There isn’t an account manager in existence who doesn’t want the maximum efficacy for the agency’s ad campaigns. And Kentucky-based startup El Toro thinks it can deliver this goal so well it may send shivers down the giant vertebrae of big beasts like Google and Microsoft.
It’s taking IP targeting to an unprecedentedly fine grain level by enabling advertisers to target not merely regions, not just clusters of homes, but individual homes. No one else seems to be doing this, which should whet the appetites of those results-focused account managers we just mentioned.
El Toro launched in July last year after raising $400,000 from friends and family. Eight months later, it’s not only cash flow positive but it’s also garnering rave reviews from far and wide. Account managers who worry about the privacy implications of El Toro’s granular targeting technology might be interested to know that the startup began life as a fraud buster for internet transactions.
CEO Stacy Griggs had lost hundreds of thousands of dollars to internet ad fraud in the past, a devastating experience he and his team resolved to do something about. But the technology his team started developing began to suggest greater potential than fraud busting alone.
As Griggs puts it:
“The Internet is fueled by advertising, without billions of dollars in ad revenue many of the free tools we take for granted today would no longer exist. Our thesis was that by eliminating fraud and waste from the system we could dramatically increase the efficacy of online advertising and build a great company along the way.”
Increasing the efficacy of online ads
El Toro can map individual IP addresses to physical addresses. With a list of physical addresses, Griggs explains, his team can “place internet advertisements on the computers at those physical addresses based solely on a mailing address.”
And Griggs is bullish about the risk of Google and Microsoft copying; he thinks they should be worried that a little startup like El Toro can disrupt their market. Maybe he’s got a point.