Getting The Most From Data Sources Available In DSPs
As many brands and agencies continue to explore the plethora of data sources available on DSPs, it’s important that they critically assess each available dimension through structured testing, therefore understanding which ones offer the most opportunity.
Choosing the most effective audience data
Third-party audience data has long been recognized as one of the most powerful ways of leveraging DSPs, as it gives marketers access to a mind-blowing number of cookie pools categorized by an ever-growing list of interest and affinity segments. However, the quality and cost of such third-party data can vary significantly, making the biggest challenge measuring whether the cost makes the targeting opportunity worthwhile. In contrast, first-party data comes at no extra cost to brands outside of the technical infrastructure costs to gather and deliver it, but very few have grasped the opportunities that it offers.
Consider digital brands that have a portfolio of consumer products/services. They should also have a vast warehouse of online behaviors and transaction information by user. Most brands don’t have access to a platform that easily facilitates the use of this data, which could be used to forecast customers’ affinity for related products, thus allowing brands to build logical pools of customers for cross-product promotion. For example, if I market digital movies, books, magazines, my customers will overindex in the likelihood to purchase a mobile tablet. The reverse relationship is also very true. The big takeaway: First-party data is free, it is proprietary, and there is a good chance it will outperform any data a brand must pay for.
Remarketing as first-party data source
While this seems like a much-discussed topic, many marketers still have a long way to go in doing it right. To this day most brands still fail to execute
on the basics, such as developing customized creative that subtly acknowledges the fact that a user has previously transacted, or at least interacted, with the brand. Simple concepts such as
offering discount incentives or modifying the call to action are still a major shortfall when digital creative is scoped and developed.
These basics become even more of a priority when we merge this concept with the idea of DSPs, as it escalates the value of an individual impression when it’s understood how a brand has previously engaged, or not engaged, with a user if used correctly. Segmenting these users into likely low/medium/high segments can make an RTB campaign all that more effective.
First, it is important that a brand retargeting audience is segmented by the method in which a user navigated to a brand, for example via search or display. These users are likely to be at very different points in the consideration and adoption funnel, and the impressions to reach them have different value.
The second dimension is time since last digital interaction, because the purchase behavior and period of consideration is different for each brand and product. Leveraging DSPs to scale bids based on this time dimension enables more effective use of remarketing impressions. For example, consider the value of users who browsed content for a 99-cent music download versus a $500 iPad. The amount of time a user will spend to research and consider these two products is quite different, and therefore the length of time available to influence the purchase is different.
In summary, the three key enhancements that a brand using DSPs should consider as data enhancement strategy is: 1) leveraging first-party vs. third-party data; 2) segmenting users by search vs. display; 3) integrating latency as a bid prioritization strategy.