Improving Dealership Loyalty Using Customer Data
It’s no secret that retaining an existing customer is far more profitable than bringing in new customers, but not all existing customers are the same. How can you be confident which customers have the highest likelihood to become loyal and which are just single-transaction?
By leveraging your existing customer data and some advanced analytics, you can not only determine which customers are most likely to become loyal, but also understand the full customer “journey.” The customer journey maps out a series of touch points that your most loyal customers follow. For some dealerships this may be a pair of visits, followed by a purchase, then a series of 4 service visits. For another dealership, a loyal customer may rarely make a service transaction, but may complete a new purchase every third spring.
So how do you measure customer loyalty? It’s important to keep a standard benchmark across all locations so that the metrics have meaning. This is where the “Customer Loyalty Score” comes in. By using a standard scale of 0–100, you can automatically score each customer on a common scale of how loyal this customer is or is likely to be.
The specifics of this score will look different based on the unique business rules of each dealership, but generally they will contain the following data points:
- Source of the original lead (direct outreach, referral, advertisement, etc)
- Demographics (income, zip code, job title)
- Distance from dealership
- Make/model of VIN
- Time between visits
- Dealership trends
- Seasonal trends
- Market trends
Once this business logic is defined, your cloud data platform will automatically assign both a score (1–100) and a journey map to each individual customer.
Now that you have these scores in place, there are a number of ways to make this work for you. Let’s walk through a few examples.
Loyal customers who have not made a recent transaction. In this example you would like to see a list of your existing customers who have a high loyalty (perhaps above a 90 score), but who have not had a sale or service transaction in over 6 months. Ideally this is a short list of customers who have a very high likelihood to make a transaction and are in the target buying window. After running this analysis, you now have a highly specific and targeted list to provide to your sales managers.
Boost individual location performance. You can also use the aggregate loyalty score at each location to get a deeper performance metric than raw sales numbers. For example — one location may be on par with others from a new sales perspective, but their customer loyalty scores average 10–20 points below the rest. This is a situation that needs to be addressed as soon as possible. In this case, leverage the customer journey map to drill down into where customers are falling-off in the process. Perhaps they are failing to return for service after the initial purchase — which would require a look at the service offerings at that location. Or perhaps the customers could be performing regular service with you but never purchasing another vehicle — which would require a look at the up-sell offerings at that location. Each of these options would require drastically different actions, so it’s important to understand the data to make the appropriate decision.
In summary, understanding the full picture of your current customers and their loyalty to your dealership is crucial in driving high-profit transactions. All of this is available with the data you already have if you are able to leverage the right tools and the right people.
Andrew Parnell, CEO of Earlybird
www.earlybird.co/auto | firstname.lastname@example.org | 312.836.4365
Earlybird is a dealership-focused data firm providing cutting edge cloud tools and next-level analysis for executive teams.