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Do you feel like you’re missing important data fields when trying to execute marketing campaigns? Are you frustrated with the disconnect between your data team’s priorities and your marketing goals? If so, you’re not alone.

As a data-driven marketer, you know what needs to be done to build your brand and meet performance goals. However, when it comes time to execute, you find yourself facing numerous data-related challenges, including missing or broken data fields and issues with data formatting.

If your data team’s priorities often feel disconnected from yours, you’re also not alone. They may be too focused on writing ETL processes, predictive models, and recommender algorithms rather than supporting your marketing and personalization strategies. As a result, you may be unable to execute against your vision, leading to misalignment with your data team.

At Simon Data, many of our clients come to us facing issues like these – for example:

• When marketers go to build segments, they may be missing critical fields, for example connections between in-app product usage data and channel information around the customer’s first touch with the brand.
• When looking to optimize channels, marketers are missing important contextual information such as direct mail receipts, campaign channels, or sometimes even basics like email funnels.
  
• Marketers may have the data fields they need, but find that they’re seemingly always broken or formatted incorrectly.

Consider the age-old abandoned cart email – what does your data look like if a customer abandons their cart with three items instead of one? Are you tracking all three items – and, if yes, are you able to independently determine which one to feature in the email? The list of data issues impacting marketing productivity goes on and on and on and on.

Oftentimes, when unpacking the divide between marketing teams and data teams we find a deep disconnect in priorities. Consider how often your requests are met with long turn-around times. Or it’s that the data is sometimes there, and sometimes it isn’t. They’re seemingly always “writing ETL (extract – transform – load) processes.” But their long-term strategy and the way they work doesn’t inspire confidence in their ability to support  marketing’s goals.

So what’s really going on here?

In a best case scenario, we often encounter data teams that demonstrate a rough understanding of the data marketers need to support their goals. They’re often focused on ensuring the data is properly collected, QA’d and aggregated to support upcoming campaigns and initiatives. In this scenario, marketers may feel supported, but reality prevails: the data they require to create segments and personalize messaging simply isn’t there. Ultimately, they’re still blocked by their data teams and cumbersome upstream processes.

In a worst-case-scenario, data teams operate off in a distant land building predictive models and recommendation algorithms that solve “problems” that aren’t. Oftentimes, the working relationship consists of talking past each other while marketers focus on campaigns and personalization use cases, and data practitioners are thinking about algorithms, deep learning and GPT4.

In this environment, marketers are absolutely unable to execute their personalization strategies, and are oftentimes forced to fall back on the limited data assets they have in their systems today.

So either way, marketers still are being held back. But the good news is there are solutions – both technical and organizational – to solving these problems.

Problem #1: Misalignment around data use cases.

One of the fundamental challenges in working with customer data is articulating exactly what data fields you need, how they need to be formatted and normalized, and how this all ladders into your marketing strategy.

For any marketer that considers themselves data-driven, it is critical that you put in time with your data team. Schedule a meeting to understand their processes, tools, and challenges. Learn about the data sources they use, how they manage data quality, and what tools they use. This knowledge will help you understand any limitations and how to work with them more effectively.

On the flip side, bring them into your strategic planning process. Make sure they have a clear idea of what you’d like to accomplish in the next 3 – 6 – 12 months and a voice in designing the pathway to get there.

Problem #2: You don’t have the right systems in place to take control of your customer data.

Marketing technologies are plagued with many data problems.

The way they house customer data is rigid and inflexible

Even once you have the data in your marketing systems, it’s often not quite right, and you still need engineering support to make it usable for campaigns. For example:

• The data is not in the correct format (ex. a field needs to be a timestamp, but is housed as a string)
• Data is not standardized across systems, or has many null values
• Raw values exist, but derived values need to be calculated (ex. they have a ‘first_click_date’ field, but marketers need to calculate ‘days_since_first_click’ which would require some derivation)

Marketing technology wasn’t designed to work with your existing data infrastructure.

Do your systems integrate natively into your cloud data infrastructure across Snowflake, BigQuery, or Redshift? Do they plug into your existing real-time data, or require new custom integrations to get things to work at the speed that you need them to?

Finally, marketing systems don’t actually understand your data.

You may have transaction data in your system, but your marketing platform isn’t going to be able to create an RFM model. They may have all the signals in place to identify at-risk customers, but simply can’t predict churn.

