Everything in this snapshot, working together
Two parts that work as one: the system that wins more good reviews, and the system that protects the reputation already in place.
Winning more good reviews
Automated review requests
Reaches out by email and text asking how the experience was, with polite follow-ups spaced over time, and guides happy customers straight to a public Google or Facebook review.
The AI that decides who to ask
Step one: an AI reads each customer's conversation and looks for signs of unhappiness. For customers with no signs of a bad experience, it triggers the automated review request. Unhappy customers are not asked and are flagged to the team.
Protecting the reputation already built
Private interception of unhappy customers
A customer who signals they were unhappy gets a calm apology and a short private survey, and the team gets a task to follow up, so the frustration is resolved privately instead of becoming a public one-star.
AI that replies to reviews
Responds to reviews in the business's voice. Reply automatically, suggest a draft for approval, or leave it off.
Spam filtering, review balancing, and a review widget
Filters junk reviews, helps balance requests across platforms, and puts the client's best reviews on display with an embeddable widget.
Review Management Pipeline
Tracks where every customer sits in the review journey, from eligible to requested to the response received, so positive, neutral, and negative outcomes are each easy to see and act on.