IT managers haven’t always been the best listeners. Here are some strategies to consider, taken from the best and worst customer interaction stories heard at a recent Teradata end user conference.
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.
When it comes to convincing your boss of the value of a data dashboard, nothing works better than when you can save money 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.
This and more stories about data dashboards from the Tableau conference earlier this month in Seattle can be found in my article on ITWorld here.
I went to a computer conference to learn about how sexist rap lyrics are. What makes this all the more remarkable is that the session was given by a woman, Julie Lavoie here in St. Louis at the annual Strangeloop programming conference.
Actually, it kinda makes sense: the idea is to parse the entire corpus of lyrics (there is a site called rapgenius that has compiled this information for hundreds of songs) and do some natural language processing to see what is being said. It was very entertaining, even though I know almost nothing about rap music. (That is Jay Z above, BTW.)
As you can probably guess, the most common words mentioned in rap songs are cuss words, and other epithets that I hesitate to use here and run up my spam scores. But Lavoie started with an interesting hypothesis: what if she searched for a particular word that rhymes with witch and is used as a common term for women. Do the rappers who have a sexist rep use it more often in their songs? How about men vs. women rappers? What about rappers from different geographies or styles of music? (Yes, that was something I never knew.)
Well, she found out that things weren’t so simple: lots of rappers use this particular epithet, and many have far worse things to say about women that are hard for a Python script to process automatically. Do you look for the association of particular action verbs with particular nouns? The mind boggles.
Lavoie at one point had to temporarily stop her analysis, because it was getting her depressed seeing the negative words that were bubbling up to the top of most often used list. But she is a trooper (and also a big fan of rap music, which is why she started the project to begin with). The project got her thinking more about how to characterize sexist lyrics and gave her fuel for further explorations. Granted, she could have chosen French literature or modern poetry, but she likes rap so that is where she focused her efforts.
This is just the sort of thing that you can find at Strangeloop: interesting tech stuff, presented by people that you probably never heard of mixed with the leading lights of major programming languages and open source projects. If the show isn’t on your fall calendar, it should be. Plus, you can come visit me in St. Louis too!
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.
At 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.
Based on a white paper that I wrote earlier in the year for them, I am holding a webinar next week with the above focus. In this webinar David S. Linthicum SVP, Cloud Technology Partners and Brandon Elliott the Chief Technologist for Rackspace and I will examine the infrastructure needs of customer-facing applications by examining the challenges faced by businesses in the most demanding industries. It will provide a framework for evaluating technology decisions from the perspective of customer experience quality and suggest metrics that can help businesses justify and benchmark the success of their investments.
As more companies hire data scientists, there is a corresponding trend to hire a new kind of employee that some refer to as “data artists,” whose job it is to tell the stories behind the data in the most accessible and revealing ways. And these folks are taking major roles on product management teams, such as Jer Thorp pictured here. In this story for ITWorld today, I talk about what is a data artist and how Microsoft and Google and the New York Times are making good use of them.
The PC server market has been a fairly boring one for the past several decades. Sure, they contained things like specialized Xeon CPUs and lots of memory modules and could attach to big storage arrays. But the for most part, buying a server meant having just something bigger than you had on your desktop. Those days are about to change with the new servers available from Rackspace and the Open Compute Project.
To show you that this is far from a new idea, do you remember the Tricord? I am not talking about the thing carried around on Star Trek. Instead, this was a server unit made in the middle 1990s. It came with eight CPUs, could hold 3 GB of RAM and nine half-height drives, along with lots of redundant power supplies, controller boards and other high-end features. All this went for $70,000. That’s right, they weren’t cheap either.
Nowadays the notion of a 3 GB PC is what you would find as a minimum desktop configuration to run Windows, and most servers have hundreds of GB of RAM installed. But again, the design of a PC server hasn’t really seen much change. Until now.
Facebook started the Open Compute project several years ago, in the hopes that they could encourage some innovation for the kinds of hardware that they were building for their own data centers. These customized servers were stripped down models that were designed to run in the cloud, not on your desktop or even in your own data center.
The project saw some major milestones this week with several announcements at the Gigaom structure show. There is an opportunity for anyone to have their own cloud-oriented server, as announced from Rackspace this week at the event.
Why is this important? It represents a big moment for servers, taking steps to finally move beyond the original PC architecture that began in the early 1980s. It is a way for Rackspace to offer an entire server that previously was only available as a compute or storage instance for cloud customers. It is also a way to get around the “bad neighbor” problem that faces many cloud apps, where another greedy server instance can hog server resources and make life miserable for your own app.
