Birdview PSA — 0.9% to 21.5% ChatGPT visibility in 8 weeks

• Started Feb 2026 at 0.9 percent ChatGPT mention rate in the PMS cluster.
• Mapped 100 LLM queries and weighted Decision-stage prompts 2x in scoring.
• Shipped 8 articles in 8 weeks — one on Birdview's site, one on Medium per topic.
• Reached 21.5 percent ChatGPT mention rate, 27.8 percent Gemini, and 103 unique queries with brand presence.
• 95 of 100 LLM queries overlap with Birdview's SEO keywords — one asset, two channels.

B2B software buyers increasingly start their research in ChatGPT, Gemini, or Perplexity rather than Google. They ask things like "how to choose PMS for a distributed team" — and get a direct answer with recommendations. If your brand is not in that answer, you are out of the buying process before the customer ever visits your website.

Birdview had strong AI authority in a narrow PSA cluster — but in the broader, more competitive PMS cluster nearly nothing. That is where the larger audience lives: consulting firms, architecture practices, professional services teams.

1. Mapped the query landscape. We collected 100 LLM queries in the PMS space and tagged each by funnel stage (awareness → evaluation → decision). We tracked which sites AI systems were already citing for each query.
2. Focused on Decision-stage queries only. We used a "Decision × 2 + Evaluation × 1" scoring model. The top 5 topics were all Decision-stage prompts ("how to choose PMS for a company", "how to pick PMS for distributed teams", "what indicates low implementation risk", etc.). No dilution across the funnel.
3. Published by protocol. Each topic shipped as two pieces — one on the client's site, one on Medium. Every article passed an LLM-citability check: answer in first 150 words, H2s as user questions, self-contained paragraphs, tables, and FAQs. Score under 80 = rewrite before publish.
4. Measured weekly from day one. We ran 16 control scans across ChatGPT, Gemini, Perplexity, and Google AIO over eight weeks. The data showed Gemini responded fastest to scenario-based content — so we doubled down on that format mid-pilot.

Three things actually drove the lift, and they all rewrite how Birdview's marketing team thinks about content distribution:

1. Platform choice over volume. Perplexity indexes Medium aggressively and cites it as a source. Publishing one piece on Birdview's site alone left significant AI reach unclaimed.
2. Decision-stage focus over funnel coverage. Awareness content matters, but at Decision stage an AI answer is directly adjacent to a purchase conversation. Eight weeks of focused effort produced measurable pipeline impact.
3. Weekly measurement over quarterly reviews. Without weekly data we could not see Gemini responding to scenario-based content. The ability to shift format mid-pilot is what made the result possible.

• ChatGPT mention rate: 0.9% → 21.5% in the PMS cluster (a 23-times lift).
• Unique LLM queries where Birdview appears: 8 → 103.
• Gemini mention rate: 27.8%.
• SEO bonus: 95 of the 100 target LLM queries overlap with Birdview's organic SEO keywords. The same content drives both channels.

Three things actually drove the lift:

1. Platform choice. Perplexity indexes Medium aggressively. Publishing one piece on the client's domain alone would have left significant AI reach unclaimed.
2. Decision-stage focus. Awareness content matters, but at Decision stage an AI answer is directly adjacent to a purchase conversation. Eight weeks of focused effort produced measurable pipeline impact.
3. Measurement from day one. Without weekly data we could not see Gemini responding to scenario-based content. The ability to shift format mid-pilot is what made the result possible.

Full case study: https://www.linkedin.com/pulse/we-grew-b2b-saas-brands-chatgpt-visibility-23x-8-weeks-shevchenko-kh6rf