Manager, Digital Partnerships
A major wave has crashed over the digital industry: the idea that marketers should only use first party instead of third party data, and that there isn’t room for both. “We’ve come to find that first party data performs better than third party data, so we’ve pivoted our focus to first party data and away from third party!” is a sentiment frequently heard at conferences and spoken by C-level management at brands and agencies alike. With GDPR and CCPA added in, the inaccurate perception of third party data as inherently non-compliant has also spread widely. Add insult to injury — the baited breath over the cookie demise has driven many to think of contextual targeting as a third party substitute.
While all of these — lately hot — topics may express legitimate concerns, many are forgetting that third party data is to acquisition as first party data is to retention. If acquisition is a goal, then it is critical to utilize both first and third party data together.
First party data is key to understanding and nurturing existing customers — but if that is the only data you use, you’ll be targeting the same people over and over again, with no opportunity to expand the customer pool. If a marketer wants new customers, they need new people and segments to target. Access to high quality third party data — backed by solid analytics — is essential.
One way of how this might be done is a look-alike model; with this type of model, a seed audience from first party data that behaves in an ideal way, like having a high purchase or response rate, would be used. Algorithms would then find people in a third party database who are “look-alikes” to the seed audience that was selected, meaning they are likely to behave the same way as that ideal group.
While it may have its place, contextual targeting will not help you with look-alike modeling. It also can’t help you with cross-channel audience targeting, and it certainly can’t help with frequency capping. It is a great tool and has its purpose to target media, but it is not a substitute for privacy-compliant and ethically-sourced data that’s rooted in PII.
There is still the question of third party data quality. Third party data’s somewhat tarnished reputation is primarily due to “bad actors” who have entered the space. Companies entered the data business without a real data background, offering data sets that were poorly developed and maintained, and thus performed poorly. Many of these companies sold “exhaust data,” data that was a byproduct of a primary business goal — and marketers were burned by bad data that didn’t improve their bottom line. Combine this with the confusion of CCPA, and many marketers are making inaccurate and short-sighted conclusions: that 1st party data is the only audience data that will survive.
Don’t get us wrong; first party data is gold! Alliant was built on managing, improving and leveraging first party data. Our proprietary database is made up of transactional first party data from our DataHub Members. That being said, we also understand the unique value of transforming first party data into a second party — multi-enterprise — view, and enriching it with additional predictive data from trusted third parties. That third party data is key to deepening our knowledge of first-party data.
The solution to hesitance about third party data is simple — find a select few third party data providers with different strengths you can trust. Curious about how to gauge the quality of third party data? Ask your data provider these eight questions before you buy.