There’s a lot of interest being displayed in Big Data right now. As much as businesses are attracted to its rewards, though, there is also some uncertainty involved in its implementation. How can Big Data align with the business decisions you’ve already made – and those you’ve yet to make? What’s the best way to gather the data your customer relationships are generating? When you have this data, how can you identify it, organize it, and harness it?
Many organizations are pondering these same questions. While the answers will depend on each business’ structure and needs, there are some universal steps that will help you leverage Big Data. What are they?

5 Steps to Big Data Success

Getting set to implement Big Data is a major component of the success of your overall endeavors. In our experience, here’s what you need to do to prepare your company to ride the data wave:

1. Start Thinking Big Data. It’s not uncommon for retailers’ database systems to be disparate. For example, your customer data system may not work well with your transaction database. The whole goal of Big Data is to get an accurate picture, using all data sources. So your first step is to invest in a good data system that can handle the input and harmonize your current systems. Azure or HP Vertica are good options.

2. Know What You Know. Where does the information about your customers live? In-house? Third-party? Identify what information you already have and what you’ve got coming in. Also, don’t be afraid to consider supplementing your data sources with a third party of there’s a need.

3. Practice the Art of Social Listening. Social media is a great tool, but you’ve got to be able to use it. If you don’t already have one, invest in a good listening tool. You need to know where you stand in the social universe; the results can have a huge and long-lasting impact on your brand and thusly on your top and bottom lines.

4. Decide Your Data Geek Strategy. This torrent of data means you’re going to need someone (or more likely, several someones) to process it for you. Fortunately, data engineers and decision engineers are up to the task. Your fundamental decision is whether to develop an in-house data analytics department or to outsource it. This isn’t something to be taken lightly; data engineers are essential to maintaining your Big Data system, and decision engineers are needed to squeeze every drop of information from your data.

So, what’s the right answer? It will largely be determined by the size of your company and the flexibility of your budget. Even if you elect to grow your own data analytics team, it is best to get started with an experienced analytics service.

5. Use Data to Optimize Flow. Once you’ve set up your data strategy, start looking for ways to optimize some less-expected data sources. Use machine learning algorithms to ID your most popular product. Take the data you’re getting from storefront and online POS and use it to manage your supply chain by adjusting production and distribution according to demand. And, whenever possible, make good use of real-time and near-real-time data input to maximize campaign planning and management.

In today’s economy, retailers need to do more than passively listen to their customers. They must use the information they glean from customer interactions, store transactions, and other sources to create a comprehensive view of everything involved in their industry, from large markets to individual customers. And, using this understanding, they need to translate their knowledge into agile and effective decisions.

Authored by – Lavanya Ramanan, Subject Matter Expert at Absolutdata and Titir Pal, Director – Analytics at Absolutdata.