From a conversation with Amit Gupta, CEO of Cardlytics
Commerce media has quietly moved from marketing experiment to commercial infrastructure. In a recent conversation with Amit Gupta, CEO of Cardlytics, the picture came into sharper focus: the data layer behind payments is now driving a measurable shift in how brands understand loyalty and growth.
What the data actually shows
Most retailers still assume that their core customers are loyal. Cardlytics’ view across trillions of dollars in annual spend tells a more complex story. Even frequent customers – those who appear loyal – often split their purchases across multiple competitors. That gap between perceived loyalty and real behavior hides the largest growth opportunity in consumer marketing.
When Cardlytics clients use transaction data to identify and reach these “non-loyal regulars,” the effect is significant. Gupta notes revenue lift as high as 7× when brands use precisely targeted, context-aware offers to re-engage these shoppers. The results repeat because they are built on verified purchase behavior, not modeled intent.
From impression to transaction
The engine behind this performance is the card-linked offer (CLO) – a reward attached directly to a purchase. Consumers activate an offer in their banking app, spend at the merchant, and receive automatic cash back. It feels simple, but the implications for media efficiency are enormous.
Across campaigns, Cardlytics has seen:
- 64% of users spending more per transaction
- 72% increasing overall spend with the sponsoring brand
Unlike impression-based advertising, a CLO connects exposure to spend with minimal friction. Every transaction produces measurable data and a verifiable outcome. Behind the scenes, Cardlytics’ platform normalizes merchant data, resolves identity across financial and retail systems, and delivers relevance at the moment of intent – all while protecting consumer trust.
Where commerce media goes next
Gupta describes a pipeline of advances already reshaping the model. SKU-level targeting now lets a CPG brand move a specific product through a specific retailer, closing the loop from audience to receipt. Early pilots show meaningful incremental lift when the right incentive meets the right moment.
Further ahead, AI-driven shopping agents could automate discovery and price optimization on behalf of consumers. In that world, a network like Cardlytics would supply verified, real-time offer data directly to those agents. CLOs evolve into a data layer that supports autonomous buying decisions – an infrastructure for transparent, performance-based pricing.
Building the strategy
Brands entering this space need structure as much as tools. Gupta outlined a sequence that separates leaders from laggards:
- Clean the data. Merchant normalization and identity resolution determine the accuracy of everything that follows.
- Build the insight layer. Compare share of wallet to category baselines to see where switchers are leaking out and what behaviors predict defection.
- Target with precision. Allocate investment toward those segments and maintain always-on CLOs for continuity.
- Measure with discipline. Use certified incrementality models to confirm causality and justify reinvestment.
- Treat loyalty as a financial asset. Strong performance data can convert retention programs into revenue-producing media inventory.
What this means for marketers
Commerce media is gaining permanence because it closes the loop between spend, behavior, and value. Cardlytics’ model proves that first-party transaction data can deliver both accountability and reach at scale. For marketers under pressure to show results, that combination changes how budgets are planned, measured, and defended.
Gupta summed it up plainly: “When media ties directly to a transaction, you’re no longer guessing. You can see exactly what worked, and why.”
