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The Danger of Pursuing Customer 360 View | @CloudExpo #IoT #M2M #BigData
The Customer 360 View is a relic of the old-school Business Intelligence and data warehousing days
By: William Schmarzo
Mar. 12, 2017 01:00 PM
One of the best parts of my job is talking to a wide variety of customers across a wide variety of industries at a wide variety of different points on their big data journey. I’ve recently had several customer engagements where the client’s top business initiative is creating a Customer 360 View. Danger, Will Robinson!! I think the Customer 360 View business initiative is both dangerous and distracting; it is dangerous because it gives organizations a false goal to pursue, and it is distracting because it diverts the organization’s resources from more actionable and financially rewarding business initiatives.
The Customer 360 View is a relic of the old-school Business Intelligence and data warehousing days. Hate to be so harsh, but for many organizations, Customer 360 View was created as an artificial goal for organizations that could not move beyond the Business Monitoring stage with their data and analytic investments (see Figure 1).
Figure 1: Big Data Business Model Maturity Index
The Customer 360 View business initiative was created as a substitute for the hard data analytics or data science work necessary to understand and quantify your customers’ behaviors, propensities, tendencies, inclinations, preferences, patterns, interests, passions, affiliations and associations. The Customer 360 View business initiative lulls organizations into a false sense of accomplishment that seduces organizations to invest scarce data and analytic resources on pulling together any and all customer data. Unfortunately, there are two significant issues with the Customer 360 View:
Yea, I hate the Customer 360 View as a business initiative.
Identifying and Prioritizing Customer Use Cases
We recommend that organizations start with an envisioning exercise to identify, validate, justify and prioritize those decisions. The envisioning process focuses on identifying and brainstorming the decisions that are being made about customers across all the different business functions (e.g., Sales, Marketing, Services, Customer Support, Product Development, Finance, Operations). The process will yield a set of decisions that we then group into use cases or common subject areas (see Figure 2).
Figure 2: Grouping Decisions Into Use Cases
For example, the following customer-centric use cases might come out of the envisioning exercise:
After we have identified, validated and vetted the use cases with the different business stakeholders, we then leverage the Prioritization Matrix process to prioritize the customer use cases based upon business value and implementation feasibility over next 9 to 12 months (see Figure 3).
Figure 3: Prioritization Matrix Process
Building Actionable Customer Analytic Profiles
Analytic Profiles are structures (models) that standardize the collection, application and re-use of the analytic insights for the key business entities at the level of the individual human (e.g., customer, patient, doctor, student, teacher parolee, mechanic) or individual physical object (e.g., cars, buildings, jet engines, airplanes, locomotives). See Figure 4.
Figure 4: Customer Analytic Profile
We will build out the Customer Analytic Profiles one customer use case at a time, ensuring that 1) we are focusing the organization’s scarce data and analytic resources on those use cases offering the optimal business potential, and 2) that we have a big data architecture in place (data lake and analytics tools with Analytic Profiles) to capture, refine and share the data and customer analytics across multiple customer use cases.
Creating “Customer Actionable View”
Figure 5: Foundational Customer Data & Analytics
Now, isn’t that better – and more actionable – than just collecting any and all customer data?
By the way, I am going to be teaching this process at Strata + Hadoop World in San Jose on Tuesday, March 14th. I running a three and a half hour workshop titled “Determining the economic value of your data.” If you sign up, show up ready to work (bring your work gloves and work boots!). I think you’ll find the simplicity of the process illuminating!
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