Salesforce’s Desk.com Gets Smarter
It was gratifying for me to see the Salesforce announcement about the latest iteration of its SMB service desk product, Desk.com because it is so in-line with my thinking as well as my book, Solve for the Customer (I know, it’s a shameless plug). While I happily acknowledge that I advise the company from time to time, there is no causal relationship between the book and product, but sometimes, correlation is just fine. This is one of those times when correlation yields validation in both directions.
Of course there’s a press release and you can find it at Salesforce.com because it is not my intention to regurgitate it here. I prefer to focus on one new function that draws my interest and shows the parallels I mentioned, Desk.com Customer Health Monitor. Billed as a category-first among service providers, the monitor does what I’ve been advocating with minor exceptions. It tracks metrics about customers that a vendor thinks are important and reports on them thus providing alerts that help to prevent churn or attrition.
FYI, Zuora, another company I advise recently bought FrontLeaf to do much the same from a different angle. This idea is gaining traction.
This approach amounts to managing by exception. A small company can’t afford the labor or even subscribe to the systems involved in constant customer outreach and this tactic focuses on what evidence shows are customers that need an intervention, perhaps by a customer success manager. All good.
Now for some nits that need to be worked out—not in the product but methodologically. The big, and for many, hidden issue is knowing what you don’t know i.e. how does a business know what things to measure? An obvious example in the press release is what happens when a customer calls support twice in a month. Is this a sign of trouble or frustration and possibly a churn signal? It could be and the point of an alert is to call for further investigation, which leads to interrogating other metrics to triangulate the situation.
For example, new customers getting up to speed will likely call in more than established customers so it’s best to correlate frequency with other factors like seniority and possibly also products in use—did the customer just install the latest upgrade?
There are many iterations of all this and the simple point is that any company will first want to identify all of the situations that need monitoring and develop accurate metrics for them. I call the situations Moments of Truth, things that both vendor and customer care about and that must be addressed, moments of truth. So we must know our moments of truth before the rest of this makes sense.
We can safely assume we know some of our Moments of Truth but that’s no longer enough. We need to know all of them or we’ll be missing things we can help with and that’s bad because successfully negotiated Moments of Truth lead to bonding which leads to customer advocacy. We really can’t have too much bonding so we need processes that find all of the Moments of Truth and instruments them via tools like the health monitor.
Discovering Moments of Truth is likely a task for a future product release and probably other products like community and analytics. Using our brains to find the low hanging fruit will do just fine for now but suffice it to say there’s more to be done.
Importance of a System
I was having dinner the other night with friends, telling them about some of the ideas in my book, Solve for the Customer. My friend, we can call him Brian though it’s a pseudonym, was interested in my emphasis on process and my belief that Customer Science has evolved from a general emphasis on process in business, especially in the back office.
Brian’s company does a lot to ensure that its customers are happy and loyal because their business involves long term relationships and agreements that renew for many years at a time. These relationships can last decades and nurturing them can be part of the work of a career. I know this because we’re both in our 50’s and Brian has had the same customers for a very long time.
That’s the kind of relationship that is worthy of the name. Account managers can come and go but Brian, who manages a region with many account managers, still knows many of the customers by name. So I was interested to understand how his company approaches the issues of bonding and retention, satisfaction and loyalty. Not surprisingly, his company’s approach to customers uses direct person-to-person contact and it has built up over time. So it is still a very manual process and while that’s not a bad thing, it can be expensive. Account managers call on their customers frequently and always have a punch list of issues, usually but not exclusively, maintenance issues, to deal with. It’s a high touch business.
In addition to the frequent communications, which happen mostly between maintenance people on one side and operations people on the other, my friend’s company conducts an annual survey of customer executives to gauge account health and they place extra emphasis on customer retention issues, especially when a five-year contract is up for renewal.
