Category Archives: Published work

How 7-Eleven Built Its Digital Guest Engagement Program From Scratch

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Two years ago, the convenience store chain 7-Eleven had no data warehouse, no smartphone app for its customers, and had a loyalty program that still used paper punch cards. Since then it has built the beginnings of a digital customer engagement program. At the recent Teradata Partners conference in Nashville this week, they described how they did it.

All it took was finding the right VAR and spending some significant cash.

Well, not quite. As you can imagine, there was a lot more involved, given that the company has over 10,000 franchisees throughout the US and thousands more overseas. They first set some important goals:

  • Develop actionable insights into what their customers bought, when, and why. “Prior to this program, we had none of this information,” said Robert McClarin, the senior CRM manager for 7-Eleven Inc. and one of the presenters at the conference session where they described what they did. “We knew we had a tremendous gap in our knowledge.”
  • Develop an initial IT infrastructure that could handle several elements of a total customer engagement platform. While they began with a loyalty program, they wanted something that was extensible for years to come, including a rich data warehouse that is constantly being updated from their point-of-sale system in all their retail stores.
  • Dramatically increase incremental purchases and customer visits. They wanted to build a program that would attract five million members during its first year. They also wanted to justify the expense of the program – which was considerable and in the multiple millions of dollars – with the additional in-store revenues generated, when measured with year-over-year same store sales.
  • Establish a personal relationship with each guest that would be natural and seamless. “If you want to be closer to your customers, you have to be on their smartphones,” said McClarin. More than two thirds of their customers carry smartphones currently, according to store surveys. They also wanted to leapfrog some of their competitors who built early smartphone apps.

Then they put together a three-step program and issued requests for proposals to find the right VAR. They humorously called the three steps “crawl, walk and run.” After getting numerous RFPs, they settled on Brierley+Partners. That company was selected in a recent Forrester Wave report as one of the leaders in the loyalty CRM space. The company is also a Teradata VAR and used several modules for the project. Brierley’s office is located near the 7-Eleven headquarters in Dallas and worked closely with the chain’s CRM and IT staffers to build the first data warehouse and develop the initial smartphone app.

Speaking of which, they spent time to make their smartphone app engaging and yet simple to use. Along with digital coupons, the app contains features such as a store locator function and a feedback area where customers can suggest new features. The user interface is clear and clean, which also helps boost usage.

 Their first foray was to come up with a coffee loyalty program that offered everyone a seventh cup free. The program coincides with a celebration marking 50 years where the chain served up the first ever to-go coffee cups. Since they, 7-Eleven has built quite a business out of selling a lot of coffee – more than a millions cups daily worldwide. Prior to the digital program, as I said earlier 7-Eleven stores used a paper punch card to keep track of these purchases. “Our franchisees were asking us to replace this with a digital program, and so they were very much on board with our program,” said McClarin.

So far the program is very successful: more than 3.2 million customers are part of the program, which is close to target for their goal., since 2,500 customers are joining daily. Year-over-year coffee sales are up for the program participants and the stores that they shop at, and they have given away more than 52,000 cups of free coffee since the program began in March 2014. One good outcome: the program has had no impact on the checkout experience. McClarin said that so far they have made it easier for customers to checkout, even though payments are not part of their app – unlike competitor Starbucks who was one of the first to offer this.

They also have seen a shift in sales to higher profit margin items for program members, and members who are shopping more days per week too. The program offers customized coupons for each customer based on their shopping patterns and is localized for each store too, which increases the feeling that the program is personalized just for that customer. For example, “a coupon could offer a discount on coffee in the early morning hours, fresh food around lunch time, and another discount for DVD rentals at the in-store RedBox video kiosk,” said McLarin.

 

Ricoh blog: How Apple Pay Will Change Mobile Payments

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There have been a lot of pretenders to the throne, but mobile payments have yet to take off in the United States for a variety of reasons. Credit cards have been ubiquitous and accepted at every online storefront. Mobile software has been buggy and cumbersome to use. eWallets were numerous and offered conflicting standards. And until the last few years, many people didn’t have smartphones to run the software anyway.

These inhibitors have for the most part vanished: now almost everyone is buying an Apple or Android smartphone. Credit cards are now at risk and breeches have become more numerous, or at least are reported more often, with the latest Home Depot and previous Target exploits as notable examples. Square has revolutionized the ability for any merchant to accept credit cards using their iPad or smartphone.

But more importantly, Apple has entered the game, with its Apple Pay and Passbook software that will be available next year.

