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Is brick & mortar ready to leverage in-store shopper data?
Through a special arrangement, presented here for discussion is a summary of a current article from the Mark Heckman Consulting blog.
Much of the growth of Amazon.com and other e-tailers can be traced to their ability to leverage the plethora of shopper behavior data that e-commerce sites yield to create an increasingly efficient, customized shopping experience. Such has not been the case for physical retail facilities.
Unlike their online counterparts, among other critical customer data, traditional retailers do not, on a regular basis, track the time spent in-store by the shopper or how shoppers engage (or not) in their merchandising efforts.
Yet affordable and practical techniques now exist to provide retailers all the information they need to measure in-store shopper efficiency.
Traffic counters with clocks provide the time shoppers spend in the store, from the moment they enter to the time they leave. Personal observational techniques can be used to create a comprehensive shopper map that includes density of shoppers, their directional flow within the store, the time they spend in each area of the store, as well as their gender and the direction they are facing. Coupled with compatible transaction logs from the retailer’s POS system, this information can yield important diagnostics as to the efficacy of the store layout and design and the critical merchandising plan within the physical store.
Part of the disconnect is that, while most retailers manage their business at the category level, customers shop at the item level. The faster the items they are looking for is found, the more likely they are to have the time to impulse purchase unplanned items.
Accordingly, it is incumbent upon category-organized retailers to better understand how and where those categories are merchandised in their stores. The shopper centricity of a category can be defined on two distinct levels:
- Shopper Exposure: What percentage of shoppers actually travel by the category in the store?
- Purchase Conversion: Once a shopper ventures by a category, at what rate do they slow down to browse and actually shop? And most importantly, at what rate do shoppers actually put an item in the basket and make a purchase?
Scoring each of a retailer’s critical categories with exposure and conversion rates is vital to truly unleash the potential of category.
Discussion Questions
DISCUSSION QUESTIONS: Do you see brick & mortar stores eventually leveraging in-store shopper data to the degree that e-commerce sites capitalize on browser data? Will increased efforts at in-store shopper data collection enhance or significantly alter category management efforts?
Poll
BrainTrust
Peter Fader
Professor of Marketing, The Wharton School of the Univ. of Pennsylvania
Chris Petersen, PhD.
President, Integrated Marketing Solutions
Mark Heckman does a terrific job of summarizing why stores need in-store shopper data and behavior tracking: merchandising, category management, messaging, offers, conversion and the list goes on.
But brick-and-mortar stores have a huge mountain to climb in terms of being able to develop in-store shopper data comparable to that available online. While in-store tracking has come down in costs, much it of it is anonymous in the interest of protecting consumer privacy. And if consumers opt in to be tracked via their smartphone, the logistics of being able to dynamically respond in a physical space in-store is much more difficult and expensive than it is online. While better in-store data will happen, the most important thing that stores can do right now is to do something online can’t — create compelling customer assistance through staff.
How can any retailer, brick-and-mortar or online, not use data? Data gives you information you need to be successful. Take advantage of it at every opportunity.
How can any retailer not use data? Very simple: just keep doing what you are doing, maybe thinking “data” will just jump up to bite you. Remember, there were a couple decades between checkout scanner data being produced and a business like dunnhumby demonstrating for Tesco one way for THAT data to be used.
Retailers really get NO credit for the creation of scan data, nor for its intelligent use. Bear in mind, its original use was strictly to speed the checkout process, showing quickly what the customer must pay. Of course, moving on to inventory control — managing the flow of products THROUGH the store was a no-brainer.
But I remember working with small chains in the ’90s that were still relying on VELOCITY data, what was coming into their stores from their warehouse suppliers to manage inventory, rather than SALES data, looking at individual items leaving the store with the shopper. Admittedly this was the far tail end of a business method that has largely receded to small relevance.
The point of this is that retailers are no more forward-looking to shopper behavior data, because with very few exceptions, they do not manage shopping, they manage merchandising — products. And they certainly are not looking for “data” to change that. This is why, after a serious presentation on how to use shopper data to enhance sales and profits, a senior executive at one of the top three major global chains asked, “Why would we do these things, if no one is paying us to?” If you don’t understand that question, you are blind to the reality of this industry.
