Sales buying guide

Car Dealer Equity Mining

Equity & database mining for dealerships: Ownership-cycle, equity, propensity and retention opportunity identification.

Equity mining compares each customer's estimated vehicle value to the loan payoff, and the gap is the opening for a trade offer. The quality of the result depends on two inputs: how accurate the value is and how accurate the payoff is.

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How to choose car dealer equity mining

Values can be refreshed nightly from market data, but payoff figures are often estimates built from the original deal terms, which drift from the lender's actual balance. Ask any vendor how it estimates both, what margin of error it will state, and how an offer is worded so it does not promise a number the store cannot honor.

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What to check before you buy

Vendors report conversion of roughly 2 to 4 percent of a contacted list on manual campaigns and 6 to 10 percent on automated programs. Those are vendor figures.

Ask for results by store size and for the list size they started from. Find out which data the tool reads from the DMS and how often.

Find out how a customer is suppressed when already in a deal, on a service appointment or opted out. Look at how the campaign reaches the salesperson and the CRM.

Include lease-end and pull-ahead opportunities in the trial. Measure sold units, not responses.

Treat the first campaign as an experiment. Choose one segment, such as customers with a positive equity estimate above a set amount, contact them by the channel they prefer, and measure appointments, trades acquired and sold units against a comparable group that was not contacted, because that comparison shows whether the tool created sales or simply reached customers who were going to return anyway.

Look at the quality of the underlying estimates. Equity depends on the vehicle's value and on the loan payoff, and payoff figures are often estimated from the original deal, which drifts from the lender's real balance after extra payments, refinances and early payoffs.

Ask the vendor how it estimates each number, what error it will state on your own data, and how a customer is told so the offer does not promise more than the store can deliver. Compare the estimates with a hand check of fifty customers.

Also look at timing. A customer who has just bought, or who is in the middle of a repair, should not receive a trade-in offer. Ask how recent activity suppresses a message, how often lists refresh, and how the campaign reaches the salesperson and the CRM so a customer who replies is answered the same day.