Today, we’re joined by Zainab Hussain, a leading e-commerce strategist specializing in customer engagement. For years, retailers have chased the dream of true one-to-one personalization, but the reality has often been clunky, manual, and limited to broad customer segments. Now, with the advent of sophisticated AI, that dream is becoming a scalable reality. We’ll explore how this new technology is moving beyond guesswork to deliver millions of unique offers, how retailers can maintain strategic control while embracing automation, and how this data-rich approach is reshaping the crucial relationship between retailers and their CPG brand partners.
Retailers have long used broad, segment-based promotions. How does your new AI-powered solution move beyond this manual approach to deliver truly one-to-one offers at scale, and what specific operational workloads does this automation reduce for a marketing team? Please share some examples.
That’s really the core of this evolution. For decades, “personalization” meant a marketer would spend days, if not weeks, painstakingly defining a customer segment—say, “lapsed high-spenders who buy organic”—and then crafting a single offer for that entire group. It was a manual, inefficient process that felt more like using a sledgehammer than a scalpel. This new AI-powered approach completely flips that model. Instead of a human defining a handful of segments, the AI analyzes each shopper individually and generates a unique offer just for them, in real time. It can do this for millions of shoppers simultaneously, something a human team simply could never do. This completely eliminates the workload of manual segment creation, offer assignment, and campaign deployment, freeing up marketing teams to focus on overall strategy and brand goals rather than getting bogged down in the tedious mechanics of execution.
Enterprise retailers could see significant topline growth from scaling personalized offers. What are the key mechanisms through which your solution helps generate this value, and can you walk us through how a retailer might measure the return per promotional dollar spent using this system?
The value generation is massive, and it’s driven by relevance. The Boston Consulting Group estimates that scaling personalized offers can create over $100 million in topline impact for a large retailer. This isn’t just a theoretical number; it’s a direct result of replacing generic, blanket discounts with offers that genuinely resonate with an individual’s shopping habits and preferences. When an offer feels like it was made just for you, you’re far more likely to engage with it, which drives both immediate sales and long-term loyalty. As for measuring return, that’s where the real magic lies. With old segment-based promotions, it was always a guessing game. You’d see a sales lift but couldn’t be sure what caused it. Because this system issues and tracks offers at the individual level, the attribution is crystal clear. We can see exactly which customer received which offer, when they redeemed it, and what they purchased. This allows a retailer to calculate a precise, undeniable return on every single promotional dollar spent, a level of financial clarity that was previously impossible to achieve.
With AI automating millions of individual offers, some retailers might worry about losing strategic control. How does Personalized Promotions balance this automation with centralized oversight, and what kind of customizable guardrails can a retailer put in place to align the AI’s actions with specific budget and brand objectives?
That’s a very valid concern we hear from retailers. The idea of an AI making millions of decisions can feel like you’re handing over the keys to the kingdom. But this system is designed to be a powerful tool, not an unaccountable black box. The retailer always remains in the driver’s seat. They establish the strategic framework from the top down by setting what we call customizable guardrails. For example, a marketing director can set the total promotional budget for the quarter, specify that offers should focus on driving trial for a new product line, or put a cap on the maximum discount percentage allowed. The AI then operates creatively and efficiently within those boundaries. It has the freedom to personalize millions of offers, but every single one of those offers will adhere to the centralized objectives and budget discipline set by the retailer. It’s the perfect balance of AI-driven scale and human-led strategic control.
The platform promises to strengthen retailer-supplier collaboration. How does individual-level attribution change the conversation around CPG brand funding for promotions, and what kind of new performance metrics can suppliers expect to see that they couldn’t get from traditional segment-based campaigns? Please elaborate on this.
This really transforms the retailer-supplier relationship from one based on hope to one based on data. Historically, a CPG brand would fund a promotion and get a vague report back saying, “Sales in the Northeast region were up 5%.” It was impossible to know if their investment truly worked or if it was just a coincidence. Now, with individual-level attribution, the conversation is completely different. A CPG brand can fund a campaign and receive clear, granular reporting showing precisely which shoppers were influenced and the exact incremental sales their investment generated. They can see performance metrics that were previously unavailable—not just audience reach, but true behavioral change at the individual level. This gives CPGs a proven, measurable way to influence customer behavior, creating undeniable proof of impact and making it far easier for them to justify and allocate their promotional funding with confidence.
Your Personalized Challenges solution has seen significant ROI with major retailers. How does the new Personalized Promotions solution complement or integrate with existing gamification and loyalty programs to create a more comprehensive customer engagement strategy? Can you provide a step-by-step example?
They are designed to work together as a full suite, creating a much richer customer experience. Our Personalized Challenges solution, which uses gamification, has been incredibly successful, generating a 7:1 ROI for retail giants like Tesco and Morrisons. Personalized Promotions acts as a powerful enhancer to that. Imagine a customer is participating in a “challenge” to buy five different types of fruit in a month to earn bonus loyalty points. The system sees they’ve bought four but haven’t purchased any berries. Instead of just waiting and hoping, Personalized Promotions can intelligently step in. It could automatically send that specific customer a personalized offer, like “20% off fresh strawberries this week,” to give them that final nudge to complete the challenge. This creates a seamless, dynamic loop where the gamified loyalty program engages the customer, and the personalized offer helps them succeed, making the entire experience more rewarding and effective.
What is your forecast for the future of AI in retail personalization?
I believe we are just scratching the surface. In the next few years, AI will become as fundamental to retail as the cash register. It will move beyond just personalizing offers to anticipating needs. The systems will become so intelligent that they can predict a customer is about to run out of milk and prompt them with a reminder, or suggest a new recipe based on their past purchases and what’s fresh in the store today. This hyper-personalization will extend across every touchpoint, from the app to the in-store experience, creating a truly omnichannel journey that feels uniquely tailored to each individual. The end goal is to make shopping feel less like a transaction and more like a helpful, intuitive conversation, and AI is the only tool powerful enough to make that a reality at scale.