The goal is to use better point-of-sale terminals that don’t rely on embedded Windows XP or older, less secure operating systems and credit card swipes. Instead, retailers will upgrade with terminals that don’t require any physical contact with your phone, using a special radio device called near-field communications that works like Bluetooth only at shorter distances. When a customer wants to pay, they send a special sequence of numbers that is unique to that transaction, so the merchant never transmits the actual credit card number through its payment network. Even if a criminal were to eavesdrop on the transmission, the information wouldn’t be of much use to them.

So the first attraction is better security, something that will take a major infrastructure upgrade to the payment networks, to the actual retail stores, and for consumers to upgrade their phones too. All of these aren’t a slam-dunk and will take some time. Outside of the US, most developed countries have upgraded their credit card systems to have special chips in them that can protect them better than the simple magnetic stripe that we use here.

The second attraction is that Apple has tremendous market power, and can unify the numerous wallet software versions behind its standard. You can read up on what is involved in adding Pay to your particular application here. Whether Android users will ever have access to this technology isn’t clear.For now, you must have an iPhone 6 or 6+.

Third, Apple has very cleverly focused on using the touch sensor on its newer phones as the gateway drug into its wallet system. Passbook was very clunky before the touch sensor; perhaps this will give the whole idea a needed boost.

Finally, Apple has signed on the major payment processors up front, eliminating one of the challenges faced by other wallet developers.

Security firm FireEye writes on its blog, “If Apple can implement its near-field communication payment system correctly, it can absolutely increase security, guarding against the disastrous types of credit breaches that have dominated headlines.” There is one weakness still: users must first enter their credit cards via taking a picture using their iPhones or typing in the information. If malware is present on the phone during this process, this information can be copied and abused.

Certainly, criminals are adaptable folks, and can focus their efforts on exploiting the new wallet technologies and point-of-sale readers. As FireEye says, hackers will “redirect their efforts toward the next weakest link in the [payments] chain.” We’ll see if Apple Pay can change the course of mobile payments soon enough.

SearchSecurity: Multifactor authentication in the enterprise

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Older than the Web itself, multifactor authentication is an IT security technology method that requires people to provide multiple forms of identification or information to confirm the legitimacy of their identity for an online transaction or in order to gain access to a corporate application. The goal of multifactor authentication use is to increase the difficulty with which an adversary can exploit the login process to freely roam around personal or corporate networks and compromise computers to steal confidential information, or worse.

This series began in October 2014 and continued over several articles with the last of the series running in January 2015:

And then I have specific reviews of some of the leading MFA tools:

The trials and tribulations of eCommerce: a look back

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I have been a keen observer and sometimes participant of the eCommerce field since its very early days back in the late 1990s. Then the websites were wacky, the software shaky, and the tools touchy and troublesome. But somehow we managed to buy stuff online and Amazon and others have been raking in the dough every since.

In the beginning, IBM had its own NT-based eCommerce product that I reviewed back in 1999 for Windows Sources magazine. These suites of products had a lot of custom configuration, and really weren’t very good. Since that point, IBM has built quite a business around Websphere and other tools. Another article about evaluating payment systems for eCommerce that I wrote for Internet.com back in 1999 described the sad state of affairs back then.

In those early days, I had fun assignments like trying to figure out how long it took staff from an online storefront to respond to my email queries. That seems fairly obvious, and there are still storefronts that don’t respond quickly enough to their potential customers.

But one area where we have come the furthest has been in online payments. A good example is the recent Apple Pay announcements last month. As the NY Times points out, even though nary a dollar has been spent with this new system, vendors are jumping on board Just Because It Is Apple. Even eBay has gotten so worried that they are in the process of spinning off PayPal, something that they have resisted for years. Here is my analysis of Apple Pay published in Ricoh’s blog.

If you are looking for some historical context of how payments have evolved, check out the following pieces that I wrote over the years:

From that last piece, I wrote:

Imagine how hard life with physical wallets would be if they acted like e-wallets. You would have to carry several different kinds of wallets around with you, since each store would accept different payment systems. You couldn’t convert your dollars from one system to another without a great deal of work. And if you lost your wallet, you would be out of luck.

sim2Today we have a lot of payment choices, including a little-known service from MasterCard called Simplify that is a web payment gateway that offers 2% rates (but only through software, no card reader yet.). We’ll see if my predictions will come true or not once again.

Network World: Slow Internet links got you down? Try Dyn’s Internet Intelligence

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dynAs businesses extend their reach to more corners of the world, wouldn’t it be nice if you could monitor any Internet service provider from any location? Thankfully, Dyn, which sells DNS management tools, acquired Renesys earlier this year and extended the features of the Renesys’ Internet Intelligence product.

You can read the full review in Network World here.

Inside the Great Firewall of China

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In the past week as massive demonstrations have taken place in Hong Kong we have also learned about how the Great Firewall of China operates. Thanks to a team lead by Harvard social scientist Gary King, it is an impressive collection of both manual and automated processes. The paper was published earlier this year in Science magazine here.

