On-Demand Crowdsourced Customer Feedback & Call Masking Engine

Collecting direct dining feedback from diners relied on dedicated, full-time in-house call center agents. Maintaining fixed salaries, infrastructure overhead, and telecom lines for hundreds of thousands of monthly diner calls created unsustainable operational costs, while handling customer phone numbers manually introduced serious data privacy and leakage risks.

We replaced the high-cost internal call center with an on-demand gig-worker platform, allowing remote freelancers to execute feedback calls at fractional costs. A cloud telephony and IVR bridge with automated call masking connects freelance callers directly to diners through a virtual dialer without ever revealing the customer's personal phone number, with a structured question flow letting freelancers quickly log ratings on food quality, service, and ambiance. A two-stage QA review console lets internal supervisors verify that feedback entries reflect actual customer responses and filter out low-quality or fraudulent submissions, and automated escalation pipelines forward critical feedback directly to branch managers for prompt resolution.

• Customer feedback collection and call-center operational costs cut by over 60%
• Significantly higher call volumes handled through an on-demand gig-worker model
• Complete customer number privacy through cloud telephony call masking
• Improved feedback reliability through structured, two-stage QA verification
• Automated escalation of critical complaints directly to branch managers