

At Simon, we have a different vision for where the category is headed. The goal of this article is to both respond to Gartner’s coverage of CDPs from our perspective (after all, it’s not an easy category to tackle) and express our views on how we see the CDP category — and Simon — continuing to evolve.

Our view of the CDP category

Different types of CDPs solve different problems, which is partially why lumping them together and placing them on a grid is complicated. 

We view the CDP as a CRM application that should connect to enterprises' customer and non-customer data assets as seamlessly as possible, enabling marketing teams access to all data and the tools to power their campaigns across any channels at the latency demanded by the use case.  

“Seamlessly,” in our case, means an application connected to a client’s cloud data warehouse, with the ability to ingest data that lives outside the data warehouse as well. 

Some CDPs function as a marketing data warehouse. Others perform data quality functions and route data back to the data warehouse. Few CDPs on Gartner’s Magic Quadrant are primarily focused on data activation for marketing use cases. None of the CDPs listed in the “leaders” quadrant offer both a marketing UI and real-time data activation, for example. 

Understanding Gartner’s dimensions

There are 13 dimensions to Gartner’s analysis, ranging from data collection and profile unification to core CDP workflows like segmentation to non-category-specific considerations like data privacy and system integration relationships. 

Reiterating the above point around intra-category direct comparison, some of these capabilities are much more important than others if you envision your CDP as a data routing solution versus a marketing automation hub. 

Gartner previously categorized CDPs into four buckets: marketing cloud CDPs, CDP engines and toolkits, marketing data integration CDPs, and CDP smart hubs. We view this sub-categorization as essential and only comparison within the sub-category as useful. However, Gartner has since abandoned that sub-categorization in favor of direct comparison across the category. 

One perplexing decision on their part is to combine B2B and B2C functionality in the same assessment. Other analysts, more logically, separate B2B and B2C-focused vendors into different categories. 

The biggest hurdle to CDP adoption is data integration and upstream data quality challenges and maintenance. Gartner, as a services company, seems to approach this as a services problem and places weight on system integration relationships. This makes sense in a legacy enterprise context, but this comes at the expense of undervaluing vendors for whom this problem is mitigated with a more modern deployment strategy. 

Embracing composability

Composability is a key trend shaping the CDP space. We believe tremendously in the value of being a composable CDP and have invested significant R&D effort in enabling our CDP to be deployed within a client’s data warehouse. 

We believe Gartner undervalues this capability in two ways: 

1. The business value and capabilities that a composable deployment enables, beyond simply the architectural principles it follows
2. How this divergence between (1) CDPs that interoperate with cloud data warehouses and (2) CDPs that want to become your data cloud, and what this means for the category going forward

The business outcomes enabled by composability

Composable deployments significantly reduce the time, effort, and cost required to implement a CDP. 

Having a CDP oriented to a source of truth for customer data that supports other types of software applications also means that the CDP can focus on what the CDP should do best — create an interface for customer marketers to interact with all of the data they need to power their customer experiences, and to do so without friction between marketing and the data teams that support them. 

As it pertains to capabilities like data science and experimentation, a composable architecture enables teams to train models that can interpret the entire customer profile and other relational data relevant to making predictions about the customer lifecycle. 

This is possible in a traditional CDP deployment, but the models will be limited to learning the data that is made available to them. 

As it pertains to data privacy, a composable deployment means that no data leaves a customer’s data environment. It’s not possible to imagine a better approach to data privacy than not actually storing or handling customer data. 

This approach has become a gold standard for enterprise data privacy and security teams and we believe it should be incorporated into any assessment of privacy. 

Lastly, because composable deployments can be implemented in days or weeks and not months or years, while there is meaningful change management and data modeling work that can accompany a composable deployment, gone are the days of massive consulting and/or system integrator contracts surrounding a composable CDP deployment. This approach saves clients six figures and is a multiplicative force on time to value and ROI.  

Overall, Gartner seems to look at composable CDPs the way that a 20th century mechanic might look at an electric vehicle, noting the absence of pistons or valves but also not capturing that the vehicle doesn’t require gasoline. I would largely attribute this to a difference in the ideal customer profile, but this is becoming less so with enterprise adoption of the modern data stack. 

Simon’s vision and short-term roadmap

Building upon the benefits of a composable approach, and, more broadly, delivering a CDP vision that supports organizations who have adopted a modern approach to their data stack, there are three key areas that Simon Data is uniquely positioned to impact. 

Customer lifecycle optimization 

There are many siloes within an organization, from tooling to data and teams. Customer marketing and advertising teams are no exception. 

Often, given these siloes, advertisers aren’t effectively coordinating their paid media strategies — and budgets — with downstream customer marketing efforts. This is especially true for organizations using enterprise marketing cloud tooling without a modern CDP in place to coordinate across data silos. This results in suboptimal efficiency (i.e., ROAS, CAC, etc.) due to targeting suboptimal customers or prospects. 

First-party data activation tooling, historically within the hands of CRM and retention marketers, is increasingly attractive to paid media teams as third-party cookies are deprecated. 

Those most prepared are looking at new first-party data strategies and how a CDP can complement their cloud data warehouse approach to drive media efficiency outcomes. 

At Simon, we offer a product called Anonymous+, a tool built entirely on top of Snowflake and does not rely on third-party cookies. It offers a workflow that brings marketing and advertising teams together, on a fully-governed, unified Customer 360, resulting in better media performance. 