I was impressed. Despite only having an annual survey, the personnel involved gathered customer data all the time providing a more real time pulse. Here was a company with its head in the right place and a mere two percent annual attrition rate to prove it. That’s right two, 2, TWO percent. Many people reading this right now would go to extremes to have that kind of number. People in the subscription market tell me that a 90 percent retention rate or better is quite good and many are happy to reach that threshold though few see the likes of 2 percent attrition. So in addition to being impressed, I was also skeptical that very many companies could have similar results in today’s business world if they relied on their existing customer facing processes and systems.
Having full time people managing accounts like this is not cheap and many industries won’t support that overhead nor will their customers accept five or ten year agreements that renew. So if we want similar results in many other businesses, we need to find ways to automate parts of the relationship to both speed up some processes and to reduce costs. At the same time though, we need to be mindful that at some point we might need to insert an expensive employee into the mix to assure a good outcome.
Applying resources is where I believe we fall down too often when dealing with customers. We’ve put a little too much faith in our legacy technologies that were made for simple lookup and retrieval but not necessarily for solving customer issues. For example, in SftC I have this example from an automated system:
“We are sold out of: 32 ct. Tums Ultra Chewy, cherry antacids (245-05-0141). Please substitute: 10-ct. Trojan bare skin condoms (245-03-0387).”
Clearly the automated system is out of its depth but so is the business’ expectation that automation can take care of all customer issues. But ironically, automation can do something even better.
Part of my enthusiasm for Customer Science is my belief that it can solve many customer issues in sales, marketing, and service, if we apply and use analytics and journey mapping to the customer’s journey. There’s nothing wrong with having a customer facing system suggest an alternative for a customer wanting to buy an out of stock item. It’s a good use of analytics and journey mapping unless it all goes wrong as in the example above.
Also, and this is key, no automated process should have as one of its assumptions that the automation is infallible. So Customer Science also suggests that analytics and journey mapping ought to be used to promote self-monitoring. Is this the right substitution? What recourse does the customer have if this is not the right substitution? Is the customer happy with this? How do we know?
If we take approaches to our customer facing processes that include modeling all of the possibilities that we need to provide for, a.k.a. moments of truth, and capturing and analyzing customer feedback, we can approach things like customer bonding which leads to advocacy and loyalty, with the expectation that our automated processes can yield the same kinds of retention rates as a more labor intensive one.
Last point, we spend a lot of thought cycles on personalizing a relationship, at least the part when the vendor and customer are in a moment of truth but I am skeptical that this is the right approach. Personal is nice, but in a business or commercial relationship what’s needed is authenticity not personalization. The business system that suggested condoms instead of antacids won’t get extra points if it addresses the customer by name. But if it suggested a store band of antacid as a legitimate substitute it likely would have preserved the transaction and at the end of the day the authenticity that can drive a transaction is what matters to both the customer and the business.
Kaizen
CRM makes several promises to its users including selling more or faster, resolving service issues faster or at least quickly, and generating more leads. But if you do root cause analysis you can quickly conclude that at least in some cases, you are looking through the wrong end of the telescope.
For instance, the best way to resolve service issues is to avoid them in the first place. Figuring out how to head them off is both highly cost effective and better for raising your profile with your customers. Heading problems off is beyond the scope of CRM though a close second in this derby is deflecting customers to other less expensive channels. Although these things have a passing resemblance, deflecting is worlds away from heading off.
Much the same can be said of selling faster. I am not a fan of faster selling because we’ve reached the point where we are pushing on a string. You need only recall that the customer buying process is in direct competition with traditional sales processes to see this.
This leaves marketing and if you look at the strides made by marketing in the last few years you might come away wondering how they did it. Marketers really are generating more leads and they are better qualified by the time they get to sales people. So how did they do it?
One of the big differences I see between marketing and the rest of CRM is that marketers constantly ask the customer for feedback. They might not launch questionnaires every minute, but the data stream coming back from numerous marketing initiatives provides them with great insight into what’s going on in their respective patches and it tells them what needs to be done next.
