As third-party cookie deprecation continues, learn how CDPs equipped with identity resolution can help improve data management in a cookieless world.
Tracking and identifying customer behavior has historically depended third-party cookie tracking. As companies like Apple and Google begin to limit third-party tracking, industry professionals are looking for new ways to manage the customer journey in a cookieless world.
But, how can organizations shift their data management strategy to create the unified customer profiles they are looking for? One way is through identity resolution.
What is Identity Resolution?
Identity Resolution compiles customer data points from a variety of data sets and aggregates it into a single customer profile.
For example, a customer might view a social media ad, read an email newsletter at home, then visit your website at work or at home through different web browsers, with different IP addresses.
Data explicitly captured about customers across these touch points could end up getting stuck inside platform-specific silos. A web marketing system that identifies users by cookie ID, for example, may not know that the email address captured in a marketing automation system are actually the same person. Data that lives in distributed systems that don’t talk to each other. In addition, the data isn’t connected or reconciled in a way that creates a unified customer profile. These data silos make it likely that a person will receive different offers and messaging from your brand based on the systems they’re using at the time, creating confusion and lower customer satisfaction.
Identity resolution compiles data collected from across first, second-and-third-party sources and attributes it to a single customer identity. There are two types of identity resolution: deterministic matching and probabilistic matching.
|Deterministic Matching||Probabilsitic Matching|
|Customer records are matched by searching for equality across identifiers such as email, phone number, or username. This approach works best when first-party data is readily available.||Profiles are matched through an estimate of the likelihood that two identities are the same customer. The identifiers could be things like an IP address, device type, browser, or OS. Probabilistic matching can be less certain than deterministic, and marketers must decide the level of confidence necessary to determine a positive match. This method can be useful when first-party data is limited, or when reach is a priority.|
Identity Resolution Solves the Problem of Cookie Deprecation
Issues with third-party cookies arose in part due to privacy concerns around how companies use personal data for advertising. At the same time, there is a desire for customers to have a personalized experience based on their interests and desires.
With identity resolution, marketers can more effectively engage with customers. Customers want to be recognized for their previous brand engagement and want the benefits that come with an established relationship. An identity resolution solution combines customer data – both anonymous and known – to give you a clear picture of customers.
The goal of identity resolution is to give digital marketers a complete customer view in a multi-device, omnichannel environment, including both offline and online activities, allowing for consistent engagement in a meaningful way.
How Marketers and Data Professionals Benefit from Identity Resolution
The benefits of identity resolution come with the processes integrated into the technology. Several Customer Data Platforms (CDPs) have integrated identity resolution technology into their overall product offering. Integrating identity resolution helps enhance the value of CDPs by improving the customer profile.
Here are five ways marketers and data professionals can use identity resolution solutions to elevate their data management strategy:
1. Match known customer data with anonymous data
This enables you to connect customer behavior even if specific identifiers change. For example, if customers replace their device, you can still link them to a personal identifier. This allows for personalization and improved customer experience.
2. Build on first-party data
Identity graphs contain information known about a specific customer. With the elimination of third-party cookies, many identity resolution platforms are using first-and second-party data to build this data picture. It can also help you address any gaps in your first-party data in a cookieless world.
3. Integrate data from across the enterprise
Marketers can also integrate information such as demographics, lifestyle, behavioral, purchase data, and other information from third-party sources that are accessed or purchased. All of this can be used to create a customer identity that allows targeted marketing messages to certain customers, while excluding others as needed.
4. Remain compliant with data privacy regulations
Data privacy is another benefit of identity resolution. Anonymized personal identifiers allows companies to share data without violating customer privacy, and remaining compliant with personal data regulations.
5. Create accurate predictive models
An additional benefit to identity stitching is the ability to do more accurate predictive modeling. This involves producing the training data necessary to identify lookalikes within other customer sets. With automated predictive modeling built into an enterprise-grade CDP, the model-building engine correlates hundreds of profile attributes to provide a recommended list of the most meaningful profile features.
Preparing for a Cookieless World
As more industries follow along with Google and Apple’s deprecation of third-party cookie data, it’s important to stay ahead of the emerging issue by creating personalized experiences for customers without violating their privacy rights. Identity resolution solves this unique and challenging problem and prepares marketers and data professionals for a cookieless future.