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Introducing Simon Data’s Zero-ETL Initiative

At Simon Data, we believe in a world where much of the work your data team is doing when they’re writing ETL processes can be automated with technology.

Our Zero-ETL initiative is all about removing what we feel are unneeded dependencies that you have today with your data and IT teams. Instead of waiting on these teams to prep, stage, and transform your data – we’ve designed our platform to understand your data as it exists today, and to work on top of the systems and technologies in which your data team has invested.

Zero ETL isn’t a feature at all – it’s a new way of working that’s powered by technology that reduces and eliminates any need to rely on – or even think about! – ETL. The goal is to optimize workflows between data and marketing by making sure the data that marketers need to affect your vision and goals is at their fingertips.

How does this all work? Well – it’s a result of many things that come together:

• Native Snowflake and Cloud Data Warehouse integrations – starting with our Dataset Explorer, our platform integrates directly with your data as it exists today.
• Deep understanding of your customer’s identity – across digital, offline, on-site channels and more.
• Out of the box modeling with Smart Segments, Smart Insights, Smart Journeys, and more – including RFM modeling!
• Best-in-class segmentation – once the data is in Simon, chances are you don’t need to reformat it or have your team to do any ETL to massage it into the right form for segmentation, which means you have free reign to build the segments you need.

At the end of the day, technology won’t solve underlying personnel issues across your organization, but it can change the way teams work together across your business and optimize how work gets done. And choosing the right technology that fits not just your marketing needs but also the data requirements for your business – is a critical path to success.

Looking for more insights like this?

Check out our earlier posts in this blog series:

• Serving Your Customers & The Recipe for Success in Choosing a CDP
• The Conundrum Between Packaged & Composable CDPs

What do all customers want?

The answer is easy: They want to feel special, they want to feel catered to, and most importantly, they want to experience great service.

This is why personalizing your marketing strategy is a must for brands who want to leave a good impression and turn their one-time customers into loyal ones.

But how can you achieve that?

This is exactly what we tackle in today’s podcast.

In this week’s episode of Data Unlocked, Jason sits down with David Wachs, the CEO of Handwrytten.

David is a serial entrepreneur with decades of experience in the marketing industry. He has been featured on the front page of the Washington Post. A number of big publications also interviewed him. Many of them you know; Direct Marketing News, Crain’s Chicago Business, the American Express OPEN network, and others.

Prior to founding Handwrytten, David founded Cellit, a mobile marketing platform and mobile agency. Under David’s leadership, Cellit became a leading player in the mobile marketing space and invented the concept of mobile customer relationship management.

Today, he is at the head of Handwrytten.

Handwrytten is the largest provider of automated handwritten notes in the world. The platform allows customers to send notes from their CRM system, such as Salesforce or through custom integration.

Used by major companies, Handwrytten is revolutionizing the way brands and people connect.

In this episode, David and Jason discuss Handwrytten, why you should be sending your customers handwritten notes, the renaissance of direct mail, and more.

Are you ready?

Let’s dive in.

An effective marketing strategy is a must if you want to grow your brand.

After all, no matter how good your products or services are, if people are not aware of them, you won’t be able to succeed in today’s market.

Brand awareness is crucial to a business’s survival, and what better way to achieve that than through great marketing?

Focusing on your marketing funnel can do just that, which is why this is exactly what we discuss with today’s guest on the podcast.

In this week’s episode of Data Unlocked, Jason sits down with Ben Dutter, SVP of Strategy at Power Digital.

Ben is a marketer with decades of experience. He focuses on maximizing marketing ROI, incrementality, and strategy for hundreds of brands.

Before becoming the SVP of Power Digital, Ben worked as their VP of Performance Marketing. His work was focused on building and leading the media planning team as well as working on strategy and client retention for Power Digital.

Power Digital is a leading, privately held growth marketing firm helping brands ignite revenue and brand recognition.

They help their clients grow their businesses by developing custom marketing playbooks fueled by data, market trends, and industry insights. This helps their clients set themselves apart from their competition.

In this episode, Ben and Jason discuss some of the Best Practices around the marketing funnel and customer lifecycle, the strategies behind them, how to measure them, and more.

Ready for this?

Let’s dive in.

