Why Big Data Is Different from Customer Analytics
Big Data. A term fantastically overused, and equally as fantastically misunderstood. Kind of like teenage gossip: if everyone is talking about something, everyone thinks everyone else is doing it, so everyone says they’re doing it too.
Google Trend shows us the meteoric rise in how much everyone’s talking about Big Data over the last couple of years:
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It’s not uncommon to see people act like teenagers when it comes to Big Data. Like teenagers, few realize what it really means to their business. While many discuss how they need to manage Big Data, not enough people are focused on how they are going to use it. That is, in a nutshell, the gap between Big Data and customer analytics. In fact, more than 50% of enterprises surveyed in a recent Gartner report stated they don’t know how to get value out of Big Data. Ah, a refreshing breath of truth.
So far, most of the discussion has been about the IT problems associated with it. The focus is on the immense volumes of data that need to be properly structured, tagged, cleansed, and stored. The topic of Big Data can start discussions on things like access and security and storage and throughput, and, and, and … These can be important conversations, but if you’re running a business, they’re the last things you want to be worrying about. You want to know how what you know can be used to make your relationship with your customer better. For most of our customers that means Big Data needs to drive your understanding of your customer.
I’m always torn when the term Big Data comes up here at Adobe. It’s unfortunate that so often when the industry talks about Big Data it’s focused on size. Size is irrelevant; infrastructure-scale problems have largely been solved. What’s important is what the enterprise can do with the data. Storing vast amounts of data in an extremely efficient manner does not benefit your enterprise if you aren’t using that data to generate insights that drive marketing and business decisions. Let’s be clear: it’s one thing to be able to run queries, it’s another thing altogether for your enterprise to be able to generate insights that drive your strategy at scale.
We are huge users of Big Data technologies—we manage tens of petabytes of data, and we process more transactions in 30 minutes than the entire credit card processing network processes in a day—but our goal is to help you get the actionable insights you need at scale, not to crunch data en masse.
Your customer data needs to be usable throughout your enterprise. It’s not enough for a few folks with really big brains to be able to glean insights from those petabytes of data. If that learning can’t be applied across the enterprise in the myriad interactions your customers have with your brand, it’s not truly helping you. Marketers and call centers alike should be able to anticipate a customer’s needs based on their previous interactions with the enterprise.
All of this means you need to be using the data you’re collecting to better understand how you can use data to make your customer’s life easier. That can mean something different for each customer. The trick is to understand how Big Data can help you tailor meaningful messages to each client. For example, Lenovo uses customer analytics to understand the customer journey between their digital property and their call centers in order to make both experiences more relevant for their customers. There is a measurable positive impact to their business as a result. That’s the good stuff.
Is Big Data important? Of course it is. But it’s not the defining marker of whether or not your business will be successful. Your knowledge of your customer is. Customer analytics helps you ensure you’re making the customer experience an easy and positive one. That type of customer service that can gain you a customer and brand advocate for life … that’s what your data is really for.