The haircare brand is frustrated. They’re running a paid discovery search for “curly hair creators” and getting back the same 15 names they’ve seen everywhere. These creators are talented, their audiences are engaged, and every competitor is pitching them too. The rates have climbed. Deliverables have tightened. Exclusivity is gone. And the brand is wondering if they’re missing something obvious.
They are. It’s the curly hair problem.
What the Curly Hair Problem Actually Is
The curly hair problem isn’t really about curly hair. It’s a metaphor for a structural flaw in how most brands discover creators. Category-based discovery systems organize creators into buckets: skincare, fitness, lifestyle, beauty, wellness, food. A brand looking for haircare creators filters for the haircare category and gets back everyone tagged that way.
The problem is that everyone else is doing the exact same search.
When discovery works only on category labels, every brand chasing the same category sees the same ranked shortlist. The top 20 “curly hair creators” get pitched by 50 brands simultaneously. The middle-tier creators see category-based opportunity and lean into it, making themselves more visible within that category. And the creators who could actually drive the best results for your brand often aren’t visible at all—because their primary category is something else entirely.
A fitness creator whose audience skews heavily toward natural hair care, wellness, and body positivity might convert at 3x the rate of a category-matched haircare creator. But if your discovery tool only filters by category, you’ll never know she exists.
Why Category Labels Create Tunnel Vision
Discovery tools work with category labels because categories are clean, sortable, and easy to filter. A creator applies to join a platform, tags their primary content focus, and suddenly they’re sortable. The UX is simple: you choose your category, adjust your audience size filters, maybe add a location, and get back a list.
This works until it doesn’t. It works for finding creators who’ve explicitly chosen to build an audience around your product category. It fails at finding creators whose audience cares about your category, even if the creator’s primary work is elsewhere.
Consider the math. A wellness creator with 200k followers might have an audience that’s 60% women aged 25-40 interested in natural products and body care—an overlap that directly matches your skincare brand’s target customer. But because this creator’s category is “wellness” rather than “skincare,” discovery algorithms deprioritize them. They don’t show up in the ranked list. You never pitch them. A competitor with better discovery tools finds them first.
This is where brands lose competitive advantage in creator selection. You’re not finding a weaker creator. You’re not finding a creator at all.
What Cross-Category Creator Matching Actually Means
Cross-category matching flips the discovery model from “what category is the creator” to “who is in the creator’s audience and what do they care about.” Instead of searching for haircare creators, you search for people whose followers include customers interested in hair care, natural products, wellness, and body care—regardless of whether the creator’s primary content is fitness, lifestyle, wellness, or something else entirely.
This requires a different technological approach. Instead of filtering by preset categories, the system needs to understand:
Audience demographics and psychographics. Who exactly follows this creator? What are their income levels, interests, locations, life stages?
Engagement patterns. Which content types drive the highest engagement from followers most similar to your target customer? A fitness creator might have viral fitness content, but their highest-engagement posts might be the ones about natural self-care routines.
Purchase intent signals. What do the creator’s followers actually buy? Audience analysis tools can surface this through link tracking, swipe-up data, and engagement patterns on product-adjacent content.
Cross-category relevance. Does this creator have credibility or audience interest in adjacent categories? A fitness creator talking about nutrition and recovery naturally bridges into wellness and personal care conversations.
When you match this way, you’re not relying on how a creator categorizes themselves. You’re relying on actual audience composition and behavior. That’s a fundamentally different starting point for discovery.
Real Examples of Unexpected Creator-Brand Fits That Outperform Obvious Matches
The proof is in the performance data. Brands doing cross-category discovery consistently find that their strongest-performing creators came from unexpected places.
A supplement brand in the wellness space didn’t search for “supplement creators” or even “wellness creators.” They searched for creators whose audiences included high-engagement users interested in fitness performance, recovery, and biohacking—regardless of how those creators labeled themselves. One of their top performers turned out to be a productivity and remote-work creator whose audience skewed heavily toward people optimizing their health and performance. The creator had never categorized herself as wellness-focused. But her audience did care about energy, focus, and long-term health—core motivations for supplement users.
A skincare brand found one of their highest-converting creators: a lifestyle and home organization creator whose audience skewed heavily female, 28-42, interested in self-care rituals and sustainable products. This creator had never built an audience around skincare. But her followers cared about rituals, wellness, and intentional self-care—the exact psychology driving skincare purchases. Her authentic voice talking about adding a skincare routine to her morning ritual converted at 2x the rate of the category-matched skincare creators the brand had been pitching.
A fitness apparel brand discovered a fashion and slow-fashion creator whose audience overlapped significantly with active, sustainability-conscious women. The creator had never positioned herself as fitness-focused. But her audience was buying athletic wear, was interested in quality and durability, and valued brands with ethical practices—a psychographic match that outperformed niche fitness creators.
In each case, the “unexpected” creator drove better results not by accident, but because audience alignment mattered more than category alignment. The fitness apparel brand didn’t need another fitness creator. It needed creators whose audiences included people who buy fitness apparel. That’s a different search entirely.
How to Think About Discovery Differently
The shift from category-based to audience-based discovery requires a conceptual reset. You’re no longer asking “who creates content in my category?” You’re asking “whose audience includes my ideal customer, and what level of credibility or engagement do they have in adjacent spaces?”
This changes how you brief your discovery process. Instead of category filters, you lead with audience characteristics. Who is your ideal customer? What do they care about? What communities do they participate in? What adjacent interests do they have? Then search for creators whose audience composition and behavior match that profile.
It also changes how you evaluate creator fit. Instead of asking “does this creator’s feed match my brand?”, ask “does this creator’s audience match my customer?” A creator whose feed doesn’t look like your category but whose audience deeply aligns with your customer is often a stronger match than a category-perfect creator with weak audience alignment.
Cross-category discovery requires different tools
Most discovery platforms organize creators the same way: by category labels and follower count. If that's how you're searching, you're seeing the same shortlist as every competitor. Finding unexpected creator-brand fits requires platforms that analyze audience composition and engagement patterns, not just category tags.
The brands winning in creator marketing right now aren’t the ones pitching the obvious 20 names faster. They’re the ones finding the creators that the obvious discovery process misses entirely. They’re not searching for “haircare creators.” They’re searching for audiences that care about hair, and they’re finding creators everywhere.
Lia Haberman, VP of Creator Partnerships, Modern Beauty Group
We stopped searching for creators by category two years ago. We started matching on audience fit, and the performance difference was immediate. We’re not competing for the same 30 names anymore. We’re finding creators our competitors haven’t even looked at.
The curly hair problem persists because it’s easy to solve the wrong way. You can build a bigger database of haircare creators. You can pay higher rates to get on exclusive creators’ shortlists. But you’re still in competition for the same narrow pool. The real leverage is escaping the pool entirely by discovering creators nobody else is looking for—because they don’t match the category label, but they match the audience.
That’s how the best brands are discovering creators now. And it’s why their campaigns outperform the obvious shortlist every time.
For more on how discovery works and what it misses, read Why Influencer Discovery Is Still Manual for Marketing Teams and How to Find the Right Influencers for Your Brand. For a deeper look at what modern discovery platforms are doing differently, see AI Tools vs Agentic Platforms: Creator Marketing.
- The best creator for your brand is often not in your category — their audience matches your customer even when their content doesn’t match your product.
- Category-based search is the default, which is exactly why every competitor’s shortlist looks like yours.
- A fitness creator whose audience is 80% women aged 25–35 with high skincare purchase intent can outperform a beauty creator with weaker audience specificity.
- Cross-category matching is an audience problem, not a content problem — the question is who follows them, not what they post about.
