May 28, 2026
Modern Retail Summit takeaways: The funnel is widening, and measurement has to keep up
I attended the Modern Retail Summit last month. It was three days of sessions, side conversations, and I got back from the Modern Retail Summit with that familiar mix of excitement and discomfort. Excitement because there is real momentum in how teams are thinking about growth. Discomfort because the old “if we just crack the channel” story is officially over.
After three days of sessions, hallway conversations, and coffee catch-ups with leaders across beauty, wellness, supplements, apparel, home, and premium retail, a few themes kept repeating. Not in a buzzwordy way. In a “we all keep running into the same walls” way.
Here’s what I heard. And more importantly, what I think it means for how we plan, measure, and build programs that hold up over the next 6 to 12 months.
1) The funnel is not collapsing. It’s getting wider and messier.
One of the most grounding moments came from Mary Beech at Thorne. Her point was simple: customers are still buying in pretty normal ways, but they are deciding in more places than ever.
She shared a stat that stuck with me: 88% of Thorne’s customers research multiple sources before purchasing. That’s not a small behavior shift. That’s a reminder that most “conversion” happens long before someone clicks “add to cart”.
What this changes:
- You cannot only show up at the very end of the journey and expect to win consistently.
- The work is less about “one perfect channel” and more about building coverage across the places people use to form an opinion.
2) Channel certainty is gone. The best teams are calm about it.
In almost every session, the most useful question was: What didn’t work?
Not because people wanted to complain. Because the teams making progress right now are the ones who treat testing as an operating rhythm, not a side project. They assume things will change. They keep their ego out of it. They move budget based on signal, not tradition.
A couple examples that came up repeatedly:
- Meta performance feels softer for a lot of brands. Not universally, but enough that it’s changing planning assumptions.
- Even “obvious” channel-category pairings are not guaranteed. Mary also mentioned podcasts didn’t work for Thorne, which is the exact opposite of what you would expect for supplements.
What this changes:
- “Should work” is not a strategy.
- The goal is a portfolio of bets with clear roles, plus a cadence to evaluate what is actually happening.
3) Creator-affiliate is moving from “nice-to-have” to a real, measurable motion.
Paid influencer is familiar territory for most teams now. What felt different in the conversations this year was how many leaders are trying to build something in the middle. Something that bridges awareness and conversion, but is still accountable.
The phrase I kept hearing (in different words) was: repeatable and measurable.
Teams want creator programs that:
- are performance-tracked (not vibes-tracked)
- can be scaled beyond a few hero creators
- can be supported by whitelisting and distribution
- have clear formats and briefs so they do not reset to zero every time
Also, gifting-only models are getting harder to justify. One story that came up was a brand handing over $40K in product with no guaranteed deliverables, and still getting asked for paid on top. The market is professionalizing. Expectations are clearer. The bar is higher.
What this changes:
- If you want creator to be a growth lever, you have to treat it like a program, not a series of one-offs.
4) AI visibility is becoming a scorecard conversation, not a separate narrative.
This one is evolving quickly.
On the vendor side, a lot of the AI conversation still centers on onsite experiences (chatbots, site search, optimization). But the question brands are increasingly asking is more basic and more practical:
Do we show up inside AI-driven discovery, and can we track it over time?
The most pragmatic framing I heard was: put it on the scorecard.
If CAC and ROAS get reviewed monthly with leadership, the board, and finance stakeholders, then AI discovery needs to become a row on that same scoreboard. Not a separate deck. Not a quarterly “innovation” update. A metric you define, baseline, and revisit.
If you want a baseline for how Google is thinking about content in an AI-first environment, their AI optimization guide is worth a skim:
https://developers.google.com/search/docs/fundamentals/ai-optimization-guide
What this changes:
- The teams who operationalize AI discovery early (even imperfectly) will have an advantage over the teams who wait for a perfect standard.
What I would do next (if I were in-house)
If you are planning the next two quarters, this is the checklist I would start with:
- Map your current channel mix to the role it plays (awareness, consideration, conversion). If a channel has no clear role, it is probably a tax.
- Set a testing cadence that your team can actually sustain, and document learnings somewhere central.
- Build a creator-affiliate “minimum viable program” with clear formats, briefs, measurement, and distribution plans.
- Define what AI visibility means for your category, then put it on the same scorecard as CAC and ROAS.
If you want to pressure-test your acquisition mix and measurement scorecard, I’m happy to compare notes. No pressure. Just a practical conversation.
FAQ
Is the marketing funnel collapsing?
No. If anything, it’s widening. People are researching across more surfaces, which makes full-funnel presence and measurement more important, not less.
Are consumers purchasing directly through LLMs?
Not in a widespread, reliable way. AI is influencing research and consideration, but purchase still flows through ecommerce, marketplaces, and brand sites.
Why is Meta performance “softening”?
Brands are seeing rising CAC, softer ROAS, and creative fatigue as dynamics shift. The practical takeaway is to diversify acquisition levers and invest in creative systems, not just spend.
What is creator-affiliate, and why does it matter?
It’s a creator motion that is performance-tracked and repeatable, often supported by whitelisting. It matters because it can bridge the gap between awareness and conversion with accountability.
How should brands measure AI visibility?
Treat it like a scorecard row. Define prompt clusters, baseline presence, track changes over time, and review it alongside ROAS and CAC.
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