LEADS AVE
See who's on your website
A multi-lot independent used-car dealer in South Carolina. One script on its website, its own customer list, and a desk its sales team works every day. Every number below was read from that desk on October 5, 2026, about ten days after the pixel went on.
An estimate, not a result. It is the daily average of the first ten and a half days carried for 182 days and rounded down, and it assumes the dealer’s traffic and advertising hold. A shopper who returns is named once, so the real count is likely to run lower. The 72 past customers found shopping elsewhere are left out: that count grew as in-market data was added, which is not a daily rate to carry forward.
Like every dealer website, this one reported how many people came and nothing about who they were. A shopper could open nineteen vehicles in a night and leave without a form, and the store would never know.
The dealer's CRM held more than thirty thousand customers across two stores. Some of them were back in the market for a car that week. Nothing told the sales team which ones.
The pixel resolved 878 website visitors to a person. We dropped 229 that failed our quality check. The 649 that reached the desk each carry a name, an email and a home address, and 629 of them a mobile number.
The dealer's customer lists arrived on September 28. Seven days later the desk had flagged 81 of those customers as back in the market: 9 on the dealer's own website, and 72 who were shopping elsewhere and had not come back yet. The sales team could time the call perfectly.
Back on the website ten months later, on two different days, looking at an Impala and a Silverado.
Opened 19 different vehicles in one night. A six-year-old sale became a shopper the store could call the next morning.
Came back and went straight to one truck, a 2022 RAM 2500 Limited.
Opened six trucks in one day, among them a 2022 Tundra Hybrid Capstone.
A match needs the same phone or email, or the same name at the same street address or ZIP. A name alone never counts. The list of customers shopping elsewhere started at 26 on September 29 and reached 72 by October 5 as more in-market data was added. It is now checked every morning.
We audited 33 flagged leads against the dealer's own records. Our data carried 3.3 phone numbers for each customer against 0.9 in the CRM, and an email address for 26 of them against 4. A flagged lead never drops off the desk until the dealer removes it.
In the CRM0.9
Our data3.3
In the CRM4
Our data26
The desk maps every named shopper's visit across the dealer's website, minute by minute. Whoever picks up the phone knows which vehicle to talk about before the first hello.
This sample shopper came five times in eight days. Friday afternoon: the home page, the inventory sorted by lowest price, then an Audi Q3. Sixty-seven hours of nothing. Monday: a search for “GMC” and a Sierra 1500 AT4. By the next Friday, a Buick Encore and a Tundra.
The record shows what they searched for, which lot each vehicle sits on, how long they stayed on the page, and the moment they moved to leave.
The desk does not hand the store a list of 649 names and wish it luck. It ranks them: past customers first, then every shopper who opened a vehicle and has a household income of $36,000 or more, closest to a lot first. This dealer sells to every credit situation, so income is the filter, not credit.
The same data answers two questions a dealer usually guesses at: which units are getting attention, and which advertising brings real people.
172 more were first seen partway through a visit, with no entry source.
For two other stores we built the outside-in half: named households inside the store's real trade area who are shopping that brand right now, each record tested against itself before delivery.
The desk is about ten days old. We have not tallied appointments, cars sold or revenue from these leads, so this page claims none.
The pixel names the visitors it can match. Total site traffic was not measured here, so there is no match rate to quote.
The screenshots show the working desk with sample people and replaced store names. The totals, the vehicles and the behavior are real.
We put one script on your site and build a verified lead file for your trade area. At day seven you see who was on your website and who is shopping your market, measured against the cost per sold unit you give us on day one.
See who's on your website