One of the most powerful aspects of digital marketing is the
ability for marketers to target customers at the moment of intent. Using data,
we can find customers in the midst of a purchase decision and target them with
advertising to sway their choice to our product at that exact moment. This all
happens in-the-moment with real-time bidding and programmatic auctions. But,
there is one big problem that is often overlooked: the data used to identify
the “right” customer is often stale. That is to say, it can be based on
behavior that happened a week or even a month ago. So, if I am selling TVs and
I want to programmatically target customers that have been browsing TVs, I
could end up showing my ad to customers with old cookies. They may have been
browsing TVs last month and already purchased a new one, meaning that they
shouldn’t be my target at all anymore!
A new ad tech startup called Rockerbox has just launched a
new solution to solve this problem. Rockerbox’s product helps to freshen up
prospecting data based on a user’s last 60 minutes of browsing activity. This
enables the advertiser to target the customer who has spent the last hour
researching TVs rather than the person who researched them 5 weeks ago. This
offers a lot of value for marketers. According to the Rockerbox CEO, “we can
back off on prospecting during lulls in the research cycle and gear up heavily
right when someone engages in behavior that matches the advertiser’s goals. It’s
less about wasting money on the wrong users and more about allocating money to
reach those users in a moment that’s really right.”
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