In January 2026, a project management SaaS we'll call Velotrack ran their category queries across ChatGPT, Perplexity, Claude, and Gemini. Their product did not appear in a single response. Competitors they knew well -- and a few they did not -- were being recommended consistently.

Their SEO was solid. DA 52, ranking for roughly 400 keywords, 18,000 monthly organic visits. By every traditional measure, they were visible. But AI search was operating off a completely different signal set, and they had none of them.

38 days after starting work with Peakmention, Velotrack was the #1 recommended project management tool on Perplexity for their primary category queries and ranked #2 on ChatGPT. Their AI visibility score went from 6/100 to 87/100. Here's exactly what we did and when.

6Starting Score
87Score at Day 38
#1Perplexity Rank
#2ChatGPT Rank

The Audit: What We Found

Our first step with every client is a full citation audit across all four platforms. We run 40+ queries across the client's category, map which brands appear, and analyze the signal sources driving those mentions.

For Velotrack, the audit revealed three core problems:

  1. No Reddit presence. The primary subreddits for their category (r/projectmanagement, r/productivity, r/remotework) had zero mention of Velotrack in threads from the past 18 months. Competitors appeared in 23 threads between them.
  2. Missing from category listicles. The 12 highest-trafficked listicles ranking for "best project management software" did not include Velotrack in 11 of them. One had a passing mention with no detail.
  3. No third-party review depth. G2 profile existed but had 4 reviews with thin content. Capterra had 2. Competitors averaged 47 and 31 reviews respectively.

The pattern is consistent with what we see across most clients. Strong SEO often means strong content on your own domain. But AI models primarily cite third-party sources -- reviews, community discussions, comparison articles, and journalism. Owned content barely registers.

Key insight: AI models don't cite your website to describe your product. They cite what other people say about you. If no one is talking about you in the places AI models monitor, you are invisible -- regardless of how good your own content is.

The 3-Week Sprint

Our standard engagement runs three focused weeks. Here's how it played out for Velotrack.

Week 1 — Foundation
Category mapping and schema infrastructure
We mapped Velotrack's category across all four platforms, identifying the specific query clusters where they needed to appear. We then implemented structured data on their pricing page, product pages, and key landing pages -- Organization schema, SoftwareApplication schema, and FAQ schema on their help documentation. We also submitted their updated sitemap and pinged Bing specifically (critical for Perplexity visibility).
Week 2 — Volume
Reddit engagement and review building
We identified 14 active Reddit threads discussing project management tools and introduced Velotrack authentically -- answering specific questions, sharing specific use cases, not promotional. We also contacted Velotrack's existing customer base and coordinated 22 new G2 reviews and 11 Capterra reviews in the span of 8 days. Each review was verified, specific, and detailed. We targeted Bing-indexed comparison articles for outreach, securing Velotrack's inclusion in 3 pieces within the week.
Week 3 — First Citations
Journalist outreach and listicle placements
Outreach to journalists covering productivity and work tools landed two substantive articles mentioning Velotrack with feature-specific language. We pursued 6 additional listicle inclusions and secured 4, including two of the top-trafficked roundups for their primary keyword cluster. By day 21, Velotrack had appeared in ChatGPT responses. By day 23, Perplexity was citing them consistently.

The Score Progression

AI Visibility Score -- Velotrack (0 to 100 scale)
Day 0
6
Day 7
14
Day 14
38
Day 21
61
Day 38
87

Platform-by-Platform Results at Day 38

Perplexity
Category queries: "best project management tool for remote teams"
#1
ChatGPT
Cited in 71% of category queries tested
#2
Claude
Appearing in comparison queries; not yet in top-3 for broad queries
Top 5
Gemini
Mentioned with feature-specific language in 3 query clusters
Cited

What Moved the Needle First

The earliest movement -- the jump from 6 to 38 between day 7 and day 14 -- came almost entirely from the schema implementation and the review building. Structured data gave AI models a clean, machine-readable understanding of what the product does and who it is for. The G2 and Capterra reviews gave that description third-party validation.

The Reddit work did not show up in citations during week 2, but it played a significant role in the week 3 acceleration. Perplexity, in particular, appeared to index the Reddit thread activity and factor it into recommendations within 10-14 days of the posts going up.

The listicle and journalist placements drove the final push to 87. These are high-authority third-party sources, and when AI models encounter a brand being mentioned across multiple high-quality publications with consistent language, it reinforces the citation signal significantly.

Traffic and Pipeline Impact

Velotrack tracked a 34% increase in direct and "unknown" organic traffic in the 30 days following the campaign, which they attributed primarily to AI-sourced visits. Trial signups from the /pricing page increased 28%. They directly attributed 3 enterprise demo requests to Perplexity citations confirmed via session referral tagging.

None of this was because we improved their website. We did not touch their site beyond schema implementation. Everything else was external signal building -- placing the brand in the sources AI models trust.

The compounding effect: Six weeks after the sprint ended, Velotrack's AI visibility score had climbed to 91/100 without any additional active work. The citations persisted. The Reddit threads continued to accumulate upvotes. The review count continued to grow organically. AI visibility, once built, tends to hold and grow on its own.

What Made This Possible in 38 Days

Speed comes from focus. Most agencies spread work across owned content, technical improvements, and vague "outreach" programs simultaneously. We do one thing: build the third-party citation footprint that AI models use to form recommendations.

That means Reddit, reviews, listicles, and journalist coverage -- the exact four workstreams in our sprint. Everything else is secondary to these four because these are what AI models are actually trained on and retrieving from.

Velotrack's results were strong but not unusual. The pattern holds across verticals because the underlying mechanism is the same regardless of what you sell.

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