Most brands that start on the internet use social media and email as their biggest marketing channels.

And though effective, these channels can become inefficient once these e-commerce brands grow and mature.

That is when companies start moving their marketing efforts to places with a wider audience, such as podcasts, TV, and radio.

However, how can they measure results when they’re using such non-trackable channels?

This question has baffled marketers all around the country (and dare we say, the world?), and this week’s guest has made it his career’s mission to find the answer.

In this week’s episode of Data Unlocked, Jason sits down with Michael Kaminsky, the founder and CEO of Recast.

Michael is a trained econometrician with a background in healthcare and environmental economics.

Before founding Recast, he built the marketing science team at men’s grooming brand Harry’s Grooming.  

Today, he is using his expertise to grow Recast.

Recast is a media measurement platform that helps marketing teams save millions of dollars of wasted advertising budget. They do so through a proprietary measurement model.

In this episode, Michael and Jason discuss how to measure marketing results for non-trackable channels, why Michael started Recast, how to allocate your marketing budget, the importance of upper funnel awareness, and more.

Ready to learn more?

Let’s dive in.

There’s been a lot of chatter recently about packaged vs composable customer data platforms (CDPs), starting with Arpit Choudhury, founder of Data Beats and astorik, explaining the two approaches in an article here, and continuing with Michael Katz, CEO and Co-founder of mParticle, who argues here that the dichotomy between packaged and composable CDPs may be false.

Others in the space are questioning what exactly a CDP is, and whether a CDP is right for them. And part of that stems from the disruption of cloud data warehouses, like Snowflake.

So we posed a question: Is Snowflake killing the CDP?

To discuss this conundrum between packaged and composable CDPs and how the cloud data warehouse has changed what it means to own and activate your customer data, we invited Arpit and Michael, along with Luke Ambrosetti from Snowflake, and our very own Jason Davis, CEO and Co-founder of Simon Data for a quick chat.

Watch the previously live video for a discussion on:

• What a CDP is?
• What is a packaged vs composable approach?
• What are the major considerations when choosing a CDP?
• Is Snowflake really killing the CDP? Or can the two applications play nicely?

Is Snowflake killing the CDP? from Simon Data on Vimeo.

As marketers, we know that advertising dollars don’t grow on trees. That’s why when it comes to paid media, we want to make every penny count. But how can we ensure that our campaigns are hitting the mark? The answer lies in data.

Data is the lifeblood of paid media. It tells us who our audience is, what they want, and how they’re interacting with our ads. By harnessing the power of data, we can create campaigns that are not only effective but also cost-efficient.

So, how can you use data to take your paid media to the next level? Here are a few tips and tricks to get you started:

Double down on data…but carefully

With the elimination of third-party cookies on the horizon, and the Apple privacy crackdown of data, marketers are increasingly trying to improve their paid media efforts and expand their reach through different channels and targeting methods. Now is the time to lean into first and zero-party data to leverage your data to create your audiences through a variety of end channels.

“Third-party data deprecation is only going to continue,” says Ben Dutter, SVP of Strategy at Power Digital. “After cookies, it’ll be IP. After IP, it’ll be unified identifiers. The only reliable way forward is to create enough value in the data exchange that the end user volunteers their data over to the business.”

But in the complex world of data, without the tools or resources to access, aggregate, analyze, and organize your customers’ data, creating lookalike, suppression, and retargeting models with real-time data becomes impossible.

Here are some common mistakes and pitfalls to watch out for:

• Most marketers manually upload CSVs with customer data to create lookalike and suppression audiences to each individual ad channel. By doing this manually, the customer data is immediately out of date and you need to continuously upload CSVs to update the customer list with new data.
• CSV files have limited overall customer data because they are being pulled from siloed sources (i.e., Shopify website, email engagement, SMS, etc.). And combining this information requires additional resources to combine the data into a usable CSV. This can take days.
• When suppressing ads, marketers will cast the net too wide. For instance, your first instinct may be to hide all ads from recent purchasers,  but you could use ads to cross-sell or up-sell other products. Someone who recently bought a mattress shouldn’t be excluded from bedding ads.

Unleashing the power of customer data platforms for paid media success

“The better a business understands it’s customer, the better it’s able to make smart marketing decisions,” says Dutter. “Building a valuable data exchange between the customer and the business means that those decisions have to benefit the customer in some way – better experience, better targeting, better recommendations, etc.”

