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Published by Tubular Labs (now part of Chartbeat Inc.), this report makes the case for moving influencer investment decisions beyond surface metrics such as follower counts, views and engagement rates. Using Tubular's proprietary social video intelligence platform, which tracks over 15 billion videos and 45 million creators across YouTube, Instagram, Facebook and other platforms, the report demonstrates how behavioural signals provide a far more reliable predictor of commercial outcomes.
The core argument is that reach does not equal influence and influence does not equal revenue. Instead, the report highlights four signals that better forecast results: audience overlap (whether a creator's audience actually reaches new customers), shopping affinity (whether viewers have demonstrated purchase intent in relevant categories), search behaviour (what the audience searches for beyond the content they watch), and cultural alignment (whether the creator's content resonates authentically with the brand's category).
Case studies illustrate the argument with concrete data: 18 billion anime views in East and Southeast Asia do not translate to gaming purchase intent, yet a small subset of commentary-driven anime content creates a high-value shopping overlap. A 136,000-follower fashion creator drove 168 million views for a beer brand because her audience's behavioural profile aligned with the product. Medical influencers on Instagram are shown to shape consumer search behaviour around wellness topics well beyond their direct followers.
For destination marketing teams, the report's framework offers a useful lens for evaluating travel content creators: reach matters less than whether an audience's travel interests, booking behaviours and destination affinities match what a DMO is trying to achieve.
Published by Tubular Labs (now part of Chartbeat Inc.), this report makes the case for moving influencer investment decisions beyond surface metrics such as follower counts, views and engagement rates. Using Tubular's proprietary social video intelligence platform, which tracks over 15 billion videos and 45 million creators across YouTube, Instagram, Facebook and other platforms, the report demonstrates how behavioural signals provide a far more reliable predictor of commercial outcomes.
The core argument is that reach does not equal influence and influence does not equal revenue. Instead, the report highlights four signals that better forecast results: audience overlap (whether a creator's audience actually reaches new customers), shopping affinity (whether viewers have demonstrated purchase intent in relevant categories), search behaviour (what the audience searches for beyond the content they watch), and cultural alignment (whether the creator's content resonates authentically with the brand's category).
Case studies illustrate the argument with concrete data: 18 billion anime views in East and Southeast Asia do not translate to gaming purchase intent, yet a small subset of commentary-driven anime content creates a high-value shopping overlap. A 136,000-follower fashion creator drove 168 million views for a beer brand because her audience's behavioural profile aligned with the product. Medical influencers on Instagram are shown to shape consumer search behaviour around wellness topics well beyond their direct followers.
For destination marketing teams, the report's framework offers a useful lens for evaluating travel content creators: reach matters less than whether an audience's travel interests, booking behaviours and destination affinities match what a DMO is trying to achieve.
