Data Your Store Should Be Leveraging, But Isn’t

Making Data Useful

One challenge when gathering data and analytics is discerning which information to focus on. It’s easy to drown in a sea of data to the point where everything seems valuable leading to nothing. Ultimately, data is only valuable if it can be interpreted and can lead to practical action.

So, what data should your retail store be leveraging?

A Forbes article, 5 Things Retailers And Brands Need To Know About Data In 2019, acknowledges the challenges in interpreting retail data. “…data is ubiquitous, but insights are rare.” However, one expert on shopper data said, “Just looking at basic data about what a consumer might have purchased before and what they may be in the market for now presents some of the biggest opportunities for retailers.”

Again, data in and of itself is not so helpful. The goal is to understand past behavior so that retailers can predict and impact future shopper behavior. This starts with retailers gaining a greater understanding of their individual customers.

In order to do this, retailers should use analytics to interpret customer demographics. Another Forbes article, How Retailers Can Make The Most Of Their Data, says, “…retailers must…bring together external data sources, such as demographics, location and market data, with internally held customer data, such as transaction histories and loyalty status.” This information helps retailers form a deep understanding of their customer and establish “a trusted single view.”

Some may believe that collecting shopper data is only essential for large retailers. As explained in Software Advice, data is useful and accessible for small and midsized retailers as well. In fact, they have an advantage over larger companies in that they are, “more agile and nimble in rolling out their analytics efforts and react more quickly to leverage data into a competitive edge.”

What Data to Collect

And what retail data should a business be gathering and analyzing? Software Advice suggests every store track sales per square foot, retail conversation rate, and net profit margin.

Regarding sales per square foot, Software Advice says, “It is one of the best metrics for gauging the performance of your store as it determines how effectively you’re using your retail space.” Knowledge gained from retail data can assist in determining the best way to lay out a store.

The retail conversion rate is a record of people who visit the store verses those who actually make a purchase. To raise the conversion rate, Software Advice suggests retail owners, “observe customers as they move through your store. … From that you’ll be able to establish how they’re interacting with your store and identify ways to improve customer experience.”

And net profit margin? “It’s the percentage of revenue your company makes per dollar of sales. It factors in all business costs, including marketing, payroll, transportation, etc. It tells you if you’ve made a profit or if you’re in the red for a certain month.” If the number is low, this means costs are too high and operating expenses need to be cut.

In regards to customer demographics, House of Bots notes that retailers should start with purchase data. “…when it comes to understanding customers …the most important data to collect is purchase information.” Brick and mortar stores have loyalty programs just for this purpose – to gain insights into their customers.

Medium says add-to-carts is the next data set to collect which can be done via RFID tags at a store. A store owner could track the “number of times a product is lifted from the rack … [and the] amount of traffic in a certain area in the store…”

Predictive Analytics

The purpose in studying past retail and shopper data is to gain insights. Predictive data and analytics, on the other hand, is forward focused. An article from 12 decisions says, “Predictive analysis uses various statistical techniques (data mining, predictive modelling, machine learning) that analyze current and historical facts to make predictions about future or the unknown events.”

Predictive analysis can be used to forecast trends. StrategyWise notes, “Retailers can apply predictive algorithms to social media posts, web browsing habits and other purchase data to figure out what will sell in the future, which in turn assists in determining how much of a product to place in stock.”

Predictions can go beyond stock and include, “understand[ing] how specific customers shopping at specific locations choose from an assortment of products, they can then predict what demand will be in different geographies.” The complex algorithms which are drawn from all types of data can also predict, “how a change will impact outcomes in terms of revenue, products sold, needed inventory and labor, among other areas,” says an article from Merrimack University.

The possibilities and information that can be drawn from shopper data and retail data are vast. Many retailers turn to data scientists to review the data and share insights.

However your small retail store uses data, it can be valuable. While it won’t answer every question you have, customer data, demographics, and retail data can help provide answers in many phases of a retail operation.