A 360-Degree View of the Customer Will Make Your Head Spin

The closest I’ve been to a 360-Degree view is the top of Mount Tallac. It turns out that my brain’s ability to capture a summit panorama is limited (and spinning around fast enough to try is risky). All I could do was take in one slice of the vista at a time, looking for value in what I could see in each one.

Those on the quest to leverage customer data latch onto the 360-Degree view metaphor.  I think this is unfortunate, and I agree with my colleagues Ben Bloom and Lizzy Foo-Kune who say this view doesn’t exist — and you’ll risk jeopardizing your business for trying. 

I am a big proponent of journey orchestration and “next best action” strategies. But even when I speak to the rare enterprise claiming attainment of a 360-degree view, they usually share how it hasn’t paid off yet. Metaphor turns to simile and clients say, “My customer data is like a pile of sand.”

Attaining Discrete Views of the Customer

Reviewing data from our recent customer data survey. I was struck by the distribution of reasons customer data leaders gave for the 360-Degree pursuit:

There is nothing wrong with any one of those reasons, but some represent very different views of the customer. Constructing each view requires different data, technologies, integrations, and processes to activate against it.

While I always warn clients about the pile of sand that is a 360-degree view, I’ve also started to talk about how to assert the value they can get from any one view of the customer as defined by the outcome they want. To wit:

• The Linear View: very clear signals (e.g. new account with email). You don’t need much data to steer them towards lower cost to serve channels or offer them to take a skin tone assessment that drives product recommendation.
• The Historical View: this looking across new and existing customers and computing the next likely purchase. Customer business records and firmographics aren’t too difficult to pull together.
• The Risk View: the challenge increases because this involves integrating with service, sales, and product usage records. But every company has a risk model that triggers mitigation efforts, so the rules exist to automate against.
• The Value View: this integrates lifetime value models and evolves an organization’s ability to prioritize risk: who’s worth saving and who is worth acquiring. The former is likely easier than the latter, but neither is normal for traditional marketers to work against.
• The Propensity View: now we are squarely in the realm of data science. This is your ability to mark those will undertake a desired behavior no matter what, those who won’t do it, and those who would if we just nudged them.

These views may sound too commercial for the high-minded marketer aching to execute “next best action” strategies. But these are the discrete views that build a return on the investment in skills, data, technology, and processes. One day, those competencies will enable efficient exploration of ‘next best actions’.

Tilting at those next best action windmills is a metaphor to be explored another day.