What is identity resolution?


Digital Channel / Analytics 184 Views 0

Identity resolution tools take simple analytics a step further by tying online behavior to a consumer’s unique identity, giving marketers the information they need to zero in on their target consumers with highly personalized, tailored offers that, in turn, lead to higher ROI.

Identity resolution has become increasingly important for marketers as people move across devices — mobile phones, desktops, connected TVs — throughout the day. Identity resolution can help marketers understand that Mobile User A is the same person as Desktop User B. Without that understanding, marketers aren’t able to control messaging to users as they progress through the customer journey on different devices and that’s where identity resolution can help.

It works by reconciling all available data points, which include those collected by first-, second- and/or third-parties. A composite is built that provides marketers with a cherished 360-degree view of a customer’s identity and user journey, and enables an insight-informed, data-driven “single-customer view”  — also known as people-based, or user-level, marketing.

Marketers use a number of tools and platforms to reconcile users’ identities, including simple customer relationship management (CRM) systems. In 2018, the martech landscape saw a proliferation of customer data platforms (CDPs)— tools that track user omni-channel behavior across different devices, platforms and channels.

At the center: the identity graph

To identify individual customers, data is plotted against an identity graph. Consumers give consent along their path for various pieces of marketing technology to collect, process and analyze data such as device ID, email addresses, phone numbers and cookie data, in addition to behavioral information such as purchases or website visits. That information is matched to other data in the graph using algorithims and patterns to create a likelihood, or probabilistic match.

Over time, the systems use artificial intelligence (AI) and machine learning to get smarter and make better guesses at matches. When a user takes an action that requires them to verify their identity, such as paying with a credit card, that guess then becomes deterministic — a perfect match.

It’s a mutually beneficial arrangement. In exchange for that information, brands provide customized experiences that are more relevant and useful to the consumer, a convenience that some studiessay is worth it even for those who are concerned with privacy.

Walled gardens such as Facebook have their own identity graphs, as do data management vendors, leading some of the industry’s leading demand- and supply-side platforms to formthe Advertising ID Consortium in 2017.

Data laws threaten the ID graph

Strict restrictions governing the use of personal data, such as Europe’s General Data Protection Regulation (GDPR), the soon-to-be implemented California Consumer Privacy Act (CCPA) and potential upcoming federal legislation, might throw a monkey wrench into companies’ ability to collect and use second- and third-party data.

Signal CEO Mike Sands, whose company provides such a solution, says that these laws provide “a strong incentive to invest heavily in first-party data that brands can own and operate with users’ consent.”

“Making a strategic pivot away from third-party data toward first-party data also puts brands on better footing in the fight against Amazon and other industry disruptors (e.g., direct-to-consumer

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