In the last year, we’ve seen some high profile acquisitions in the cross-device space that have proven out the importance of cross-device identification, or at least that identity resolution companies are ripe for the picking. The rationale behind these acquisitions is sound: marketers can’t afford to be in the dark when it comes to knowing their audience and the details of their customer’s journey, which is why cross-device tracking is so important.
But what has also become increasingly clear is that despite the consolidation and the significant investment, the challenge of cross-device for the ad industry is still not solved; cookies are not an ideal solution, there are massive daisy chains of bad and old data that impact match rates, and the need for privacy safe persistent identity is growing faster than most providers in the industry can manage.
Most vendors in the cross-device space fall into a category which we refer to as “Master Device Graph” companies, where data is co-mingled from various sources, including each of the client’s datasets, and built into a single output which is licensed over and over – in essence, becoming a commodity. These vendors typically only update their graphs every seven to ten days. According to our own analysis of trillions of events, the average half-life of a cookie pool is 6 to 8 days. What good are cookie-linkages if you get them 7 days late? The inability to leverage fresh data is one of the main reasons that there are sub-par match rates across the industry and data freshness impacts everything from retargeting to frequency capping.
About match rates, if you’re working off of a deterministic graph, you’re facing some of the same “data freshness” issues. There are also significant issues related to the general accuracy of deterministic data, issue of scale, and importantly there is the issue of deterministic pieces of PII that are associated with pseudonymous IDs that depreciate very quickly. With GDPR around the corner, the challenge for master device graphs is going to get worse.
Speaking of GDPR, privacy is another looming challenge for the industry. Companies using deterministic and probabilistic matching will have to constantly review privacy regulations and laws to ensure they know which pieces of data they can collect without consent, with consent, or cannot be collected at all. The heft of the new regulations, which give more control and transparency regarding data use to European consumers, will impose many additional, potentially cumbersome, requirements on all vendors in the cross-device space. Solutions need to be built with global privacy in mind and have the ability to adapt and adhere to local regulations.
One of the reasons why traditional targeting, frequency capping, and cross-device profiling are able to provide reasonably accurate results is because they rely on cookies stored on a consumer’s device. In the cross-device space, there are many challenges with cookies; most importantly, with iOS 11, which affects roughly between 10% and 30% of inventory in the space (depending on your reliance on mobile web).
Since the other providers who rely on Master Device Graphs work off of a centralized cookie-pool, which is a 3rd party cookie, they are not capable of working in iOS11. However, providers who work server-to-server, offline, to probabilistically match identifiers, can maintain the 1st party cookie status of an identifier, and therefore, are able to work in iOS11.
Cross-device technology presents a tremendous opportunity for the entire industry to optimize campaigns and meet the promise of highly-targeted and relevant advertising for consumers. But to think that the issue for cross-device identification is solved is actually a disservice to the industry. As consumer habits change and as markets evolve and expand, there is an ongoing need to innovate in the cross-device space and find ways to know your audience. Cross-device is certainly not solved and the journey has, in fact, just begun.
Recommended Read: Portable Biometric and Cross-Platform Visualization Key to IDaaS