Recognizing a substantial number of consumers isn’t worth much if it’s not done with a high level of accuracy. And this is something we understand well. With our highly complex solution that we’ve spent 15 years developing, we match consumers to their data with 95% accuracy, compared to the industry average of ~50%.
Contributing to our accuracy is our transaction-based matching, using verifiably accurate, closed-loop reporting of 75 million purchases (both online and offline) every day.
Here’s how we’ve learned to avoid some big mistakes that other solutions make:
Some solutions match only with email addresses—though many consumers use a different email address for purchasing. As we mentioned above, it’s much smarter to match with online and offline transactional data, too. When consumers make purchases, they enter their home address and most optimal email address. It doesn’t get more accurate than that.
The match pool that some solutions use is too small, reducing campaign potential. Marketers should use a quality match pool, filled with people who have high household incomes and a history of transacting online.
Some solutions match with third-party cookies, which are rejected by Safari. These matches exclude 35% of educated, high-income individuals. Marketers should work with a partner that knows how to reach users on all browsers, including Safari, on display and mobile.