Strategy Stop Thinking “Big” About Big Data

jared_blank
By Jared Blank

To get the most value out of big data, you need to think small

 

For all the value that the enormous amount of data available today can bring to retailers, it brings just as much hardship.

In fact, the amount of data in play combined with the mounting pressure to use that data in innovative ways have become so overwhelming that they’re actually paralyzing.

 

Has Big Data Become Too Big?

We’ve been talking about big data for years now, swooning over its ability to help us make smarter decisions that lead to measurably better results. But has big data gotten too big for its own good? In many cases, data has become so unwieldy that marketers are simply immobilized when trying to figure out how to actually understand what it all means and use it to take action.

Most often, this immobilization happens when companies try to boil the ocean with a massive project to get all of their data in a single place. These CIO-led integration efforts require an “all hands on deck” approach and can take years to deliver any results.

Fundamentally, there’s nothing wrong with this big-bang approach. In a cross-channel world, getting all of your data into one place makes a lot of sense. However, it’s not the only way to put all of the consumer data you’ve collected to good use. And it’s certainly not the fastest way to do so.

 

Putting Big Data Into Action Requires Thinking Small

When all is said and done, it turns out that the best way to get value out of big data quickly is to think small. And this “think small” approach extends to both data projects and decision-making.

In terms of data projects, taking an iterative approach by collecting data from a handful of systems rather than combining every piece of data allows you to make a big impact in a short timeframe. For instance, one good place to start is to combine your ESP data with web analytics or loyalty data. In contrast to the boil the ocean approach, you can implement this iterative method quickly and do so with fewer stakeholders.

Looking at decision-making, a lot of teams start by asking “what do we want to know?” which is as loaded a question as I’ve ever heard. Instead, marketers would be better served by starting with very small, very specific questions. For example, think about a new product launch. You might ask questions like:

  • Who would be most interested in this product?
  • Which of those customers are most valuable to me?
  • How can I make those customers feel like they’re getting more value from our brand? Should we let them buy a day in advance? And what’s the best way to tell them that — over Facebook? Over email?
  • When it comes time to mark down the product, which of our customers are most price sensitive (and therefore most likely to be interested)?

Breaking down what you need to do into such specific questions makes approaching all of the data you have much less intimidating, ultimately allowing you to use your data in a smart way that delivers results.

 

Empowering Users to Make Data-Backed Decisions

In the abstract, thinking small makes a lot of sense. But even if the “think small” approach is far simpler than a big-bang effort, you still need the right tools and processes in place to make it happen.

Specifically, using data to augment decisions will inevitably require a cultural change. Marketing has traditionally been a very creative-driven field, especially in the retail space. And while creativity remains critical, teams need to start balancing creative ideas with data-backed decisions.

Getting your team accustomed to answering questions with data requires a shift in culture around how people think about, engage with and use data. That said, once everyone starts to see how easy it can be and the astounding results it can deliver, it becomes an easy sell.

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