This feedback loop is not new; it goes way back to W. Edwards Deming and his regimen of statistical analysis. Deming was all over manufacturing like a cheap suit. He collected data and ran stats on manufacturing so that he could know what worked and what didn’t. He then went the extra mile and tried to weed out what didn’t work and reward or encourage what did. In the process manufacturing got better. There were fewer defects, better tolerances between parts, and manufacturing costs declined because there was less waste.
Japanese manufacturers were, famously, the first big adopters of Deming’s ideas and we all know what that led to. They have a word that’s useful to remember, kaizen, which roughly means continuous improvement.
So how does this apply to CRM? Quite simply, modern marketing has its own kaizen thing happening and I think it’s worth asking how we can apply these principles to sales and service. In service, we have metrics that look at speed like time in queue, time in resolution process, and lots more metrics that measure speed but not necessarily effectiveness of the encounter. It’s great to get customers on their way quickly, but what does this do for handling cross-sell and up-sell opportunities?
But it’s in sales that I am most intrigued by the possibilities of a kaizen strategy. A slim majority of sales people makes or exceeds quota every year. Jim Dickie, Managing Partner of CSO Insights puts the number at 58 percent in most recent years, plus or minus a little. The interesting thing about selling for me is that there’s usually only one evaluation point — did you close the deal? But what if we used a more incremental approach to assess sales like marketers do when they capture customer input throughout the nurturing process?
That might be a scary proposition for a lot of sales people. If there was a natural point in the process when everybody stopped swimming for a moment to look up and determine if they’re still on track, the feedback might be very useful. For example, how was the demo? It’s a very important part of the sales process and good reps will ask during and after if the demo answered the customers questions and concerns or “Was it alright?”
Customers will often play along but saying that the demo answered all questions is not the same as saying that the demo showed me that this solution would work in my shop. A customer running a buying process wants to be able to have alternatives at decision time so it’s not good to eliminate all contenders lest there be no leverage when discussing price. So everybody keeps swimming until most of the sales people are surprised at the end when their solutions aren’t selected. After all, everything in the process went according to plan.
That’s why it might be useful to go up a level of abstraction in the sales process by sponsoring a mid-process questionnaire. But rather than asking about nebulous things like the rep’s professionalism or even if the five major points of the demo were articulated well, ask open ended questions about fit. On a scale of 5 or 10, how would you rate this solution’s suitability for your needs?
There are a lot of questions you could ask and they will give you a better picture of your position in the account than relying on traditional process milestones that are completely vendor oriented — i.e. if we’ve done the demo we must be X percent of the way through the process.
If we take a kaizen approach and don’t simply wait until the process is over to assess our performance we may not be able to impact an ongoing sales process (though we might) but we will do two other useful things. We’ll improve selling over a short time and we’ll be able to safely weed out deals that won’t go anywhere. Eliminating bad deals saves resources and is the ultimate form of sales acceleration.
Zoura Pads Its War Chest
Zoura announced a funding round worth $115 million today including investors Wellington Management Co., BlackRock, Premji, and Passport Capital as well as some investors from earlier rounds. Calling it a mini-IPO, CEO Tien Tzuo said the company will behave more like a public company from now on as we await the inevitable reality of an IPO.
Zuora invented the subscription billing, payments, and finance market about 8 years ago and has been riding a wave it calls the subscription economy. Briefly that means an economy that is rapidly adopting subscriptions as a business model which makes all the sense in the world.
Subscriptions as we know them started with companies like Salesforce.com which began delivering software as a service and at the time, this was considered an advantage because so many larger software firms were getting hung up on software implementation. You could easily spend two to three times the million-dollar software price tag on getting the software to work which is why Salesforce’s original and still to be topped tagline is “no software.” Tien Tzuo learned a lot at Salesforce as its 11th employee gradually rising to be CMO and chief strategy officer before leaving.
