How to Use Big Data to Improve Your Retail Store Sales

improve your retail store

The term “big data” has been generating a lot of buzz in the past few years. But if you’re tuning out every time you hear it, assuming it’s only for major corporations and not for your small retail store, you need to start paying attention.

While there’s no uniformly agreed-upon definition of big data, in general it means gathering data from multiple sources, both online and offline, and using it to improve your business — often by predicting what customers will do. A big company like can gather tons of data from customer purchasing history, browsing history, product reviews, website analytics and social listening and use algorithms to interpret the information.

But even the smallest retail store has its own “big data” to tap into. In fact, you’re probably already tapping into yours. Chances are, though, you could be doing a lot more with your data.

Below is a list of the valuable kinds of big data that you can use.

How to Improve Your Retail Store Sales

Sales Receipts/Point-of-Sale Records

How big is your average sale? Does the average size go up or down at certain times? How many sales involve discounts or promotions vs. full price purchases? What times of day, days of the week and months of the year do you make the most sales? Conversely, which ones are slow? You can use information from your POS system and sales receipts to staff your store appropriately or make adjustments to your store hours. For example, if you find that customers rarely come in after 6:30 p.m., consider closing earlier or reducing the number of sales associates on the floor at that time. You can also use this data to plan for seasonal fluctuations in sales, helping you manage cash flow better.

Inventory Tracking

Whether your inventory tracking system is part of your POS or standalone, it can tell you what items are selling the fastest, when to reorder, how much buffer stock to have on hand and when items are getting to the point they need to be unloaded at a discount (i.e., winter coats in March). Look at year-over-year inventory

Customer Loyalty Programs

If you don’t already use a customer loyalty program, start! Forget about paper punch cards.  Today’s digital customer loyalty tools are not only simpler and less hassle for customers, but most products also provide you with reams of information on what types of offers attract your loyal customers into the store — and what tactics are likely to work on others.

Website Analytics

Even if you don’t sell any of your retail products online, studying your website analytics can show you how customers find out about your store, what websites drive traffic and what they do on your website. For example, if you see that lots of customers are searching for products, maybe you should start offering some of the most popular search items for sale online. Or at least include photos of what’s sold in your store so that customers can get a visual before they come in. Seeing what websites drive traffic to your store will enable you to put your focus on the places you’ll get the best results. For instance, if 80 percent of website traffic comes from Yelp, then you’ll be sure to keep your Yelp page updated. If most visitors are driven by pay-per-click ads or local search, you’ll want to focus on those.

Email Marketing Analytics

I hope you’re still using email to market to your customers. It’s still one of the most effective ways to engage with them. Review your analytics to see what subject lines, times of day, days of the week, etc., get the most opens and clicks. What do people click on most? What types of offers work best? Keep track of printed coupons or digital codes in-store so you know what offers are getting redeemed.

Social Media

You can use social media analytics to see what your customers do after interacting with you on social media. Do they go to your website, come to your store with a coupon code, etc.? You can also track what customers talk and ask about on social media. Do they all want to know about a certain product, or rave about it? Maybe it’s time to stock more or expand that line. Do they consistently ask if you have X when you only sell Y? Maybe you should order some of X and see how it sells.

As you can see, even the smallest retail operation has access to a lot of big data. By taking time to analyze it, you can do more of what works and less of what doesn’t and improve your retail store sales.

Retail Sale Photo via Shutterstock


Rieva Lesonsky Rieva Lesonsky is a Columnist for Small Business Trends covering employment, retail trends and women in business. She is CEO of GrowBiz Media, a media company that helps entrepreneurs start and grow their businesses. Visit her blog, SmallBizDaily, to get the scoop on business trends and free TrendCast reports.

8 Reactions
  1. Analytics can do a lot for your market research. It will help you know the factors involved in your sales and can help you improve your overall output.

  2. Thanks for this great article. I especially appreciated your focus on smaller retailers, who may not have the same budget and hence capabilities in terms of business intelligence solutions as some bigger ones. Great read!

  3. Thanks for demystifying the word “big data”. We all as small business do all these data collection stuff everyday and that is how we know what and what not to as we run our business. If any business big or small do not gather data, it will be difficult if not impossible to remain in business.

  4. These are great pillars to analyzing retail store management. Customer loyalty program data is awesome as you can see usually run multiple campaigns at the same time and get almost immediate feedback. Whether social, email, or web-based, the trick is to combine them into a unified front to keep your customers engaged. I’d add 2 additional pieces where we’ve been able to help our clients in utilizing data: One, is commissions, and while you may not be a store that utilizes them, POS data and CRM data is imperative for both designing a plan, and payout. Lastly, do not forget about data outside of your own. Industry publications, forecasts, and larger competitor’s earnings, along with web traffic, etc. can be used to find patterns, foresee trends, and stay ahead of curve. Nice work.