A month ago I saw a Forrester presentation on Customer Experience measurement that began with a great quote from the Global Bank: “We are drowning in data and starving for insight.”
Aren’t we all?
Most organizations have more data than they ever could have wanted. That data, however, sits idle in databases or cloud environments. Or, it is used sub-optimally. Why, for instance, can WeWork build a tool to manage its 350 properties as a website and view every detail about every building digitally, but Fairway regularly emails me with first time user coupons I am not eligible to use as an existing customer?
Make Data Usable
The answer to this question is fundamentally simple, but practically complex. First, centralize and clean the data so it can be used in an actionable way to extract insights. For existing companies this requires organizational redesign. That makes this step complex, political, and difficult to execute.
In one case, a major brand acquired three small start-ups with a strategy to grow its customer base. The brand worked on learning how the three customer segments feel and what each segment wants in order to optimize the brand’s offering with three different products.
Even though this was the correct first step, the strategy did not progress well. The company was not ready to centralize the customer insights systems and the teams of the three distinct brands they had acquired. Each start-up had its own customer database and customer definitions. None was open about giving access to that data.
This case only scratches the surface of how companies miss opportunities with data. Accessing and aggregating data is an essential first step for all organizations. But that is not enough to derive insights. Even after teams and data are centralized and aggregated, insights are not available until the definitions of the data are aligned. How is a customer defined? How far back should the data go? What spend per customer makes that customer “valuable”?
Get Everyone in the Room
Organizations must answer these and many more questions in order to make the capability of data insights available. Often, companies complete the first step. They aggregate the data. But they fail to analyze it and define its key parameters. Why?
The answers should come from the consumers of the insights, not the technology teams that build the insights. And those people are not in the room. Until there is a real engagement by the business and collaboration among teams, no one is going to get insights from their data.
The last step of getting insight out of data might seem the simplest. But often, it is missing. The quality of insights correlates directly to the quality of the questions we ask the data. I will repeat that. The questions asked of data are the engine of the insights derived from data.
This is where democratizing the cleaned data with a user friendly UI is key. Good questions are rarely formed on the spot. As business challenges arise and new situations emerge, questions come out. Data must be readily accessible (no coding or SQL skills required!!) to all. This allows end users to run reports and get the answers they need. And that lets them act in real time.
Successful brands like WeWork turn data into a tool. When companies perceive data as a tool, they create real value for customers. On the other hand, when they fail to take the difficult steps of organizational redesign, or to pay for cleaning the data, customers end up with those coupons they can’t redeem.
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