First we talked about getting them in the store. Once we got them into the store, we talked about making them purchase. Once they were buying, we talked about up-selling, cross-selling and re-arranging the floor sets to encourage impulse purchases. Do we really need to do more to get the consumer to buy? Why don’t we just come up with interesting, attractive product that is correctly priced to provide profit to the retailer while providing the perception of value to the consumer?
Absolutely. Stores are fast becoming service providers rather than primary sellers. How can they possibly survive when they are not paid a cent for what they actually do best?
Store are “selling” services to customers who often prefer to buy the product elsewhere. When an online retailer loses a visitor, at least it knows about it. It is crucial that physical stores acquire similar or better capabilities of collecting and processing customer-behavior and conversion data.
Once they do, they can work towards charging brands and online shops a fair commission for servicing showrooming customers.
“Service” is what gives the whip its crack; it puts the morning sun in the sky and is the water that makes a garden thrive.
The tragedy of being buried in data and knowing the paralysis of analysis are THE call to action, for to have data and not use it is simply criminal (fiduciary duties not excluded!).
The challenge of location-based consumer behavior is met and then served well by anonymous viewer analytics that can link what shoppers do related to the messaging presented. A webcam-capture of facial detection attached to a digital sign can tell those who are messaging what information is relevant to the customer. Cell phone, electronics and sporting goods retail have known it for years and modify their in-store messaging based on target audiences and their behavior.
Sometimes the “low-hung fruit” of data can offer insights that move the needle the most.
While stores can do a much better job of using data to drive their planogramming efforts, I don’t think they’ll ever leverage data to the degree that e-commerce sites do. The reason is that in a physical store, retailers must set the store to cater to the “average” customer. In a virtual store, every visitor can have a different experience.
Using data to tailor that experience increases relevance, engagement and sales in a way that isn’t possible in the retail store environment.
I’m looking forward to seeing more results of lower-cost technologies to capture and analyze in-store shopper data. Auto-analyzing existing security video footage is a very active category. I also like the emerging category of motion-sensing and analysis. With motion sensors like Microsoft’s Kinect technology mounted 16 feet above a shelf, the technology can analyze which SKUs are taken off the shelf and then put back or put in the cart. One of my favorite stories is that a cereal brand used this technology to measure lift in putting the healthier SKUs at eye level and moving the sugary items lower. The results were that when a parent was shopping alone, more of the healthy items went into the cart, but when the technology measured a child accompanying an adult, more of the sugary stuff at their eye level went into the cart.
Of course they should be using their data more — this goes without saying (but I said it anyways). That said, Mark’s suggestion of exposure, conversion and purchase would put all categories in the same part of the store. Most of the time, shoppers are exposed to the categories they need to be exposed to — it’s not like we can’t find most stuff in the grocery store. When a category is high on exposure, the question is whether it’s the category or the location. This is a relative measure, comparing to other stores or other chains. When shoppers stop at it, look and don’t buy, it’s usually a price or assortment problem.
I agree with much of the article’s premises. Brick-and-mortar retailers need to do more to better understand the in-store pathway to purchase.
On one consulting opportunity, I was asked to observe consumers purchasing milk and other fluid dairy products. I was intrigued by a focus group comment that described this portion of the store as “cold, white, dull, boring metal.” I actually sat in the aisle with a stopwatch and observed behaviors. I discovered that in this area people don’t shop. Instead, they buy, spending only a few seconds observing the color of the milk cap and the expiration date. On the other hand, time was spent considering the value-added dairy products, like dairy creamer. We recommended that the retailer put a small refrigerator in the coffee aisle and found that away from the cold dairy section and within the coffee environment, these value-added products experienced significant sales increases over the more traditional placement.
Lesson learned: don’t assume anything and set your stores for customer convenience, not yours.
These new techniques in shopper data collection and analysis are promising, but retailers should first focus on fully understanding their purchase data from their POS system. Using a shopper identification (or loyalty) program, retailers can track purchases by shopper and identify key segments and trends among their shoppers. They can target specific shoppers with specific promotions based on the insights.
Analyzing data around shopper traffic and conversion can be interesting, but retailers should first ensure that they are getting the full benefit from analyzing their purchase data and taking action based on these results.
Although data could be useful to stores, I’m not sure how accurate it would be and how possible it is. Stores have a huge advantage over online sales in creating a customer experience that makes them stand out. Perhaps more energy should be put into creating an exceptional experience, analyzing the effects of that and improving it from the data collected.
