Reputation & Referral
AI gets more reviews by asking every eligible customer at the right time with a direct link — automatically, consistently, without anyone on your team remembering to do it. The volume advantage compounds: 100 automated asks at 20% conversion produces 20 reviews; 10 manual asks at 20% produces 2.
The AI mechanism: when a job is marked complete, the AI identifies the customer, checks whether they're eligible for a review request (first-time job, positive satisfaction signal, not previously asked), and sends a text or email at the optimal time window (48–72 hours post-completion). The message includes a direct link to your Google review form. No one on your team initiates or monitors this — it runs on every job automatically.
Consistency is the core advantage. Manual review requesting is sporadic — it happens after particularly good jobs, when someone remembers, when there's time. Automated requesting happens for every job with no variation. Over 6 months, a business completing 25 jobs per month has 150 automated review opportunities versus maybe 30–40 manual ones. At the same conversion rate, that's 5x more reviews.
The AI also handles the satisfaction filter — suppressing review requests for customers who indicated dissatisfaction and routing them to complaint handling instead. This protects your rating while still maximising review volume from happy customers. The net effect is more reviews, better average rating, and fewer resources spent managing the process.
Common questions
Personalised based on available data — customer name, job type, and technician name are inserted automatically. 'Hi Sarah, hope the new water heater is working well — if you have a moment, Tom would appreciate a Google review' converts better than 'Please review our business on Google'.
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