Categories
What drives sneaker purchases? AI-moderated research finds design and wearability matter more than celebrity collaborations.
Sneaker sales have been fueled by a surge in running footwear, a rise in price-sensitivity, and a shift in market share away from legacy brands1. The latest trends show that versatility, retro design, and collabs aligned with cultural moments generate demand.
Sneakerheads are a group with their own subculture with layered identities and motivations that are often guarded from outsiders, even when openly discussed inside the community2,3. This guarded, fast moving subculture is challenging for brands to understand.
Conveo’s AI qualitative research & insights platform pairs fast data collection with in-depth participant interviews, revealing the nuances behind this group’s reactions to recent “marketing collabs”, buying preferences, and price sensitivity. We ran this study to answer three linked questions: what actually drives a collab purchase, whether the winning concept wins for those reasons, and what that is worth in price.
Our study recruited 100 sneaker enthusiasts to explore what collecting and sneaker culture mean to them, surfacing distinct sub-groups, purchasing triggers, and revealed preferences.
Within that sample:
Each interview ran in three stages:
Participants were US sneaker enthusiasts aged 18 to 55, recruited from an online panel, each owning 10+ pairs and consenting to appear on video; the price ladders were answered by 50 participants for Nike, 37 for New Balance and 13 for Adidas.
Conveo's open-ended interviews let participants share their answers for however long they choose. Comparing what people said about past purchases with what they claimed to want exposed the gap between the two, the kind of distinction a closed-ended survey can't surface. The anecdotes that followed revealed real emotional stakes: meaningful gifts, milestones, trips, childhood aspirations, and sports culture. Three factors consistently made a pair someone's favorite: design/colorway, comfort/wearability, and personal story or meaning.
Design and Colorway:
“So these dunks are my favorite pair of sneakers … It was, like, a limited release, and this is the other shoe, but they're two different colors. There it's like a similar colorway on one side, blue, brown, then green, and then yellow, brown, then red. But I like them because they're very unique. They're very loud and expressive.” - Jake J.
Comfort/Wearability:
“They're kind of like the Europe Gazelle, seems a little bit different. I got these last fall in October-ish and the yellow is just a nice pale yellow and the blue is pretty vibrant and they're just super comfy and are super cool and go with everything.” - Vanessa T.
Personal Story/Meaning:
“The reason they're so special is because, one, I've always wanted them. I could never afford them. And I love the color of them, but it's because my wife got them for me and surprised me, and I was totally shocked … I know how much that probably cost her. But I think that's what makes them so special is that, like, she knew that it really meant a lot to me. And weirdly, I usually don't wear my really nice shoes, but for these, I do. And every time I wear them, I just feel like I feel loved.” Kate K.
What is clear from people’s closets is that for collabs design is the entry ticket, comfort is the verdict. A shoe has to be liked on sight to be considered at all, and wearable to stay in the rotation. Nothing else gets evaluated until both are satisfied. In addition, personal meaning is earned after the purchase, not constructed before it. The stories participants told were about who gave them the shoe, where they were, and what they had saved up for. A brand can create the conditions for that, but it cannot manufacture it at launch. The collaboration as such is almost never the reason. Collabs appear constantly in these stories, but as the setting rather than the motive. Almost no one named a favorite pair because of who the brand partnered with.
That last point was assessed in the next two stages of the interview: if the collaborator is not why people love the shoes they already own, how much is it worth on a shoe they have not yet bought?
Conveo's MaxDiff produces the same preference shares as a traditional MaxDiff. The difference is what sits behind them. The platform probes any attribute a participant marks as most or least important and, critically, the ones that land in the middle. In a conventional MaxDiff that middle tier is a black box: the researcher can only infer why an item wasn't polarizing. In this study, participants explained it directly, whether they felt genuinely neutral about it, other options were strong enough to push a decent choice into the middle, or they simply weren't familiar with it. The output is the same scoreboard, with the reasoning attached.
Across all 100 participants, three attributes dominate in terms of preference or utility: design and look (31%), comfort and everyday wearability (24%), and sneaker brand (16%). Everything else, from colorway or price and story to the collaborator, sits at 5% or below (Table 1).
Conveo’s Talk to Your Data analysis engine, then splits that hierarchy by sub-group, and the two audiences want different things as soon as design is accounted for (Table 2).
Design is the universal entry ticket. It takes roughly a third of preference share in both groups (34% and 33%). No collab of any kind survives failing here. After that, the two groups diverge.
The commercial read is that “Release Chasers” are the volume and they are won with wearability. Serious Sneakerheads are the margin and they are won with credibility. A collab that only does one of the two leaves either volume or price on the table.

