Retail Data: How and Why You Should Use Big Data for Your Store

Retail data | Shopify Retail blog

By now, you’ve likely heard of Big Data and how it’s going to transform the shopping experience. But, you may be wondering: How, exactly, can retail data be useful in an in-store setting? 

Although the collection — and subsequent crunching — of data is a mostly digital task, it has a tangible outcome: You’ll know more about your customers and their shopping habits than ever before.

That retail data can be used to organize and stock your store to appeal to your existing customer base, while still welcoming newcomers. It’s also key to delivering a strong multichannel experience to today’s customers, who demand that their online and in-store experiences be as consistently personalized and seamless as possible. 

Fortunately, there are many data streams and technologies available to help retailers gain intel on their customers. Smartphones, wearables, and beacons are being embraced by companies looking to crack the ideal customer service formula.

Online conversion tracking, meanwhile, has emerged as a popular tool, and for good reason. It can help track who shops on your site, what items they look at, and, if they abandon their carts, it can remind shoppers to complete a purchase. Paired with in-store technology, these insights can help seal the deal.

Because Big Data can be such a boon to retailers, it’s worth investigating. So, here are some technologies to consider when applying data findings to your store, and reasons why Big Data could be a life saver for your business.

More Sales Platforms = More Data: How to Deliver a Multichannel Experience

Although some media outlets, research firms, and industry experts have been eager to sound the death knell for brick and mortar shops since online shopping became deeply integrated into our modern lives, statistics show the physical retail industry isn’t all doom and gloom.

Online sales made up just 3.4% of total retail sales in Canada in 2016, according to Statistics Canada. Meanwhile, according to the U.S. Census Bureau, about 8% of retail sales in the U.S. in 2016–2017 were done online. And a survey conducted last year by the Pew Research Center noted that 64% of Americans said they still prefer in-store shopping. (We’d be remiss not to also mention that a similar percentage of people said they use the internet to comparison-shop, especially for pricing, before pulling out their wallets.)

Retail data | Shopify Retail blog

Retail data | Shopify Retail blogAlthough these figures may be distorted by the fact that people tend to buy high-value, big-ticket items like cars, appliances, and furniture in store, ecommerce’s cut of total retail sales is still far smaller than in-person sales. However, when taken into the larger context — that is, comparing these numbers to previous years’ sales figures — one trend is apparent: Online shopping has been growing steadily in popularity year over year.

As our dependence on the Internet grows, it’s likely only a matter of time before the ratio of online shoppers to in-store shoppers evens out. Along with the notion that the majority of Americans in the Pew Center study said they use their smartphones to compare pricing, it’s clear mobile technology has a major role to play even with in-store shopping (particularly with the appearance of trends like showrooming).

Still, in-store shopping will never be obsolete. The fact of the matter is, most people don’t buy exclusively online or exclusively in store. Rather, many of today’s consumers have a blended approach to shopping, buying some items in store and others online.

That means shoppers expect retailers to offer a blended, multichannel approach to customer service. 

It also means that today’s shop owners need to get smart about their sales strategies — and retail data is key to this new intelligence.

FURTHER READING: Want to build a true multichannel experience? Check out 7 reasons online businesses should consider selling offline.

Smart Strategies for Catching up to Ecommerce’s Retail Data Momentum

Online vendors have had a head start over brick-and-mortar store owners when it comes to tailoring its services to modern customers’ demands.

Some ecommerce retailers have initiated try-before-you-buy programs, as well as free shipping and free returns, to help convert shoppers who would normally buy their product in person to try it online. For example, American bra-and-underwear brand Third Love allows American customers try its bras for free for 30 days before charging them. This is a radical departure from the norm; buying a new bra is a very personal choice when it comes to fit and feel, and women have traditionally shopped for them in person.

Third Love — which has made a name for itself because it offers rare half-cup sizes — detailed in a recent blog post how it used data to devise its unique sizing structure, and how data still contributes to its manufacturing process: “At ThirdLove, design is an ongoing process and ‘our fit gets better as we grow because of the data we collect and what we learn from customer feedback,’ says [founder Heidi Zak].”

Third Love’s program, along with its mobile at-home sizing app (which also collects sizing data to help the company decide what bras to make), are meant to incentivize consumers to try online bra shopping on for size.

This could be seen as problematic for brick-and-mortar retailers, but it actually presents a unique opportunity. Sure, a shopper who didn’t like the bra could return it by mail for free and get their money back. Or, they could return it in person and use the in-store visit as an opportunity to get a fitting done and try on other bras.

That’s the line of thinking that Canadian fashion brand Frank and Oak has taken. The company’s approach to multichannel encompasses two key components: A comprehensive ecommerce shopping site (with free returns) and brick-and-mortar stores powered by a mobile point of sale (POS) system. 

In stores, customers are welcome to return items they purchased online, try on merchandise, and order out-of-stock items and have them shipped to their homes. Meanwhile, Frank and Oak’s style plan offers personalized recommendations — and, if customers log in to their profiles while at a store, the clerks then also have access to order history, typical spend, shopping frequency, and product preferences.

📚 FURTHER READING: Learn how to use point of sale (POS) data to quantify your retail store's impact on customer acquisition costs, online sales, and lifetime value.

