Customer Analytics Surpasses Product Analytics

In the Introduction of Tom Peters’ new business book The Little Big Things, he mentions, perhaps unwittingly, a trend in what management consultants were focused on by decade.  He writes about being passionate on a number of things, including“…scintillating customer service (I pretty much had that “space” all to myself in the mid-1980s—believe it or not—“everybody” was doing quality, I was doing service)…”.  This tiny mention speaks to a macro trend that drives an argument that our businesses will have a huge focus on customer analytics in the coming decade.  Where businesses have focused on product analytics in the past, tomorrow’s analytics will predominately focus on customer.

Imagine the following assumptions.  First, what if management consultants were a leading indicator or even a causal factor into how managers decided to analyze their businesses.  (N.B. One can even ignore causality and say ‘It doesn’t matter if widely published and listened to consultants and visionaries talking about a concept drives use of the concept, or whether the concept is right and its wide usage drives consultants to talk about it.’ ) The fact is Peters marked a trend—the topic of the 80’s was quality for the most part.   Perhaps the mass of consultants talking quality—a product attribute—drove companies to develop analytics around product…but this implementation took ten years.  Thus the 1990s was the decade of quality analytics.  Fast forward to the 2000s.  The 2000s were the decade of management consultants talking customers.  Which means the 2010s will be the decade of customer analytics.

As an aside, if you want to know what analytics will occur in the 2020s for most companies, they’ll be about interactions.  Today, innovation has just begun in collecting huge amounts of interaction and social networking data.  The bleeding edge ‘interactions companies’ (which happen to mostly be Internet companies as they happen to have easiest access to a paradigm to drive the most interactions per second and have recordable data on the interactions) are just starting to think about how to analyze interactions as a marker of the health of their business and offerings.  It follows that once the ‘interactions companies’ work out best practices by the middle of the 2010s and they start to seep into leading edge companies, by the 2020s you’ll see early and late majority companies investing heavily into recording and analyzing interactions.  These interactions will be employee-to-employee, management-to-employee, customer-employee, customer-customer, influencer-customer, and on and on.  More ought to be considered on this topic.  And one should not forget that if you translate Tom Peters’ passion for service as a proxy for interaction, you can see he’s about 20 years ahead of his peers….

Back to customer analytics, n interesting piece of anecdotal evidence showing the rise of focus in customer analytics follows.  Performing a search on Amazon.com for books with the subject of ‘analytics’ shows a steady growth of books by decade: 2,400 come up published in the 1980s; 4,000 come up published in the 1990s; and 5,500 come up as published in the 2000s–a steady rise.  However, change the search term to ‘customer analytics’ and it brings back 0 results for the 1980s, 1 result for the 1990s, and 109 results for the 2000s.  The curve of acceleration for books mentioning or about customer analytics is exponential.

Assuming the focus on customers of the 2000s will lead to customer analytics in the 2010s, what does this mean for the workers, managers and executives focused on using, investing in, or building these analytics?  It means

a)      There’s a good chance you’ve had some exposure to customer analytics, although it’s likely failed, given that the majority of business intelligence projects fail—unless they make use of a purpose-built data warehouse appliance,

b)      There’s a good chance the more dashboards and leading indicators you have been making include customer as a part of a key performance indicator, measure, or attribute,

c)      The momentum toward predictive analytics mixed with this emerging focus on customers should be driving a rise in interest in behavioral economics…which it is: meaning you’ll be exposed to more service offerings and interest in predicting customer behavior,

d)      Your analytic technology will need to grow and perform with much more data.  It’s a rare company that has fewer customers than products and stores.  The business intelligence technologies of the past were about analyzing combinations of products and stores.  It’s typical that the number of customer greatly surpasses this combination.

There are many other events, trends, and factors that emerge from this focus that will happen around customer analytics.  The chief drivers to success will be to embrace it and be excellent at it, which means one’s method of collection, strategy, and most importantly delivery will be paramount.