Look at all this information we have. Now what?
An appropriate question. Organizations have been collecting information on shoppers, marketing promotions, and many other details relevant to their businesses for years. But it wasn’t until recently that we’ve begun to understand the real potential of that information.
Enter big data. Unless you’ve cut yourself off from all digital sources over the past few years, you’ve almost certainly heard the term. Big data is the collection of structured and unstructured data from a wide variety of sources. Unlike normal data collections, there is so much that it’s too complex to process using traditional applications.
By gathering all this information from a number of sources, companies begin to learn more not only about their organizations, but they also gain better insights into the environment where they operate. They can determine the variables that can lead to success, and those that tend to have negative outcomes.
When it boils down to it, big data is all about patterns. Historical information is gathered and interpreted to recognize patterns and create predictive models. And just like this information is collected from any number of sources, its findings can also be applied to any number of industries or business scenarios.
In fact, one of these scenarios should be using big data to build better business strategies. Now, that doesn’t mean we approach the data with a blank page hoping it’ll magically tell us everything we need to do. That’s not how it works. Organizations need to have a predetermined goal when sifting through the big data mine. There is so much information available, having a proper business goal orients us and points us where we need to go. We can then begin to ask the right questions in order to gain the right insights. A strategy is the means by which a goal is realized, which is precisely why every organization should be referring to big data in order to come up with something that has a higher chance of success.
Let’s look at a couple of examples that demonstrate how big data can help create a more informed strategy:
Retail
Retailers have a number of ways to collect information on their customers. Loyalty programs, for example, help retailers track purchases while simultaneously receiving detailed information about the customer. They can also use data show how in-store promotions influence shopper behavior.
Let’s say the store decides to cut the price on a specific product. That could influence people to make an extra trip to the store, where they may buy more things in the process. Or, it could push people to only buy more of that discounted item, leading to lower future sales when the item would produce a better margin. Or what if retailers decide to introduce more low-cost products. They may attract more customers, but higher-end products may start to sell less.
Using big data can help retailers improve their promotional strategies. It’ll help them understand the short-term and long-term effects of their decisions, enabling them to optimize their promotions for the greatest return.
Advertising
It’s not always easy to measure the impact of media spend. Sure, Web 2.0 has helped with that, with online ads and website analytics to monitor conversion rates and other metrics. However, it’s difficult to measure the impact that digital ads may have on in-store sales.
Using big data, organizations can use in-market testing to better understand the correlation between online and brick and mortar. They’ll learn where online ad spending should be increased (or decreased) in order to see the highest offline returns.
There are so many insights awaiting those willing to make the investment in big data analysis. However, like we stated earlier, there is so much information available, relying on traditional applications won’t suffice. Organizations will need to invest in the right services in order to better manage and analyze the data to their advantage. Using a proper data service, like Amazon Elastic MapReduce, will limit the challenges of mining big data and make data processing accessible, easy, fast, and inexpensive. Now’s the time to stop using the gut-check when building your business strategy, and instead use the data to create a better plan.
