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DJI Studio

case study
Panoverse caught a shift in how ChatGPT was describing our product. It told us exactly which articles to publish to fix it. We would have missed that.
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Lisa Wang
Director, Digital · DJI Studio
industry
creative tools
size
enterprise · global
markets
global
using since
2026-02

DJI Studio sells creative tools — drones, gimbals, mics — into a market where more and more purchase research starts with an AI search box. When that channel shifted, they needed to know fast.

Context

Early 2026: DJI Studio's organic acquisition was increasingly being driven by users asking ChatGPT and Perplexity for product recommendations. The team knew this in principle. They didn't have a way to measure it.

Problem

In February, citation rate on a cluster of priority queries — “best gimbal for solo creators”, “wireless mic for podcasts under $200” — dropped from an 81% hit rate to 56% over about three weeks. No traditional marketing tool would have caught this. It didn't show up in Google rankings; it didn't show up in social mentions; it just showed up as a quiet decline in AI-referred sessions.

The hardest failures to diagnose are the ones that don't trip any alarm — they just slowly stop working.— Lisa Wang, Director, Digital

Approach

Panoverse runs continuous AI-search tests across 240 priority queries for DJI Studio. When the citation drop triggered, the system not only flagged the decline but produced a read on how the AI descriptions had changed — the product category language, the comparison brands cited, the specific competitor names that had risen.

The diagnosis was specific: an LLM update had shifted emphasis toward products with more long-form ingredient/spec-depth articles on third-party review sites. DJI Studio's competitors had that content; DJI Studio didn't.

Result

The content brief Panoverse produced covered nine articles — spec-dense, use-case focused, specifically addressing the query cluster where citation had dropped. DJI Studio's content team published them over six weeks.

Citation rate on priority queries recovered to 80% within 60 days of publication. On some queries it now exceeds the pre-drop baseline.

We wouldn't have known what was wrong. We definitely wouldn't have known what to do about it. That's the whole game.— Lisa Wang