The Problem
Across our nine rooftops, we see thousands of customers come through the service drive every year, and we’ve always known that service represents one of our biggest sales opportunities. The challenge wasn’t a lack of traffic, it was a lack of clarity. We didn’t have a consistent, data-driven way to determine which service customers were actually in a position to buy versus those who were simply in for routine maintenance.
Our data lived in multiple systems, and because those systems weren’t fully working together, our teams were often forced to piece information together manually. That meant equity position, ownership cycle, service history, and CRM activity weren’t always aligned in one place.
Each store, and sometimes each salesperson, was interpreting the opportunity differently. What should have been a strategic, repeatable process instead depended heavily on individual judgement.
That inconsistency made prioritization extremely difficult. Sales teams were reaching out to customers who weren’t ready or weren’t a good fit, while higher-value opportunities were missed entirely. Follow-up wasn’t always timely, and it was hard to hold anyone accountable because we didn’t have a clear, measurable process to reference.
At a group level, we lacked visibility into what was actually happening across our rooftops; which stores were executing well, which weren’t, and why.
As we continued to grow, it became clear that this approach wouldn’t scale. We needed a solution that could eliminate guesswork, connect our data, and create a standardized service-to-sales strategy that worked the same way in every store.
“Sales teams were reaching out to customers who weren’t ready or weren’t a good fit, while higher-value opportunities were missed entirely.”
