DETROIT – An auto maker debuts a hot new car, prompting a flood of Internet leads at auto dealerships.
But not all those inquiries are from serious prospects. Many are casual contacts by people who are interested in an all-new product but not necessarily ready or able to buy it.
The spike in leads can jam a dealership’s Internet department, which can handle only so many inquiries and doesn’t readily know which are serious and which aren’t.
“That’s where lead scoring comes in,” says Jack Bowen, chief marketing officer for Urban Science, the first firm to rank leads.
“You can only cover so many leads when the volume goes through the roof, increasing, say, from 800 to 1,400,” he says. “There are good and bad ones mixed together. If you can only follow up on 1,000, which should they be?”
Lead scoring uses a blend of collected data, such as a prospect’s purchase history, in an attempt to determine likelihood of buying.
Bowen now wants to take scoring to the next level by comparing dealerships’ actual close rate compared with an expected close rate.
He calls it close-rate effectiveness.
Often, lead providers blame dealership mishandling when leads don’t pan out, while dealerships accuse providers of sending low-quality leads.
The new process may help answer: Is it the lead or the salesperson?
Here’s how it works:
Expected close rates are based on various factors for individual dealerships.
That includes geography. “You wouldn’t expect a dealership in New York to sell the same number of pickup trucks as would a dealership in Texas,” Bowen says.
Quality of leads is factored in, too, with dealerships earning extra credit for closing leads with low scores and losing points for failing to close leads with high scores.
Also analyzed are a dealership’s up-and-down monthly sales volumes, which on the surface can be misleading.
For example, by looking only at Internet lead close rates, a dealership might appear to do well in August but not in December, when in fact the opposite could be the case.
That’s because August is a brisker sales month, with more leads coming in. So even though the dealership may have had fewer lead closings in December, it had a higher close ratio based on the modest number of leads, and therefore a better close-rate effectiveness.
At the end of a month, individual dealers would be given a grade, with 100% being the national average for closing Internet leads.
“If someone is at 70%, you would want to work with them to get them to 80%, then 90% and so on,” says Bowen, who came up with the idea for measuring close-rate effectiveness about a year ago. “It took a while to get the math right.”
Urban Science now is trying to sell the patented process to auto makers.
“It is a pretty advanced analytical tool, and the industry right now is in a walk-before-you-run mode,” Bowen says. “But I think the industry will come around to it.”
He predicts dealers ultimately will be asking their auto makers for lead scoring.
“If manufacturers are pressing dealers to follow up on leads the auto makers send them, dealers should be saying, ‘We want lead scoring.’
“And as for close-rate effectiveness, an enlightened dealer will want to know how his people are doing,” Bowen says. “We can show that.”
Information used to score Internet automotive leads comes from various sources, such as data from auto makers indicating which prior Internet prospects became car buyers.
“Past behavior predicts future performance,” Bowen says.
Other buying predictors include lists of previous owners, people with vehicles coming off lease, auto-show attendees and the zip codes of shoppers submitting leads to dealerships.
Another indication of buyer seriousness is how much someone writes in the “comments” field of a Web page for lead submissions.
“The longer the comments, the more likely a person is to buy,” Bowen says.
Lead quality varies by website.
For example, says Bowen, someone researching cars for 45 minutes on Edmunds.com and then submitting a lead through that website is more likely to buy than someone on a non-automotive website who’s submitting a lead as part of playing a video game to win a free pickup truck.
For one brand, a shopper showing an interest in a metallic car color indicates a greater chance of buying. (Bowen won’t name the brand, citing client confidentiality.)
In scoring leads, Urban Science has developed these three categories:
- Urgent. This person appears ready, willing and able to buy.
- Priority. In the market but may need in-depth sales consultation or an incentive.
- Standard. “They are further away from the purchase horizon but should be followed up with,” Bowen says.