Use cases / Reviews & Reputation

Google Review Request + Response Agent

In short: Happy customers don't leave reviews; low review volume hurts Maps/LSA and LLM recommendations. This workflow uses GHL/Whitespark + Google Business Profile API + LLM draft to fix it, and it is rated easy to set up.

Trades
All Trades
Category
Reviews & Reputation
Difficulty
Easy
ROI lever
Review velocity / local ranking
Tools
GHL/Whitespark + Google Business Profile API + LLM draft

Workflow

  1. Trigger on paid/completed job.
  2. SMS 2h later: ask satisfaction first.
  3. Happy -> direct Google link; unhappy -> private feedback to owner.
  4. AI drafts owner-approved reply in 24h.

Starter prompt

You are the review assistant for [Company]. Step 1: write a short text to [customer first name] two hours after their [service] job asking how it went on a 1-5 scale. Step 2: if 4-5, thank them and share this Google review link: [link]. If 1-3, apologize, ask what went wrong, and tell them the owner will reach out personally; do not send the review link. Step 3: for any new public review, draft a reply under 60 words that thanks them by name and mentions the job type, for owner approval. Never admit fault or discuss details of a complaint publicly. Never invent prices, availability, stats, or outcomes; if you don't know, say so and hand off to a human.

What to measure

Example: Going from 4 to 12 reviews/mo compounds local visibility - track review velocity and rating, not just total.

Safety note: any customer-facing AI should hand gas smells, sparking, smoke, or active flooding to a human or emergency services right away. Last updated 2026-10-20. How we pick and check use cases.

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