A Customer Data Platform (CDP) can remove the friction between data and media deployments, enabling that link between better data and customer experience. Simon Data is built on Snowflake’s cloud data warehouse, enabling real-time activation of the most up-to-date data from every source, effectively eliminating those blocking data silos. This removes the need for manual CSV uploads, easily integrating directly with ad channels to create audiences using Simon’s segmentation tool, then creating a trigger to upload these audiences to paid channels in real-time.

This feature also automatically removes and re-assigns contacts from audiences as they meet specific criteria. You can use triggered-based actions to develop your audiences (i.e., abandons cart and hasn’t subscribed to any channels, send to FaceBook) within Simon’s orchestration tool and automatically send customer data based on the action criteria. Simon allows you to better understand your customers by segmenting based on LTV, churn propensity, and product recommendations through our Simon Predict ML models.

How to maximize the impact of first-party data

“There’s only two ways to make revenue: more customers or more valuable customers. Integrating first and zero-party data on your customer list is the most reliable way to maximize the value of each customer, purchase, and cohort,” says Dutter. “While paid media is traditionally an acquisition effort, it can also be used to carefully upsell, and message existing or lapsed customers to maximize their LTV.”

Here are some ways Simon Data can help your paid media strategies in all three use cases:

Acquisition:

• Use lookalike models based on activity to help lower customer acquisition costs. For example, add people who recently abandoned a cart or return customers who are likely to purchase higher-cost items.
• Improve ROAS by suppressing known users from acquisition campaigns. This ensures you’re not wasting your budget on marketing to already-loyal customers and not offering new customer deals and discounts to those who don’t need them.
• Sometimes, potential customers simply need to learn how others use your product in ways they haven’t considered. Use customer testimonials that show the success of others using your product to spark interest for targeted abandonment and lookalike campaigns to those who have browsed specific pages and items.

Retention or Upsell:

• Reward those who reward you. Ask for new customer referrals in exchange for discounts and gifts by encouraging feedback on social media or your website with your highest LTV customers.
• Send a push notification for new, popular social posts to drive engagement. Then create lookalike models for people who received and clicked the notification.
• For customers that made their first purchase, create a lookalike audience, encouraging them to join your loyalty program and get a certain amount of points for signing up in a specific time frame.
• Send pre-targeted ads to inactive lookalike audiences before you reach out to them via email. This way, once they receive your sales team’s email, they’re already re-acquainted with your product.
• If you plan to have an event or sponsorship near a specific area, create audiences with that specific location and a sign-up sheet to encourage customers to go.

Re-Engagement:

• Create segments of lapsed users based on their engagement data and reach out to them via social or owned channels with tailored content, supporting more frequent—and deeper—engagement. Customize these messages with information about each user’s historical activity and purchases to highlight their previous usage.
• For customers that have left a complaint or written a bad review recently, suppress them from your advertising campaigns and nurture campaigns through their preferred channels with personalized content to win back their trust.
• Leverage the user data at your disposal to lure back lapsed users by sending personalized re-engagement messages based on their past engagement. Use owned messaging channels and social advertising to reach them where they’re active, and consider using promotion codes to provide clear value and drive future conversions.

Better customer data = Better customer experiences

The most important thing to remember is that your data is the foundation for all your campaigns. If you’re not using the right segments, sources, and models, it doesn’t matter how much effort and spend you put into your paid media strategies; you’re not going to see the results you want. Tools like CDPs can take the burden off of not only marketing teams but the IT and data teams who support them. By putting accurate customer data at the heart of your strategy, your outcomes will not only be higher revenue results but happier customer experiences.

Learn about how Simon Data can help support your paid media strategy.

If you were on the internet in 2022, then chances are you stumbled upon articles, think pieces, and TikTok videos about the formula shortage.

In February 2022, the FDA recalled three types of the most popular powdered formulas for safety reasons. Add to that the impact of the pandemic on the market, supply chain issues, and suddenly, we had a formula shortage on our hands.

Many other formula companies were overwhelmed by the sheer amount of demand.

One company wanted to be able to keep supplying their subscribers with formula, so they took a peculiar decision: They shut off all of their marketing. And we mean, all of it.

