It’s easy to lose sight of people in a CRM discussion by focusing instead on the great technology and what it lets us do under optimum circumstances. But we should always keep the customer in mind for without them what are we? Forgetting the customer is dangerous for both customers and vendors in this social age. Far from being a universal good, automation can make it hard to reach a human being when only a human can help to make sense of reality. It’s dangerous for vendors too because when that happens you get unhappy customers who have the ability to exact revenge in the most public forums.
United Breaks Guitars (UBG), the song, the book, and the YouTube series, provides a graphic example of how things can go bad and how some organizations are culturally misaligned with the era of customers. For the uninitiated, UBG chronicles a months long saga of one customer trying to get the airline to repair a guitar badly damaged in transit by baggage handlers—all to little avail. The customer, Dave Carroll shredded United’s reputation by writing songs about the incident, which were recorded on the way to going viral on YouTube. UBG might be the poster child for what not to do and how important it is to adapt to the customer era but it is not the only example.
I recently became aware of another incident involving an airline in which CRM, the attitude and approach to business, if not the technology, were completely lacking. The Villaluz family of three, Americans of Filipino extraction, wanted to fly from Boston to Dallas on American Airlines in July and through a series of missteps instead ended up broke, baggage-less, and blacklisted in New York’s LaGuardia airport.
The original flight from Boston, American 2607, was delayed and ultimately canceled after about six hours. Passengers were given the option of taking AA 2172 Boston to LaGuardia for a connection to Dallas AA 1144 leaving at 7:59 PM. They were also given food vouchers by the airline.
This family is not wealthy though sources tell me they are salt of the earth types, always volunteering and giving to their church and to the community. Their trip was part vacation and part work. The father, Ken Villaluz is a pastor and was scheduled to perform two house blessings in Dallas and the remainder of the trip was scheduled as a family visit. The wife Ruby is a nurse and the 12 year-old daughter does not like flying, she’s actually phobic, and one parent needed to be seated with the daughter.
In New York, the family needed a little assistance from the ground crew to help ensure that their daughter was accommodated because while they all had boarding passes, no two seats were together thanks to the original cancellation. This is something that’s often taken care of onboard by a flight attendant asking other passengers if they’d mind switching seats. The Boston ground crew assured the family that their need would be taken care of by the New York crew but that didn’t happen though the family was allowed to board early.
What happened next is the stuff the make movies about. Since the family was onboard early and very polite, they didn’t simply take seats expecting to deal with the ramifications as the plane filled. Instead they asked for assistance from the crew. The flight attendant instead told the family to ground check their bags (including a live lobster) and stand out of the way. They were confused because they’d arrived from Boston on a smaller plane with their bags in the overhead bins. It makes no sense that they were boarding early and were already being told to check their bags but a lot doesn’t make sense at this point.
The father, the pastor, asked to speak with a manager and one Brady S. approached. But rather than helping, Brady S. only wanted to get their bags checked. When the minister complained about Brady S.’s demeanor, he escorted the family off the plane and told them to wait and that he’d deal with them once the plane had gone. The daughter began to sob, the father already humiliated, sobbed too. The plane left without the family but with its gate-checked luggage including the lobster.
The father tracked down a policeman to be present as a witness when he had his next encounter with Brady S. but after the facts were laid out, the cop excused himself from the conversation saying that it was not his jurisdiction and nothing criminal had happened. Nothing.
The family then sought to rebook on American yet again hoping to exchange the value of their original tickets. Unfortunately, though they found another American flight, the agent told them they could not access it. Brady S. had blacklisted them making it impossible to fly American. Now the value of their tickets was inaccessible.
So family was now stranded, it was about 8 PM and all of their luggage was on a flight to Dallas. They didn’t have much money and had to call family in Dallas to help them rebook on United for the next morning. Meanwhile the 12 year-old was melting down and the family had to get a hotel in New Jersey near the Newark airport which required an expensive cab ride from LaGuardia. United flight 1993 left Newark at 6:30 AM bound for Houston meaning that the broke, bag-less, and blacklisted family would get all of 2 hours sleep that night. The next day, the family got to Houston and eventually Dallas though the father missed his house blessings. Naturally, the family is trying to get its money back and unsurprisingly, American Airlines is doing its best imitation of see no evil, hear no evil, speak no evil.
