Baseball is a game of statistics.
At the professional level, armies of statisticians keep track of everything from an individual’s batting average, on-base percentage and earned-run-average. The data surrounding each player can be both extremely informative and overwhelming.
To help in providing a much-needed human context, teams spend a lot of time and money on hiring the right professional scouts. In doing so, teams match both “Big Data” statistics with “Small Data” human context to make crucial decisions around each game.
I was first introduced to the idea of marrying both “Big Data” numbers with “Small Data” context in a recent New York Times article titled How Not to Drown in Numbers. The authors, Alex Peysakhovich and Seth Davidowitz, suggest that the key question surrounding Big Data today is not necessarily “what did I measure?” but instead “what did I miss?”
They argue that without providing human context to the 1s and 0s, companies and teams are missing a great deal of actionable insights living within their own data. The article left me with the question of, “how do companies and teams quickly and easily unify these two types of data sets to make sense of what they have?”
In speaking with both clients and prospective customers, this tends to be the question I get asked the most. With that in mind, I’ve worked to compile a list of five recommendations below that I focus on when answering this question.
Conduct An Internal Data Audit
This may seem like a no-brainer, but it seems like a majority of companies big and small are trying to capture as much data as possible without understanding what they already have at their fingertips. An internal data audit is critical before you start down a path of data unification.
“Google” Your Data
Once you have a grasp of the data you own and control, the next step is to figure out what you don’t know. What questions are you trying to answer of your data? More often then not, companies are looking beyond the 1s and 0s and want to better understand the “why” behind certain customer behaviors or actions.
Assign Consumer IDs
When it comes to consumer data, each known consumer interacting with your digital site, purchasing at your physical store or filling out your old-fashioned paper survey should have a unique ID. Typically, this is an email address or purchase record ID. These are critical when it comes to matching and unifying records across the enterprise to create a single 360-degree consumer profile.
Plug and Play
Before you start pushing massive amounts of sensitive consumer data around, you need to understand how your current internal systems, 3rd party platforms and legacy databases plug and play with each other. Typically, they all speak a different language. Be prepared to ask tough questions on how to securely connect and push data together to make sense of it all.
Right mix of humans and machines
We’re heading toward a world where machines will be able to do a majority of the thinking and hard work for us, but until that day comes, humans still have to play a pivotal role as “scouts.” Do you have the right “scouts” on your team? Machines do a fantastic job of collecting and sorting Big Data, but humans are still needed to define, direct and contextualize the Small Data sets.
Scout your big and little customer data properly and the statistics will likely be in your favor.