The Influencer Metric Nobody Tracks

We've worked with over 1,000 influencers at Testbook. At peak, we were producing 1,500 videos a month.

At that scale, you learn very quickly that most of the metrics brands use to evaluate influencer performance are wrong — not slightly off, but fundamentally measuring the wrong thing.

Views. Reach. Follower count.

These are the metrics that appear in every influencer marketing brief, every post-campaign report, every agency deck. They're also, in most cases, vanity metrics.

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Revenue Is a Lag Metric. Stop Using It to Evaluate Creators.

The instinct to measure influencer marketing by revenue generated is understandable. Revenue is what we care about. But using revenue to evaluate individual creators is like using today's share price to evaluate a hiring decision you made two years ago.

Too many variables sit between the input and the output:

• Product quality and pricing
• Landing page experience
• Brand trust in that market
• Competitor activity that week
• Whether a sale is running
• Whether the audience has seen your product before

The same creator, with the same content quality, promoting the same offer, can generate 5x different revenue outcomes across two months depending on these variables.

Revenue is therefore a poor signal of creator quality — it's a signal of campaign conditions.

If you evaluate creators primarily on revenue, you'll systematically undervalue creators whose audiences are highly relevant but who happened to run during bad campaign conditions. And you'll systematically overvalue creators who ran during good ones.

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The Metric That Actually Predicts Performance

The strongest lead indicator I've found: clicks per view — or more precisely, click-to-view ratio.

• Views measure how many people saw the content
• Clicks measure how many people were interested enough to act
• The ratio between them is a proxy for audience relevance — how well this creator's audience matches your target user

A real example from our influencer programme:

The second creator will convert better on the other end of the click. Not because they're a better creator — but because their audience is our audience. The general creator's audience contained our users as a small subset.

Audience relevance is the variable. Click-to-view ratio is how you measure it.

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What to Optimise For

If the click-to-view ratio is the lead metric, the optimisation logic becomes:

Reach × Relevance — not Reach alone.

For any given budget, the question is: what combination of creators maximises relevant reach?

Sometimes that's one large creator with moderate relevance. Sometimes it's twenty smaller creators with high relevance. Often it's both.

The practical implication: Cost per relevant view is a better budget allocation metric than cost per view.

You're not buying eyeballs. You're buying eyeballs that belong to your target user.

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Comment Quality: The 5-Minute Audit

Comment quality is a secondary signal worth tracking. A quick qualitative scan before finalising a creator partnership takes five minutes and catches a lot of mismatches.

High-signal comments:

• ✅ "I've been using Testbook for 2 years"
• ✅ "Which course should I take first?"
• ✅ "Is this better than [competitor]?"

Low-signal comments:

• ❌ "Great video!"
• ❌ "🔥🔥🔥"
• ❌ "Keep it up bro"

High-signal comments tell you the audience is genuinely engaged with the category, not just watching content.

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The Volume Game and the 1-in-100 Rule

Here's something that took me a while to accept: influencer marketing is partly a volume game, and that's not a bug.

Roughly 1 in 100 videos goes viral — dramatically outperforming expectations, spreading beyond the creator's direct audience, generating outsized returns.

You cannot reliably predict which video will be. The content quality matters, the topic matters, the timing matters — but there's an element of unpredictability that no amount of pre-analysis eliminates.

The implication: Scale is itself a strategy.

At 1,500 videos/month, we were virtually guaranteed to participate in the upside of multiple viral moments. That one breakout video — the one that does 6 lakh views when the creator normally does 2 lakh — often covers the cost of many others in the portfolio.

This doesn't mean volume at the expense of quality. But it does mean the answer to "how many creators should we work with?" has a higher ceiling than most brands are comfortable with.

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Evergreen vs. Spike Content

One distinction that significantly affects how you evaluate creators:

Spike content: Performs well immediately after posting, then drops off. Most influencer content. Generates a burst of views, then stops working.

Evergreen content: A video titled "Best apps for SSC CGL preparation" or "How I cracked UPSC in 6 months" continues accumulating views through search traffic for months or years.

For our category — exam preparation — evergreen content was often more valuable than spike content:

A user searching "best app for bank exam preparation" at 11pm before their exam registration closes is a very different user from someone who saw a creator's video in their feed this morning. The intent is higher. The conversion is higher.

We learned to look for creators who produced both types:

• Spikes for campaign timing and awareness
• Evergreen for sustained, high-intent acquisition

Creators who could do both were worth significantly more than their view counts suggested.

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The Practical Checklist

Before partnering with a creator:

1. ☐ Click-to-view ratio on their recent sponsored content
2. ☐ Comment quality scan — are commenters in your category?
3. ☐ Content type mix — spike vs. evergreen
4. ☐ Audience demographic overlap with your target user
5. ☐ Cost per relevant view vs. your benchmark

After a campaign:

1. ☐ Click-to-view ratio vs. channel average
2. ☐ Conversion rate on clicks vs. channel average
3. ☐ Comment sentiment — new users or existing users engaging?
4. ☐ Evergreen trajectory — still accumulating views at day 30?

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Revenue is a useful lagging signal over time, across many creators, controlling for campaign conditions. It's a poor signal for evaluating any individual creator on any individual campaign.

The metric nobody tracks — click-to-view ratio — is the one that actually tells you whether this creator's audience is your audience.

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Dhairya Mehta is Director of Growth and Marketing at Testbook, where he owns the P&L of India's largest exam-prep subscription. He writes about growth, India's developing market, and building things.

Connect on LinkedIn · dhairyamehta.in