Why did this happen?
There’s some evidence that American is doing what it can to speed up its boarding and aircraft turnarounds to help ensure it gets the most productivity from every flight. A story originating on Bloomberg describes the speedup as an effort to improve on-time performance. But The Allied Pilots Association (APA) warned about the changes. According to the Bloomberg article, “The airline is directing that some flight plans increase air speeds to near plane limits and on routes expected to hit turbulence, as a means of making sure that crews comply with FAA guidelines on hours worked and avoiding the delays associated with assigning fresh personnel, the union said.”
The article goes on to quote a letter from union President Dan Carey that, “’APA pilots are now reporting that management is manipulating flight plans in order to keep an operation under duress from coming apart at the seams,’” the letter said. “’These last-minute manipulations are used to make a flight appear legal when in reality it’s not or is, at best, on the ragged edge.’”
You can only wonder if the speedup prevented this family from getting the attention their simple request deserved. If all this is true, it suggests an almost total failure of what CRM should be about—customers and our relationships with them. Moreover, this story suggests just how decrepit the airline business model is at least for some. This was not a technology failure, it was caused by a lack of empathy up and down American’s structure from senior management who wanted faster turnarounds and greater profitability per flight, to customer service people whose jobs have been corrupted to serve profits almost to the exclusion of customer service.
An airline focusing on on-time arrivals and departures might be able to say that it has its customers’ best interests in mind but that single focus, without attending to all of the other moments of truth involved in making air travel successful is ultimately self-defeating.
I recently read a user story about how Harlequin—the publisher of romance novels—keeps its customers loyal. I don’t usually give a plug to a company like this but for what it’s worth, Stellar Loyalty provides technology to make loyalty happen. What’s interesting to me is how many of the ideas in my current book (“You Can’t Buy Customer Loyalty…” (I know another plug)) get put to good use by this publisher. The things that I think work really well include emphasizing a consciousness of customer loyalty, keeping things simple, and focusing on personalizing relationships and engagement.
Consciousness is relatively easy, but someone high in the org chart has to be willing to say, “This is important.” Other things might be important to this publisher too, like finding good writers and editors, but that’s in a separate realm. In the customer realm being conscious of working to maintain relationships is about as important as it gets because it becomes the animating principle for everything else.
I had always assumed a consciousness of maintaining customer loyalty and that works for me because it’s already my primary focus, but for lots of people in organizations that’s not true. People have jobs with concrete deliverables and expectations and unfortunately there aren’t typically metrics for individual customer loyalty promotion. It’s something the organization has to do together and as individuals so starting with consciousness is really a pretty smart idea because it leaves less to chance.
Simplicity is another big idea that comes from other research. Customers—you and I—have a lot on our plates and don’t always want or need a vendor’s extravagant display of affection to make us know we’re loved. What we crave is time and that boils down to simple processes and systems that we can get through on the march through the daily bucket list. In Harlequin’s case simplicity means having a mobile app that enables customers to scan receipts to notify the loyalty program of a purchase so that rewards points can be automatically tallied. Giving points for this activity is important to the publisher because it gives them insight into who is buying what and where and if you’re selling books, that’s pretty important. This also provides the data that enables personalization at a meaningful level.
More importantly though, Harlequin places equal emphasis on the ways customers reach out to them. You can’t ask for a better sign of customer loyalty than when a customer engages online such as by writing reviews or engaging on the company’s Facebook page or by answering a survey. This is the engagement that any company would want because more than a business’s outreach to customers (which can be ignored) this identifies things that customers reach out for.
Finally, Harlequin analyzes all of the customer data that it collects which helps it to both identify customer moments of truth and how well it is performing in them. That’s how you build constant improvement into a loyalty program—knowing what customers care about and then ensuring that’s where your people and automation focus.