Anonymous+ resolves customer identity across known and anonymous touchpoints. This enables brands to unify and leverage customer data across the entire customer journey — from first touch to first purchase and throughout the customer lifecycle. 

This is the first and only of its kind solution in the CDP space. Several Simon customers have seen mid-double-digit improvements in paid media efficiency and seven-figure outcomes leveraging this product. 

High ROI use cases require more non-customer data than customer data 

Great personalization is more than “Hi [first_name]”. Marketers also need context about customer intent, discount sensitivity, product affinity, etc. 

For a customer of ours like ASOS, for instance, there’s a ton of basic customer intent data that can be used to create the right marketing and engagement experience: the number of products they viewed, how many times the customer has visited the site or made a purchase, and what acquisition channel(s) the customer engaged with. 

But there’s also a deeper layer of context and product-related data that can make personalization even more impactful. For example, there’s the price within the category of products, inventory, weather in the customers’ location, and what the SKU(s) viewed imply about other purchasing preferences.

Marketers need easy access to this level of customer intent and context to design the next-best interaction. Our connected architecture enables our application to access this type of data in a way that’s significantly broader than other CDPs and to also do so in a way that doesn’t result in data overload or storing data for the sake of it (after all, in a composable deployment, we don’t store or charge for it). 

Access to this non-customer data in Simon, including things like inventory, pricing, and cost data, is available across the entire customer lifecycle, and leveraging non-customer and product-related data helps marketers and advertisers optimize everything from channels to media costs and even product selection. 

Our goal at Simon is to help D2C customer marketers leverage all types of customer and non-customer data by building products that are easy to use, easy to integrate with, and that minimize the complexity of marketers’ interactions with the data. ‍

The CDP is an application owned by marketing and should optimize marketing outcomes 

Marketing teams should demand measurable results from their CDP, especially in the current sustained macroeconomic environment. Winning customer marketing teams will have to do more with less. 

Not a hot take, but at Simon, we believe GenAI will have a lasting change on marketing workflows, and that advances in GenAI will be best applied to a true Customer 360 from the CDW. 

We see AI as key to achieving a future where Simon autonomously delivers value to customers by leveraging available data and adapting to customer behavior and market trends.

We've identified four main challenges our customers face in realizing that today:

1. Difficulty in using data effectively for campaign creation
2. Generating ideas that may not always align with business goals
3. Learning from past actions
4. Lack of time, energy, or skill to create campaigns and their components

Our first GenAI-powered content creation tool went GA in Q3 2023. This tool helps non-technical marketers create complex content personalization code from simple natural language prompts. 

Now anyone can create complex personalization logic by writing a few sentences describing their use case (which used to require complex code) without the need to ask for technical support.

Normally, my process for content creation was to go to Simon documentation, look for the section on how to format, and then go through trial & error to get the results I needed. With Simon AI for Content, I asked the AI…and it created what I needed in maybe 30 seconds.” — Valerie Decker, Lifecycle Marketing Manager at Zillow

Our vision for GenAI goes well beyond content creation. Generative marketing can expand to the audience and channel optimizations as well. 

Our long-term vision is to use AI to decrease time to value and increase ROI. We believe we can do this by using AI to develop a “semantic understanding” of our customers' data, and then use that understanding to automatically create “complex data aggregates” and marketing campaigns that drive customer value.

In summary, these three investment areas, alongside our connected architecture, will enable our customers to automate audience, channel, and content decisions across the entire customer lifecycle and personalize interactions with any data point, all while optimizing for revenue and non-customer data that matter most to the business (e.g., margin, LTV, inventory, etc.). 

This is a broad vision relative to the current capabilities of most CDPs that don’t operate as part of a broader marketing cloud ecosystem. 

Contrasting customer profiles

With the above note on the completeness of product capabilities, Simon Data is not the right fit for every type of customer. Simon is purpose-built for customer marketing teams at customer-focused businesses to deliver the next generation of customer experience. 

Relative to the overall array of customers that Gartner advises, Simon is naturally not going to cover the breadth of capabilities Gartner assesses. 

We believe this is a strength of our product vision and execution. CDPs that are focused on solving a massive array of customer problems and those who rank highest in Gartner’s completeness of vision axis are often the CDPs our customers are least satisfied with when they switch to working with us. 

Our customers value a platform that can deliver measurable ROI as a customer marketing and personalization solution that enables them to access all of their data — that can be implemented in days or weeks and not months or years. 

Many enterprises, including the largest, are adopting a data-warehouse-centric approach to data management and CDP deployment. We believe this trend will benefit the broader industry, and our clients, and this has already proven to be a significant market opportunity for Simon. 

Our predictions for the future of the category

As more large enterprises centralize their data in a cloud data warehouse and expect that their applications come to the data (as opposed to bringing their data to all of their applications), such enterprises will realize huge efficiencies and will reap the tremendous benefits that AI can create for organizations with centralized and well-structured data. 

Many CDPs included in Gartner’s report that do not currently orient around data centralization in this way will either adapt or struggle. These include all of the Customer Data Infrastructure CDPs (e.g., Twilio and Tealium) and all of the C360-focused CDPs (e.g., Treasure Data, Amperity). 

