AI Dealer Performance Diagnostics for a Retail Company

The Challenge

A retail company working through a dealer network followed the performance of each dealer, but mainly through outcome data. Channel sales teams, regional managers and commercial operations teams could see when a dealer’s results fell, but not necessarily why.

Understanding the reasons meant looking at several indicators separately, from sales volume and visit frequency to quote conversion, stock sufficiency and participation in campaigns. A drop in results could have quite different causes, and each one called for a different kind of support. Without a combined view, it was harder for regional managers to decide which dealers needed attention first, to identify what was behind lost revenue or to direct support programmes to the dealers that needed them.

The Solution

With cognipeer Studio, our team configured an AI-assisted dealer diagnostic workflow. Instead of reviewing results in isolation, the workflow analysed several indicators together, including sales volume, visit frequency, quote conversion rate, stock sufficiency and campaign participation, to build a fuller picture of each dealer’s situation than results alone could provide.

For dealers showing a deviation, the workflow categorised the possible causes and prepared a short report for the regional manager, with suggested actions. The report explained what the indicators pointed to rather than only restating the results, and it was kept short and focused on the dealers that needed attention. Regional managers reviewed the findings and decided which actions to take, using the report to guide their field management.

Implementation

1. Selected the performance indicators. We defined the indicators to be analysed together, such as sales volume, visit frequency, quote conversion rate, stock sufficiency and campaign participation.
2. Configured deviation analysis. The AI workflow identified dealers whose indicators deviated and examined those indicators in combination rather than one by one.
3. Added cause categorisation. For each dealer showing a deviation, possible causes were grouped into categories to make the picture easier to interpret and compare across dealers.
4. Delivered short reports with suggested actions. Regional managers received a concise diagnostic report for each relevant dealer, with suggested actions for them to assess.

Business Impact

Dealer performance reviews moved from looking only at results to understanding their likely causes. Regional managers had a clearer basis for deciding where to focus, and decisions about support could draw on a combined view of each dealer’s indicators rather than results alone. Support programmes could be matched more closely to the likely causes of each dealer’s underperformance.

• Clearer prioritisation in field management.
• Quicker identification of likely causes behind lost revenue.
• Better-targeted support programmes for the dealers that need them.
• Short, action-oriented reports for regional managers.

Technology Behind the Solution