Consumers are recalibrating their spending habits, focusing more on value than price due to economic uncertainties.
Havas Edge economist Thomas J. Thompson highlights a shift in consumer sentiment, with spending likely to remain flat but value-driven.
The BNPL market poses a potential risk to economic stability, according to Thompson.
Thompson also warns of overbuilding in the AI sector, drawing parallels to the late 1990s tech boom.
After a stretch of economic vertigo—tariffs in flux, indicators flickering—consumers didn’t just hit pause. They redrew their entire value maps. What’s emerging isn’t mere caution, but a full recalibration: less about price tags, more about what something is truly worth.
Thomas J. Thompson, Chief Economist at Havas Edge, offers a clear lens into how shifting conditions are reshaping what people value—and how they spend.
Rewriting value: “People are reassessing the concept of value versus price,” says Thompson. “When two things are equal or close in price, consumers ask: Which one gives me more?” It’s not just belt-tightening—it’s strategic trade-offs through the retail hierarchy. “Bloomingdale’s drops to Nordstrom, Nordstrom drops to Macy’s, and so on until you land at Dollar General,” says Thompson. Consumers aren’t panicking, they’re optimizing. “They might pick up spending again, or they might still feel hesitant,” he says. Sometimes it’s as simple as choosing store-brand over name-brand—same result, lower cost.
Take a breather: Thompson traces the shift back to “tariff uncertainty”—a fog that blurred how people read the economy. “Most economic indicators look backwards,” he says. “The JOLTS report just came out, talking about April. Okay, well it’s June.” Hard data held, but sentiment and confidence “went off a cliff.” It wasn’t panic, it was pause. “They were just saying, ‘I need a minute,'” explains Thompson.
That minute passed. “Consumer sentiment isn’t climbing, but it stops declining. And consumer confidence goes up a little bit,” says Thompson. “The real-time data starts to show that consumers are thinking, ‘the storm hit, but the hurricane wasn’t as bad as we thought.'” Wage growth, job stability, and low quit rates tell the same story: “Everybody just sort of took a breath.”
Eyes on the sky: That breath set the stage for a slower, more value-conscious recovery. Thompson sees three potential paths for consumer spending: up, flat, or down. “I don’t see down. I’m not seeing indicators of down, but I’m not really seeing indicators of up either,” he says. The most likely outcome? Flat. Consumers may still spend—but carefully, with more brand-switching in search of value. One early signal to watch is domestic travel. “If domestic airfare picks right back up, then that’s a great sign that things are starting to be fine,” explains Thompson.
Beware the IOUs: But a shadow looms over that cautiously optimistic outlook: the buy now, pay later market. “The next great bubble burst is probably going to be in that industry,” Thompson warns. “Everything I said could be completely wrong if this hidden ‘buy now, pay later’ data is as bad as I’m hearing whispers.” Economists, he adds, “hate hidden data”—because it clouds the true economic picture.
To AI or not to AI?: For now, Thompson sees artificial intelligence delivering the most value behind the scenes. “Where we measure impact is on the input side,” he explains. “Economists understand that a robot builds a car faster than a human can weld. So us economists, we’re sliding in AI as a productivity tool,” says Thompson. But in advertising, results are mixed. “It’s certainly not achieving better results overall,” he says. “For every person that thinks an AI-created ad is cool, there’s another who says ‘What is this AI crap?'” says Thompson.
Where AI is delivering is data processing, and that’s where first-party data gains serious power. “The more I know about you, the more I can line up and send you ads that are targeted to you,” Thompson says. With AI, that personalization scales.
Familiar frenzy: The current AI boom feels a little too familiar to Thompson. “Everything that we’re facing now has happened before. This looks like 1998 all over again to me where people said, ‘I’m just going to build this, and then figure it out later.'” He draws a parallel to post-pandemic overbuilding: too many warehouses, too fast, based on assumptions that quickly changed. “We’re building for the future we see now. But by the time what you’re building hits, that future is different,” says Thompson. Companies that survive, he argues, will have gotten the foundation right—like Amazon, which built around logistics from day one.
Through the AI looking glass: Thompson believes economists are being asked to do more than interpret the past. “I think where economists can really lock in is identifying the efficiencies that AI brings and where to maximize that efficiency,” he says. But the job doesn’t stop there. “We’re being asked to be predictive analysts more than look-back. I get more questions now about the probability of something happening, and people are making decisions based on that probability,” Thompson explains. AI, he hopes, can help economists “drive a better probabilistic interpretation” of complex, fast-moving data—and build a more responsive economic narrative for what comes next.
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