CDPs that fit as part of a broader marketing cloud strategy (e.g., Salesforce, Adobe) are naturally going to score well in a measurement of surface area. These products are also capable of depth if you’re operating with infinite resources and budget. These platforms also naturally lock customers into their ecosystems. 

Going forward, we expect teams to value efficiency and measurable ROI. From the conversations we have with customers, the most important considerations around data architecture are: (1) limiting data replication throughout the enterprise, (2) cost management, (3) avoiding vendor lock-in and (4) creating best-in-class data privacy management. 

For this reason, we see the “CDP as a data cloud” as an unsuccessful strategy for our customers.

A few appendix notes:

1. It’s probably a bit of a quandary as to how Gartner treats the big marketing cloud players because while their overall product surface areas can achieve anything (with the above caveat around budget and resourcing), it’s hard to know where they draw the boundaries around their CDP products. They also all have huge relationships with Gartner that create an obvious conflict of interest. 
2. Gartner omitted a lot of the more technology-persona-focused solutions that teams often use to achieve their CDP use cases. While this isn’t surprising, given the scope of Gartner’s evaluation, it’s worth noting that this report includes almost entirely packaged software that marketing teams buy (as is Gartner’s definition of a CDP) but without as much consideration around how data teams solve for CDP use cases. 
3. It’s unclear how the MQ scoring relates to anything resembling the way we or the businesses we speak to see the market or the vendors our prospects and customers ultimately select in a competitive process. This likely has to do with many of the factors discussed here. 

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Many businesses are sitting on a gold mine of rich, valuable customer data. They know how much their customers are willing to spend, when and where they tend to engage, category/item preferences, and so on. If you want to know more about your customer, that data is likely there. Well, it’s likely somewhere.

A common theme we see is that this gold mine is scattered across various sources. This translates to messy and disorganized pools of data, making it a challenge for marketing teams to harness its full potential. 

In the worst-case scenario, it could render the data virtually useless. You can have a world-class marketing team, but if they’re not optimally making use of customer data, their innovative marketing strategies can only go so far (and its results will reflect that, too).

Enter Customer Data Platforms (CDPs). According to CDP.com, a customer data platform (CDP) is “a customer data management solution that consists of a centralized database that can ingest, integrate, manage, and deliver customer data to other technology solutions to personalize the customer experience (CX).”

A CDP can function as a full-service tool for your marketing and data needs. You can create personalized experiences, streamline your marketing processes, and drive more customer engagement, ultimately resulting in business growth. Because of that, having a CDP in your marketing tech stack is becoming increasingly important — or, arguably, necessary. 

The business benefits of using Snowflake and a CDP

Marketing and data teams alike rely on cloud data platforms like Snowflake to help unify and access their real-time, first-party customer data. “There’s been a significant shift in the industry over the past few years when it comes to collecting, storing, and activating data,” says Jim Warner, FCTO for Marketing at Snowflake.

“It only continues to evolve as budgets shrink, privacy and data laws tighten, and  more and more enterprise data and  marketing teams realize that using a cloud data platform can break down data silos, keeping their data clean, accessible, and ready to use.”

Customers using a cloud data platform have seen many benefits and increased ROI within their data-driven business and marketing strategies over those who don’t.

Vimeo, for example, analyzes billions of streaming CDN events per day with Snowflake, enabling millions of dollars in revenue by identifying enterprise customers who require additional bandwidth. 

CDPs like Simon that are built on top of Snowflake extend this benefit even further by empowering marketers to use and activate this data within their marketing campaigns and overarching strategies. 

In Vimeo’s case, the company has been able to leverage enriched marketing data to minimize customer acquisition costs, and they saw a 300% increase in trial conversions once they implemented the Simon CDP on top of Snowflake.

Here are some of the primary benefits of using a cloud data platform and CDP within your business.

1. Unified customer view (Customer 360)

CDPs provide marketers with a comprehensive, 360-degree view of their customers sourced from different touchpoints and channels. With a unified customer view, marketers will have holistic visibility into their customers’ preferences, behaviors, and interactions across channels. 

This single customer view not only enables marketers to make informed decisions and targeted marketing strategies but also supports the remaining use cases in this article.

2. Improved segmentation

With a centralized point for all customer data, marketers can take audience segmentation to the next level. A CDP will allow you to create audiences (as granular as you want them to be) that stay up-to-date while the tool continues to ingest from the scattered data sources.

 You can identify high-value, at-risk, engaged, or unengaged customers — the possibilities are endless if the data is available. The cherry on top: marketers can do it directly in the platform without involving a data engineer.

3. Advanced personalization for the customer experience

Similar to how CDPs can improve the way you segment, this essential MarTech tool can also enhance personalization across multiple channels. You’ll have access to accurate and fresh customer data for marketing purposes. 

Knowing that a user recently browsed your website and clicked on certain products is valuable, real-time information. Use that to trigger an abandon browse campaign displaying the product they were browsing for. 

With a CDP, you can personalize content to deliver the most relevant message on the right channel at the right time. 

4. Understanding and optimizing the full customer journey

The unification of all customer data in one platform means getting visibility into the full customer journey. You can see when a user browsed your website, downloaded the app, favorited items, opened the chat, and more. 

By identifying each customer touchpoint, you’ll understand how, when, and where your customers interact with your business every step of the way. Leverage these insights to message your customer at the right time and place, ultimately resulting in increased conversion rates and lower acquisition costs.

