Email NPS surveys in India get a median response rate of 12.4%. An AI voice agent calling the same customer base gets 45-65% — a big enough gap that it changes whether feedback data is actually representative or just the opinions of the small slice of people who bother filling out a form.
Why voice surveys work differently, not just better
- Higher response rates — people answer a call they wouldn’t have opened an email for.
- More honest scores — voice conversations reduce social-desirability bias; voice surveys typically capture a higher share of genuinely low scores than the same question asked by email, where people tend to round up.
- Real-time capture into a CRM — answers get written in as the call happens, not manually transcribed afterward.
- Open-ended feedback, not just a number — a conversation can follow up on a low score and capture why, which a static survey form usually can’t.
Why this is different from the review-request post already on the site
Automating Google review requests on WhatsApp is about public reviews — asking a happy customer to leave a rating other people will see. This is private, structured feedback data for the business itself, including the low scores nobody’s going to post publicly but that matter most for actually fixing something.
Why this is different from the conversation-insights post
What insights do you get from your AI agent’s conversations covers passive patterns pulled from conversations that already happened. This is active — a deliberate outbound call asking a specific question right after service, not something inferred after the fact.
Where this fits
Extends AI Voice Agent into post-service feedback, alongside its existing inbound and outbound call handling. Tell us how you currently collect feedback and we’ll show you what the response-rate difference actually looks like for your customer base.