Will brick-and-mortar locations leverage more shopper data then they do now? Yes, absolutely. Will they ever have the level of data that online retailers have? Not likely.
One of the many tools online has that brick-and-mortar retailers don’t have is cookies that track not only what users did on that retailer’s site but perhaps others as well. I doubt any significant segment of the population will agree to allow that same level of data gathering on their behavior in brick-and-mortar stores regardless of what they are given in exchange.
If the focal question asked “should” brick-and-mortar stores leverage in-store shopper data, then the answer is obviously yes. But the question really asks whether they’re ready to do so, and unfortunately for most retailers the answer is a resounding no. They can’t properly leverage their transaction log data, so forget about in-store shopper data. Retailers need to walk before they run: first figure out who’s buying what before you worry about who’s doing what. Given the disappointingly slow progress on the former, I’m not holding my breath for the latter. But I hope I can be proven wrong in the next few years.
This technology has been around for a while and it always seemed like a natural thing for retailers to do.
BUT … the store multiplier makes the task more capital-intensive than retailers are willing to bite into.
For what it’s worth, I don’t agree with the statement that “most retailers manage their business at a category level.” While this is true with regard to open-to-buy, in fact, some sectors are far more item-specific than others. The one that comes immediately to mind is shoes — right down to the color level. There are other verticals where the same is true. To use a grocery phrase, items are not “fungible” in most retail segments.
So while I agree that retailers should use insights in stores, I disagree with the reasons given. Sadly, it’s mostly all about the Benjamins and, secondarily, it’s about retailers’ inability to sift through the massive amounts of data that now threaten to bury them.
While I agree that data is important, I believe retailers’ in-store efforts right now should focus around the experience. Often a customer shopping online is looking for something in particular while the in-store shopper may be browsing around for the “find.” Retailers should cater to that.
They should also provide assistance to facilitate the find. Those serendipitous moments can’t be replicated online.
For my 2 cents.
Sure, physical stores need to become expert at gathering and leveraging shopper data. But Chris Petersen makes a great point about shopper anonymity in brick-and-mortar retail. To be more competitive with digital environments, shops need to know who is browsing and connect that with who is buying.
To accomplish this, facial recognition technology or an RFID chip-type technology should be employed. The mere suggestion of this is enough to scare many pundits (and shoppers). However, let’s not forget that it was not that long ago that the very presence of video cameras was shocking. Now, those are de rigueur.
The technology to monitor shopper activity has been available for several years, unfortunately no retailer has taken advantage of it. I would be surprised if Kroger is not currently working on this.
Research data shows that shoppers want two things desperately while in stores. One is helpful assistance and the other is compelling experiences. Delivering on these doesn’t take mountains of data, but it does take an understanding of the gaps shoppers feel and the specific categories where shoppers need help.
If brick-and-mortar retailers are not focusing in this area, they only have themselves to blame for the future. Shoppers will seek out what they want and leave slow-moving retailers in the dust. Look at Macy’s as they close stores and try to deliver better via digital. If shoppers decide Amazon is better online, they’re in trouble. If shoppers decide Nordstrom delivers better in real-life situations, they’re in trouble.
Hmmmmm.
Brick-and-mortar stores definitely need to take advantage of any and all shopper data they can get. Increased data will alter category management and enhance it. With e-commerce going strong, they need to leverage any data they can and should be investing in better technology so they can better compete.
Relevant data is essential. Winnowing-down the data to be useful is key and no small task. The opportunity is immense for retailers.
Perhaps the greater opportunity exists for major mall owners, such as Simon and Forbes and/or credit card companies to partner on a closer level with their tenants/clients.
The winners in retail will be the ones most able to manage executable customer data.
Data — in any business — is vital. What e-commerce sites have been able to do is adapt, respond and react to data in a meaningful, personal way. Brick-and-mortar stores cannot possibly respond in the same way across an entire enterprise of “physical” plants. But what could and should they do?
First and foremost, use the data! There are far too many retailers who claim to be collecting data and amassing information — but too few turning that data into executional changes (I’ve often referred to these stuck-in-a-rut retailers as “establishment” retailers who are unwilling and/or too immobile to step outside their comfort zone).
Next, stores must think beyond the four walls of their physical plant. The consumer shopping experience should not be confined to their brick-and-mortar operation but rather extend to omnichannel practices. That’s how consumers want to interact with a brand.
