This is the fifth installment of our “Customer Data Strategy” playbook.
There’s an old adage that goes something like this…
A police officer sees a drunken man intently searching the ground near a lamppost and asks him the goal of his quest. The inebriate replies that he is looking for his car keys, and the officer helps for a few minutes without success then he asks whether the man is certain that he dropped the keys near the lamppost.
“No,” is the reply, “I lost the keys somewhere across the street.” “Why look here?” asks the surprised and irritated officer. “The light is much better here,” the intoxicated man responds with aplomb.
Marketers working without a solid command of user identity are like the drunk near the lamppost. They’re performing an activity for the sake of doing it, not for the sake of getting results.
While cookies are particularly problematic, the same “lamppost” issue can occur with any other data type. Identifiers like email addresses and mobile device IDs are important to capture because of their persistence over time, but too many marketers capture these data points without thinking through (and therefore acting on) the long term value they can provide. Email addresses, for example, are often left in newsletter systems, just as cookies are left in ad targeting and personalization systems.
To overcome these challenges, you need identity resolution, or the ability to unify identifiers across systems and attach related attributes and behaviors to a unified profile. Rather than just a single lamppost, identity resolution establishes a grid that powers the full spectrum of marketing, advertising, customer support and analytics activities so you’re never in the dark when it comes to identifying a user across platforms and screens as being the same person. Identity resolution achieves this goal by helping create a 360-degree view of customers for analytics, personalization and targeting and by enabling true omnichannel engagement.
Putting identity resolution processes in place starts with the following four steps:
1) Collect and Connect Identity Information
In the multi-screen world, almost every new digital source and platform has its own identifiers, but you can broadly group user identities into two categories:
- Implicit characteristics: Mobile identifiers (IDFA/IDFV, Google Ad ID), IP address, web cookies, etc.
- Explicit characteristics: Email address, Facebook ID, Google Account ID, etc.
Together, these characteristics can help you identify users based on factors like location, device type, search and session history, events, email and social handles. This type of identity data is important when it comes to converting anonymous users to known users, which you need to do to capture leads.
2) Append User Attributes and Arrays
Identifying users is a big step in the right direction, but to deliver a truly personalized experience, you also need to take into account descriptive user attributes. The implicit and explicit characteristics like those listed above only provide a two-dimensional view of users, which makes it hard to understand who they truly are and what they want. It’s the ability to weave in user attributes like gender, referral source, reward program status and preferences that really bring this image to life by delivering a more three-dimensional view of users. There are countless descriptive attributes you can use to categorize users, and the ones that are most important to your business will depend on your business objectives and data plan.
You can also take these efforts to better understand your users one step further by enriching their profiles with third-party data. These additional insights can cover everything from demographic and behavioral data to cross-device data. For example, while you can learn a lot about your users from the data you collect inside your app, you can gain a much better understanding of who your users are by overlaying data collected in-app with data from third-party sources that cover areas of interest like brand affinities, household purchase data and more. Ultimately, this overlay helps you obtain a more comprehensive picture of users so that you can understand their interests better and use that understanding to serve them in more meaningful ways.
One of the best ways to understand all of the different attributes that make up a user persona is to create user attribute arrays. Unlike traditional approaches that require a binary view of users in which you can only indicate a single attribute, user attribute arrays account for multiple points that describe users. This type of view is particularly important as you get to know users more deeply over time, which has become possible thanks to the ubiquity of mobile.
3) Manage User Identity
How you manage user identities is an important part of validating your efforts and preparing the data for distribution to your various systems of engagement and insight. This management includes activities like making sure you have a single profile for each user (as opposed to duplicates across channels or devices), ensuring the accuracy of the information you have and priming the profiles for different use cases. This last point is especially critical, as you need to understand what information you can use where. For example, users now have to give permission for everything from push tokens and email messages to location capturing, and it’s important to keep track of those permissions so that you collect information and engage with users accordingly.
Additionally, identity management activities should be ongoing as user information (both identity information and user attributes) is very likely to change and expand over time.
4) Distribute & Apply Identity Information
Finally, user identities are only as valuable as how you use them (after all, you don’t want to collect identities just for the sake of doing so like the drunk near the lamppost). The good news is, by following the first three steps, you should have a deep level of insight into who your customers are, what they want and what actions they’ve taken along the entire customer journey that you can use to create fully coordinated, engaging and individualized customer experiences.
For example, you can use identities to segment users into different groups to personalize outreach based on things like preferences or location and make predictive offers based on what similar users previously liked or purchased. Specifically, you can use these segments to filter for all users who fit mold X and took action Y (e.g. women in California who added products from a certain line to their shopping cart on your mobile app) so that you can engage with this group in a very personalized manner.
Historically, many systems that have been great at user identity resolution have been closed off islands unto themselves. A system like mParticle changes that by enabling you to pass unified identity data to multiple systems in multiple ways in order to put that information to use. For example, mParticle allows you to build custom audiences and segment users based on real-time and historical data as well as in-app activities. You can then easily pass this information to executional systems like ZenDesk and Cloud Data Warehouses.
Last but not least, remember to link user identity data to other data that you collect, as orphaned data won’t provide any value. As a result, in addition to following the steps outlined here, you also need to set and manage user identity from the very beginning so that subsequent behavioral data, such as event and session data, gets properly linked to specific users. This linking will help create a customer-centric data model and ensure that you’re not just thinking about user identities, but actually putting those identities into action and making them the center of your data model.
These identity resolution activities will go a long way toward helping standardize data practices, avoid issues and squeeze the most value out of the data you collect.
As the final part of this series, learn How to Manage Privacy and Security in a Multi-Screen World.