Summary: Cognitiv's Daniel Mahl and Welch's Katelyn Nugent explore how CPG brands can activate retail and purchase data in-flight, using AI-powered predictive modeling to identify high-intent audiences, optimize campaigns in real time, and drive incremental growth beyond traditional post-campaign reporting.
Digiday's Media Buying Summit in Nashville brought together innovative minds in agency, brand, and adtech. On the mainstage, I had the opportunity to be joined by Katelyn Nugent, Head of Integrated Marketing and Communications at Welch's, for a conversation about what happens when retail data stops being a recap tool and starts becoming a growth engine.
For years, most CPG brands have used retail and purchase data to understand what already happened. Sales lift. Regional performance. SKU breakdowns. All useful indicators of campaign success, but they are inherently backward-looking.
What we explored on stage was a different model, powered by Cognitiv’s deep learning advertising platform. One that leverages retail data to inform decisions in-flight, predicts who is most likely to convert next, and enables real-time orchestration across portfolios, occasions, and audiences.
Moving Beyond Static Segmentation
Welch's manages three distinct product portfolios, each with its own seasonality and occasion-based marketing strategy. As Katelyn shared, the risk isn't just inefficiency — it's missed incremental growth.
When data lives only in reporting decks, it informs the next brief, but it does not build on momentum for the current campaign. Cognitiv's predictive technology transforms those retail signals into actionable inputs mid-campaign, enabling smarter orchestration across audiences and products.
The most common question I kept getting, more so in hallway conversations after our session, was: "How fast can I actually implement these retail data in my live campaign?" There is still a perception that retail data has to be lagged and locked inside post-campaign reporting. Many CPG brands are familiar with Circana as a trusted measurement partner, but seeing how AI can enhance that data, and not replace it, by activating it in real time was eye-opening.
Essentially, the source of truth stays the same. The opportunity is in how quickly you act on it.
The Zero Sugar Turning Point
The launch of Zero Sugar became a case study for this approach, and a chance to see how deep learning surfaces opportunities that traditional analysis would never reveal. The goal was twofold:
- Re-engage lapsed buyers who had left due to sugar concerns
- Bring in new-to-brand buyers, particularly Millennials who grew up with Welch's jam or snacks but had not yet entered the juice portfolio
Some assumptions held, while others evolved. The most surprising signal came from the diabetic community, an audience that was not explicitly prioritized at launch but was converting and advocating with clear intent. In a traditional setup, that might have surfaced as an interesting footnote in a post-campaign recap. Instead, it became an actionable growth segment while the campaign was still live.
Turning Campaigns Into Live Experiments
One of the most resonant moments in our session was Katelyn's take on the traditional 70/20/10 budget model; 70% to proven tactics, 20% to emerging channels, 10% to true experimentation. Activating retail data in-flight allows for greater fluidity within that framework. Instead of waiting months for post-campaign analyses, brands can optimize in real time, and the test-and-learn budget becomes a living engine rather than a behind-the-curve allocation.
My challenge to brands still using retail data strictly for reporting is, if you already have the signal, why wait to use it?
If there was a single throughline across summit conversations, it was that knowing what happened is table stakes. What you do with that knowledge, and how fast you can apply it, is where the real advantage lies. Retail data is powerful. AI is powerful. But the real unlock happens when they are connected inside the campaign window, not after it closes.
If you want to learn more about Cognitiv’s session or discuss how we can help you optimize your real-time media strategy, contact me via email or LinkedIn.
