I originally wrote today's post for Logi Analytics. It appeared on their blog on December 14, 2017.
Data is just data until you do something with it, right?!
That statement has plagued companies for a long time. For a variety of reasons, not the least of which is that they just don’t know what to do with the data.
In December 2017, I hosted a webinar with Logi Analytics titled 5 Steps to Making Data Actionable, in which I shared tips on moving beyond data for the sake of data – and dashboards for the sake of dashboards – to recommending insights and outputs that drive action, I thought I’d share some details about one of the areas I covered during my presentation: how data-driven decisions and actions have evolved, particularly for customer experience professionals.
Customer experience professionals know that, in order to deliver a great experience, companies must listen to customers, link customer feedback to transactional (and other) data, and act on what they hear. There’s an old Gartner statistic that I still like to share because I believe it’s relevant to this day:
95% of companies collect customer feedback, yet only 10% use the feedback to improve, and only 5% tell customers what they are doing in response to what they heard.
This statistic is a good, high-level representation of how companies have matured or evolved (or haven’t) along the continuum of data-driven success.
Let’s take a closer look at that continuum. And let’s assume that Phase 0 is not listening or looking at data at all.
Phase 1 (Feedback) is where we see companies in the primitive stages of understanding the importance of data, i.e., they know they need to listen to their customers, oftentimes because everyone else is doing it. But that’s all they do; they check the box to say, “We listen.” And they’re paralyzed by the reams of data that exist within their systems.
In Phase 2 (Metrics), companies pick up their next bad habit when it comes to customer listening and understanding: they focus on a metric, on making their number, on moving the needle on the score. Doing that, instead of using data to improve the customer experience, is not really progress, and it’s not really a good thing. When you focus on the metric, you reward the behaviors that move the number, not on those that deliver a better experience. those (former, not latter) behaviors are often bad behaviors.
The next level in the data-driven success continuum is Phase 3 (Insights). Now we’re starting to make some progress. Companies at this level are interpreting the data, digging for insights, and telling the story of the data. They are making some data-driven improvements, mainly tactical at this point.
In Phase 4 (Outcomes), companies realize they cannot just make improvements without linking the findings and the work to be done to operational metrics and business outcomes. They realize they’ll make greater progress and get the resources (human, capital, and more) if they can show that “if we do X, it will impact Y.”
And finally, in Phase 5 (Innovation), we see some real progress! Companies us the data, the insights, and the linkages to make some real, significant, strategic improvements: they use the data to develop new products that solve problems for customers and help them do some job, and they redesign the customer experience to better meet customers’ expectations.
The important component along each phase is, obviously, the data and what is done with the data. Critical to that is the way the data is presented to the one who consumes it and needs to do something with it. There’s definitely an evolution in analysis and reporting, as well, as companies mature along the continuum. The output goes from basic descriptive statistics to metrics and trends to insights and stories to ROI and financial linkages to predictive and prescriptive recommendations that retain customers.
Consider these things when you’re developing reports and dashboards for customer experience professionals or for those who need to consume customer data in order to improve the experience. The data needs to be presented in a way that’s actionable; more specifically, it needs to tell the user exactly what needs to be done, why, and what the impact of making the change will be.
There are two goals when presenting data: convey your story and establish credibility. -Edward Tufte
Read the original post here.