What “finding creators” really means
Finding creators is a repeatable sourcing process: you generate a wide pool of potential partners, capture comparable data about each one, then narrow to a shortlist you can confidently contact. The goal is not “find the biggest accounts,” but to identify creators whose content style, audience, and performance patterns match what your campaign needs.
To keep sourcing efficient, treat it like a funnel:
- Discovery: collect many candidates quickly (often 50–300).
- Qualification: verify basics (activity, content fit, audience signals, any deal-breakers).
- Shortlist: rank and select a manageable set (often 10–30) to contact first.
Step-by-step discovery methods
1) Manual platform search (keywords, hashtags, suggested accounts)
This method is free and often produces the most “native” creator fits because you’re seeing what audiences actually consume.
Step-by-step: keyword search
- List 10–30 seed keywords tied to use cases, problems, and product category language (e.g., “meal prep,” “running shoes review,” “budget skincare routine”).
- Search each keyword on the platform’s search bar and open the “Top” and “Recent” tabs (or equivalent).
- Open 10–20 posts per keyword and capture the creator handle if the content is relevant.
- Check creator profile quickly: posting frequency, content themes, and whether they regularly speak to your target audience.
- Save candidates to a dedicated collection/folder and log them in your spreadsheet immediately (don’t rely on saved posts alone).
Step-by-step: hashtag search
- Start with 5–10 broad hashtags (category-level) and 10–20 niche hashtags (specific problem/format/community).
- Sort by recent to find active creators and avoid only seeing the biggest accounts.
- Follow the “hashtag trail”: when you find a good post, open the creator’s other posts and note which hashtags they consistently use—add those to your list.
- Capture format signals: note if the creator excels at tutorials, reviews, “day in the life,” comparisons, or storytelling—this matters for later scoring.
Step-by-step: suggested accounts and “similar creators”
- Open a strong candidate’s profile and click “suggested,” “similar,” or “people also watched.”
- Collect 10–30 adjacent creators from that cluster; these recommendations often reflect shared audience overlap.
- Repeat in loops: do 3–5 loops per niche cluster to build depth.
Practical tip: Build “creator clusters” by niche (e.g., “beginner runners,” “trail runners,” “marathon training”). Clusters make it easier to diversify your shortlist and avoid picking creators who all speak to the same micro-audience.
2) Competitor content audits (and adjacent brands)
Competitor audits help you find creators who already convert in your category. You’re not copying; you’re learning which creator types and content angles brands are paying for.
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Step-by-step audit
- List 5–15 competitors and adjacent brands (adjacent = same audience, different product).
- Scan their tagged posts (if available) and recent feed for creator collaborations.
- Look for disclosure signals like “paid partnership,” “ad,” “sponsored,” affiliate codes, or link-in-bio callouts.
- Open the creator profile and check whether they’ve done multiple brand deals in your category (could be a positive signal of experience, or a saturation risk).
- Log “prior sponsors” and the type of integration (review, tutorial, unboxing, comparison, etc.).
- Capture performance snapshots from the last 10–12 posts: views/likes/comments, and note any unusually high spikes (possible paid boosting or viral outliers).
What to watch for: If a creator promotes direct competitors very frequently, you may still shortlist them, but flag it for negotiation (exclusivity windows) or for brand-fit review.
3) Customer and employee creator scouting
Your best creators are sometimes already using your product. Customers and employees can also surface micro-creators with high trust in niche communities.
Step-by-step: customer scouting
- Search your brand mentions (tags, comments, UGC hashtags, product name searches).
- Identify repeat posters who show authentic usage, not just one-off tags.
- Check content quality and consistency (do they post regularly, do they speak clearly, is the video/audio usable?).
- Log them as “warm leads” and note the evidence of product usage (link to post).
Step-by-step: employee/community scouting
- Ask teams for nominations (sales, support, community managers) using a simple form: creator handle, why they’re a fit, example link.
- Review for conflicts (employees should not be pressured; ensure compliance with internal policies if employees are creators).
- Prioritize community credibility (e.g., creators who answer questions, teach, or review thoughtfully).
Practical tip: Add a “relationship” field in your sheet (customer, employee, fan, cold). Warm relationships often reduce outreach friction and improve response rates.
