Identity resolution is the process of creating an addressable customer profile by analyzing and resolving data across multiple touchpoints, attributes and systems. This includes email addresses, cookie identifiers, device identifiers, postal addresses, social media identifiers, and more.
AI-based advanced identity resolutionbrings together customer data from different sources and automatically matches multiple spellings of customer names to create a single strong customer profile. Salesforce has also introduced new capabilities for creating anonymous profiles with rich data histories, ready to be merged with an existing customer profile when the match is made.
To illustrate this concept, let's consider Mia, one of your clients. Mia communicates with her organization in many different ways - she can call customer service if she has a problem with a product or service, browse your website or application and perform any number of actions, or open an email or SMS from your marketing or sales team. Each of these interactions creates a record in a database. Identity resolution is the act of reconciling those records to create a single view of Mia.
If done correctly, it allows you to communicate with her in a way that is more valuable to both her and your organization. If done incorrectly, it can lead to frustration for your customer and inefficiency for your organization. In regulated industries, it could even involve legal or governance issues. To ensure accuracy, some data leaders have chosen to outsource the problem of identity resolution to their customer data platform (CDP) partners.
The goal is to create a robust and accurate profile of each individual customer. Mixed cascade heuristics is a type of identity resolution algorithm in which different rules or subalgorithms are applied in order from the strictest to the least strict, and can also include probabilistic matching. Probabilistic identity resolution is a statistical model with a certain confidence interval, in which it is known with some confidence that this user will do so. Organizations often lack visibility into how identity resolution is being carried out, which can lead to a lack of faith in the process, lack of portability and dependence on a vendor, even if they no longer need other services offered by the CDP.
Deterministic identity resolution is a high-trust approach that uses first-party data when it is known for certain that this user did it. There are some third-party services that offer to do the identity resolution work for you if you send the data to your SaaS platform for processing. With identity resolution, you can reconcile anonymous visitor data with your known visitor data and gain deeper insights than ever about customer behavior to drive sales and retention. It allows marketers to use more conversational intelligence and identity resolution capabilities to drive customer engagement.
To obtain that unique view of the customer, companies must have good identity resolution. The cost of SQL-based computing has been reduced due to strong competition between cloud data storage solutions, making SQL-based approaches to identity resolution attractive from a cost perspective.