Finally, stop bemoaning what the other guys have. Just because online can react more quickly to data does not mean they have the advantage. Why? Because they don’t have the ability to literally touch their patrons and observe them in the same way brick-and-mortar operators do. That competitive edge goes to the brick-and-mortar retailers. Problem is, not enough retailers fully capitalize on this HUGE advantage.
The title of this piece says it all, “Are retailers ready?” Is effective technology in the marketplace today to attack this data? Yes, and there is some really cool stuff that can take most of the traditional “gut feel” out of merchandising and marketing decisions. However, the vast majority of physical stores are not yet taking advantage of these tools for one reason or another. Most of those reasons are not deal breakers, though. I know of very small retailers that are reaping ROI for some great shopper insights investments. These investments are around store-level order optimization, category management and real-time personalization.
If you divide the world (conveniently) into grocery and non grocery and rephrase the question as should “non grocery” brick and mortar … you might get a slightly different take on things. With smaller store sizes, and frequent product change outs, the world of non grocery is not as strong a candidate here. I go with Bob’s response — create better, more interesting products. For grocery (and maybe big box) where you have higher shopper frequency and greater possibilities for how to place and promote a product in the stores, go for it.
The key word is eventually. Remember, Amazon already has and uses the data. Stores have (or could have) access to vast and invaluable shopper data. The challenge is to determine what data should they be sifting through and which data is actually going to help them sell more to the digitally empowered shopper. Their first challenge is to create seamless and delightful experiences that resonate with online shoppers. Why go to a brick & mortar store — for the experience. Unless the holistic shopping experience is enjoyable, shoppers will shop from their kitchen table — not because it’s more fun, but because it’s easier and has far fewer hassles.
More time should be spent concentrating on “little data” — data that actually can translate into real commercial results. Creating seamless tracking from manufacturing through the sale in the aisle using RFID technology is “little data.” It’s very focused data, but with powerful supply chain and consignment sales process ramifications. These technologies will change the entire brick & mortar landscape.
We’ve been talking about this for many years, and this topic will be part of the store operations meeting I’m managing in Las Vegas in October. That said, progress is (at best) incremental, with no breakout examples of what the technologies might do. I don’t expect this to creep up the priority list any time soon.
It is imperative that brick & mortar retailers leverage customer data beyond digital channels, which means in physical stores. There is more data and increasingly affordable technologies that can distill critical insights in what we describe as “the last three feet of retail.” Between payments, geospatial data, digital “sensors” (e.g., beacons, apps, RFID/Bluetooth and WiFi), the opportunities exceed the willingness of most retailers to innovate.
Retailers that fail to innovate are increasingly vulnerable to Amazon, as well as other innovative merchants (PIRCH comes to mind as an example). More than vulnerable, they are going to be “retail road kill” as Amazon and others focus on customers, data and relevance, relegating others to fight for scraps and ultimately, liquidation values.
The more time and money you spend on gathering in-store data, the less time you spend on the training and education of associates on the floor. I think it’s a mistake. “Observational techniques” are mentioned in the story, which is great, as long as associates are doing the observing and absorbing. And if you’re talking about data that tells you what you’re selling and that isn’t already a huge “duh” for you; lotsa luck, period.
If you’re a big box or a mid market grocer with huge stores and with the same product that AMZ carries, you’ve got bigger problems than in-store data. In any case, I still believe that the answer to the “how do we beat Amazon” question lies in the associates.
Retail is so simple in so many ways — having great product, brilliant associates, best-in-class real estate, wonderful stores … it always makes me chuckle when we try to over-measure what will be obvious if you’ve focused on those fundamentals.
It’s tough to execute on insights, especially in bricks and mortar and across a chain, so I’d suggest wiring-up a few stores immediately — the popular design thinking expression: fail fast and early comes to mind. It might make sense to get in now before you lock things down for the holiday to help inform/update your 2017 IT budgets. (I suppose there’s still time.)
I’m not really following things here and as always it’s retail-segment specific, but here’s some ideas that came to mind regarding outcomes that might come from this technology. I did it as a personal exercise so it’s probably stating the obvious.
One more thing. Starting a test early will also help identify issues on the people and business process side when you move to a more data driven decision making process.
