Agents built from your buyers’ own reviews, posts and calls read your content and tell you who it lands with. You get a ranked title list, the sub-markets you are missing, and what to change.
Before they meet you: review sites, community threads, competitor complaints, and how all of it shifted over 18 months. After they meet you: call recordings, CRM notes, win/loss reasons.
Most tools get one half. A persona doc gets neither. How Ground Reality works→
From one asset to a ranked, tested list of who to target.
Reads your content. Keeps the signal, drops the fluff.
Finds where real fit exists. Not where titles match.
Specific titles like “Quant Developer,” not “Head of Data.”
A sceptical version of each one reads it. The list gets ranked.
All three show up the same way: rising cost per acquisition.
“Head of Security” at a bank and at a FinTech share a title and nothing else.
On G2, Reddit and Slack. None of it shows up in your analytics.
The sub-markets that love your content surface after months of spend, if ever.
Weeks of manual ICP research. Replaced by a validated list.
Specific titles with resonance scores.
The language that lands, per title.
Sub-markets that out-resonate your ICP.
SEM exclusions to cut low-intent traffic.
A coaching report when content is too thin.
Know which titles to target before turning on spend.
Justify expansion with data. Cut CAC.
Confirm the asset matches who responds.
Cross-vertical evidence before a TAM bet.
Thirty of 140 candidate titles cleared, placed by subvertical and reader. Of the ones that scored too low to target, 17 were economic buyers and 2 were guardians — the two roles that stop deals. The page spoke fluently to end users and champions, and not at all to the people who sign.
Read the full report this came from →
Send us one content asset. You get the ranked title list back.