Capturing Real-Time Digital Behavior for Programmatic Advertising Buys
by Sid Shah
posted on 07-06-2016
There’s a lot of talk about Big Data and who is using it best. Everyone claims that they’re going to tackle data in a new way. But, at the end of the day, behavioral data is only useful if you have a tangible way to make it actionable. One way to make digital-behavior data actionable is to use it to drive your programmatic- advertising campaigns. We have seen a number of brands implement this strategy with very strong results.
At its core, analytics is used to track users’ digital behaviors — where your traffic comes from, which pages a user visited on your site, which page was the last a user visited, and so forth. Data science allows you to understand your customer behavior very well. Data science can apply algorithms to this digital-behavior data that allow you to segment your users into various personas. You can create an almost unlimited number of segments with these algorithms, allowing you to target each of your campaigns to a specific subset of users.
Why Programmatic Advertising?
The purpose of programmatic advertising is to increase the likelihood that someone will purchase from your brand. Programmatic advertising can be improved by using digital-behavior data to optimize your advertising campaigns. With access to behavioral data, you can more effectively personalize your online advertising campaigns to increase sales.
For example, if a user on your site browses for luxury bags around a $200 price point but does not make a purchase, you can use behavioral data to understand what types of campaigns that user may be most likely to respond to. You can look at her demographic information and behavior to understand which segment of users she most closely represents. You can get answers to questions like:
- Which other users have been looking at luxury bags at $200 price points?
- What did they end up purchasing, if anything?
- Which ad were they last shown before finally converting?
- What platform were they on when they viewed the ad that prompted their conversions?
- Were they likely to shop via mobile?
- Did they prefer making purchases online or via brick-and-mortar stores?
From there, you can better understand what types of ads users in this segment respond to, allowing you to carefully personalize your online advertising campaign. This can include specially crafted in-app messaging, discounts for related products, targeted remarketing campaigns, and more.
Ultimately, when digital behavior is used to improve programmatic advertising, organizations see an average additional lift of 18 percent over ads where behavior has not been utilized. You can actually mold and transform the data to display more relevant ads and then display those ads to appropriate audiences in a very customized way. The more data you have access to, the greater your organization’s ability to parse data and get down to a more granular level of understanding. Simply put, the more behavioral data you have, the greater your ability to send the right ad to the right audience at the same time.
The beauty of the technologies at the center of digital-behavior and programmatic-advertising integration is that they get marketers out of the business of manually parsing data. This allows them to focus their energies on more strategic marketing decisions. They have opportunities to reach broader audiences with increasingly more personalized messages. Being able to have a wider reach, while also increasing personalization, essentially means you are reaching more people more effectively and at a lower cost than ever before. With all of that on the table, who wouldn’t want to be able to integrate behavioral data into their programmatic-advertising decisions?