Review Response Brand Voice Calibration (Onboarding)

Review Response Brand Voice Calibration (Onboarding)

1. 01

   Collect the client's existing review responses and brand guidelines

   Gather at least 20 past replies across platforms like the App Store, Google Play, and Google Business Profile, plus any tone-of-voice documents. This gives the AI a concrete baseline to learn from.

2. 02

   Define the escalation criteria for negative or sensitive reviews

   Work with the client to specify which topics (refunds, legal issues, safety) must route to a human. Set a rule that any review below a 2-star rating or mentioning a competitor is never auto-published.

3. 03

   Configure the knowledge base with store listings and product facts

   Feed the tool the app's store description, feature list, and FAQ answers so drafts reference accurate details. For example, Reply Argus builds its knowledge base from the store listing and marketing page, so verify those are current.

4. 04

   Set approval rules for auto-publish versus human review

   Decide which review types can be auto-published (positive, routine questions) and which require a click-to-approve. Start with a 48-hour review window for all replies to catch tone drift before it goes live.

5. 05

   Draft a brand voice cheat sheet for the AI

   Write 10 example replies in the client's voice, covering praise, a bug report, a refund request, and a neutral comment. Include banned phrases and preferred sentence lengths to keep drafts on-brand.

6. 06

   Test the system on a sample of historical reviews

   Run 30 past reviews through the tool and compare the AI drafts against what the client actually sent. Measure how many drafts need editing and adjust the knowledge base or voice rules accordingly.

7. 07

   Document the human escalation path and response SLAs

   Confirm who on the client's team handles escalations and what the target response time is (e.g., under 24 hours for negative reviews). Put this in a one-page handoff doc for the delivery team.