The problem with manual feedback collection is simple: it only happens when someone has time, which means it happens inconsistently or not at all. Businesses that do collect feedback typically ask for it at the point of sale, before the customer has had the chance to form a real opinion. AI employees solve both problems. The feedback request goes out at the right time: after a service is delivered, after a product is received, or after a specific interaction has had time to settle. The request is personalised to the specific transaction, which increases response rates significantly. When feedback is received, the AI analyses sentiment. Positive responses trigger a gentle request to share the experience on Google or another review platform. Negative responses trigger an immediate alert to a human team member, giving the business the chance to resolve the issue before the customer takes their frustration public. ZingZee's AI feedback systems consistently improve the volume and quality of public reviews for the businesses that deploy them.