Table 1 - What matters when buying a collab sneaker: MaxDiff preference share and utility scores

Figure 2 - The same hierarchy as utility scores, with 95% confidence intervals: the gap between the top three attributes and everything else

Table 2 - What each sub-group is won on: MaxDiff preference share by segment
Each participant then saw all three collaboration concepts in randomized order, discussed each one, and chose a favorite to take into the pricing questions (Figure 3).
Nike x Nigel Sylvester AJ4: a familiar Air Jordan 4 silhouette in a red-and-white, brick-inspired colorway, with subtle collab detailing and a prominent toe-box Swoosh.
Bembury x New Balance 992: the classic 992 shape in a nature-led palette of green, yellow, blue and brown, with mixed premium textures and a rugged outdoor character.
Adidas x Bad Bunny BadBo 1: a bulkier, skate-leaning silhouette in suede with an oversized tongue and unusual lacing, styled as a statement shoe.

Through Conveo’s Talk to Your Data function, researchers can assess how the results of the MaxDiff match criteria participants used to evaluate real collaborations as shown in Table 3.

Table 3 - How each concept performed against the MaxDiff hierarchy
The Nike collaboration was the clear winner because it is a collaboration that still looks like a shoe people could wear. One participant said it is, "A good combination of the design, the collaboration and the exclusivity… you could wear it with streetwear or with everyday clothes."
New Balance led the second-ranked attribute of comfort and everyday wearability. However, the colorway undercut the very wearability the shoe was promising. One participant said, "I don't think that they're that cute, and I wouldn't spend that much money on a shoe that I wouldn't wear often." While another participant liked the structure but thought there were, “too many colors going on.”
Adidas is the clearest test of the hypothesis, because it had the strongest cultural asset of the three concepts. Bad Bunny gave fans a real reason to consider the shoe. It was not enough.
"The suede and the lacing are interesting, but that tongue is so big it makes it look like a skater shoe."
The MaxDiff explains why. The actual “collaborator” accounts for 5% of preference share. Design accounts for 31% and everyday wearability for 24%. Bad Bunny was being asked to carry a shoe that had already lost on both of the attributes that matter most, and no partner is large enough to do that. The sub-group data confirms the point rather than softening it: Serious Sneakerheads (the deepest collectors) were more receptive to the Bad Bunny concept than Release Chasers (38% vs 22% likely to buy), but even within the most collab-literate audience it stayed a minority proposition.
We ended the study with a Gabor-Granger question to test each concept at a series of prices and asked whether participants would buy at each price and why or why not. This question illustrated how much purchase intent held up as price increased and where it started to break. Comparing the Gabor-Granger curves against the MaxDiff rankings shows that the logic is consistent: the shoes that score highest on MaxDiff attributes are also the ones that command the highest price ceilings in the Gabor-Granger data. The data shows that price acceptance is bought with design and wearability, and underwritten by brand trust.
Participants did not describe $180 as the price of a Jordan; they described it as the price of a Jordan they would actually wear.
"The design, the street-culture connection, the textures — it feels more elevated than the other Jordan sneakers."
Above $180 the curve breaks, and the reason is specific: participants started asking for visible proof such as materials, craftsmanship, Nigel-specific detail rather than more of the Nike brand.
73% would buy at $120, which was the strongest acceptance measured, but $120 sits at the bottom of the tested ladder. That is the signature of an appealing product that is not read as a premium collaboration. The binding constraint is comparison: participants benchmarked it against the regular 992s at around $105 and asked what the extra was for.
"It's a standard price. I can get a New Balance pair for about a $105"
One participant was explicit about what would change their mind: credible evidence of regenerative or recycled materials would move them to $180. The route to a higher tier is a more wearable colorway and visible proof of materials — not more story.
Bad Bunny does create price headroom: for fans, he was the stated reason $160 felt reasonable to participants. However, the base of participants was narrow — only 13 people selected Adidas as their favorite shoe and were presented with this question. As a result, the findings should be treated as directional — and roughly 31% of those participants would not buy at any tested price. Artist equity opened a premium for a segment, but the silhouette closed it for everyone else.
"I wouldn't pay more than eighty for it. The design is basic and too similar to the Yeezy-type styles."

