In the first blog in this series we addressed the core definition of identity resolution and the use cases that are critical to brands focusing on improving customer experience as well as the ways in which identity resolution relates to data quality management.
As discussed previously, identity resolution is the process of finding, cleansing, matching, merging and relating all the disparate signals (martech touchpoints, enterprise systems, databases/lakes) about a customer to produce an accurate, complete and up-to-date view of the customer. It is a fundamental building block for delivering a quality customer experience.
Own the Process: Why Data Quality & Identity Resolution Can’t be Outsourced
Many companies evaluating a customer data platform (CDP) today focus heavily on either the data ingestion or orchestration component of the process in delivering personalization and rely on other vendors to perform data quality and deliver identity resolution. This is not an ideal approach – identity resolution is a core functionality of a what Gartner calls a “Smart Hub CDP.”
Ownership of identity resolution (IDR) is what enables your business to ensure that you have the most accurate and up-to-date golden record of your individual customers. If this process is left up to a third-party data service to process and deliver data into the CDP, you violate the user trust that you will protect and secure their data and you slow down the process tremendously.
A paid search/paid ad team may be intrigued by a CDP’s ability to aggregate customer data, which can be helpful for finding look-alike audiences, for suppression and attribution. Yet these users often do not understand or appreciate the CDP’s use of real-time high quality identity matching to deliver one-to-one marketing across other touchpoints. Businesses fail to be personally relevant, and have ongoing issues with data quality and timeliness without strong IDR.
Why Probabilistic and Deterministic Matching Matter
Delivering accurate probabilistic and deterministic matching in a real time, a persistent golden record is critical for delivering personalization at scale. Conflicting signals may happen in household settings or usage of various devices and contact information may create confusion as can human error in adding information into a record. Utilizing both probabilistic and deterministic matching is critical to finding the appropriate balance for your business.
Setting the standards for the match quality of those identities varies by industry and risk tolerance as much as what type of data is collected. A financial institution or a healthcare provider may need a much higher confidence level in identity than a retailer or travel provider for marketing purposes. Identity resolution must be accurate but flexible to tune for the needs of the business – and it must be built on quality first-party customer data. Redpoint IDR is high performance, tunable, transparent, and consistent and can be delivered in the cadence the customer desires (whether it is milliseconds or hours).
Join us on Tuesday, Aug. 9 at 11 am ET for a webinar hosted by Redpoint’s VP of Engineering Kris Tomes and Sr Product Marketing Manager Steve Zisk on this topic. This is part two of a four-part series on the topic, with a deeper dive into use cases coming up on August 25th with VP of Product Management Beth Scagnoli.