One of my favorite quotes is from coaching great Vince Lombardi: "Let’s start at the beginning—this is a football." If we start by asking what the role is of analytics in improving customer management, I would suggest that we start at the beginning—and think about the role of analytics in for-profit businesses.
Sticking with our football analogy for a moment, the goal is simply to get the ball into the end-zone more times than your opponent. In business, the goal is to maximize profit by meeting a customer need. There is no physical goal line in business, so the first step is to paint the goal line by determining the maximum potential business (and therefore customer) profit—which is where analytics starts. With that clearly-defined objective in sight, all business activity can be tied quantitatively to the end profit-maximizing objective.
So it is my perspective that analytics are more than just "models," "data," "insights" or "results." When done right, as I have seen several companies do, customer management analytics become the very language of the business, connecting employee actions to positive business outcomes and harnessing customer analytics across internal organizations to keep everyone focused on working together to maximize results.
If this sounds like a tall order, let’s start with a few steps any company can take to move toward this analytic framework to optimize business and customer results.
Define the Goal Line in Your Customer Management Analytical Framework
Determine your current profit contribution from your customers (and prospects), and what their profit potential is. Closing this quantified gap then becomes your end goal.
This will be most revealing when you use analytics to segment your customers into groups and track group migration to identify "move-up" and "move-over" opportunities.
Also determine the current ROI from all of your marketing activity, whether offline or online, using the same yardstick. I saw this come to life at the direct marketing firm Wunderman over the course of a long partnership with Ford Motor Company.
We first set out to determine customer value and potential value by building behavior-based models. As the digital age came about, we trained our sights on identifying online marketing and Web site contribution to customer value. By monetizing the impact of marketing tactics on offline and online behaviors, and building a linkage between online and offline activity, we were able to create a holistic model to quantify marketing investments and shift spend toward areas of maximum return—getting us closer to the goal line.
Know Your Customer
As consumers, the "data trails" we leave behind as we shop, play, buy and converse are a gold mine for the savvy marketer. In an increasingly connected world, it is increasingly important for marketers to put all of that data in a data warehouse so it can be used to develop multi-faceted profiles of your customers that can be accessed to optimize any point of customer contact. No matter the current state of your data integration, create a broad plan to capture, store, analyze and act on the full set of your customer data. Think across product lines, across functional lines (e.g. sales, credit, customer service) and across channels.
Measure What You Do
Quantifying your business objectives and modeling your customers might seem like hard work, but you’re not done yet! The dimensions of the playing field are set, and you have your playbook ready. But what separates great teams from good teams is how well they learn and adapt. Think about how you bake this mentality into your customer management.
Are you actively trying new approaches, offers and creative treatments? Are you developing new "challenger" landing pages, search strategies and direct mail campaigns to test against your current "champion" campaigns?
The shorter you can cut your time to learn and implement changes, the faster you will be able to adapt your strategies for customer engagement. It takes dedicated focused effort, but it pays off by allowing you to outmaneuver your competition. Over time, you’ll be optimizing your customer value through this powerful but simple analytic framework.
First published on Call Center IQ.
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