5. Automate cross-channel marketing

It’s the digital age, and noise is everywhere. Reaching your customer at just one touchpoint or channel won’t drive results. CDPs that are built on cloud data platforms go beyond data unification and provide features that enable marketers to do cross-channel marketing. 

With Simon Data, for example, you can orchestrate customer journeys that are as complex or as simple as you want. In these journeys, you can send communications or sync custom audiences to the desired end channels through robust integrations. 

A welcome journey can be sent through email and SMS, while your win-back campaigns can be sent through email, SMS, Facebook, and TikTok. Once the campaigns are live, you can sit back and watch the numbers to see where experimenting and optimizing can be done.

6. Data governance and compliance

By now, you should be aware of what the General Data Protection Regulation (GDPR) is.The California Consumer Privacy Act (CCPA) followed shortly in the United States, with more regulations to come globally. 

These new laws have set a precedent as to how businesses should handle customer data – correctly, respectfully, and with care. Beyond marketing benefits, unifying data allows your team to manage data more easily from a legal perspective. 

Consent regulations vary, but you’ll be able to ensure the right rules are applied to the right segment with a CDP (e.g., European customers are tagged for GDPR). 

7. Optimize operational efficiencies

We’ve seen customers with marketing teams that previously relied on their data team to pull customer information and segments before using Simon Data. 

We’ve also seen the customer experience team pull customer data from various sources through manual, time-consuming work. With centralized data in a CDP, you can automate data processes for cross-functional teams. 

The tool becomes a one-stop shop for marketing, data, and CX teams alike, which can streamline their workflows and improve the customer experience. In turn, your team’s time is freed up, enabling them to do more things that can drive revenue for your business.

8. Predict customer behavior

Marketers and data teams can spend a lot of time — perhaps too much, at times — analyzing data for segmentation purposes. This is where a CDP helps these teams shine. CDPs use artificial intelligence (AI) and machine learning (ML) to leverage historical and present data for predictions. 

Examples include predicting churn or making product recommendations. Not only does this streamline internal workflows, but these predictive insights drive business growth and customer engagement. 

9. Identity resolution

Customers interact with businesses across multiple channels and devices leading to fragmented data points. A CDP can offer identity resolution, allowing businesses to reconcile disparate customer profiles to create that customer 360. 

By accurately linking customer identities across touchpoints, you’re improving personalized campaigns which will drive better results and increase campaign conversions.

10. Increase ROI

Each use case, such as improved segmentation and enhanced personalization, all funnels up to one overarching goal: Return On Investment (ROI). The overarching goal of implementing a CDP is to drive tangible business outcomes and maximize the return on marketing investments. 

By harnessing the power of unified customer data, you can optimize marketing and data efforts, improve customer experiences, and drive revenue growth.

Conclusion

A CDP built on Snowflake is a tool that will help your business drive revenue by using your most treasured asset: customer data. The heart of a successful marketing strategy stems from a deep understanding of your customers based on the data you’ve collected. 

Without a central repository for this data, truly comprehending your customers' behavior and effectively leveraging their data can be challenging for marketing and data teams. 

Whether or not you currently have a CDP, we encourage you to explore the potential of this tool. There are different types of CDPs, but each one has the same goal: unifying customer data. This has a positive downstream impact for many teams involved and can only be a beneficial addition to your tech stack.

If you’re in the market for a CDP, use our 2024 CDP Buyer’s Guide to assist you with the evaluation and our Improve Your CDP RFP Process to ensure you’re optimizing the search process.

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Ever since their creation back in 1994, cookies have played an integral part in the way that both businesses and individuals interact with the internet. 

For individuals, cookies made it possible to experience a web that remembered them. This meant that a person didn’t need to log back into a website every single time they visited it; it also meant that they could experience a version of a website that was tailored to them — even if tailoring was slight in those early days. 

For online businesses, meanwhile, cookies offer a means of tracking customers between multiple sessions. This provided the business with a wealth of customer data that could be used to better target those customers with advertisements and marketing efforts. 

In recent years, however, consumers and lawmakers have become increasingly concerned with issues of online privacy — as seen with the passage of laws like GDPR in the European Union and the CCPA in California. This has caused companies like Google and Apple to make plans to restrict and eventually kill the use of third-party cookies on their platforms: Apple in 2020, and Google by Q3 of 2024. 

For businesses that rely on third-party cookies, this means the loss of valuable data. Without a replacement, it will be much more difficult to segment your customers with any sort of granularity. It’ll also be virtually impossible to understand who your customers are on an individual level — or to offer a personalized experience when they visit your website. 

The good news is that third-party cookies aren’t your only option for collecting this data. Zero- party and first-party data are fast becoming the new gold standard. 

Below, we take a closer look at what zero- and first-party data are, and how they work. We also walk through different ways you can begin collecting this data and strategies you can deploy for utilizing it once you have it. 

Zero- and first-party data: The new holy grail

To understand what zero-party and first-party data are, it’s first important to understand what third-party data is. 

Third-party data, as its name implies, refers to any customer data that is collected or aggregated by a third party — someone without a direct relationship to your customers. 

It’s not data that you are collecting; it’s not data that your partners are collecting. It’s data that a data provider is collecting and sharing with you. As such, third-party data is typically stitched together from multiple sources, including (as you might have guessed) those third-party cookies we mentioned earlier. 