The study set out to answer three questions. Each one points to a decision.
What drives purchase: product first, story second. Design and everyday wearability decide whether a collab gets bought. The collaborator, the origin story and the limited-edition framing sit well below them. They are not worthless, they are conditional: they make an already desirable shoe more special, and they give a brand permission to charge more.
The two audiences also mean different things by product: Release Chasers need to believe they will wear it often, Serious Sneakerheads need to believe the shoe has a credible lineage.
Whether the winning concept wins for those reasons: yes, and predictably so. The concept that led on the fundamentals also led on purchase intent and on final choice, while the one carrying the biggest cultural name finished last. What people said mattered in the abstract held up when they were looking at real shoes. That makes a concept judgeable before launch: a strong partner attached to a difficult silhouette is a predictable disappointment, not bad luck.
What that is worth in price: the product sets the ceiling. Willingness to pay followed the same order. Where design, wearability and brand trust all pointed the same way, the premium held. Where the shoe was liked but not clearly different from the brand’s own line, price stalled at entry level. Where the partner was carrying the shoe alone, the premium existed only inside their fanbase. Price the shoe on what it delivers, and use the collaboration to justify the number rather than to set it.
Brands normally answer this in three separate exercises - a qualitative deep-dive, a quantitative MaxDiff, and a pricing test - run at different times, on different samples, stitched together afterwards. We did it in one 24-minute interview, with 100 people, who showed us their favorite pair, ranked the drivers, judged the concepts, and walked the price ladder in a single sitting.
The MaxDiff put the collaborator at 5% of preference share - a number people gave us with no shoe in front of them. Then we showed them three real ones. Nike, the strongest fit on paper, won. Adidas, the weakest, came last. Stated preference and revealed choice are normally two different studies, on two different samples, reconciled on faith after the fact. Here they were the same 100 people in the same interview, so the concept test didn't test a hypothesis about the MaxDiff - it tested the MaxDiff, live.
The MaxDiff told us the collaborator is a 5% driver. The follow-up probing told us why. A purely quantitative study hands you the 5% and leaves you guessing, which is a bad place to decide from on the most expensive line in a collab budget. The analysis doesn't stop at the original question either: Talk to Your Data lets us keep asking, and every answer comes back with the verbatims behind it. That's the difference between a report that tells you what people said and a tool you can make decisions with.
Comments
Comments are moderated to ensure respect towards the author and to prevent spam or self-promotion. Your comment may be edited, rejected, or approved based on these criteria. By commenting, you accept these terms and take responsibility for your contributions.
Disclaimer
The views, opinions, data, and methodologies expressed above are those of the contributor(s) and do not necessarily reflect or represent the official policies, positions, or beliefs of Greenbook.
ARTICLES
How does the ICC/ESOMAR Code address AI in market research? Explore its role in transparency, accountability, and ethical practice.
5 min read
Discover top AI platforms for consumer insights and how to choose the right tools for research, CX, and analytics.
Learn how directories, case studies, reviews, and expert content help research companies gain visibility in AI-generated search results.
Explore how AI can become decision infrastructure for insights teams by preserving context, connecting research, and activating learning.
Sign Up for
Updates
Get content that matters, written by top insights industry experts, delivered right to your inbox.