Customer Clarity
v1.2
POWERED BY GAMESHIFTERS
Build evidence-based buyer profiles from real customer language. · Updated June 9, 2026
Why This Tool Exists
Customer Clarity mines real customer language for the psychological patterns that predict buying — pains, desires, objections, and trigger events — then builds a buyer profile from evidence instead of demographic guesswork. It quotes your customers' exact words back to you and grades your own assumptions against what the data actually shows.
Two Modes
- I Have My Own Customer Data: Paste transcripts, tickets, emails, reviews, and lost-deal notes. The more raw and unedited the language, the better the analysis.
- Borrow from Market: Pre-launch? Name your niche and competitors and the AI drafts a starting buyer profile from its general knowledge of those markets. It does not pull live reviews or forum data — treat the output as hypotheses, and use the built-in validation plan to test them in real conversations.
What's New in v1.2 (June 9, 2026)
- Engine selection: Claude Sonnet 4.6 (default) or Claude Fable 5, Anthropic's newest frontier model.
- Assumption Audit: Tell the tool who you think your buyer is, and the report grades that hypothesis as confirmed, contradicted, or untested.
- Lost-Deal Forensics: A dedicated input for refunds, cancellations, and deals that died — the language of "no" is often more revealing than the language of fans.
- Sample-size-aware confidence: The analysis scales its claim strength to how many customers your data represents.
Your Business Context
One line. e.g., "8-week group coaching program for agency owners" or "B2B SaaS for invoice automation."
Buyer psychology changes radically by price tier. e.g., "$49/mo subscription" or "$5K one-time."
One or two sentences. The report will grade this assumption against the evidence: confirmed, contradicted, or untested.
Your Customer Data
Raw beats summarized — the analysis mines exact wording, not your paraphrase. Up to 5,000 characters.
0 / 5,000
Frustration language reveals what customers actually expected to get. Up to 5,000 characters.
0 / 5,000
Pre-sale questions expose objections and decision criteria. Up to 5,000 characters.
0 / 5,000
Include the bad ones — complaints carry the objection language your marketing needs to answer. Up to 5,000 characters.
0 / 5,000
The exact words of people who said no, asked for money back, or quietly left. Often more revealing than fans. Up to 5,000 characters.
0 / 5,000
This calibrates how confident the analysis is allowed to be. Five customers = early signals. Two hundred = patterns.
Market Inputs
Be specific. "Client onboarding automation for marketing agencies" beats "agency software."
List 2–5 competitors. The profile is drafted from the AI's general knowledge of these markets — a starting hypothesis to validate, not live review data.
Engine
Sonnet 4.6 is fast and sharp. Fable 5 is Anthropic's newest frontier model (released June 9, 2026) — deeper reasoning, slower, costs more per run.
Enter data to continue •
Analysis takes ~30-90 seconds
Copied to Clipboard