One in Four Grocery Shoppers Is Financing Their Food.
CPG Isn’t Ready for What That Means.
Nearly half of buy now pay later users now use the service at least once a week. Forty-one percent paid late on at least one loan in the past year, up from 34% the year before. And the purchases they’re financing aren’t just big investments like electronics or furniture, they’re groceries, utilities, and subscriptions - The everyday stuff.
By mid-2025, a quarter of buy now pay later users had already started financing grocery purchases (up from 14% the year before). Gen Z adoption was at a third. Since then, every indicator of how deep and how frequent the behavior has become has gotten worse. Klarna is live at Walmart and Target, in-store and online. Affirm runs at Costco. Afterpay operates through mobile wallets at major chains across the country. The infrastructure for financing your weekly grocery run didn’t exist five years ago. Now it’s at every major register in America.
This isn’t a payments story. It’s a consumer relationship story - and most of the CPG industry doesn’t have the infrastructure to see it happening.
The stress underneath is broader than any single payment method. The personal savings rate is hovering around 4%. Consumer confidence dropped to 84.5 in January, the lowest reading since 2014. Layer on $1,300 per household in annual tariff-driven cost increases and the picture is a K-shaped recovery that scan data flattens into a single line. Upper-income households are absorbing the price increases (perhaps annoyed, but without changing behavior). Lower-income households are either trading down to private label and discovering they’re getting 90% of the product at 60% of the price (which turns a temporary switch into a permanent one), or financing branded purchases through installment plans. Both show up as transactions. One is durable volume while the other is volume on a timer. The aggregate number that lands in the category review mixes the two cohorts into a single trend line that looks like a modest, manageable decline while hiding that the brand is increasingly dependent on a narrower, wealthier base and a lower-income cohort that’s one credit squeeze away from deteriorating.
The problem for branded CPG isn’t that consumers are using installment plans. It’s that scan data (the foundation of every category review, every pricing model and every volume forecast in the industry) can’t distinguish between a transaction funded by cash flow and a transaction funded by four payments. Nielsen tracks that someone bought the product. It doesn’t track that they split the payment because their grocery bill outran their checking account balance.
So when a CPG company reads scan data and concludes “volumes are stabilizing” or “the consumer is holding,” they may be right about the transaction and wrong about the consumer. A portion of the volume that looks like loyalty is actually inertia financed by debt. And debt-financed volume doesn’t behave like income-financed volume. It doesn’t erode gradually, it falls off when credit tightens or defaults spike or the consumer hits their installment ceiling and has to make actual trade-off decisions at shelf.
This is a first-party data problem and it exposes the gap at the center of most CPG operating models: The majority of branded manufacturers are fully intermediated through retailers, working off syndicated data that arrives 60 to 90 days after the transaction, with zero visibility into the financial health of their consumer base. They don’t know if their repeat purchaser is a financially secure household that chose their brand or a stretched household that hasn’t gotten around to switching yet.
That’s always been a strategic disadvantage. In an environment where a growing share of grocery spending is financed rather than funded, it becomes an analytical blind spot with direct P&L risk.
Consider what a company with deep consumer relationships would do differently. First-party data and direct consumer channels (those with a real sensing capability, not just a CRM list) let you see purchasing pattern changes before they show up in syndicated scans. You would be able to identify when your consumer base is under financial stress by watching order frequency, basket composition, and product-level substitution behavior in real time, while allowing you to respond with pack size adjustments, promotion timing and mix shifts that protect both the consumer relationship and the margin. You could answer the question that scan data can’t: is this consumer loyal, or leveraged? Are they choosing your brand because it earns the premium, or are they still on the shelf because Klarna made the decision painless enough to not revisit? That’s not a nuance, that’s the difference between a volume base you can build on and a volume base sitting on a credit bubble.
If you’re a branded manufacturer reading this and thinking “we can’t answer that question”, you aren’t alone - Most can’t. But you can start closing the gap faster than you’d think.
The first move isn’t building a DTC channel or investing in connected packaging. It’s overlaying what you already have. Take your syndicated scan data and cross-reference it against publicly available consumer financial stress indicators at the ZIP code level (delinquency rates, savings rates, BNPL penetration where the data exists, etc.). You won’t get individual-consumer visibility, but you’ll get a heat map of which geographies your volume is most exposed. If your strongest scan data markets overlap with the highest financial stress indicators, that’s your vulnerability map; It changes how you allocate trade spend, where you test pack size adjustments and which markets get promotional support versus price holds.
The second move is retailer data partnerships. Most major retailers have loyalty card data that reveals purchase frequency, basket composition shifts and trade-down behavior at the household level. This data is far more granular than anything syndicated panels provide. The retailers won’t hand it over for free, but the joint business planning conversations are already happening. The question is whether you’re using those conversations to ask about volume trends or about consumer financial health. Same meeting, different question, completely different strategic value.
The third move is the one that takes longer but matters most - Building your own first-party consumer sensing capability. That means something different for every company: it could be a DTC channel, a loyalty program, connected packaging with QR-driven engagement, or social listening infrastructure that tracks real-time sentiment and substitution intent. The mechanism matters less than the principle - you need a signal that tells you what your consumer is doing and feeling before the scanner tells you what they bought.
None of this requires a two-year digital transformation. The ZIP-level overlay is a thirty-day project. The retailer data conversation is already on the calendar. The first-party build is a longer arc, but you can start scoping it now with a clear mandate: we need to know whether our volume base is loyal or leveraged before the next earnings cycle.
Looking forward, I’d expect every CPG company heading into Q1 earnings season (i.e. PepsiCo on April 16, Nestlé on the 23rd and P&G on April 24 and the entire sector reporting through May) to talk about volume trends, pricing strategy and consumer resilience; But the number to listen for isn’t in the earnings release. It’s the one none of them can report - what share of their volume is financed rather than funded?
The companies that figure out how to see that number, through direct relationships, first-party data, or partnerships that give them visibility past the transaction, will be the ones that see the floor before it drops. The rest are running a forecast model with a growing blind spot that appears to get bigger every quarter that installment financing spreads deeper into the grocery aisle.
When a growing share of your consumers are financing their groceries, “the consumer is holding” isn’t a data-backed conclusion, it’s a hope, and hope is usually a lagging indicator.