Privacy Fears Hit Retailers' Big Data Analytics Plans by Jeff Bertolucci

18/01/2014 09:50

Brick-and-mortar retailers plan to link in-store analytics with shoppers' mobile devices. Shoppers say not so fast.

Top 10 Retail CIO Priorities For 2014
Top 10 Retail CIO Priorities For 2014
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Privacy will "almost certainly" be the leading big data issue this year as consumer advocates focus on controversial spying activities of the US National Security Agency (NSA), according to a new 2014 predictions report from global consulting firm Stratecast | Frost & Sullivan.

If this prediction holds true, it's unclear how it might impact big data efforts in the retail industry, particularly a new class of in-store analytics systems that use WiFi-enabled devices -- typically smartphones -- to gather information on customers' shopping and purchasing habits.

Why kinds of systems? Silicon Valley startup Euclid, for instance, sells analytics software that can uses a shopper's smartphone's WiFi signal to monitor his or her movements inside a store and in front of it.

It's not a stretch to suggest that consumers may react negatively to stealthy monitoring apps, despite the fact that their movements are closely tracked by online retailers as well. As public awareness of in-store analytics grows, a consumer backlash isn't out of the question.

"I talk with people who I didn't think thought about this much, and they say, 'Oh yeah, I turn my WiFi off when I go shopping,'" said Stratecast | Frost & Sullivan analyst Jeff Cotrupe in a phone interview with InformationWeek.

This type of shopper reaction, if common, will create a challenge for retailers, who have a lot to gain from in-store analytics, said Cotrupe, who manages Frost & Sullivan's big data and analytics global program.

"It's a great thing for retailers," said Cotrupe of mobile analytics. "It's one of these really, really essential things they need to be doing in addition to using customer data, crunching numbers, comparing different in-store sales, and scanning QR codes to indicate which flavor of peanut butter you like best."

Privacy-wise, there are at least three levels of mobile analytics in the physical retail space. Some systems require a customer opt-in, others don't.

Location-based analytics firm Digby, for instance, has the least furtive approach.

"Their claim to fame is that they help retailers, the brick-and-mortar folks, compete and survive in the age of Amazon," said Cotrupe. "They do mobile apps and barcodes and integrated mobile marketing campaigns."

Smartphone-toting customers have to download and install the Digby app, which makes the mobile analytics process relatively transparent. Customers get discounts, deals, and other perks for their efforts.

"That's the biggest level of involvement a consumer has with one of these (services)," said Cotrupe. "In order to interact, they have to download the app" and agree to the terms of service.

Nearbuy Systems, which was acquired recently by RetailNext, another in-store analytics provider, requires a little less effort on the consumer's part.

"You have to log into the retailer's WiFi network in order for their system to monitor you," said Cotrupe. "That's a slightly less level of involvement. You didn't have to download an app, and you didn't have to log in."

The opt-in approach sends a clear message to shoppers: "Hey, if you don't want to do this, don't log in," said Cotrupe.

The third -- and most stealthy -- level of WiFi analytics is Euclid's approach.

"You don't have to log in or take any proactive step," said Cotrupe. "If your (mobile) device has the WiFi turned on, and if that device comes within range of their system, they're able to monitor you."

This is the sort of big data operation that raises the hackles of privacy advocates, and understandably so. To ease critics' fears, Euclid and retailers plan to make their intentions clear, Cotrupe said.

"What Euclid does is make people very aware," he added. Retailers put signs in the windows to inform customers, who can scan a barcode to avoid being monitored by the WiFi analytics software.

While Cotrupe believes in-store analytics can help brick-and-mortar retailers, particularly smaller vendors, compete with online giants like Amazon, he's sympathetic to consumers' privacy concerns.

"I do appreciate the need for privacy," he said. "People have the right to turn that WiFi and location stuff off, and that's great."

Jeff Bertolucci is a technology journalist in Los Angeles who writes mostly for Kiplinger's Personal Finance, the Saturday Evening Post, and InformationWeek.

Mobile, cloud, and BYOD blur the lines between work and home, forcing IT to envision a new identity and access management strategy. Also in the The Future Of Identity issue of InformationWeek: Threats to smart grids are far worse than generally believed, but tools and resources are available to protect them. (Free registration required.)


Which Information Do Consumers Most Closely Guard?

By Ilana Westerman and Gabriela Aschenberger

January 29, 2014

We know that consumers don’t always understand how companies collect their data, and that these misconceptions can create a trust gap between retailers and shoppers.

This doesn’t mean that consumers are completely unwilling to share their data with retailers, though. Our team at Create with Context surveyed 800 consumers in the U.S., asking them which information they’d be willing to give up in exchange for 50 percent off of three different items: a gallon of milk, a large-screen television and a new car.

The survey results—which reflect consumer attitudes, rather than actual behavior—show that 97 percent of respondents said they’d be willing to give up at least one piece of data about themselves in exchange for a discount.


But shoppers don’t guard all their information with equal vigilance.

Our research shows that consumers place a significantly higher value on some pieces of personal data than they do on others. Respondents were most likely to share their names with retailers, and least likely to share photos and files stored on their phones—with items like their current location, their credit scores and their fingerprints falling at different points along the spectrum.

When we analyzed the numbers more closely, we discovered that the survey responses sorted into five distinct “clusters” —groups of survey questions that asked about similar types of personal information, each of which a similar number of consumers were willing to share.

Directory Information

The information that consumers were most willing to share in exchange for a discount were—in order—name, phone number, age and address. Consumers were also relatively comfortable sharing their current location, which we included in this cluster. It’s interesting to note that much of this data is traditionally considered personally identifiable information (PII) —and is, therefore, the subject of privacy laws—and yet consumers are least protective of these bits of information. It’s possible that consumers consider this information less sensitive because much of it is readily available in online phone directories, and because they are accustomed to providing this information when signing up for programs like store loyalty cards.

Interests (Offline)  

After basic directory information, the next data points consumers were most comfortable sharing concerned their interests.  We’ve divided the category of “Interests” into offline and online, because respondents were twice as willing to provide their offline interests as they were their online interests. That difference in attitude may signal an inherent apprehension surrounding digital data, since in reality consumers’ online and offline interests are likely to be similar to each other. The survey items that fell into the offline interests cluster included one about what books and magazines consumers read, and a more general item about “what your interests are.”

Interests (Online)  

This cluster is composed of questions about what consumers buy, what they search for online and which apps they use on their phones and when. Again, it’s interesting to note that consumers were only half as likely to share this information as they were their offline interests.

Sensitive/Financial Information  

Consumers were understandably apprehensive about sharing data in this cluster, which includes items like their incomes, their credit scores, their passport photos and their fingerprints. In every cluster, consumers were more willing to share information for a discount on the big-ticket items like a large-screen television and a new car than they were for a couple of dollars off a gallon of milk. But the increase in consumers willing to share information for the new-car discount was especially large in this cluster, perhaps because people are accustomed to giving access to their incomes and credit scores when financing a vehicle. This may suggest that consumers are more comfortable giving their information in scenarios where they’ve done so in the past, or when they see a clear rationale for doing so.

Personal Digital Data

This is the cluster of data that consumers guarded most closely, and it includes info such as where they’ve been, their phone’s address book, e-mail messages they’ve sent and received, pictures and files stored on their phones and their social networking connections. Consumers were five times less likely to share this type of information than they were basic directory information like their names and addresses.


In our next post, we’ll look at just how closely consumers guard their personal digital data.

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