Customer Data Unification
What is the Ultimate Customer 360 View?
Customer 360 View: Definition and Checklist
There are many names for customer data that have been aggregated at the individual level: unified customer record, single customer view, customer 360-degree profile. Consumer brands urgently need this view for creating personalized marketing and customer experiences. But are all customer profiles the same? No.
In this blog post we explore the unique characteristics of the Ultimate Customer 360 View, so you can take full advantage of all your customer data.
What is the Ultimate Customer 360 View?
Customer views sound simple, but there are a variety of factors brands should consider. The Ultimate Customer 360 View:
- is built using all available customer data;
- is precisely connected at the individual level;
- includes and maintains context from each data source;
- is updated as new data becomes available;
- is available when and how you need it.
To get a view like this, brands must focus on the following three dimensions: completeness of the data, precision of data unification (identity resolution), and timeliness of your ability to use the data.
Completeness of Data
You need ALL your data.
If your Customer 360 View is missing data such as in-store purchases, social media interactions, or loyalty status, your personalized marketing initiatives will be less than relevant. You will market products to people even after they’ve purchased them; promote the brand’s credit card to people who already have it; and recommend products and offers that have nothing to do with an individual’s current interests.
No one likes to be ignored. Customers are giving you their data and they expect you to use it. If you fail to use your customer data to personalize your marketing and experiences, you risk losing out in a highly competitive, customer-centric marketplace.
According to Accenture, 41% of consumers switched brands in 2017 due to poor personalization and lack of trust. Boston Consulting Group predicts an $800 billion transfer of market share to the 15% of brands that get personalization right, over the next 5 years.
Here is a check-list of all the types of data the MUST be included in your Ultimate Customer 360 View:
- Personally Identifiable Information (PII): email addresses, current home address, first name, last name, former last names, phone number, birthdate;
- Transactions: all online and offline purchases ‒ historical and recent;
- Preferences: opt settings, preferred channels, interaction frequency;
- Clickstream: where, how, and when a customer interacts with your site and mobile apps;
- Geographic: where customers live, shop, and travel;
- Social: handles, interactions, likes, shares;
- 3rd Party Data: demographic, occupational, lifestyle, and buying intent
- Custom Attributes: attributes derived through data modeling techniques, including propensity to buy, predicted LTV, customer and engagement scoring, etc.
Precision of Connections
Customer data doesn’t neatly fit together.
It’s clear that including all your data in your Ultimate Customer 360 View is important, but how should you bring it all together? Simply co-locating the data isn’t enough to make it into a usable profile. Data must be organized around individuals, even when the sources have diverse formats and lack unifying keys. This process is called identity resolution.
There are more and less sophisticated approaches to identity resolution. For example, fuzzy matching involves a set of rules that when met, results in two records being matched. This approach is problematic because it assumes 100% confidence in the match, even when this is not the case. It also ignores a lot of valuable data that doesn’t fit neatly into the ruleset. This limits a brand’s use of data and the personalized marketing use cases it can bring to life.
To achieve the Ultimate Customer 360 View, brands need a better approach: probabilistic identity resolution.
Probabilistic identity resolution is performed with machine learning algorithms that can predict the likelihood that two records are a match (i.e. belong to the same individual). When match likelihoods approach 100% confidence, a customer view can be used for 1:1 experiences and order confirmations.
When likelihoods are somewhat lower, the customer view is ideal for personalized marketing that includes product recommendations and micro-segmented emails, push notifications, and site experiences. Using data this way drives meaningful results like improved engagement and increased conversions.
Probabilistic identity resolution allows brands to use all their data, and connect it with controlled confidence and precision.
Timely Use of Data
Timing is everything.
Customers make purchases, they change their preferences, and their buying intent is about as static as the weather. To create relevant offers, marketers need to use their customer data while it is still fresh. But at the volume, variety, and velocity of today’s customer data production, making data usable in a timely manner is not as easy as it sounds.
Using all your customer data from all your disconnected sources requires probabilistic identity resolution, as discussed above. To do this in a timely manner, marketers require an advanced system with an unlying distributed infrastructure so they can connected records rapidly. A complete, unified view should be created in hours, not days or weeks, in order to fuel effective personalization. It must also be refreshed continuously as new data enters the system, so the view is constantly as accurate and complete as possible.
In addition, for some select use cases, customer data must be seconds or milliseconds fresh. Therefore, your Ultimate Customer 360 View must also offer you the option of streaming customer data directly from a source to a destination. This will leverage a thinner slice of data, but unlocks valuable use cases such as real-time site and app personalization, and push notifications. These two methods of connecting customer data must both be available for you to have a true Ultimate Customer 360 View.
A Note About Scale
If your Ultimate Customer 360 View can’t be built at scale, then it isn’t complete. Do you have trillions of records spanning Terabytes of data? Then your 360 View must be able to incorporate them all. This requires intelligent data ingestion that again leverages a distributed data infrastructure to rapidly bring in, unify, and store huge amounts of data.
Building the Ultimate Customer 360 View is not as simple as bringing customer data together into one system. It involves scalable, probabilistic identity resolution using a distributed data infrastructure, performed rapidly across all your data. And it results in a complete, nuanced customer view that can be pivoted, depending on the use case, for optimal timeliness and precision.
For this, brands need an Intelligent Customer Data Platform. Intelligent CDPs, built in the post-big data era, came about for the express purpose of giving brands the Ultimate Customer 360 View. To learn if an Intelligent CDP might be right for you, read Why An Intelligent CDP Is Best Suited For Your Customer Data Unification Needs.