All of these are valuable insights that can help the clerks offer a more personalized shopping experience, while at the same time helping the company to merge the online and in-real-life experience of shopping at Frank and Oak. To achieve this kind of multichannel service, the company used Tulip Retail; Frank and Oak co-founder Ethan Song explained how Tulip’s technology enabled this kind of service in this video:

Even for smaller shops, tapping into this kind of multichannel service could be as simple as subscribing to a comprehensive retail platform and buying a couple of tablets. Some key performance indicators to look out for in retail are:

Meanwhile, engaged and connected sales associates are essential to the multichannel experience. Salesfloor is a B2B software company that allows sales associates tend to a cohort of loyal customers by creating personalized stores. Customers can shop directly with the associate rather than with the store itself, allowing the associates to collect commissions even for online sales. In this case, the sales associate acts as the bridge between online and the physical store.

This model has worked well for department stores, which constitute a large portion of Salesfloor’s clientele. That’s because consolidating a customer’s shopping experience and giving them just one person to deal with will be rewarded with loyalty — and loyalty leads to data.

Elsewhere, smartphone, beacon, and wearable technology have made it possible to capture data about consumers while they’re shopping in store.

Take Toronto-based startup Rover, for instance. The company’s platform enables stores and other establishments to deliver on-location content, deals, and other incentives meant to drive loyalty, engagement, and of course, sales. In practice, part of Rover’s service allows retailers to locate customers inside their stores with incredible accuracy, providing tailored content such as product reviews for the items directly in front of the consumer. I

t can also push limited-time offers of bonus loyalty points on items the customer is likely to purchase based on previous purchases, like what pharmacy chain Shoppers Drug Mart does with its app and points card.

Manage Your Inventory Better

Data-powered insights help to serve more than just track and improve sales, store traffic, and customer relations; they can also help you manage your store better.

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As we know, one of the most expensive parts of running a retail business, whether online or offline, is storing inventory. For one, it takes up precious warehouse space — or, if you run an ecommerce business from home, that corner of the kitchen where your dining table once was. And what if the surefire blockbuster doesn’t end up selling as well as you thought? You don’t want to have 1,000 T-shirts no one wants to buy — but at the same time, you do need enough in stock to ensure customers don’t experience lengthy details in getting their hands on your goods.

Using integrated point-of-sale and inventory management software can help lead to a more efficient business. Live inventory tracking, whether an item is sold in store or online, helps reduce bottlenecks, reveals shopping trends, and issues restocking alerts when supplies run low. Plus, there’s no more need to physically count every single item in stock on a routine basis, leading to time savings as well.

TRY SHOPIFY POS: Shopify POS offers built-in inventory management for retailers. Learn how to take care of business with Shopify POS.

Another data-driven initiative is dynamic pricing, like Amazon’s notorious algorithms that work to undercut competitors’ pricing on certain items. In this case, the data is derived from rival stores’ sites, and is used to incentivize customers to pull the trigger on that new blender or cat toy right now — before the price increases. Dynamic pricing, of course, is currently most useful for retailers who move extremely large volumes of goods and can take a hit on their sales margin in exchange for increased loyalty.

As it currently stands, dynamic pricing may not be a safe bet for small- and medium-sized retail businesses. That said, some retailers and service providers have integrated a rebate system that automatically sends out discount codes to people who lingered on a site, perhaps put some items in their baskets and entered their email addresses, only to never check out.

A number of Las Vegas hotels do this; would-be guests who put in their email addresses but who don’t follow through on their booking get a follow-up email typically offering a discount of 10-20%. MailChimp, Swell Rewards, Spently, and Bizzy are among the many companies that do automated coupon follow-ups. In the store environment, beacons and smartphone technology can be combined to push limited-time coupons to shoppers.

In-store coupons are, of course, nothing new. But combining it with a digital retail data component can help track the success of a particular offer, as well as who redeemed the coupon, what else they bought and how often they stop by. To do this, you could use a free QR code or barcode generator to issue digital coupons (or even print up the customers’ codes for easy scanning at the cash). Using magnetic stripe “punch” cards — ones that can collect purchase data — is another option.

You could also offer customers who visit your store a special promo code to get a limited-time discount on online purchases from your site. And, if you have a loyalty program, you can offer customers points that can be redeemed for other goods. Brownie Points, for instance, is a startup that allows any business to create its own loyalty program.

Getting into promotions is a win-win situation; this kind of action is an easy enough way to breed customer goodwill and loyalty toward your brand.  

Moving Forward With Retail Data: Setting Your Goals

While brick-and-mortar businesses aren’t going anywhere, they also can’t ignore the pressure ecommerce has put on them. What’s clear is that, to succeed in the modern age of retail, there needs to be some kind of digital component built into the customer experience. That could look like an in-store customer login, or using beacon technology to track customers who have enabled location services on their phones, or it could mean having connected staff.

Though we only mentioned a few, many platforms exist to equip shop owners with the most useful and intuitive retail data tools.  

That said, gathering data is pointless if it isn’t actionable, and it’s only actionable if you set clear goals for the data’s purpose. Do you want to track who moves from your site to your store? How about gaining more time-of-day insights, or the age range of your most frequent shoppers? How many customers make returns in store versus by mail? What about live-tracking inventory? And then what’s the constant, in the search for data: Is it the customer, the sales clerks or the store itself that serves as the X axis on your retail data table?

What’s for certain, though, is that introducing some data-collecting tools and technologies to your shop is a smart move. As they say, the best way to fight fire is with fire — or in this case, adopting some of the technologies that made e-commerce such a force to be reckoned with is the best way for brick-and-mortar retailers to not only survive, but thrive in today’s marketplace.