First-party data, on the other hand, is any customer data that you have collected yourself — importantly, with consent from your customers. Because you’ve collected this data yourself, you have direct control over it without needing to worry about the policies or motives of other companies (third-party data providers, platforms, etc.). 

And because the user has consented to the collection of this data, you don’t need to worry about running afoul of GDPR, CCPA, and other privacy regulations.

First-party data can come from a variety of sources, including your business’s website or app, your POS system, CRM, accounting system, and more. Examples of first-party data includes things like: 

• Transaction history
• Average order value and lifetime order value
• Page and product views (including repeat visits)
• Products added to carts
• Mouse clicks
• Keystrokes 
• and more

Zero-party data, meanwhile, technically isn’t data that you collect. Instead, it’s data that a customer chooses to share directly with you voluntarily. 

Any time a customer fills out a form, signs up for a newsletter, completes a survey, answers a quiz, takes a poll, or voluntarily shares some other sort of information directly with you, they are helping you generate zero-party data. 

Zero-party data comes with all of the benefits of first-party data, plus the knowledge that it came directly from the customer — making it an extremely powerful tool for personalization. 

Building ‌a first-party data fortress

If you’re still relying on third-party cookies and data to understand who your customers are, you must begin putting in place a plan for transitioning to zero- and first-party data. Failure to do so may mean you’ll be left in the dark when Google finally pulls the plug on cookies later this year.

Luckily, there are many strategies you can use to start generating this data. Some options you may want to consider include:

Website forms

When you embed a form on your website, you’re giving potential customers who are not yet ready to make a purchase an opportunity to still interact with your business — and provide you with valuable zero-party data that you can use to begin marketing to them. 

How much data, and what data, a person is willing to share with you will usually be directly tied to how much value they believe they’re getting out of the interaction. While perceptions about value vary from person to person and from industry to industry, generally speaking, you want to keep the length of your forms aligned with the perceived value you are providing. The guidelines below can help you design your form strategy:

• Newsletter signups: Usually perceived as low value. Keep forms short. At a minimum, collect the individual’s email address and possibly their first name. Provide an option that allows users to self-segment, for example, an “I’m interested in…” checkbox.
• Coupon codes: Provides direct value in the form of a discount. Tie the length of forms to how generous the discount is. Customers will usually be willing to share more information than they would in a newsletter signup. They might, for example, agree to opt into SMS marketing and provide you with their phone number on top of their email address.
• Downloadable assets: Value depends on the asset you are offering. If you are helping the individual solve a real problem they’ve been experiencing, they will likely be willing to tell you anything you want to know. A B2B company offering a high-value asset, for example, might ask the individual to segment themselves by industry, job title, company, and even “challenges faced.”  

Don’t be afraid to get creative in your forms, so long as the questions you ask are always proportionate to the value you provide. 

Behavior tracking 

How a customer interacts with your website — what pages they navigate to, what videos they watch, what links they click on, what text they read — can provide you with a lot of valuable first-party data. 

Once you’ve collected enough of this data, it’s possible to use it to conduct A/B testing on site design and layout, and to ultimately optimize your product pages and landing pages for conversion. 

You can even use it to tailor your marketing efforts to individuals, such as offering them a discount on an item that you know they viewed, or by making them aware of similar products they might be interested in. 

Not sure what customer behavior to collect? Some options that you may want to consider include

• Click maps: This shows you every time a user clicks on your website, which can help you understand how a user navigates your website.
• Scroll depth: This shows you how far down on a web page a user scrolls before they navigate to a different page or end their session altogether, which can help you prioritize what information belongs closer to the top of the page and what information should fall lower on the page.
• Mouse movement: People often move their mouse along with their eyes as they read text and navigate a website. This can help you see where text or images are hitting the mark — or, conversely, where they are not.

Surveys, polls, and quizzes

Another great way of collecting zero-party data from your customers is creating surveys, polls, and quizzes for them to complete, which can be embedded directly on your website or delivered to your customers via email. 

Not only are these interactive tools more fun and less intimidating for your customers than form submissions, but they also make it easier to collect data that can be difficult or impossible to collect in other ways. 

Surveys and quizzes, for example, can help you gather information about your customers’ preferences — information that you can use to individualize your product recommendations, promotions, email marketing, and other efforts. 

Like behavior tracking, they can also help you conduct A/B tests to optimize your website and products based on user feedback. 

First-party data strategies for customer marketing success

Once you've collected zero- and first-party data from your customers, you can begin leveraging it in several ways. A few powerful examples include:

Personalization across the customer journey: Once you’ve acquired a customer, first-party data can help you re-engage them periodically after their initial transaction. Imagine you are an online retailer that sells clothing, shoes, and accessories. The behavioral data you collect shows that a particular customer has only ever engaged with product pages on your website related to shoes. 

This allows you to be more targeted in your email marketing approach, tailoring your offers, recommendations, and messaging to the products that they’ve already demonstrated an interest in.

Customer loyalty: First-party data can provide you with insights that make it easier to provide value to your customers, instilling loyalty and preventing churn. Knowing a customer’s birthday, allows you to gift them a coupon code that a.) brings them back to your website and b.) makes them feel like they’re being rewarded for shopping with you. 

Customer retention: A customer’s behavior on your website can sometimes be a clue that they are a retention risk; collecting this information makes it possible for you to implement targeted retention campaigns. 