The servers are from Quanta and called OnMetal and come in three different version that are focused on CPU, storage or RAM. If you have to build an Internet service that is going to need a lot of firepower, you might want to take a closer look.
I know this past weekend is more associated with barbeque than pizza, but I came across an interesting study of pizza that I thought I would whet your appetite this morning. For those of those you have spent time on the site Reddit, you know one of their communities is called “Random Acts of Pizza” or RAOP. On the site, people can submit requests for free pizza and if their story is compelling enough a fellow user might decide to send them one. Why not? Who doesn’t like a free pizza?
Users can only ask for pizza, and only one user can supply the pizza. For example, a request might go something like this: “It’s been a long time since my mother and I have had proper food. I’ve been struggling to find any kind of work so I can supplement my mom’s social security. A real pizza would certainly lift our spirits.” Anybody can then fulfill the order, which is then marked on the site, often with notes of thanks.
It is an interesting community. Because of the way it is structured, a group of data and social scientists used RAOP as the basis for a study that looked more closely at altruism, or what motivates people to give when they do not receive anything tangible in return. Tim Althoff of Stanford University and others wrote the paper published earlier this year in a research journal.
The researchers were able to download the many thousands of requests and eventually analyzed more than 5000 of them where they could track a response, whether it was successful or not, and other variables that they were able to quantify. From the data, they parsed this information and then built a mathematical model that would be used as a predictor of the success of the individual posts.
They found that it helps to ask for pizza earlier in the month, make your request post longer (see the graph above), include an image documenting your request (a copy of a job termination letter or an empty fridge), and show that your request should state that are willing to give back to the RAOP community. This last item bears some further explanation. Most of us would probably be cynical and say, yeah, sure, these folks are trying to game the system and get a free pizza. But the researchers showed that nearly 10% of those that were claiming to pay it forward actually did, which is a pretty high percentage given that many people probably haven’t had an opportunity to reciprocate.
You can also see from the graph above that those stories about jobs, money, or family situations were also more likely to result in pizza deliveries. One item they didn’t find to improve deliveries was that it wasn’t true how the mood of the author was expressed, something that traditional social science research has found in the past.
What if you could have access to a cheap supercomputer in the cloud, and one that automatically upgrades itself every couple of years? One that taps into existing unused processing power that doesn’t require a new ginormous datacenter to be constructed? This is the idea behind Devin Elliot’s startup called Unoceros.com.
I was skeptical when I first heard him talking about it. This is because he borrows processing time on millions of cellphones at night. Think this through for a moment: these phones are charging, often connected to your home Wifi network, and they are sitting completely idle next to your bed. Why not put them to a good purpose? Think of SETI@Home only instead of searching for intelligent life in space, it is being used for running intelligent apps here on planet Earth.
I mean, the puny cellphone? Can’t we find a better collection of processors? Turns out that while we were sleeping, all that CPU power can add up to quite a few petaflops of processing. If you have a couple million cellphones, you can construct a distributed supercomputer that can rival some of those that are on the top500.org list. Today’s modern phone has the processing equivalent of a medium Amazon Web Services instance. That is far from puny.
I have been fascinated with this topic for some time ever since I participated in a rather unique “flash mob” computing experiment about ten years ago in San Francisco. This was the idea behind a course offered at University of San Francisco and taught by scientist Pat Miller, who works full-time at the Lawrence Livermore Labs. Call it Bring Your Own Laptop. One of the participants was Gordon Bell, who was the father of the VAX while he worked at DEC and now at Microsoft. I was one of hundreds of volunteers and left two laptops of my own for the weekend while the class tried to knit them all together to run the usual benchmarks to prove we had created a supercomputer.
While this flash mob failed at assembling a top supercomputer, they were able to get several hundred machines to work together. But that was ten years ago. Now we have the cloud and efforts like CycleComputing,com to build more powerful distributed processors.
Anyway, back to Unoceros. They have developed some software that can be included inside a regular cellphone app that, with your permission, makes use of your idle time to become a distributed compute engine for those developers that are looking for spare cycles. They are working out the kinks now, figuring out how to distribute the load and make sure that bad actors don’t harness their network for evil purposes.There is also the not-so-small issue about who pays whom and how that aren’t trivial either.
Could it work? Perhaps. It isn’t as crazy as having hundreds of people carrying their gear into a university gym one weekend.