Finding and vetting creators

0:00 Finding and vetting creators

A Dubai supplement brand once shortlisted ten creators and nearly signed the one with the biggest numbers. Then someone asked for her native analytics. Only twelve percent of her audience was in the Gulf. The brand would have paid Dubai prices to reach people who couldn't buy the product. In this lesson, you'll learn where to find creators and how to vet them with a four-part framework. By the end, you'll be able to build a written scorecard and spot the red flags that public numbers hide.

0:38 Where to find creators

Let's start with where to look. Your own community comes first: customers and followers already tagging you are often the most authentic partners. Then platform marketplaces, where available in your market: TikTok One, the Instagram Creator Marketplace, and YouTube BrandConnect. These can show first-party audience data with the creator's permission. Then third-party discovery tools, hashtag and keyword search in local languages like Arabic and Urdu, agencies and talent managers, competitor partnerships, and regulator registers where they exist, such as checking a UAE creator's advertiser permit.

1:15 The vetting framework

Here's the framework. Fit, trust, performance and safety. Think of it like hiring an employee. Fit is whether they suit the role: does their audience match your target by location, age, language and interests, and does their style suit your brand? Trust is the background check: are the followers and engagement real? Performance is the track record: what do their posts typically achieve, including sponsored ones? Safety is the reference check: have they said or done things that would embarrass you? The golden rule sits across all four. Ask for native analytics, screenshots or exports from the platform itself, rather than trusting public follower counts.

2:01 Trust red flags

Let's zoom in on trust, because this is where money gets wasted. Red flags include a sudden follower spike with no viral post or press moment to explain it. Engagement that's very low for the follower count, or suspiciously high with generic comments like nice pic from unrelated accounts. An audience mostly in countries unrelated to the creator's language or content. And views that don't match engagement. There's also a legal angle in the US now. The FTC's rule on consumer reviews and testimonials, in force since October 2024, prohibits buying or selling fake indicators of social media influence, like bot followers or views, for commercial purposes.

2:48 Example 1: engagement by views

A simple example: engagement rate. Say a TikTok creator's last post had forty thousand views, and it got two thousand likes, three hundred comments, four hundred shares and three hundred saves. That's three thousand engagements. Engagement rate by views is three thousand divided by forty thousand, times a hundred. Seven and a half percent. On short-video platforms, many marketers prefer engagement by views rather than by followers, because reach is driven by recommendations. Just be consistent, compare creators on the same platform and niche, and be wary of any generic good engagement benchmark you find online.

3:30 Example 2: Dubai supplement vetting

Now a realistic scenario, with illustrative details. Omar vets ten creators for a Dubai fitness supplement brand. He requests native analytics from all ten. Creator three is Dubai-based, but only twelve percent of her audience is in the GCC. Removed. Creator seven gained eighty thousand followers in one week with no viral post, and his comments are mostly emojis from unrelated accounts. Removed. Creator five is a great fit, but promoted a banned supplement two years ago. Omar raises it with her directly. She explains she publicly changed her stance, and shows the post. The team discusses it, decides to proceed with a stricter claims brief, and records the reasoning. That record matters if anyone asks later.

4:21 Watch me: weighted scorecard

Watch me build the scorecard. I open a sheet with five criteria and weights. Audience fit from verified analytics, thirty percent. Content quality and style fit, twenty percent. Authenticity signals, twenty percent. Performance, using median views and engagement quality, twenty percent. Brand safety, ten percent. Now I score Creator A: four, five, five, three, five. And Creator B: five, three, three, four, four. I multiply each score by its weight and sum. Creator A lands at four point three. Creator B at four point one. Close. So I look at the notes. Creator B's authenticity score came from some odd comment patterns. That tips it. And notice I used median views, not average, so one viral hit doesn't inflate performance.

5:13 The data request

Let me add a practical step between shortlisting and scoring: the data request. Once a creator replies positively, send a short, polite message asking for five things from native analytics. Top countries and cities and the age and gender split for the last thirty days. Reach or views for their last ten posts in the format you want. Two recent sponsored posts with reach, views and link clicks. Any licenses or permits they hold, like the UAE advertiser permit or a Saudi Mawthooq license. And any current exclusivities in your category. Professional creators will have this ready in minutes. If someone refuses to share any native data at all, that's not proof of fraud, but it's a reason to be cautious, and often a reason to move on to the next name on your list.

6:12 Safety + common mistakes

Before we finish, safety and the common mistakes. For safety, review several months of content, including older posts, highlights and comments. Look for offensive language, misinformation, risky stunts, undisclosed ads and controversial associations. Check how they handle criticism, check competitor deals, and confirm licenses in the UAE and Saudi Arabia. Now the mistakes. Relying on follower counts and public screenshots. Using averages skewed by one viral video. Skipping the content history review. And ignoring licensing in regulated markets.

6:46 Recap

Recap. Source creators from your community, marketplaces, tools and local-language search. Vet for fit, trust, performance and safety using native analytics. Know the red flags, and remember that buying fake followers or views is now explicitly prohibited under the FTC rule. Calculate engagement consistently, use medians, and write your decisions down in a weighted scorecard.

7:10 Try this now

Try this now. Copy the data request message from your lesson and adapt it for your next campaign. Then build the weighted scorecard and score three real creators in your niche using public information. For each, write down what you'd ask them to verify with native analytics. In the next lesson, we'll write the brief that gets great, compliant content from the creators you pick. One more habit worth building: save every creator's analytics screenshots and your scorecard in a shared folder with the date. When you review the campaign later, you'll be able to see which vetting signals actually predicted strong results, and adjust your weights. Over a few campaigns, your scorecard becomes a real competitive advantage, tuned to your own brand and markets rather than to generic advice.