A pretty drastic decision, right? And yet, it worked!

This is exactly what we discuss in this episode of the podcast.

In this week’s episode of Data Unlocked, Jason sits down with Cherene Aubert, Head of Growth at Bobbie.

With over a decade of marketing experience, Cherene is an award-winning ecommerce leader who’s grown over a hundred direct-to-consumer businesses.

Today, Cherene is using her expertise to help grow Bobbie.

Bobbie is the first and only mom-founded and women-led infant formula company in the U.S. Their European-style recipe is the only infant formula to receive both the Clean Label Project’s Purity Award and Pesticide Free Certification.

In this episode, Cherene and Jason discuss the transformative time Bobbie went through during the pandemic, navigating the Great Formula Shortage of 2022, what’s driving the company’s marketing, how Cherene went from Head of Growth to Head of Slowth, and more.

Ready to learn more?

Let’s dive in.

It’s tough out there. Marketing budgets have been cut, teams are busier than ever, and resourcing is as tight as it’s ever been.

Yet, despite all this, customers just don’t care. They expect just as much today – if not more – than they did yesterday. Your customers are as hungry as ever and you need to serve them.

Data is to marketers what ingredients are to chefs. Even with the fanciest kitchen equipment (or in marketer’s case technology), without good ingredients you’ll never serve a good meal.

Usable, accurate, and precise data is one of the biggest limiting factors for modern marketers. Every time you might try to “cook up” a new campaign data is invariably missing, incorrectly formatted, or just straight up incorrect.

In my last post, I discussed the conundrum between packaged and composable CDPs.

As a quick recap, here’s the general landscape of packaged and composable CDPs.

Packaged CDPsComposable CDPsThe positives…Streamlined workflow designed for key marketing applications and campaignsData flexibility, purpose built for your cloud data environment and modern data stackThe negatives…Severe data limitations across integration and ongoing data support and accessDisconnected workflows with campaign execution that requires multiple systems and teams for execution

Now let’s take it a step further.

Option 1: Composable CDPs

Data is the problem.

Your first stop as a Michelin starred chef–ahem, digital marketer– is a conversation with your data team around what’s hot and what’s new.

Within moments, you regret having asked this question, and you’re overwhelmed with a dizzying set of technical problems and buzzy words like “Reverse ETL.” The data team is talking about building a kitchen from scratch and setting up a fully organic farm for the best ingredients. Why not just fabricate your own tableware while you’re at it?

At one level this approach sounds great in enabling you to solve your data challenges with your data team, even though it sounds really, really complex..

But, as you dig deeper into this plan, you find yourself asking why you’ve never heard of (or used) any of these tools – and then start asking if any part of the Composable CDP was actually designed for marketers to use. You don’t really know how a sous vide works – and you don’t have the staff to shrink wrap, par boil, and do hours of prep every time you need to cook a steak.

Option 2: Fully Packaged CDPs

Packaged CDPs take the exact opposite approach and are designed to work out of the box without any dependencies.

This unfortunately comes at two real costs. First is the cost of implementation – you’re effectively rebuilding what your data team has built and while the “out of the box” nature of these systems is prescriptive, it’s also costly and slow. The second cost pertains to capabilities. Whereas the Composable CDP allows you to specify your identity model with infinite precision to create the perfect framboise, Packaged CDPs serve up a much more consistent – yet at times bland – end customer experience.

On the one hand you have nearly limitless flexibility with the Composable CDP but that comes at an enormous technical and financial cost. On the other hand, Packaged CDPs feel, well, underwhelming.

Like setting up the right kitchen, your CDP selection needs to focus around two key dimensions:

Speed & Access: Ultimately your team’s success is limited by lead times and workflow limitations related to data. Ultimately, just as extra trips back and forth to the grocery store or a bad Instacart shopper can mean you’re cooking your meal well past dinner time, there are many things out of your team’s control that may hinder success in your CDP implementation. For instance, you may need additional IT support and resources to overcome data formatting issues and segmentation limitations. Waiting on these resources takes time, and can prevent your team from being able to move quickly and efficiently.

Quality & Prep: Your grandmother may have made everything from scratch, but in today’s world you don’t have time for this. Sauces, stocks, fillings, etc. – even if you have the ingredients in your fridge to make these, you’d still rather not. Finding the right mix of pre-made ingredients is critical. Hamburger Helper is certainly easy to make, but the end result lacks the quality your customers expect and deserve.