4) Creator marketplaces and influencer databases
Marketplaces and databases speed up discovery with filters (niche, location, audience demographics, average views). They’re especially useful when you need volume fast or want to search across platforms.
Step-by-step usage
- Define your filters before you search: niche keywords, location, language, typical content format, and minimum activity level.
- Use performance filters carefully: avoid setting minimum follower counts too early; prioritize average views and posting consistency where possible.
- Export results into your shortlist sheet and standardize fields (handles, links, metrics).
- Manually verify the top candidates by watching 3–5 recent posts; tools can miss tone, quality, and brand safety signals.
Common pitfall: Over-trusting “engagement rate” without context. A creator can have high engagement but low relevance, or engagement driven by controversy. Always sample comments for audience intent and sentiment.
5) Agencies and talent managers
Agencies can be helpful when you need creators at scale, want access to higher-demand talent, or need negotiation support. The tradeoff is less direct control and often higher costs.
Step-by-step: working with agencies
- Send a creator profile request with clear constraints: niche, content style, region/language, and any non-negotiables (e.g., no competitor promos in last X days).
- Ask for a standardized media kit set (or consistent data fields) so you can compare creators apples-to-apples.
- Request recent performance examples (links to 3–5 posts) rather than only aggregated stats.
- Clarify communication flow (who approves content, who handles revisions, who provides reporting).
Practical tip: Even when using agencies, keep your own shortlist sheet. It prevents vendor lock-in and builds institutional knowledge.
6) Inbound applications (creator sign-up forms)
Inbound applications create a steady pipeline of interested creators. Quality varies, so the key is building a form that collects the right data and makes screening fast.
Step-by-step: set up inbound
- Create a simple landing page or form linked from your website, brand social bios, and post-purchase emails.
- Collect structured fields (platform handles, audience location, average views, content examples, rates, contact email).
- Add a required “why us?” question to filter for genuine interest and product understanding.
- Auto-tag entries by niche/category so you can route them to the right campaigns later.
- Review weekly and move qualified applicants into your shortlist sheet.
Screening tip: Ask applicants to share links to three recent posts they’re proud of. This reveals their best work and their current content style.
How to build a shortlist with consistent fields
Shortlisting fails when you track inconsistent data. Use the same fields for every creator so you can compare quickly and score fairly.
Core fields to capture (minimum viable)
- Creator name
- Handle + platform (and profile link)
- Niche (primary) and sub-niche (secondary)
- Audience description (what they seem to care about; include 1–2 notes from comments)
- Location/language (if relevant)
- Average views (use a consistent method, e.g., median of last 10 posts)
- Engagement (likes/comments per post; optionally engagement rate)
- Content quality notes (hook strength, clarity, editing, storytelling)
- Brand fit (tone, values, category credibility)
- Contact info (email, manager, contact form link)
- Prior sponsors (last 5–10 brand deals if visible)
- Red flags (brand safety, inconsistent posting, suspicious engagement, competitor saturation)
How to compute “average views” consistently
Pick one approach and apply it to everyone:
- Median views of last 10 posts (recommended): reduces the impact of one viral spike.
- Average views of last 10 posts: simpler, but more sensitive to outliers.
- Average views of last 30 days: good if posting frequency varies widely.
Log both the number and the method you used (e.g., “Median last 10”). Consistency matters more than perfection.
Common red flags to track (examples)
- Engagement mismatch: very high likes but extremely low comments, or repetitive generic comments.
- Audience confusion: content topics are scattered with no clear niche.
- Brand safety risk: frequent inflammatory content, harassment, or unsafe claims.
- Over-sponsorship: feed dominated by ads, especially in your category.
- Inconsistent activity: long gaps, sudden bursts, or frequent deletions.
- Unclear ownership: repost-only accounts without original content.
