Retailers now have access to more information than ever. They’re using loyalty cards, cameras, POS transaction data, GPS data, and third-party data in an effort to get shoppers to visit more often and buy more. The focus is to provide better shopping experiences on a more personalized level. Operationally speaking, they’re trying to reduce waste, optimize inventory selection, and improve merchandising.
The barrier to personalized experiences is PII (personally identifiable information), of course.
“[What retailers know about you] is still largely transaction-based,” said Dave Harvey, VP of Thought Leadership, branding and retail services provider Daymon. “Information about lifestyles, behaviors and attitudes are hard for retailers to get themselves so they partner with companies and providers that have those kinds of panels, especially getting information about how people are reacting through social media and what they’re buying online.”
Transactions Are Driving Insights
The most powerful asset is a retailer’s transactional database. How they segment data is critical, whether it’s transaction-based reach, frequency, lifestyle behaviors, or product groupings. Retailers can identify how you live your life based on the products you buy.
“The biggest Achille’s heel of transaction data, no matter how much you’re segmenting it and how much you’re mining it, is you’re not seeing what your competitors are doing,” said Harvey. “Looking at transaction data across your competition becomes critical.”
As consumers we see the results of that in offers, which may show up in an app, email, flyer or coupons generated at the POS.
Social media scraping has also become popular, not only to gauge consumer sentiment about brands and products, but also to provide additional lifestyle insight.
Some retailers are using predictive and prescriptive analytics to optimize pricing, promotions and inventory. They also have a lot of information about where their customers are coming from, based on credit card transactions. In addition, they’re using third party data to understand customer demographics, including the median incomes of the zip codes in which customers live.
They’re Watching Your Buying Patterns
Retailers monitor what shoppers buy over time, including items they tend to buy together, such as shirts and ties or eggs and orange juice. The information helps them organize shelves, aisles, and end caps.
“There’s a lot of implications for meal solutions and category adjacencies, how people are shopping in the store, how that might lead a retailer test way to offer a right combination of products to create a solution somewhere in the store,” said Harvey. “You can’t be everything to everyone, so how can the information help you prioritize where to focus? The information you can mine from your transaction database, your loyalty card database can help you become more efficient.”
Information about buying patterns and price elasticity allows retailers to micro-target so effectively that shoppers visit the store more often and spend more money.
They May Know How You Shop the Store
Shopping carts and baskets are a necessary convenience for customers, although the latest ones include sensors that track customers’ paths as they navigate through the store.
“They can get the path data and purchase data about how much time you spend at stations, and they can use it to redesign the store or and get you move through the store much more because they know the more you move through the store the more you buy,” said PK Kannan, a professor of marketing science at the University of Maryland’s Robert H. Smith School of Business.
Retailers also use cameras to optimize merchandising to better understand customer behavior including where they go and how long they stay. Now they’re also analyzing facial expressions to determine one’s state of mind.
Driving Business Value from Analytics
Different kinds of analytics result in different ROI. If a retailer is just starting out, Kannaan recommends starting with loyalty cards since other types of data capture and analysis can be prohibitively expensive and the analysis can be cumbersome.
“The ROI on loyalty cards is pretty good,” said Kannaan. “The initial ROI is going to be high and then as you go into more of these cart or visual data, video data, your ROI is going to level off.”
Strategies also differ among types of retailers. For example, a specialty retailer will want data that provides deep insight into the category and shoppers of that category versus a store such as Walmart that carries items in many different categories.
“If you’re a retailer trying to sell a ton of categories you want to understand how people are talking about their shopping experience,” said Harvey. “There’s still a lot of untapped opportunity in understanding social media as it relates to doing better analysis with retailers.”
Retailers are working hard to understand their customers, so they can provide better shopping experiences. While personalization techniques are getting more sophisticated, there’s only so far they can go legally in many jurisdictions.
Kannan said a way of getting around this is to take all the informational content, remove any PII, and then extract the resulting information out of the data.
“It’s like I’m taking the kernel from this thing because I don’t have the space to store it and keeping it is not a good policy, so I am going to keep some of the sufficient statistics with me and as new data comes in, I’m going to combine the old data with new data and use it for targeting purposes,” said Kannan. That’s becoming more of a possibility now, and also it’s a reality because data volumes are increasing like crazy. That way I don’t have to store all the data in a data lake.”