A retail group running a national mystery shopping programme was drowning in raw survey data. Reports were produced manually by an agency, arrived weeks late, and were too aggregated to drive store-level action.
Mystery shopping scores existed but had no impact. By the time regional managers received results, the context was lost. There was no way to benchmark stores, track trends, or tie scores to commercial outcomes.
Built an automated pipeline ingesting raw mystery shopping submissions into Google BigQuery.
Designed Looker Studio dashboards with store-level drill-down, regional benchmarking, and trend tracking over time.
Connected mystery shopping scores to sales and NPS data to identify the commercial value of service quality.
Configured automated weekly email reports delivered directly to regional managers.
Report delivery time reduced from 3 weeks to 48 hours.
Regional managers could identify and act on underperforming stores within the same week as the visit.
Correlation analysis revealed a 0.74 relationship between mystery shopping scores and basket conversion rate.