Longitudinal AI visibility tracker for SaaS brands
Build a longitudinal AI visibility tracking tool for SaaS brands that runs consistent prompt sets against ChatGPT, Perplexity and other AI assistants on a schedule, then shows volatility trends over time rather than single snapshots. Sell it to marketing teams and SEO agencies who need to monitor how often their product gets recommended versus competitors, with alerts when ranking drops or a competitor suddenly appears.
What to build
A scheduled AI-visibility tracker for SaaS brands that runs a fixed prompt set against ChatGPT, Perplexity and other AI assistants daily, stores the results, and shows marketing teams and SEO agencies volatility trends plus alerts when their ranking drops or a new competitor appears.
AI assistant answers about which SaaS tools to use are far more volatile day-to-day than people assume, so brands need ongoing tracking instead of one-off prompt checks to know how they're actually being recommended.
Demand
Marketing teams and SEO/AI-visibility agencies managing competitive positioning want this now because AI assistants are an emerging discovery channel, and the only current workflow is manual, inconsistent spot-checking.
- r/microsaasObservation
Reddit post 'Tried tracking 20 SaaS competitors across ChatGPT and Perplexity for several days and the results were more inconsistent than I expected' — firsthand account of manual multi-day tracking revealing output volatility.
- Signal author (first-hand experiment)Observation
Author manually tracked 20 SaaS competitors across ChatGPT and Perplexity over several consecutive days and found recommendation results more inconsistent than expected.
Stack
- OpenAI API
- Perplexity API
- Python + cron / scheduled serverless jobs
- Postgres or Supabase
- Next.js dashboard
- Resend or Slack API for alerts
Solo + AI difficulty
Easy to MVP: scripting daily prompt runs against two APIs and logging results is a weekend project. The hard part is designing a stable prompt/scoring methodology so volatility reflects real shifts, not prompt noise. Rough time-to-MVP: 1-2 weeks.
- Entry threshold
- A solo builder can ship an MVP in days using LLM APIs to run scheduled prompts, store results in a database, and visualize trends; the harder part is building a defensible prompt methodology and enough historical data to make the trend charts valuable.
- Window
- 6-12 months
Where to find first users
- r/microsaas
- r/SEO
- Indie Hackers
- Product Hunt launch
Competitors
Counter-signals & risks
The observed inconsistency comes from a small, informal sample (20 competitors, a few days), which may not generalize into a reliable product-defining metric.
Existing SEO rank trackers could bolt on AI-visibility volatility tracking as a feature, eroding differentiation for a standalone tool.
ChatGPT and Perplexity could tighten API terms, rate limits, or scraping restrictions, creating platform risk for a product built on repeated automated querying.
Original title: Tried tracking 20 SaaS competitors across ChatGPT and Perplexity for several days and the results were more inconsistent than I expected
Related signals
- Marketing#2
Weekly digest of threads AI cites for your brand
Build CiteScout, a weekly email digest that tracks which external threads and videos (Reddit, YouTube, forums) are being cited by AI answer engines like Perplexity and ChatGPT for a brand's buyer questions, showing what is missing from each source so the brand knows exactly where to engage. Target is small SaaS and DTC brands already paying for AEO/GEO visibility trackers who are frustrated that those tools show a score but no actionable next step.
Demand6/10est.Buildability8/10est.Competition10/10est.via Reddit0No named competitors