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Turn big data into smarter media buys

Turn big data into smarter media buys Tim Koschella

First-party data, collected via on-site or in-app interactions and voluntary registrations, has great potential to drive smarter, more valuable programmatic buys. However, data without insight is meaningless, and the sheer volume and complexity of first-party data has the potential to overwhelm.

The ways in which to use first-party data to segment and target various visitors and audiences are limitless. Even so, there are three key ways in which marketers can drill down into the mass of data available to them and turn the possibilities of big data into the reality of smarter media buys with programmatic.

Mobile first-party data better speaks to intent

User behavior on mobile is fundamentally different. On desktop, users tend to browse; one might click on 10 links in a single minute, browsing and skimming content, and closing the tabs as they go. Even so, the cookie drops once that tab opens.

Page owners collecting that first-party data are left with an inordinate volume of largely low-intent users to target. Take the idea to mobile, though, where there's no such random browsing behavior in apps; users can't jump from app to app as easily. Furthermore, the way we use apps is very intentional. One might browse websites related to cars just to look at pictures of cars -- who knows?

If the user is navigating an app designed to help people find a used car, however, they're a far better target for ads about used cars.

First-party mobile data partnerships solve for vague third-party segmentation

First-party data, primarily used on desktop for retargeting ads, is far more interesting on mobile. One of the issues with first-party desktop and web data is that, because it's linked to cookies, it's more perishable and has a shorter shelf life.

Cookies aren't permanent identifiers; data is deleted as users or systems delete cookies. In mobile, the identification uses the device ID, which is trackable for the lifetime of that user's ownership of the device.

Understanding the ways in which first-party data differs for mobile helps drive more effective ad targeting based on your users' behaviors, traits, and intent. For example, picture an advertiser with a type of mobile pawn shop/lending app. A user can give up their Rolex in exchange for an instant loan, then get the watch back once the loan and interest are paid. Third-party data might enable that app developer to buy data in audience segments like "finance" or maybe even "seeking loans." However, the way those third-party data audience segments have been collected is mostly intransparent thus leaving the buyer of such data questioning about its true quality and value for his specific campaign goals.

As a better alternative to buying blind audience clusters, the developer could partner with specific app developers that are non-competitive but cater to the same niche audience and use their first-party data. Let's take a gambling app as an example. The target customers of a digital pawn shop and mobile or online gambling services have a significant overlap. Thus, using its first-party data to buy ads on RTB in order to acquire new users helps the pawn shop target ads to the right prospects.

First-party mobile data enables timelier, more effective buys

Timeliness between when data is collected and the media buy is executed is key. On mobile, we're currently seeing an issue where a lot of the first-party data buying strategies are driven by DSPs using offline batch uploading of data segments to target users.

Say you have a travel app and a list of IDs of people who have searched for hotels in Asia. You'll bulk upload those IDs into your media buying system within a week or so, but between the date of collection and execution on those insights, much intent is lost. In that week, many will have moved on in their search or converted to booking.

Instead, advertisers need to connect that data directly back to the media buy, thus eliminating the manual step of the bulk upload by connecting their data collection and segmentation systems seamlessly with their media execution partner (mostly a DSP) by streaming target segments via an API. Searchers seeking a hotel room in Asia will see an ad within a couple of minutes, not five days later once the campaign manager has had time to do the bulk upload.

This is a fundamental challenge mobile has to overcome as the (device) identifier used to build audience segments and retargeting groups has to be transmitted via a server-to-server connection rather than a simple browser cookie, which is the common practice on desktop.

Yes, there are still technical barriers in mobile, and many systems aren't built to accommodate the most efficient, effective use of mobile first-party data. Advertisers need to seek out systems to eliminate the manual steps that slow down the application of timely, accurate, high intent first-party data to smarter programmatic buys.

Tim Koschella is the co-founder and CEO of AppLift.

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Tim Koschella is a dedicated expert in international mobile and online performance marketing (CPI, CPL, CPA, CPE) with a particular focus on the games industry. As Co-Founder and CEO of AppLift, he has been working with 100+ mobile companies to...

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