For those of you that aren’t familiar, China for years has been blocking a great deal of Internet traffic based on all sorts of criteria. Many of the world’s more popular social media sites, such as Facebook and Twitter, are completely unavailable inside the country. Newspapers that are freely read in the rest of the world are also blocked. King’s team conducted the first large-scale study of exactly what was censored and how it was done. They did so by creating thousands of social media accounts and posts and seeing what got blocked and when.

table2And more cleverly, they set up their own websites from within China and then paid to have them censored by the same firms that the government uses. This gave them access to the censor’s tech support lines, so they could engage them in a dialog to understand what was going on and be able to reverse engineer things. “We were even able to get their recommendations on how to conduct censorship on our own site in compliance with government standards,” they wrote.

The study shows exactly how hard it is to censor Internet traffic, especially on the level that is seen in China where a half a billion social media posts are created every day. Automated keyword matching is flawed and requires a great deal of manual intervention. Posts that are critical of the Chinese government are routinely allowed but other posts that involve discussions of collective action (such as the recent Hong Kong demonstrations) are routinely blocked.  Earlier research was less thorough and relied on more anecdotal information, not to mention was riskier since censors weren’t as willing to talk with outsiders about their processes and procedures.

Contrary to what has been written about the Great Firewall, social media site operators actually have a great deal of flexibility in how they function and what they allow online. And while the censors employ a wide variety of automated censorship routines across more than two-thirds of Chinese social media websites, these routines are for the most part ineffective and require thousands of people to monitor and censor the vast collection of content that is posted in China.

censor2The team found that there was little censorship of posts about collective action events which occur outside mainland China, collective action events occurring solely online, social media posts containing critiques of top leaders, and posts about highly sensitive topics (such as Tibet) that do not occur during the actual collective action events themselves. Censors were more focused on the actual events that were taking place themselves and posts that related to organizing these “meetups” and the reactions to them.

A few posts critical of the government were blocked, but not on the level that posts about the actual events were censored. “The censors don’t care about what you say, but about what you do,” said King. You can listen to King being interviewed by Ira Flatow on Science Friday here.

ITWorld: What is the value of a data dashboard?

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When it comes to convincing your boss of the value of a data dashboard, nothing works better than when you can save some dollars as a result of a trend that you visualized. This is what one of the data-driven marketing staff did for the Texas Rangers baseball team; their dashboard saved about $45,000 in annual costs.

 

The Rangers are big fans of data dashboards, and they should be: dashboards can spot trends, communicate a particular position to management, or call out trouble spots while you can still doing something about it. I heard from Sarah Stone, who is the marketing and advertising manager for the team and also a Big Data junkie.

 

Stone gave a talk at the annual Tableau Software user conference held earlier this month near their Seattle headquarters; I also met with her separately to get more information about her situation. She told me that she was new to the team’s front office (as they call the folks who don’t actually get into uniforms) and was looking to support one of her colleagues who were involved in a discussion with one of their long-time contractors. Their contract was up for renewal and thanks to Stone’s help they were able to produce a visualization that was used to shave off $45k from the contract. This was a great example of how data science could be used to benefit other marketing and sales efforts.

 

Tableau Software is big into dashboards and I came across many of them during their conference. One issue is that they can easily overpower management, who may be used to squinting at a series of spreadsheet figures. “The first time you show your boss a visualization can almost be a magical moment, it can really reveal things in your data that weren’t very obvious before,” said a data analyst at a Defense Department contractor I met at the conference. At another session, Vaidy Krishnan, an analyst from General Electric’s Measurement and Control group said, “Dashboards are just a starting point for a discussion. You can’t get everything right out of the gate but using them helps you ask critical questions.”

 

Stone is the person who has to decide on television and other media advertising buys for the baseball team and has to spend wisely: she needs to know which games are selling slowly, or what kind of ticket buyers are likely to come to which games. To do this, she uses Tableau Software’s tools and connects to several public and private data sources to produce her visualizations.

 

For example, she wanted to see whether the Dallas market was saturated with professional sports teams and used census data to compare the raw number of seats for each metropolitan market. Not surprisingly, St. Louis (as shown below) showed lots of rabid sports fans (something that I can attest to, after living there for several years) while Dallas still had room to grow.

 

Another analysis looked at how they could save money on their corporate cell phone bills. She was able to find several staffers who were frequently on scouting trips out of the country, and try to adjust their plan to handle more international minute usage. “We also saw a spike in the bills during August but then figured out that was when the whole team was in Toronto for a series of games, so it made sense.”

