Brands deploy AI and audits to fight fake influencers

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Influencer marketing is central to brand-building in India, but inflated metrics and fake profiles are creating costly pitfalls. Smaller brands, in particular, are vulnerable to nano-influencers with bot-driven audiences. A D2C snacks company recently admitted losing money after partnering with a fake food vlogger — underscoring the risk.

To counter this, marketers are moving away from vanity metrics like likes and follower counts. Instead, they track cost per authentic engagement, watch time, and audience overlap. New frameworks like the “View Quality Index” are also being used to rank meaningful interactions.

Large players including Dabur and Duroflex have put formal checks in place. Dabur’s digital team relies on third-party audit tools and platform analytics to identify anomalies such as sudden follower spikes, mismatched engagement ratios, or low-quality comments. Their approach prioritizes engagement rate, cost per engagement, and cost per view to measure efficiency. Duroflex conducts manual reviews of influencer comments and follower quality to flag inconsistencies.

Artificial intelligence is emerging as the most powerful filter. “AI-driven authenticity checks are becoming the weapon of choice,” said Sagar Pushp, Co-founder of ClanConnect. These tools can evaluate credibility scores, detect bot-driven engagement, and streamline the vetting of large influencer pools. Dabur, for example, has begun using AI-based audit systems to analyse audience credibility and regional distribution.

Marketers also emphasize that long-term partnerships with creators provide stronger safeguards than one-off campaigns. Consistency, they argue, is a more reliable marker of authenticity than sudden bursts of activity.

With influencer marketing spends projected to climb further, the shift toward AI tools and data-driven vetting reflects a broader industry pivot: safeguarding trust is now as critical as driving reach.