Consider some of the metrics that the publisher shared in the use story,
- Percent of customers that engage with the loyalty program monthly and the direction of the trend.
- Percent of customers who redeem rewards and percent who have redeemed multiple times.
- Percent of members providing feedback and percentage that’s positive (much more useful than a Net Promoter Score).
- Time in the loyalty program and propensity to repurchase.
This isn’t hard to do and almost any company could benefit from a program like this with a few well-chosen metrics like these. My studies show that companies are increasingly moving in this direction and away from simply awarding points based on purchase transactions. The simple reason for the movement is that it takes much more than points to keep customers in the fold and more than simple transactions to diagnose vendor health.
That’s why loyalty programs are taking on greater prominence but not just any loyalty programs. Modern loyalty is based on customer engagement and understanding moments of truth so that vendors can be there when customers need them. If you’re wondering about your loyalty program, this is an approach to get you thinking different.
Salesforce isn’t even waiting for Dreamforce to begin the drumbeat over its AI offering which is or will be called Einstein. There is so much to discuss over this turn of events that it’s hard to begin so rather than starting at a conventional jumping off point let’s think for a moment about the name.
You couldn’t have lived at any point in the 20th century and not have some idea of who Albert Einstein was. For most of that time he was regarded as special, a savant, one who could see things that no one else could. But I prefer to think of him as one of the first to build models of reality that he could test his ideas against. History is full of these people most of whom did a one off. But Einstein systematized the approach—he had to because he was a theoretical physicist.
Einstein may have invented the word “thought-experiment” because his work centered on the very small and the very large, things that happened in nanoseconds and things that have taken up the 13 or so billion years of the universe’s life and the billions more to come. Things you couldn’t easily see or handle.
In theoretical physics you don’t set up an experiment in a lab. You look for evidence in nature that you or others discover because your alternative is to build an impossibly expensive collider to smash nuclei together to simulate the Big Bang. You also do a lot of thinking because your imagination is the best modeling tool.
Perhaps Einstein’s greatest modeling effort was to imagine what reality would be like to ride a beam of light. That simple idea led to understanding that the speed of light is the ultimate speed limit in the universe and that if nothing can go faster then all communication is ultimately limited by the speed of light. This includes time or the perception of time. Traveling at or very close to the speed of light causes time to slow down. Einstein did all of this with a few equations and his mind. He was quite a modeler.
In this context I think Einstein makes perfect sense for an AI product name because it enables a business to model the salient points of its reality in dealing with customers and helps us all to make logical deductions that we might have missed with prior brute force methods. Salesforce’s Einstein brings together several types of AI/BI/machine learning/deep learning/machine intelligence and whatever from prior acquisitions including RelateIQ, Implisit, PredictionIO, Tempo, and others.
Here is why I think this is significant. AI of this caliber significantly signals the end of transaction oriented business and conventional CRM that supported it. The better the model of your business the more you can see into the processes you are involved in and importantly the less you’ll focus on any transaction because transactions will be a foregone conclusion. You’ll focus on the process that leads to a transaction, which will help to assure a transaction takes place.
As a practical matter this doesn’t mean you’ll suddenly have superstar sales people who nail every deal. But having good AI might tell you when you’re wasting your time, when a deal isn’t going to be yours. Knowing this you’ll redeploy resources with the confidence that you’ve made the right decision.
Don’t worry this isn’t only about selling, it’s equally important for every aspect of your business. AI in service can tell you not only the next best action or offer, but it can also tell you the customer’s likelihood of being satisfied with the engagement and therefore what else you need to do. AI in marketing has many opportunities but let’s look at one that seems to always get neglected, the installed customer base.
Too many businesses assume that customers will come back for more and many do, but others keep looking for better opportunities. Worse, too often businesses that do big deals with multiple tranches of purchases spelled out in agreements forget where they are in the life-cycle and leave money on the table. There’s no easier way to make your numbers than to sell to existing customers but for some reason, we neglect the low-hanging fruit. AI could be an effective agent for changing that situation.
