Gautam Kumar

Data Scientist

In a previous blog, I gave readers a general idea– say, a 30,000 ft. flyover– of what is a 360-degree view of the customer. I wanted to take it a step further and dive into 3 key characteristics that make the most Optimal 360-Degree view of the customer. 

The optimal 360-degree view of the customer
The optimal 360-degree view of the customer

Unified customer record, single customer view, customer 360 profile, etc– there are numerous names for customer data floating out there today– all of which represent the same foundation that consumer brands are striving to grasp and leverage for creating personalized marketing and customer experiences. Although they sound the same, not all are created equal. 

Customer views sound like a simple concept, but there are a few questions to ask when building the Optimal 360-degree view of the customer:

  • Does it use all available customer data?
  • Is it precisely connected at the individual level?
  • Does it include and maintain context from each data source?
  • Does it update in real-time as new data becomes available?
  • Is it molded to your timeframe and specific use cases?

To achieve the optimal 360-degree view of the customer, brands have to pay close attention to the following three pillars: breadth and depth of data, accurate and aligned unification (identity resolution), and real-time usability of the data. 

Breadth and Depth of Data:

All of your data
The relevance of your personalized marketing initiatives is reliant on your customer view having all data points. If you’re missing data like social media interactions, in-store purchases, or loyalty status, you run the risk of marketing products to people after they’ve purchased; promote a first-time purchase coupon to customers that have already used it, and/or recommend products and offers that don’t align with the individual’s current interests. Customers are quite literally handing over their data and information to you and they expect you to use it. The mistake of not using customer data to personalize marketing and experiences could be damaging your company’s success. In fact, 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, and according to Accenture, businesses saw nearly 41% of their customers switch brands in 2017 due to poor personalization and trust. 

Accurate and aligned unification

Identity Resolution
The reasoning behind making sure all of your data is included in your 360-degree view of the customer is obvious, but now you have to ensure the data is unified into a usable profile. The process in which data is organized around individuals, even when the sources have diverse formats and lack unifying keys is called identity resolution. There are many forms of sophisticated and basic approaches to identity resolution; however, these formats become problematic due to their assumption of a 100% confidence match, even when it is incorrect.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.

Real-time usability 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 most optimal 360-degree view of the customer 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 the most optimal 360-degree view of the customer.

“But, does it scale?”

If your optimal 360-degree view of the customer can’t be built at scale, then it isn’t complete. Do you have trillions of records spanning Terabytes of data? Then your 360-degree 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.

In Closing..

Building the most optimal 360-degree 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 Optimal 360-degree View of the Customer.

Categories:

  • Customer 360
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