Imagine a company that provides a subscription service to its customers, for example, noticing that a particular customer has visited the cancellation page of its website multiple times in the past few weeks. They may choose to preemptively send that customer a discount or credit to keep them around, or an email poll to gauge their level of satisfaction with the service.

Deeper audience understanding: Once you’ve collected enough first-party data, it’s possible to analyze your customer base en masse to potentially uncover hidden trends and segments for more targeted marketing efforts. This can lead to higher campaign relevance, conversion rates, and ultimately ROI.

How a CDW and CDP help

As you can see, zero- and first-party data are extremely powerful assets, and a crucial part of successfully navigating the cookieless future that we are transitioning into. But it doesn’t come without its challenges.

One key challenge lies in the fact that this data typically doesn’t all come from a single source. In most cases, it will be generated by many different tools and systems —  your POS system, accounting system, CRM, website management system, and behavioral tracking tools — which don’t always intuitively communicate with each other. 

Effectively leveraging your first-party data will require you to find a way to unify all of these disparate pieces of data into a single profile of your customer. 

Turning your zero- and first-party data into actionable insights is a two-step process. 

The first step involves extracting all of that data from its various sources and bringing it under one roof. This is what a cloud data warehouse (CDW) like Snowflake is for: Storing, structuring, and unifying first-party data safely and securely, regardless of where it originated.

The second step involves taking that data from its raw state and turning it into easily understandable assets. This is where a customer data platform (CDP) like Simon Data comes into play: Quickly and intuitively turning your raw data into customer profiles, segments, and audiences that you can use to drive personalized marketing campaigns. 

Ready to start building your first-party data strategy? Take a look at our CDP Buyer’s Guide to learn more about what to look for as you evaluate your options.

Interested in learning more about how Simon Data and Snowflake can help you truly unlock the power of zero- and first-party data? Request a demo today.

Imagine a world where you can anticipate your customers' needs, deliver personalized experiences across their journey, and drive meaningful engagements at every touchpoint in the marketing funnel. Sounds like a marketer’s dream, right?

Well, forget the outdated funnel metaphor. Today's customers are dynamic — flitting between channels, evolving their preferences, and expecting brands to keep pace. Siloed third-party customer data and generic outreach simply won't cut it anymore. 

First-party real-time data is where the future of customer marketing is, and if you’ve invested in a cloud data warehouse like Snowflake, you’ve probably heard of a composable customer data platform (CDP). What is it, exactly? 

In short, a CDP is your secret weapon for understanding and engaging customers at every measurable stage of their journey.

Think of a CDP as the conductor of your customer data orchestra: It harmonizes information from websites, emails, apps, and CRM systems, transforming it into a symphony of insights ready for you to personalize. It’s a cheesy metaphor, but you get the picture.

So, how does using a CDP translate to concrete results within every aspect of a customer journey? Let's explore what a 1:1 personalized customer experience could be with your CDP.

Take your customers from curious browsers to devoted advocates with a CDP

Remember Sarah, the outdoor enthusiast searching for a tent on your website? Instead of a generic welcome message, she sees a banner showcasing camping tents based on her previous searches – the perfect example of a CDP in action!

Intrigued, she delves deeper. But Sarah's not just any hiker; she's eco-conscious and enjoys solo adventures, so your CDP-powered paid ads target relevant Facebook groups like, "Sustainable Solo Backpacking," reaching Sarah with laser-focused precision.

But it doesn't stop there. When Sarah subscribes to your newsletter, she receives an email offering an exclusive 15% discount on eco-friendly tents, personalized based on her browsing behavior and interests — meaning that your business will see a significant increase in click-through rates compared to sending out generic emails.

Keep your customers interested and engaged throughout their journey

Sarah bought a tent! She loves it so much that she even buys one for her cat. Fantastic!

But Sarah’s customer journey doesn't end there. CDPs are experts at transforming one-time buyers into loyal fans. Imagine sending Sarah a post-purchase email suggesting complementary hiking poles and a reusable water bottle based on what other tent buyers purchased.

You could also send her personalized training tips and exclusive trail snack offers, gleaned from her website interactions (who doesn’t love snacks on the trail?). 

And, on her birthday, Sarah receives a special text message offering a discount on a personalized adventure experience, like a guided kayaking tour or a wilderness survival course.

This unique offering shows you care about her individual interests and adds a special touch to her day — helping to build brand customer loyalty. One of our customers, ASOS, implemented a CDP to improve marketing personalization and saw over 80,000 products used for personalized recommendations.

Sarah is the perfect example of a happy customer who continues to engage with your brand. But what about customers who last visited six months ago and haven’t made a purchase in over a year?

Here’s another place where a CDP can help. CDPs identify at-risk customers, allowing you to send targeted "We miss you!" emails with special discounts or reminders about their loyalty program points. These re-activation campaigns can help recover at-risk customers and lead to a win-back conversion rate of 5.3%.

Seal the deal with an end-to-end frictionless customer experience

Cart abandonment – the online retailer's nemesis. But fear not! 

With access to real-time data from your cloud data warehouse, you can identify Sarah as she abandons her cart, Merino wool socks still sitting inside. 

Here’s where a CDP shines: you can send her a personalized email that reminds her of the forgotten item and offers free shipping or a limited-time discount. Every recovered cart counts toward your revenue goals! 

