A mystery shopping provider was conducting call audits for a network of storage facilities, where shoppers posed as prospective customers and evaluated how inbound inquiries were handled. Each interaction followed a defined process. Shoppers called the facility, asked about pricing, availability, and service options, recorded the conversation, and then completed a detailed post-call survey. The evaluation process introduced inefficiencies and inconsistencies. Survey completion required significant time and effort, and subjective questions such as tone, clarity, and helpfulness were interpreted differently by each shopper.
Because subjective responses varied across shoppers, completed evaluations often required a secondary review process. Editors or proofreaders listened to recorded calls, verified responses against the conversation, and adjusted reports where necessary to align scoring and interpretation across evaluators. While this helped improve consistency, it added another manual and expensive step to the workflow and increased the time required to deliver completed reports.
To address these challenges, the MSP implemented DataPure’s AI-driven approach that transferred the responsibility of report writing from the shopper to DataPure’s AI. This shift reduced reliance on manual interpretation and ensured that every interaction could be assessed using a uniform criteria. It also created a foundation for scaling evaluations without increasing operational complexity and overhead.
Automating Call Evaluation and Report Generation
Instead of requiring shoppers to complete detailed surveys and reviewers to validate responses manually, recorded calls were processed directly through an AI-driven evaluation workflow. The system analyzed each interaction against the mystery shopping questionnaire and generated completed reports using the same framework already used by the MSP.
The solution enabled:
- Automatic transcription of recorded calls
- Evaluation of every stage of the interaction, including greeting, inquiry handling, pricing discussions, facility features, appointment setting, and call closure
- Extraction of factual responses directly from the conversation
- Consistent assessment of qualitative criteria such as professionalism, clarity, engagement, and helpfulness
- Generation of completed reports without manual survey completion or secondary review
- Full traceability between report responses and the underlying call recording
Results and Operational Impact
By automating report generation and standardizing evaluation, the MSP significantly reduced the operational effort required to manage call audits while improving consistency across locations.
Key outcomes included:
- 85% reduction in report completion time
- 98%+ evaluation accuracy
- Faster reporting turnaround times without increasing operational overhead
- Elimination of scoring variability across shoppers and reviewers
- Consistent evaluation of every interaction using the same criteria
- Improved visibility into recurring execution gaps, including incomplete needs assessments, inconsistent communication of pricing and fees, missed upsell opportunities, and ineffective call-closing practices
- Shoppers are able to complete more calls in the same amount of time leading to increased revenue for the MSP
The result was a more scalable and reliable mystery shopping program that delivered faster reporting, more consistent evaluations, and clearer operational insights.
