ByteStack turns the open web into a live competitive intelligence feed. By querying multiple platforms in a single prompt, you can track competitor mention volume, gauge public sentiment, surface feature requests your rivals’ users are making, and identify the influencers amplifying their brand — all without writing a line of scraping code.Documentation Index
Fetch the complete documentation index at: https://docs.bytestack.com/llms.txt
Use this file to discover all available pages before exploring further.
Track competitor mentions
Find out which competitors are getting the most positive attention on the platforms where your audience lives. Example prompt“Which competitor gets the most positive mentions on LinkedIn and X this month?”Expected response excerpt
Compare brand awareness
Measure how your brand’s visibility stacks up against a competitor across every supported platform. Example prompt“How does our brand awareness compare to CompetitorBrand across all platforms?”Expected response excerpt
awareness_gap means the competitor has more total mentions. Use this metric to track whether a marketing campaign is closing the gap over time by scheduling the query to run weekly.
Find feature requests
Discover what improvements your competitors’ users are asking for publicly, and use those signals to inform your own roadmap. Example prompt“Summarize the top feature requests about CompetitorProduct from Reddit and X.”Expected response excerpt
Monitor influencer mentions
Identify creators who are already recommending a competitor organically — before they become paid partners. Example prompt“Which influencers are organically talking about CompetitorBrand on YouTube and TikTok?”Expected response excerpt
All results reflect publicly available data at the time of the query. ByteStack does not access private posts, direct messages, or gated content. Data freshness depends on how recently a source was indexed — most major platforms are updated continuously, but a small delay between a post being published and it appearing in results is normal.