Shortlist scoring rubric (weighted)
A rubric prevents “vibes-based” selection and helps teams align. Score each category from 1–5, then apply weights to get a total out of 100.
| Category | Weight | What a 1 looks like | What a 5 looks like |
|---|---|---|---|
| Brand alignment | 30% | Tone/values mismatch; frequent competitor promos; risky topics | Natural fit; credible category voice; clean brand safety; authentic product adjacency |
| Content quality | 20% | Poor audio/visual; unclear messaging; weak hooks | Strong storytelling; clear demonstrations; high watchability; consistent production |
| Audience fit | 20% | Audience interests don’t match; comments show different needs | Audience clearly matches; comments indicate relevant intent/questions |
| Consistency & reliability | 15% | Irregular posting; frequent topic shifts; unpredictable performance | Stable cadence; repeatable formats; steady baseline performance |
| Measurable performance | 15% | Low baseline views; weak engagement; no evidence of action-driving content | Strong median views; healthy comment quality; prior integrations performed well |
Scoring formula
Use a simple weighted score:
Total Score (0–100) = (BrandAlignment*30) + (ContentQuality*20) + (AudienceFit*20) + (Consistency*15) + (Performance*15) where each category is scored 1–5 and then multiplied by 20 to convert to 100-scale, or use the normalized method below.Normalized method (easy in spreadsheets):
Total Score = (BrandAlignment/5)*30 + (ContentQuality/5)*20 + (AudienceFit/5)*20 + (Consistency/5)*15 + (Performance/5)*15Example scoring (how it changes decisions)
If a creator has high views but weak brand alignment, the rubric will keep them from dominating your shortlist.
| Creator | Brand (30) | Quality (20) | Audience (20) | Consistency (15) | Performance (15) | Total |
|---|---|---|---|---|---|---|
| Creator A (huge reach, weak fit) | 2 | 4 | 3 | 4 | 5 | 67 |
| Creator B (strong fit, solid baseline) | 5 | 4 | 5 | 4 | 3 | 86 |
Creator B ranks higher because they’re more likely to deliver on-message content to the right audience consistently.
Practical shortlist spreadsheet schema (copy/paste)
Use this schema as your standard “creator CRM” tab. Keep columns stable across campaigns so your data compounds over time.
| Column | Type | Example | Notes |
|---|---|---|---|
| Creator_ID | Text | CR-00127 | Unique ID for deduping across campaigns |
| Creator_Name | Text | Jordan Lee | |
| Platform | Dropdown | TikTok | One row per platform account |
| Handle | Text | @jordanruns | |
| Profile_URL | URL | https://… | |
| Niche_Primary | Dropdown | Running | |
| Niche_Secondary | Text | Beginner training | |
| Content_Formats | Text | Tutorials; reviews | Comma-separated |
| Audience_Notes | Text | Comments ask about injury prevention | Qualitative, from comment sampling |
| Geo_Language | Text | US / English | |
| Followers | Number | 84,200 | Optional; don’t over-weight |
| Avg_Views_Value | Number | 22,500 | |
| Avg_Views_Method | Dropdown | Median last 10 | Keep consistent |
| Avg_Likes | Number | 1,450 | Based on same sample window |
| Avg_Comments | Number | 95 | |
| Engagement_Notes | Text | High question density in comments | Quality > quantity |
| Brand_Fit_Notes | Text | Evidence-based tone; no risky claims | |
| Prior_Sponsors | Text | Nike; Strava; local running store | List visible sponsors |
| Competitor_Saturation | Dropdown | Medium | Low/Medium/High |
| Red_Flags | Text | Promotes 3 shoe brands monthly | |
| Contact_Name | Text | Alex (Manager) | |
| Contact_Email | Text | alex@agency.com | |
| Contact_Method | Dropdown | Email/DM/Form/Agency | |
| Relationship_Source | Dropdown | Competitor audit | Manual search / customer / inbound / agency / marketplace |
| Last_Checked_Date | Date | 2026-01-17 | Refresh metrics periodically |
| Score_BrandAlignment | Number (1–5) | 5 | |
| Score_ContentQuality | Number (1–5) | 4 | |
| Score_AudienceFit | Number (1–5) | 5 | |
| Score_Consistency | Number (1–5) | 4 | |
| Score_Performance | Number (1–5) | 3 | |
| Total_Score | Formula | 86 | Use weighted formula |
| Status | Dropdown | Shortlisted | Prospecting / Shortlisted / Contacted / Negotiating / Passed |
| Notes | Text | Great for tutorial-style integrations | Anything not captured elsewhere |
To make this immediately usable, create a second tab called “Sampling Window” where you paste links to the last 10 posts you reviewed per creator and record views/likes/comments. Then reference those cells to calculate medians/averages consistently.