Reversal of negative AI search labels in 30 days: GEO practical case of new brand “Three Steps”

In the age of AI information, a company’s reputation often depends on what customers see first in AI search results. What many businesses fear is not competitors, but negative sentiment and complaint posts appearing frequently in front of customers, which influences potential customers’ decisions. Can this problem be solved? The answer is definitely yes. Below, Dabing shares a complete practical case of turning negative sentiment into positive recommendations, reversing negative labels in AI search in 30 days.

1. Project example

Client: a weight loss product (brand in early launch stage), with negative labels from initial AI search (pyramid scheme risk, lack of third-party certification), low user inquiry volume and high user skepticism.

2. Our actions (within 30 days)

(1) Days 1–7: Authoritative response
Publish official test reports and compliance certificates on the official website and official accounts (PDF downloadable); simultaneously publish interview transcripts of the founder / head of R&D (expert endorsement).
(2) Days 8–14: Scenario-based and intent coverage
Produce 6 short articles: 3 targeting investment / franchise intent, 2 targeting consumption / effect intent, 1 educational (ingredient principles). Each uses structured lists and case data.
(3) Days 15–21: Soft article matrix deployment
Rankings (Top 5), brand (in-depth reviews), and case (user operation diaries) content published simultaneously to official accounts, Zhihu, industry sites and DeepSeek-friendly platforms.
(4) Days 22–30: Testing and consolidation
Monitor AI response tendencies. For negative keywords still shown by AI, add targeted supplementary content and link internally to authoritative report pages. Use small-scale paid promotion to drive high-quality content into initial user behavior (driving clicks and dwell time).

3. Results (key quantifiable points)

(1) Positive descriptions appeared in AI responses after 14 days.
(2) Over 200 private message inquiries within 30 days, with 18% converting to sales follow-up.
(3) Sentiment monitoring shows a significant drop in the occurrence rate of negative keywords in model answers.

4. Case summary (replicable)

(1) Authority first, then volume;
(2) Scenario-based coverage of different intents;
(3) Keep authoritative proof in the “answer pool” long-term with structured content and internal links.