Oh, okay, last thing, I’ve been hearing about advances in video technology – I’ll call it Intelligent Video Analytics version 2.0 – techniques that include the use of deep learning. It’s interesting stuff and might be worth tracking.
What to do with the insights?
Using shopper data to improve category management decisions is just the tip of the iceberg. Retailers need to move beyond just tracking shopper movement and if they ultimately make a purchase, to proactively enhancing and influencing the shopping experience.
With the right customer identification services technology that is integrated with the retailers’ customer data and product data, retailers can offer guided selling based on customer context. We call it “digitizing the black book.”
The key enabler to guided selling and clienteling services is understanding everything about your customers and having access to this information in real-time. With a wealth of data from customers who opt-in, mobile devices and a strong network, retailers have the ability to personalize the shopping experience based on customer context. BRP defines customer context as “the interrelated factors of customer insights and environmental conditions that make the shopping experience relevant.” The advent of real-time retail allows us to coordinate what’s in someone’s closet, home, garage, locker, pantry, refrigerator, etc. with what they may have browsed online and create a dialog across all channels that creates an intimacy that has the potential to change retail forever. Until real-time retail is implemented, retailers need to at least enforce Planograms that are matched to product movement data and customer counting info to enhance the category management efforts.
Most shoppers have less of an issue having their web navigation tracked, but much more when they are tracked in real life. Part of the challenge I think is that you can very clearly articulate how tracking user navigation helps drive better customer experience since you can dynamically change web pages or pop up offers, it is less clear to consumers (and frankly to merchants) what you can do to execute changes to improve the customer experience. All the benefits described by Mark benefit the retailer if they can act on it, which is harder in brick and mortar than on the web.
Actually I don’t see retailers using shopper data to the degree of e-commerce. Websites were created with data streams as part of their DNA. It took some time to recognize how to optimize handling visitor information and transactional journeys to develop strategic insights on an ongoing basis.
For brick and mortar, the vision I get is turning that big ship around. Extracting observations, recommendations and history from the previous comments in this post suggests there is no cohesive perspective on what insights brick and mortar stores need. Consequently, attempts at using in-store shopper data are unlikely to deliver what management needs…because management doesn’t know what it needs.
I think we’re accustomed to accessing data without really knowing how to use it. Therefore, as someone wrote today, there are these mountains of numbers no one can manage to streamline into valuable insights. Furthermore, management wants “dashboards,” a simplification of the data, from which reports can be written and possible recommendations made. But it’s about reading between the lines and numbers, i.e., taking an expansive view of the data that typically leads to “aha” moments.
Management has to believe it needs fresh strategies and the appropriate information to guide them. Otherwise, there won’t be any serious and effective effort to harness in-store shopper data.
As brick & mortar retailers understand more about the value that their e-commerce sites provide in terms of consumer data, they will look to mirror the data collected. Additionally, as technology advances, they will find it easier and more efficient to obtain the details that will lead to better understanding.
Better in-store insights will lead to a change in category management practices across the board. It’s an evolution that brands need to understand and address.
The simple answer is no. In-store cannot advance as fast as online unless the infrastructure is in place to do so. However, in order to do this properly right now requires a large amount of expense. In order to pull this off efficiently, the systems between consumers and retailers need to be more frictionless. In this case, customers would simply be buying from the store, using it as a giant warehouse, with the store navigating customers as if they were pickers in a warehouse, to their desired product. All the while the store recognized previous purchase history and browser cookies gathered about this customer to show relevant and timely in-store offers as they are navigating to their desired purchase. This all begins, however, along the online journey of the customer when they are in the pre-purchase decision-making mode. In this case, data is only used by algorithms to sort and deliver more relevant/timely offers for customers so they buy more at the point of purchase, as well as in the future.
Combining store traffic, path and dwell times with loyalty transaction data, as Mark suggests, also creates an accurate and quick reading test marketing laboratory. Make a marketing, merchandising or operational change in selected test stores, then compare results in those metrics with (ideally matched) control stores to see quantified results of the test’s efficacy. Useful for retailers and their vendors.
This has been a serious issue with brick and mortar retailers for years. They have a plethora of data available to them, yet they fail to use it. I don’t see this changing any time soon. Until retailers fix their biggest issues of great customer service, as well as out of stocks on inventory, they need to first fix their operations issues before worrying about maximizing their usage of data.