I don’t know all of Salesforce’s plans for Einstein, although they are a client and they brief me from time to time, it’s a big kimono. But with this early signal, I expect that Dreamforce 16 will have a distinctly AI flavor. That’s not very surprising and the company has been signaling in that direction for a while without making announcements like this. What will be surprising will likely be the many different applications of AI they’ll find and the timeline for releasing it all.
There’s lots of talk pro and con these days about bots, AI, and intelligent assistants. A lot of this talk is not necessarily new; it’s been percolating around the industry for decades. Vinnie Mirchandani, a friend and truly gifted analyst, wrote a book recently, Silicon Collar that accepts that this automation might be eliminating jobs but optimistically holds out for the silver lining. Mirchandani firmly believes and documents how businesses and individuals are taking advantage of an opportunity to build new human mediated processes (and jobs) that leverage intelligent systems.
Another friend, Esteban Kolsky who is also a gifted analyst, says not so fast. Like many of us Kolsky has seen this movie before. He points out that adoption has been painfully slow—so slow in fact that AI fails what I call the Gates Test. You might recall that Bill Gates once said that we over-estimate what we can do in two years and underestimate what we can do in ten. Indeed, the gestation period for an overnight success seems to be ten years these days.
But as Kolsky points out in a recent post, “The latest survey, to be shared at Dreamforce 2016 and published soon thereafter, says that from the single digits in adoption they enjoyed for the entire 2002-2012 decade we are seeing adoption nearing 15% now for automated bots and intelligent assistants.” Slow indeed. What’s been holding things back has been a lack of two things: 1) not enough computing power and 2) a clear need.
We can all think up scenarios where a little help from something with AI embedded might be good but on closer inspection we realize there are other ways to get the job done. AI is a heavy lift, or at least it was once. Back when the working models of AI were set down, computing power was not up to the job but really fast processors, multiple cores, flash memory, and the cloud have made it possible to concentrate the power needed to drive AI. But this still leaves us with finding a clear need.
I offer the following analogy: we live in a spreadsheet-dominated world with a linear mindset but we are moving to a world where the lines are anything but straight. To make sense of curved lines you need calculus. It’s calculus, especially the integral variety that tells us what’s going on in a process that has plenty of funky ups and downs. In the spreadsheet era, which I firmly believe is ending or at least transitioning, we searched for averages and made straight-line derivatives from them.
This led to some dumb ideas like calculating what an average deal is and trying to fit all deals into it as if it were a straight-jacket. It also harkens back to the statistical awakening in the 19th century when the term “average man” first came into use. The average man is a fiction but a highly usable one that gives us a basis for modeling.
But when you go for an average you have to ignore some profitable outliers or other things that don’t fit your model. In the age of business by transaction, the straight-line model was good enough. Nonetheless over most of this century so far, we’ve seen that model become less effective as the vendor-customer relationship moved toward the micro-transactions of subscriptions. A straight-line model doesn’t work very well in subscriptions because at a micro level all transactions look the same. It’s only when you expand your view that you can see the micro-transactions that show trends that might be good or bad. As a result we’ve been left without a model.
A model for the vendor-customer relationship that works involves calculus, at least at the metaphorical level. Calculus gives us the flexibility to model many variables involving customer demographics, purchase history, life-cycle stage, and of course the transaction before us.
I think many people in business have a working appreciation of all this, though they are certainly still in the minority and this is where AI comes in because I see its algorithms as calculus in a box. AI gives the average businessperson who has no interest in calculus, or who might have studied it decades ago, the ability to apply more sophisticated modeling to increasingly complex business.
So this is a long-winded attempt to say that at last we have a clear need for AI as well as the horsepower to run it. The need is all around us and if you’ve ever caught yourself wondering at how sophisticated business and our supporting systems have become, you’ll likely be grateful that there’s a new weapon in the arms race.