The world’s best restaurants have figured out how to prep ingredients during the day  to accommodate peak demand at night during dinner. Your CDP should be no different: core problems around identity modeling, multi-channel data management, and lifecycle prediction can and should be handled flexibly by your CDP without making big sacrifices around quality or speed.

Ultimately, success lies in finding the right solution that allows your team to move quickly and deliver high quality results.

As you’ve undoubtedly seen on late night infomercials, there has to be a better way!

At Simon, we’ve taken a unique approach that allows you to have your cake and eat it too.

Philosophically, we believe that a CDP should work out of the box and satisfy core use cases & requirements of today’s marketing workloads. But at the same time, we’ve designed our core data layer to work natively with your existing data infrastructure in a way that enjoys the same benefits of composable approaches.

We believe in a world where packaged conveniences shouldn’t require huge sacrifices – both in terms of aligning with your data strategy and more importantly serving your customers well.

In part three, I’ll unpack just this – and show how modern marketers are leveraging their cloud data investments to drive powerful customer experiences.

As brands, the only way we can achieve success is if we understand our customers and our target audience better.

And that means asking and answering the right questions.

We need to understand how our customers think, feel, and behave. And to do so, we need to answer two important questions: ‘How?’ and ‘Why?’

Knowing the answers to these questions will help you not only read your customers’ minds, but offer them what they truly need and desire.

And to achieve that level of understanding, you have to use the right data, which brings us to this week’s guest…

In this week’s episode of Data Unlocked, Jason sits down with Lucie Buisson, Chief Product Officer at Contentsquare.

Lucie started her career over a decade ago at Sarenza. Then, nine years ago, she moved on to Contentsquare, and she’s been with them ever since.

Contentsquare is the global leader in digital experience analytics. Their mission is to move beyond traditional analytics and enable an unprecedented understanding of the customer experience.

The company’s AI-powered platform provides rich and contextual insight into customer behaviors, feelings, and intent, which enables their clients to build customer trust and scale their businesses.

In this episode, Lucie and Jason discuss the lifecycle of data, how to understand your customers better, Contentsquare’s work, and more.

Ready to learn more?

Let’s dive in.

The ways brands use and track consumer data are under a white-hot spotlight. Once, data attribution and consumer identifiers were easy to come by. Now, data privacy has taken center stage, making it more difficult for marketers to deliver on their directives of personalized experiences for every customer.

In June 2021, Apple announced a Mail Privacy Protection (MPP) feature to allow users to mask their email open rates and device usage. This is a prime example of how ad targeting is being directly affected by privacy concerns.

Because of such updates, marketers are having to change the way they collect relevant data to personalize their campaigns and user experiences. Third-party data is no longer the bedrock of digital advertising.

This means marketers have to find creative new ways to optimize their messaging, reach their ideal customers, and capture revenue.

Welcome to the cookieless future.

What does cookieless mean?

Cookieless tracking refers to a company’s ability to track users’ online activity without relying on third-party cookies.

Cookies are small pieces of data sent from a website and stored in a user’s web browser while the user is browsing the site. Cookies enable companies to track people’s online activity, such as which pages they visit, how long they spend on the site, search queries, what they click on, and even more private information that can be used for targeted marketing purposes.

Thanks to privacy and data security concerns coming to light, many people have become more aware of the potential risks associated with cookie-based tracking—especially third-party cookies. This has led to an increased demand for more private, secure options. As a result, we’re seeing an increase in companies moving toward cookieless tracking.

Cookieless tracking relies on other technologies, such as scripts that run when a user visits a web page. That information is then sent to a storage server rather than being stored in cookies.

Though different, this kind of tracking doesn’t come without its benefits. Because cookieless tracking is less dependent on third-party data, it is a more secure and reliable way for companies to track users’ online activity.

It also enables companies to track users across multiple devices and platforms, allowing them to build more comprehensive user profiles. Cookieless tracking also helps companies comply with new privacy regulations, providing a better experience for users.

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The reality of a cookieless future is imminent. How are you preparing your clients for it?

Watch a discussion on how to help your clients adapt and thrive in a cookieless world. Gain practical insights on how to speak to client needs for managing and activating customer data.

