Sentimental Analysis

You've just finished two days of creator shortlisting. The list is ready. You send it to the client. They come back asking why three creators have unusually high follower counts. One of them has an audience that is 70% outside the target market. All of that work. Done manually. And the mistakes were completely avoidable. Meanwhile, the same team is three campaigns behind. Because discovery, vetting, and reporting all go through the same two people every single time. This is t

You ran a campaign with a macro-influencer. Premium rate. Big follower count. The results came back at 1.2% engagement. Six months later, same brief. Five micro-influencers this time. 3.8% engagement. Lower spend. The question after isn't "did micro win?" You already know it did. The real question is why it took a failed campaign to get there. Most brands are still picking influencer tiers based on follower count and gut feel. The data tells a very different story. What the t

Reach came in 40% below projection last quarter. Every influencer posted on time. The content looked decent. Engagement rate was fine. The client still wants to know why it underdelivered. The problem was that the brief was written in 2023, but implemented in 2026. Think about it: the platform, the algorithm, everything has changed, but the brief was written in such a way that it would have ranked in 2023, not 2026. In 2026, saves and shares perform much better than likes bec