It’s Time to Stop Fighting and Start Aligning
Over the past few weeks, we’ve had the chance to sit down with senior CRM leaders over lunch in both Manchester and London. No slides, no hard sell—just honest, open conversations about what’s really going on inside customer marketing teams.
One theme cropped up in both cities: the familiar push-and-pull between CRM and Trade.
It’s a classic tension. CRM teams aim to build long-term customer value through personal, relevant journeys, while Trade is often focused on reaching the widest possible audience, fast. It’s a dynamic that came up time and again—where personalisation pulls one way, and commercial pressure pulls the other.
This isn’t about which team is right. It’s about how to bring performance and personalisation into the same conversation. Because right now, they’re often pulling in opposite directions.
What Some Teams Are Doing Differently
A number of CRM leaders we spoke with are starting to experiment with more intelligent audience strategies—especially at category level. One approach that came up repeatedly is the use of category affinity modelling.
Put simply, it’s a way of predicting how likely each customer is to buy into specific product areas, based on a mix of past purchases and digital behaviour across channels. The smarter versions of these models can refresh daily, so they keep up with real-world behaviour—not just historical averages.
One fashion brand recently tested this approach on a sandals campaign. Rather than pushing the promo to their entire CRM list, they used category-level signals to send it only to customers who were showing interest in that area.
The results highlighted a few key lessons:
- Over 40% of the email volume could have been removed, without any drop in revenue.
- Opt-outs fell by 90%, simply by sending something more relevant.
- The same targeting model was used in paid media, delivering a 3.7x return on ad spend.
- And altogether, the campaign generated £100ks in incremental revenue—without overwhelming the wider database.
The team ran the campaign using Plinc’s own Category Affinity Model, which uses daily data signals to predict what product areas each customer is most likely to care about. But the broader point here goes beyond any one tool: smarter targeting doesn’t have to mean over-engineering. When teams move from static segmentation to dynamic, behaviour-led signals, both CRM and Trade win.
Why This Matters
This kind of approach doesn’t just help CRM teams prove their value—it also helps Trade teams get smarter results from their activity. It moves the conversation on from “how many people can we reach?” to “how many people are likely to care?”
And crucially, it allows teams to hold onto something both sides can get behind: measurable performance.
What You Can Take Away
Whether or not you’re using advanced modelling, there’s a broader principle here: better targeting doesn’t have to mean over-engineering. Even simple signals—like past purchase category or recent product views—can give you a steer on who’s more likely to respond.
A good place to start? Test message suppression in just one category. Measure the impact. See what happens. You don’t need to wait for a transformation project to start making improvements.
One Last Thought
The CRM vs Trade dynamic probably isn’t going anywhere—but with the right data and approach, it doesn’t have to be a tug-of-war. We’ll be sharing more insights from our CRM leader lunches over the coming weeks.
And if this sounds like a conversation you’d like to be part of, let us know. Or even better—if you’re a client-side CRM leader, join us at the next lunch. The food’s good. The chat’s even better.