Watch today.

The impact of a cookieless future

The end of tracking with third-party cookies will have a major impact on the digital marketing industry, as well as a slew of other industries that rely on tracking user activity to grow their revenues.

How specifically will the cookieless tracking trend affect the marketing industry? We see six major areas of impact:

1. Development of new strategies

Marketers will need to develop new strategies for targeting audiences, gathering insights, and understanding the performance of their campaigns.

2. Budget allocation

New measurement strategies mean marketers will need to reallocate funds as they transition away from cookie-based analytics. Additional spending may also be required in the short term to bring together the teams who can plan and implement these strategies.

3. Additional involvement of IT teams

This shift in tracking will require more input from IT teams in order to successfully structure new cookieless tracking solutions.

4. Greater reliance on contextual targeting

Cookieless tracking will lead to an increase in contextual targeting. Marketers will have to develop a deeper understanding of their target audiences and their online behaviors. It will no longer be enough to build customer profiles based on basic cookie-supported data.

5. Prioritization of data privacy

With the increasing focus on privacy, marketers will need to prioritize data privacy as they update their tracking practices to comply with regulations such as the GDPR.

6. Growing need for cross-device tracking

With cookieless tracking, marketers will need to invest in cross-device solutions in order to accurately track user activity.

With a robust customer data platform (CDP), you can gather data from across devices and platforms to create unified customer profiles and create sophisticated audience segments that sync to all the places you engage with your customers.

How will cookieless targeting affect the customer experience?

A cookieless strategy can be great for the customer experience in a number of ways. For one, using first-party data—that is, data provided directly by customers—allows companies to target customers with more personalized and relevant offers that they’ll actually be interested in receiving.

Additionally, cookieless tracking is more secure and transparent than traditional cookie-based tracking, which means customers can better trust the companies they are dealing with.

Finally, cookieless tracking can help companies align with new privacy regulations, ensuring that marketing data is handled in a way that is both ethical and compliant.

A note on cookieless targeting and first- and third-party data

First-party data is data collected directly from the customer, such as user name, email, and survey responses. Third-party data is collected from external sources, such as data brokers.

Cookieless strategies can be used to target users without requiring the use of third-party data. This means that companies can use sophisticated targeting methods without sacrificing privacy or security, as the data is not shared with any external sources.

How can marketers prepare for a cookieless world?

As the cookie-based tracking model becomes obsolete, the collective approach to digital marketing will go through its own evolution. Marketers who want to stay ahead of the curve should start preparing for the cookieless future now.

Here are a few tips to help you get started:

1. Understand the different technologies. Familiarize yourself with the different cookieless tracking technologies available—essentially first-party data tracking—like through point-of-sale systems or email marketing efforts.
2. Identify the most suitable tracking solutions for your business. Evaluate different tracking solutions to determine which ones will provide the best results for your business.
3. Have a comprehensive user privacy policy. Make sure your privacy policy is comprehensive, covering all the data you collect and how you use it.
4. Educate your team on cookieless tracking. Ensure your team is educated on alternative tracking technologies and how to use them.
5. Re-evaluate your marketing strategies. Consider how cookieless tracking could influence your marketing strategies and adjust accordingly.

By understanding and preparing for the cookieless future, marketers can ensure they remain competitive in the digital marketing landscape without sacrificing revenue or slowing down growth.

Cookieless targeting strategies

Believe it or not, cookieless targeting strategies can be more precise and effective than cookie-based targeting.

Here are a few targeting strategies that work without the use of cookies:

• Offline data targeting: This means using offline data, such as purchase history from your customer relationship management platform (CRM) or CDP, to target your customers with relevant ads.
• Contextual targeting: This is when contextual data, such as the type of content being viewed, is used to target users with relevant ads.
• Geotargeting: Geotargeting employs users’ location data to target them with location-specific ads.
• Device targeting: With this type of targeting, users’ device-specific data—such as device type and operating system—is used to deliver them relevant ads.

By using cookieless targeting strategies, marketers can ensure their campaigns successfully reach the most relevant users.

But how do you actually implement these strategies?

Cookieless tracking with the Simon CDP

Simon Data offers a comprehensive customer data platform that helps marketers track, store, and analyze customer data without relying on cookies.