In fact, Simon Data found that one customer using CDP-powered cart abandonment campaigns increased its trial conversions by 300% by optimizing abandonment.

But let’s take personalization even further. Imagine offering Sarah, a loyal customer, express checkout, tailoring her payment options and promotions based on her past purchases — all while guiding first-time buyers with helpful prompts during the checkout process.

Delivering a personalized experience is all about creating a smooth, frictionless experience that makes buying from your brand a breeze. For a Simon Data customer, a high level of personalization translates to $350K incremental revenue per year.

How CDPs benefit enterprise marketing teams

This is just one example of how CDPs can provide an elevated customer experience that keeps your customers coming back for more. For enterprise marketing teams, CDPs can also:

• Streamline customer marketing workflows
• Create customer 360s with real-time data from various sources with identity graphs, painting a holistic picture of your audience and helping drive personalized experiences across all touchpoints, regardless of how and when a customer interacts with your brand
• Hyper-segment your audience with precision, creating targeted micro-campaigns. Imagine segmenting customers based on purchase history, website behavior, and social media interactions to create campaigns with dramatically improved click-through rates
• Identify anonymous users in paid search campaigns to improve your ROAS 
• Deliver seamless omnichannel experiences, ensuring your message resonates across all touchpoints. Picture Sarah seeing the same "We miss you!" email offer on her phone that she saw on her laptop, creating a consistent and connected journey
• Predict customer needs before they arise, making you a pro at proactive support. This can translate to increased customer satisfaction and reduced churn rates

A CDP is the key to unlocking personalized experiences that build deeper relationships, drive conversions, and turn marketing teams into customer journey rockstars. 

Remember: Don't worry, you don't need a data science degree to use a CDP. Most platforms are user-friendly and have plenty of resources to help you get started. If you’re ready to invest in a CDP, check out our CDP’s buyer guide.

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In today’s customer marketing world, data isn’t just for data teams. 🤯

While brands recognize — and customers demand — the need for a personalized marketing experience, it’s tricky to implement a truly data-driven marketing strategy. Why? Many orgs have relied on the cookies from their sites and the often siloed, stale crumbs of data they get from their data teams.

But Google has closed the lid on its cookie jar, and customers are more leery than ever before when it comes to maintaining their data privacy and trusting companies to keep it secure.

As if that wasn’t challenging enough, marketing budgets are shrinking, Gen AI is taking over the world for better or for worse, and martech stacks have become overly complicated, rendering them inefficient and ineffective. No more.

Enter the customer data platform (CDP), a platform designed to work with a cloud data platform (CDW) like Snowflake to enable marketing teams to activate real-time, third-party data to build and orchestrate personalized customer experiences to deliver the right message on the right platform at the right time.

As brands mature in their data and marketing strategies, the benefits of using CDP with your cloud data platform compound, and, with this dynamic duo in place, marketing can even share its data and insights back into the cloud.

With over 160 CDP vendors on the market, there’s no doubt that the space is growing rapidly — and becoming more difficult to navigate. If you’re in the market for (or recently invested in) a CDW like Snowflake, a CDP is a wise addition to your investment. 

Here’s why.

Understanding the Customer Data Platform (CDP)

Gartner defines customer data platforms (CDPs) as software solutions that support marketing and customer experiences by “unifying a company’s customer data from marketing and other channels.”

Unlike the other components of your martech stack, the CDP’s job is to orchestrate between all of your marketing tools and your data platform, helping to create a “single source of truth” for your buyer.

The beauty of the CDP lies in its ability to assist disparate systems to communicate with each other to power a complete picture of your customer. 

A true CDP must:

• Ingest customer data from multiple sources
• Unify customer profiles into a single view (resolve identity)
• Create real-time customer segments
• Integrate customer data from other systems, out of the box

By integrating with other components of your martech stack, a CDP improves the performance and efficiency of the stack as a whole, while also eliminating the bottleneck between data engineering and marketing.

Identity resolution and personalization that drives ROI

One of the most essential unique functions a CDP brings to your martech stack is a modern, robust identity solution. 

To build a truly personalized customer experience, brands need a CDP based on a flexible data model that understands complex notions of customer identity while offering real-time recognition and enrichment capabilities to drive revenue.

Simon AI was recently cited as a “game-changer” in Snowflake’s recent Modern Marketing Data Stack Report. In particular, the report cited Simon’s Connected Customer Data Platform for its ability to tap directly into the data cloud to help enterprises craft tailored experiences for their customers. Simon’s customers, including brands like 1-800-Flowers, JetBlue, WeWork, and Vimeo, are achieving personalization at scale.

The CDP readiness checklist

First, consider whether your company and its marketing teams are ready for a CDP. Our experience working with companies reveals that those getting the most ROI from their CDPs share these common points:

• They have or will implement a cloud-based data warehouse such as Snowflake
• They are actively maturing an enterprise-wide data strategy
• They have a need to define new customer segments and achieve a high degree of personalization

This article will give you the quick-hit information you need to know to get end-to-end ROI with your Snowflake CDP.

Need more information or looking to purchase a CDP? Our in-depth CDP Buyer’s Guide will walk you through everything you need to know.

What features should your CDP have?

