Retail marketers need AI that delivers ROI now

Marketing leaders at retail brands are under pressure to prove AI can drive revenue now. At Shoptalk Fall 2025, I heard the same sentiment over and over—urgency to show results, hope that AI can deliver them, and confusion about how to get there.

Retail brand marketing teams are expected to elevate the customer experience and drive both conversion and LTV with the same or fewer resources. AI has moved fast from experiment to mandate.  Leaders expect AI to finally solve the personalization challenges that have slowed their marketing teams for years.

But most teams aren’t ready. Teams are lean, data is often locked away or incomplete, and many depend on data teams (and sometimes they don’t have them). The promise of personalization still feels more like an aspiration than a reality to many marketers. 

I’ll sum up what I heard from marketing leaders in dozens of meetings last week in Chicago: 

1. Data is still the biggest barrier

Only about one out of three marketers I spoke with had their data in a good place, running both a cloud data warehouse and a customer data platform. Too many are still treating their CRM as the database of record. That’s a barrier to AI success. 

Without a modern data foundation, AI can’t deliver. AI works as well as the data it operates on. Personalization at scale requires data that’s unified, accessible, and ready to act on. With that in place, AI agents can handle complex work and deliver value. 

• Simon AI helps marketers explore all their data - first, second, and third-party data, structured and unstructured. It turns messy data into marketer-ready fields in minutes, not weeks. Learn more about the AI-first Composable CDP and the new operating model enabled by Composable Simon AI Agents. 

2. Context is the signal marketers don’t realize they’re missing

Marketers spend most of their time wrestling with first-party data, with some dabbling in second-party data. But bring up third-party signals like weather or social trends, and the energy changes. Everyone agreed context is powerful, and most immediately asked, “How would we do that?”

Traditional data sources and CDPs tell you what happened (clicks, opens, drop-offs) to what customers, but they can’t tell you why. Without context, personalization is generic.

• Simon AI activates real-world signals like weather, inventory, and social spikes to make campaigns timely and relevant. Learn more about contextual personalization. 

3. Execution is the everyday struggle that forces a painful trade-off

This was the most consistent frustration I heard. Even with data in place, teams struggle to move from insight to action. Campaigns take too long to build, and there’s too much dependency on technical teams. By the time a campaign goes live, the customer moment has passed.

Most marketing platforms force a painful trade-off. When you focus on volume, performance drops. As you personalize to convert better, volume drops. All your effort is on a few big bets. That’s the reality holding brands back.

The Simon AI Personalization Studio ends that trade-off — using Agentic AI on an AI-first Composable CDP to automate attributes, audiences, and workflows on live data while marketers stay in control.

4. The CDP market is noisy — and confusing

On the expo floor and in conversations with marketing leaders, it's clear that the CDP category has never been more crowded. Every vendor promises personalization. But most are layering on point-solution AI — faster content, better predictions, next-best actions.  

That isn’t solving the real problem. Real personalization depends on two giant leaps forward: 

• Marketer access to live, usable, complete data that is ready for a campaign
• The ability to execute hundreds or thousands of contextually relevant campaigns at speed and scale

Instead, most CDPs still leave marketers stuck with limited, predefined data, an inability to generate insights quickly, and a heavy dependence on data teams. This results in slow execution and a default to generic campaigns for segments. Campaigns take six to eight weeks to launch, long after the customer moment has passed.

• Simon AI cuts through data complexity with an AI-first Composable CDP and Data Agents that transform messy inputs into usable fields and live audiences. Learn more about Simon AI Data Agents that are live with customers now. 
  

Turn messy data into marketer-ready attributes in hours, not weeks.

5. The cost of inaction is rising — differentiation depends on AI now

Marketers told me competition is fiercer than ever, and the gap between their investments and ROI is only growing. Time is essential — fast movers that use AI to solve customer experience problems today will have the edge in a future defined by rapid innovation and learning cycles.

For the moment, teams are overwhelmed with data but too slow to activate it, leaving campaigns generic and mistimed. Consumers, meanwhile, expect relevance instantly — whether in email, SMS, ads, or future agent-driven experiences.

Brands that move first will define the new standard for performance. Differentiation depends on using AI to close the gap between signals and execution.

• With Simon AI, brands accelerate differentiation by launching campaigns faster, acting on more signals, and scaling personalization without trade-offs. Learn more about the new marketing workflow that starts with a goal, and agents handle the hard work to wrestle with data and execution.
  

Early adopters of Simon AI are seeing measurable impact:

• Launch contextually relevant campaigns up to 10x faster
• Achieve higher conversion rates through adaptive personalization
• Drive material revenue growth by putting more campaigns in market, faster

Summing it up

Contextual personalization at scale is no longer optional, and the cost of waiting is only rising. Brands that move first are setting the new standard for performance.

That’s my read from Chicago. If you’re wrestling with the same challenges, let’s connect.