A brief, a customer journey, a playbook and a prompt library, built from what you tell us and what we find on the company. Your AI customer experience advisor does the homework. You decide what to act on.
The business, its customers and the findings worth a closer look, each one showing what it is built on.
Illustrative example
A prompt library in every playbook
Every step in your playbook comes with a prompt that has already done the homework on your company. Paste it into Claude or ChatGPT and skip explaining your business to a chatbot for the fourth time this week.
Example inputs, yours to replace
| Metric | Baseline | Current | Delta | Revenue per year | Confidence |
|---|---|---|---|---|---|
| Churn rate | 14% | 9% | 5 pts lower | $96K | based on your inputs |
| Time saved | [your number] | [your number] | [your number] | [your number] | [your number] |
| Cost avoided | [your number] | [your number] | [your number] | [your number] | [your number] |
Rows 1 to 3 of 6. $96K a year = 5 points of $1.92M ARR (40 × $48K), if the lower churn rate holds for 12 months. It is the revenue tied to the change, not proof of what caused it. Check the assumptions before using this estimate.
Then a three-sentence script for the renewal call, with blanks where your numbers go.
Revenue impact estimate for the renewal conversation
You get: Six rows, before and after, every figure left for you to fill. Shown on the left.
Objection battle card for the deals that stall
You get: The objection in your buyer's words, the worry behind it, and a five-line answer.
Day-30 feedback decision framework
You get: What each answer means, what goes out automatically, and when a person steps in.
Your own company or a client's. One conversation, no integrations.
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