With Simon, you can gather customer data from across various platforms and touchpoints and combine it into a single, unified customer profile. With all the data in one place, it’s easier to understand your customers and create better, more granular audience segments. This means you can create more personalized, secure customer experiences—all without using third-party cookies. Simon also enables marketers to comply with new privacy regulations, such as the GDPR, ensuring all your customer data is handled in a legal and ethical manner.

Learn how Simon Data can help support a cookieless paid media strategy

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If we’re living in the “decade of data,” why is data driven marketing still so hard?

The answer lies in the fractured martech landscape.

On one side we have fully featured marketing clouds. Salesforce Marketing Cloud is largely derived from an acquisition they made in 2013 of ExactTarget – a company which prided themselves as “marketers building software for marketers”.

But, more recently, a secondary camp has emerged with the fundamental premise that data today is incredibly complex – and that maybe marketers shouldn’t be building the software that powers all this. This camp has focused on complex data requirements – but has fallen short of marketer usability north stars that the ExactTargets of the world set out to build.

Let’s dig into what happened and how this split has resulted in a real conundrum for marketing teams trying to align on their martech & CDP strategy.

Path #1: Reverse ETL & The Modern Data Stack.

The Modern Data Stack has evolved as a set of roughly 1,000+ companies designed to clear, transform, aggregate, analyze, and integrate data.

At the core of the Modern Data Stack is the Cloud Data Warehouse with the primary players being Snowflake, Bigquery (Google), Redshift (Amazon), and Databricks.

These tools in some sense represent the ultimate playground for today’s data engineers, analysts, and data scientists. The tech is new, cool, fun, and interesting – and data experts spend their working hours comparing options, evaluating path forwards, and making noise on social media as well. If you’ve heard of the “Composable CDP”, these are the tools that need to be plugged together.

Path #2: Fully Packaged CDPs.

The roots of CDP as a category lie in data collection and data infrastructure that was built specifically for Martech applications. Today, platforms such as Segment & Tealium have reached a point of maturity where they’re able to satisfy many core marketing and customer facing applications – but they do so at great cost of integration and infrastructure investment. =

The beauty of the Modern Data Stack & centralized data infrastructure is that of building once, build great, and building completely – and then benefiting downstream. Specialized data infrastructure is by its nature duplicative.

Packaged CDPs

Composable CDPs

The positives…

Streamlined workflow designed for key marketing applications & campaigns

Data flexibility, purpose built for your cloud data environment & modern data stack

The negatives…

Severe data limitations across integration and ongoing data support & access

Disconnected workflows with campaign execution that requires multiple systems & teams for execution

With this divergence of data & technology strategy, the decision on which path to go down is a big one – and the implications are real.

Should you go down path #1, align yourself with your enterprise data strategy, and hope you can come out the other side with something that actual works?

Or do you go down path #2, invest heavily in integration & implementation, de risk your ability to get to end value – at the cost of undermining your data investments and unlocking the untapped potential that your organization has spent millions of dollars on?

At Simon, we believe that there’s a “have your cake and eat it too solution” – stay tuned for more next week as we dive into our approach to the category and something we call “Zero ETL”.

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In today’s market, crypto is more present than ever.

The pandemic has made it easier for people to buy, sell, and trade digital currencies such as Bitcoin and Litecoin.

The last few years has also seen the rise of NFTs all around the world, which has completely changed the game.

Suffice to say, cryptocurrencies are democratizing the financial world.

However, that doesn’t mean that the crypto market doesn’t face its own set of unique challenges.

To discuss these problems and challenges, we’ve invited an expert on today’s podcast.

In this week’s episode of Data Unlocked, Jason sits down for a second time with Mayur Gupta, the CMO of Kraken.

Mayur is an engineer who evolved into a marketer with several pivots through his career.

He spent the first half of his career in tech and product management, but today, his focus has shifted to marketing.

Mayur has worked with some of the biggest companies in the world, such as Spotify, IBM, Freshly, and now Kraken.

Kraken is a digital asset exchange whose mission is to accelerate the adoption of cryptocurrency. They help their customers buy, sell, and trade digital currency in simple and effective ways.

In this episode, Mayur and Jason discuss the challenges with crypto and marketing, his role as a CMO of a fast-growing crypto business, financial education, and more.

Ready to learn?

Let’s dive in.

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