Imagine having the ability to know each and every one of your customers intimately, simply by harvesting the data gathered from their interactions and purchases with your business – combined with a little ‘enriching data’ courtesy of third party systems. Imagine also having access to the analytical tools to make it possible to interrogate this data to come up with new ideas for products and services, new promotions, new ways of delivering services (and more) – to then test your BIG IDEA using the BIG DATA you’ve assimilated to validate which hypothesis works best. Finally, imagine having situational applications development tools that enable your enterprise to quickly apply its learning lessons and turn BIG IDEAS into BETTER PROCESSES. Now I admit that’s a lot of imagineering but that’s essential what the process of accelerated business innovation is all about. Like any other business process, accelerated business innovation has inputs, outcomes and systems and resources attached to it.
What is happening in organizations around the world is that the basis of competition is changing how leaders think about their enterprise; how it creates shareholder and customer value – how its economic engine functions. Even the core capabilities that define what makes an enterprise special are up for review. Drop all of this ‘blue-sky thinking’ on the ground and take a step back for a moment. The reality of the digital era becomes self apparent: Customers want fine-grained, event-driven products and services to satsify their unmet needs. They will consider any provider that meets their criteria for conditions of supply – but an individual’s criteria may well include the ethics of the enterprise, the persona of the leader, the reviews on the offering and what their friends like. Gone are the days when marketers could focus their efforts on beating their now all too familiar competitors vying for business in their chosen target market over months and years. It’s been a long time since Micheal Porters’ principles of markets and competition seemed to fit the reality of today’s digital always-online markets.
So what is replacing the aged principles of how markets work? I would argue the answer is customer science. (See my introductory slide presentation here.)
Customer Science is the intellectual and practical activity encompassing the systematic study of the structure and behavior of customers through observation and experiment. It’s about leveraging huge Cloud CRM data-marts of sifted and nurtured customer insights – largely captured by harvesting data from real-time systems (operating in the back-office or on the front-line in the form of eCommerce sites, campaign websites and the social-sphere) – to build new hypohesis, test them through experiment and analysis and apply them through the iteration of systems and processes.
There exists no single tool-kit, methods statement or competency for customer science; while the foundation of the discipline is around the deep understanding of customer structures and behaviors, every industry has its unique blend of wants, needs and outcomes that makes it almost impossible to architect a silver-bullet system or water-tight unifying process. What is common however to all customer science oriented capabilities is the acknowledgement that effective marketing now comes from smaller steps of innovation, finer-grained promotional campaigns and a more forensic appreciation of what customers want. This has led to the growth in the size and scale of data-marts and the introduction of a new term – BIG DATA. No longer is the majority of customer data held within internal IT systems. Much of the customer characterization and profiling depends on data harvested from third party systems. Technology platforms best suited to create these landscape views thrive on private-clouds and scale to unprecedented levels. Quickly the ‘industry’ of customer science is forming. It’s now thought that marketers hold the purse strings for the majority of future IT spend (that’s a pretty clear indicator of where accelerated business innovation is likely to be sourced from). It’s also expected that the drive for richer analysis of stuctures and behaviors will lead to a short-fall in the global talent pool for analytical skills.
Customer Scientists aren’t all going to come from the traditional discipline of marketing. Consider that much of the customer interaction activity for any business now takes place in social media sites and online – so people of the digital native generation are going to possess a great advantage and awareness of the future buyer. Also consider that when it comes to appreciation structures and behaviors, Zoologists are well equipped (same skills, different field). I would argue nevertheless that instincts sharpened by marketing research skills will be in much higher demand than ever they were.
The future customer scientist is going to need to be a pretty tooled up individual. They will need to be analytical, computer litrate, digital natives, creative and thoughtful – yet factual and pragmatic. It’s an interesting profile and one that will require many years of education to build. Many of the methods that have emerged since the turn of the century to analyze customer insights and harvest learning lessons from the tea leaves – outcome driven innovation, blue ocean strategy mapping, balanced scorecard, GOAL, issue signature analysis, Six Sigma – all contribute in some way to the methods now being adopted by enterprise to assimilate and learn from customer data. But nothing I’ve seen so far looks like a complete method statement to success.
Is customer science here to stay? Yes in some form or other I believe it is, but it remains in its infancy and we may be looking at decades rather than years before the ‘science’ becomes truly a science.