In order to fully use your customer relationship management data, you need to maximize the accuracy of your customer matching processes. That means you need to implement high-precision entity resolution technology to identify potential customers more efficiently. The process of identifying particular individuals through specific personal data, called personally identifiable information (PII), helps facilitate more accurate entity matching. The more you understand PII, the more you understand who your current and potential customers actually are and how to better market to their tendencies and behaviors.
What Is PII?
PII is any data that on its own can be used to positively identify a specific person, or data used to identify an individual in the context of other related data. PII can be either sensitive or non-sensitive data that when correlated with anonymous data points, it delivers an exact match to an individual. Examples of such sensitive data includes Social Security and passport numbers, medical history, and financial records. Non-sensitive data is anything contained on websites and directories that is public record.
How Does PII Affect My Customer Matching Process?
Through the use of PII in entity matching, you have more power to drill down into the identities of your target market than ever before. It’s now possible to individually identify 87% of people in the United States through only three pieces of information: zip code, date of birth, and gender. Unfettered, PII is an extraordinary data matching tool that can help you to drill down into the personality, buying habits, and preferences of specific customers based on their data set and the smallest online interactions with your website, ads, and content.
Additionally, you gain the ability to tier your markets and take full advantage of the Pareto Principle, also known as the “The 80/20 Rule”, which states that 20% of your input creates 80% of your results. Entity matching allows you to minimize your outlay of resources on the 80% of customers with a low ROI and focus in on the 20% of customers that generate the majority of your revenue.
However, the trend has been for customers and data brokers to provide less and less PII. As the threats of identity theft and fraud have increased, access to PII has decreased. For example, many credit card issuers and processors are adopting mobile pay technology that reduces the amount of PII provided to the merchant as part of a credit card transaction. In addition, the use of PII is dictated by laws and court rulings at both a federal and state level, so there are always legalities to consider before you make full use of personally identifiable information on a large scale.
How Can Customer Matching Be More Accurate With Less PII?
Entity resolution technologies that rely entirely upon traditional name and address PII for entity matching are at a disadvantage as consumers try to redact more and more of their PII footprint in the marketplace. More sophisticated approaches are needed. One of the most promising is persona attribution. A persona is the identity of a person in a particular domain or context. For example, your driver’s license name may be John Smith, but on WeChat you are “Johann the Destroyer”.
The most sophisticated entity resolution tools are able to collect these personas from different context such as Facebook and Instagram, and watch for information that will connect them. Again using the mobile pay example, your persona is a combination of your name and a numeric token representing your credit card. When an entity resolution system first ingests this data, it may create a persona with only this information. However, later transactions using the persona may include additional PII such as a loyalty card number. This may be enough to attribute (connect) the mobile pay persona to a record in the merchant’s customer master, thereby filling in the missing information.
Entity Matching with HiPER
Black Oak Analytics’ primary software solution, High Performance Entity Resolution (HiPER), is an entity identity information management (EIIM) system that allows you to legally and effectively identify and market to a targeted audience with increased efficiency through entity matching and resolution that support persona attribution. PII is one type of information used to match entities in datasets, but not the only one. HiPER also leverages non-obvious relationships and non-PII data to support the entity resolution process.
HiPER’s highly configurable matching capabilities allow our team to design specific rules that incorporate PII and other persona data to best support your organization’s needs. While some other systems can perform similar functions, HiPER can also be installed behind your company’s firewall, which is critical to meet compliance and regulatory standards for PII.
To learn more about entity matching, contact Black Oak Analytics today at (877) 805-0736 or request a consultation to learn more about our HiPER platform.