 

Her work on tracking ticket sales is an example of how a typical Big Data analysis session goes. Often, you don’t know what questions to ask or how to go about collecting the data that you’ll need for your analysis. At the conference, Neil deGrasse Tyson, the director of the Hayden Planetarium in New York, gave one of the keynotes where said the “really difficult thing was formulating questions that we are currently too stupid to ask now, let alone understand the answers to.” He gave as an example if someone from the 1700s were to try to figure out when the next asteroid would hit the Earth. No one from that era would have even asked such a question.

 

Stone admits that she often will run several queries and create several different data dashboards before she figures out what she is trying to accomplish. This is very typical behavior in the Big Data world. She is in the process of putting together an interactive seating chart of their stadium, showing characteristics of which seats were purchased by season ticket holders, what concession sales happened on particular games, and whether promotions or team performance helps to fill seats.

 

Not surprisingly, all those bobble-head doll giveaways do drive ticket sales. “And a post-season win translates into three seasons of subsequent increased sales,” she told me. Some of the data is downloaded from StubHub, the secondary ticketing retailer that Major League Baseball helped start. She is also working with the local Southern Methodist University business school students as interns to help integrate regression models based on R.

 

“Our sales department knows what they are doing when it comes to selling tickets, but when it comes to looking more globally at this process and how it coincidences with other variables such as team performance or the weather, they need help.”  For example, her analysis can predict attendance so the team can better staff the stadium for more crowded games.

 

Before she started, the marketing department had to make frequent requests for reports from the box office, and these reports didn’t reflect real time sales either. “Producing real-time, holistic visualizations is the holy grail. We’ve always been able to obtain real time data, but it hasn’t been all that accessible and only a few people could gather that information,” she told me. “Our seat inventory is very perishable, and if I can design a discount program or arrange for an ad media buy for the next day’s game, it can have a big impact. Having a stale report doesn’t really help if you are trying to move thousands of tickets. We need to know how sales are trending because once the game is over, we can’t sell those tickets anymore.”

Ironically, when she started with the Rangers last year, Stone knew virtually nothing about baseball—she jokes that she didn’t even know the difference between an out and a hit then. (Now her game knowledge has improved to the point where she accurately scores each game she watches.) She came to the Rangers from another competitive landscape: professional politics, where she used data analytics to help focus media buys and to track what the other candidates were doing. “Really, politics and baseball are very similar,” she told me. “Both marketing groups have no control over the quality of the product you are promoting and you still have to get people to either come out to vote or to go to the game. Data is still data.”

Holding office hours for your end users

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I was at the Tableau Software annual user conference in Seattle this week, and one takeaway was an idea that I heard from one of the presenters about holding “office hours” to support your end users. It is an old idea that may be worth revisiting.

Back when I toiled in the IT end user computing fields for Megalith Insurance, we had several staff for our own phone-based hotline to support the insurance agents around the country. That was great for them, because we couldn’t really make house calls. But we had several thousand users in our three office towers in downtown Los Angeles that were only an elevator ride away. These folks had to call us when they were in need or distress and wait for us to get to their offices. We never really thought about holding office hours where the users could drop in, frankly because we didn’t want them to know where we worked. Maybe there was some other reason, I was never quite sure. It was probably because back then we had mainframe programmers in abundance, and no one ever ventured into their holy of holies offices either.

But that was then. Today we all work in bullpens and people bring their bikes and dogs into work. And there are a lot of end-user oriented tools besides spreadsheets and word processors.

And when it comes to a visualization tool such as Tableau, seeing is literally believing. Having a steady hand and someone who knows their way around the interface can make a big difference in speeding up the learning curve for a newbie.

mod2At the Tableau conference, I spoke to Krystal St. Julien, a data analyst with eCommerce retailer ModCloth.com. She comes from a academic biomedical research background, which is why she calls what she offers “office hours.” Only instead of students waiting outside her office door, she schedules her time with Google Calendar. It is working well for her, not just on an efficiency level but on a user empowerment level too. She helps her users over learning speed bumps and gets an entire team up and running with Tableau in record time. (An interesting side note: all of her data analysis department are mostly women, with the exception of the boss. Some lesson to be learned there, too.)

Maybe it is time we bring back this concept into wider use. Who knows, it could help some IT shops over their image problems.

 

A Better Way to Do Multifactor Authentication with Authentify xFA

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xFA can add multifactor security to any web service with a few lines of code. We tested xFA on a small network in August 2014. It has cloud-based components to manage multifactor security, along with apps for iOS and Android.

Price: $19.95 per user per year

http://info.authentify.com/authentify-xfa-screencast

Fingerprint authenticators for iPhone 5 and Samsung Galaxy are expected for the near future.