4 Real-World Examples of Retailers Profiting From Big Data

Marketers and retailers are aware that big data stands to impact their businesses; what not everyone gets is how this can happen. Exactly what are retailers doing with big data that helps them outsell the competition, improve customer service, and inevitably better the bottom line? Here are your answers.

1. Predict Heavy & Light Shopping Times for Better Customer & Product Management

It’s no secret that purchases pick up during the holidays. What is usually a secret is how much. For example, will you get your heaviest traffic on your website or in stores? Which should you be most prepared for: Black Friday or Cyber Monday? Are people going to go nuts for electronics this year, or clothing? Is it going to be a banner year for decorating homes and yards, or more of a serving the family on heirloom kitchenware kind of year? Will it be a year that shoppers get the bulk of purchases made early or a year for last-minute catching up?

These answers help you keep coveted items in stock, while avoiding wasted cash tied up in inventory that isn’t moving. You can also use this info to hire enough temp workers, partner with the right shipping companies, and offer the right incentives for customers to choose your business over the competition. All of these answers are in the data.

2. Align Pricing With Demand & Competition

When a new product rolls out, you can use data from a variety of sources to determine demand, assess competitors’ pricing, and develop your own pricing structure for maximum sales and profits. For example, using data gleaned from social media, browser histories, forum groups, and demographic information, you can determine if the next video game or toddler toy is slated to be the next Tickle Me Elmo and which are likely to sit gathering dust on shelves with their “discounted to $9.99 for quick sale” signs.

3. Target Customers at the Right Place & Time

Geolocation data on mobile apps is a powerful way to maximize customers’ lifetime values. For instance, you might not convince them to trek across town on a busy Saturday for a 10% discount off a single item, but if they’re next door you probably can. Use geolocation data to target customers near your stores and incentivize them to come visit (and spend some money). Likewise, many businesses are affected by the weather. Use weather data from customers’ areas to make offers on weather-sensitive products like snow shovels, sleds, sunscreen, bug spray, allergy medicine, and more.

4. Make Recommendations Based on a Shopper’s Purchase(s)

Based on her preference for one product, big data can deduce her need or desire for related products, helping you turn a single sale into several sales for far greater profits.

A $600 tablet sale is sweet, but what if you could turn that into a $650 sale? Or a $750 sale? Learn to leverage product recommendation engines to upsell at the POS. For example, along with that tablet computer, offer them a wireless keyboard and mouse setup, a car charger, and a rugged, waterproof case. You’ve easily added another $100 or more to the sale for little more trouble than a couple of extra clicks. These recommendations aren’t even viewed as you trying to sell them more. It’s viewed as a valuable customer service, because who wants to forget those essential accessories for their new tablet?

Want to learn even more about how retailers are leveraging big data for higher profits and better customer experiences? Then you’ll definitely want to check out Big Data Week.