All CDPs must offer these four core competencies:

1. Data ingestion: A CDP must gather, standardize, and validate all data from across sources, both online and offline‍
2. Profile unity: A CDP must dedupe and consolidate customer data into one, informative profile for each customer‍
3. Segmentation: A CDP must leverage consolidated profiles to allow marketers to build custom segments from a single platform and increase personalization
4. Integration: A CDP must allow marketers to make immediate use of created customer segments by seamlessly integrating with end channels to quickly deploy personalized experiences. ‍
5. End-to-end service models: Today, more data-driven marketing teams are choosing CDP vendors that offer end-to-end service models with proven ability to drive ROI

Choose a CDP that offers comprehensive customer support and partners with you to ensure you’re getting the most value from your CDP.

Why is it necessary to use first-party customer data? 

Reason 1: Meet customer expectations

Customers expect that brands understand and relate to them based on past interactions. This is one of the key benefits of attaining a single, unified view of the customer, also known as a customer 360.

Reason 2: Build emotional connections

Centralized, accessible customer data is the only way to make informed decisions that support delivering personalized experiences to each customer.

Creating customer lifetime value starts with that emotional connection.

Reason 3: Increase ROI across marketing

If your data is siloed, no one is operating with a full, valid view of the customer. This wastes marketing spend and a lot of time. 

A modern, cloud-based CDP can ensure that all stakeholders are using live, real-time data, making analytics far more reliable and campaign measurement far more accurate.

Reason 4: Ensure compliance with privacy regulations

Privacy, privacy, privacy. This is the old-but-new-again customer data mantra. Siloed data runs a higher risk of non-compliance. A CDP with built-in compliance functionality ensures you are up-to-date and compliant across the full martech stack. It also creates customer confidence.

What does a CDP do, exactly?

A CDP enables you to better understand and relate to your customers so you can easily build personalized customer relationships at scale. 

It also allows you to create offers and opportunities that align with your customer’s preferences, even to the point of helping to anticipate what they might need or want in the future (hoorah, Gen AI and ML!).

Ultimately, CDP should help create the kind of regular experiences that make your customers feel emotionally connected to your brand with a, “They really do know me!” feeling. 

The ultimate CDP value proposition: Deliver centralized and actionable customer data at your fingertips. 

Can your CDP do this?

• Enable your marketing teams to better understand and relate to your customers. 
• Improve marketers' agility and help them move more quickly to optimize and personalize campaigns.
• Provide a single view into customers in a campaign to enable non-technical people to adapt/quickly change messaging based on real-time data.
• Make data activation easy.
• Deliver intuitive tools for data enrichment, identity resolution, data activation, and measurement/analytics all from a single interface.
• Alleviate the bottleneck of reliance on data engineering teams to gain an actionable view of the customer.
• Help marketers know their customers better. 

Genuinely connecting with your customer is about anticipating their wants and needs and delivering on them in their channel of preference.

How CDPs (like Simon AI) and CDWs (like Snowflake) work together

CDWs are cloud-based databases that store valuable data from nearly every part of the business, including first-party customer data. CDWs were primarily constructed as a business intelligence tool, and access to the data is oftentimes limited to IT, engineering, or other technical gatekeepers.

Think of your CDW as your dad’s garage. It’s completely chock full of valuable stuff, and a total mess — rendering it completely impossible for anyone who’s not him to find anything. 

While CDWs provide a centralized source of customer data, supporting activities like personalization and segmentation require brands to invest in technologies that integrate directly with a CDW, like a CDP, to enable marketers to access and use the data within.

Your CDP should flex to your current and future data architecture. A connected customer data platform is designed to integrate seamlessly with your CDW and enable you to easily access unified customer profiles directly in your CDW.

There’s no one-size-fits-all approach to personalization. Successfully building a modern marketing data stack for personalization depends on your data infrastructure, available technology, and your team’s organization and governance, among other things.

What value will a CDP bring to your business?

You can expect the following business outcomes from your CDP:

• Increased operational efficiency for the business
• Increased revenue
• Reduced media spend
• Streamlined technology costs

Specifically, customer marketers will gain:

- The ability to segment audiences almost as fast as you can think

Think of all the tests you could run if segmentation weren’t slow and inconvenient.

- More granular and dynamic personalization

With a CDP, you can get much more granular and personal than you can with even your fanciest rules-based ESP settings.

- A single, unified, and real-time view of your customers

For the customer, a lack of orchestrated messaging results in over-messaging, inconsistency, or delivery promotions on CTAs that the customer has already seen. 

- The ability to experiment in omni-channel campaigns

Aligning customer data and omni-channel orchestration in a single place transforms your unified customer view into a 360-degree view of your marketing efforts. Your marketing stack can become a marketing ecosystem where visibility and collaboration between disparate marketing functions are straightforward.

- Omni-channel experimentation 

With a CDP that allows for cross-channel experimentation, you can manage end-channel execution from a single platform.

Conclusion

Now’s the time to make the most of your Snowflake investment. By using a CDP with Snowflake, marketers can activate the customer data required to build personalized marketing campaigns.

Simon AI, an industry-leading CDP, is reimagining the road to 1:1 customer relationships by unblocking data, simplifying workflows, and putting the Data Cloud at the heart of the tech stack.

The Simon CDP is loved by marketers, trusted by data teams, and empowers enterprise teams to deliver the personalized experience customers crave. 

Ready to dive into the CDP selection process? Check out our latest CDP Buyer’s Guide for the information you need to know.

Learn how Simon AI can help fyou create personalized customer experiences

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