2 Ways Big Data and Little Data Are the Perfect Couple

August 1, 2017

Big Data is so in vogue, that it’s at risk of becoming the next “synergy”. Ah yes, all those wonderful hip words used by executives trying to show just how young and hip they are. While executives wear ball-caps to cover up their bald spot, Big Data is bandied around the Board Room. But what’s the point of Big Data if it doesn’t actually drive decision-making in an effective direction? Or, worse yet, it’s used instead of the tried and true set of smaller data metrics that have driven sales teams and marketing departments for generations? 

At the risk of showing my bald spot, I think it’s time we look at Big Data for what it is; a fantastic tool that is more than welcome inside the successful company’s toolbox, but not at the expense of smaller data. 

Big Data vs. Small Data 

To understand my point, I think we need to set some ground rules. Big Data, in my opinion, is information that’s gathered by pulling together information streams from a variety of sources and then compiling that data-set so that analysts can make heads and tails of what the people consuming products and services really want.  

On the opposite side of the spectrum is information, we’ll call it Small Data, that is more traditionally used to judge companies in their efforts to grow market-share and increase shareholder value. Things like customer conversion rates, same-store sales and average basket sizes all help a company understand the results of their efforts. 

So how can companies responsibly combine the two and get the maximum value out of every metric? Here are five humble observations and suggestions I’ve learned through consulting a variety of firms on their customer engagement efforts. 

  1. Understand the Why with Small Data to Explain the Resulting Big Data 

Average basket size is boring. But, for ecommerce companies the size of a customer’s order has a direct impact on all sorts of important statistics; customer acquisition costs, average margin per item and the value of each client over their lifetime. And while adding context to this information is great, emotion is the most critical aspect of small data. 

For example, Penn States’ Wharton School of Business published an interview with Martin Lindstrom, author of Small Data: The Tiny Cues That Uncover Huge Trends. He pointed out a story about Lego and how they saved their company from the edge of bankruptcy by simply focusing and pivoting their company based on the emotional feedback of their customers.  

Lindstrom mentions in the interview: “The issue right now is that the corporate world has become completely blinded by Big Data. But it’s very, very hard to describe emotions using data. 

  1. Small Data Insights Are Easier to Communicate to Your Sales and Marketing Department 

The Founder and CEO of MoversCorp.com, once told me, “Our business lives or dies based on our ability to find the path of least resistance and make the customer feel like their frustrations are melting away the more they work with us.” It stuck with me because it perfectly sums up why smartphones, websites and automated applications are so popular. 

Big Data will tell you that we’re leaning on technology for more and more in our life, but you need the Small Data points to understand why. What is happening in the micro-transaction that is rewarding the customer and building a sense of loyalty with their subconscious that turns a trial into a habit? 

Your sales team speaks in small data terms. They’re not analysts, they’re emotional connections with your customers. When explaining the needs of your business, try to focus on emotion. For example, using a sales acronym like WUWSD (Welcome Understand Wow Sell Deliver) is far more effective than trying to explain that there’s a demand for immediate gratification in the marketplace, which is causing a shift towards automation. 

For marketers, product devs and salesman, understanding the small data gives context to big data. Is your company giving all of the data the diligence necessary to make the right decisions and earn customer loyalty?