All that’s well and good, but I firmly believe we’ve already overshot the subscription economy. That’s not to say everyone is on board, there are lots of conventional companies just getting up to speed in subscriptions and Zoura will undoubtedly use its new cash to market and sell to them. But as Sheik Ahmed Zaki Yamani of Saudi Arabia once said about the impending end of the petroleum age, “The Stone Age didn’t end because we ran out of stones.”
Things have a habit of morphing. The Old Stone Age morphed into the New Stone Age and here we are. Likewise, the subscription economy has morphed into the subscription culture, which is part of the reason Zoura could raise that $115 million (on top of the roughly $100 million it already raised) to begin with.
The subscription economy delivered a fact to the market; the subscription culture is what happened when customers figured out how to leverage that fact. Sure, they learned that they could pay monthly for things that normally cost millions of dollars all at once enabling small businesses to afford the same things their larger competitors had and this leveled many playing fields. But it also meant that no customer had to feel stuck in a bad fitting relationship any more—it’s too easy to leave one subscription and get another.
Customers were empowered by this new knowledge and it has led us to a new model for business—not the same as a business model. Relationship Business Management or RBM is what Zoura is calling it and the idea has legs because it encompasses the reality that subscriptions are now central to the relationship and that CRM as we knew it has to account for this.
RBM starts by assuming subscriptions and leverages data about customers—their use habits, payments history, lifetime value, and many other factors to drive outreach and interaction well beyond simple purchase and sales issues. That’s where I believe the culture part comes in. Even vendors that do not offer subscriptions are beginning to behave like subscription providers for the simple reason that the model is more customer friendly and in a competitive world no vendor can afford not to cater better to customers.
Zappos is a vendor of shoes and not a subscription company but you’d never know it from the way the company behaves. Their body language suggests a company focused on customer lifetime value and working to get customers to come back for the nth time. They’ve internalized subscription culture from their customers and exude it back. Customers love them for it.
Lots of companies are looking more like subscription companies today, which is why the future looks bright for Zoura as it begins leveraging its new cash to spread the word about subscriptions and RBM to a larger audience.
Salesforce Announcement Promises Better Marketing Processes
If you ever wanted to give yourself a nice, easy job you probably would not pick on-line retail marketing—the pseudo-math alone will kill you. Consider the algorithms that keep the balls in the air. You need to track and predict customer behaviors of all sorts like what was previously bought or even looked at, who the customer is demographically, as well as the vagaries of your own products, promotions, locations, people and who knows what else.
Ironically, these are the kinds of things that human beings can do rather well. I once went into a Nordstrom store to buy a shirt because a business trip went long. The woman who greeted me in the men’s department sized me up immediately and directed me to the color I wanted and my size all in about 10 seconds. I was amazed.
But people are finite resources, don’t scale well, and they are relatively expensive. My sales associate had a lot of colleagues and they all had the advantage of seeing customers to size them up. Today’s retail environment is not often that simple and we find ourselves dealing with thousands of customers at once who are often online and not subject to visual inspection. Consequently, we need software that not only does the sizing up, but that also figures out what we want or need, sometimes before we do. That’s the goal that modern retailer software vendors have set for themselves and something that Salesforce this week signed up for when it introduced Salesforce Marketing Cloud Predictive Decisions.
Like other products in this niche, Predictive Decisions analyzes customer engagement and proactively delivers recommended content, products, or offers, to create personalized customer journeys across channels at massive scale. It is hard to analyze this offering and to say whether it is better than a competing brand or not but that’s not the point.
Predictive Decisions is a great example of how companies can take the next steps in solving for the customer. In my recent book, I make the observation that empowered people + adequate computing + well-tuned processes are the secret to future business success and Predictive Decisions is a great example of this “rule” in action.
This is really the old People, Process, and Technology mantra turned on its head to great effect and if you break down my little formula you can reach a startling conclusion. Consider this: people and technology are in a dead heat today. Organizations understand that they can’t simply recruit and hold onto only the top talent and therefore they have to succeed with rank and file employees—that has always been true.
Likewise, technology per se (let’s say hardware to be specific) is not the game changer it once was because great, fast computing is now ubiquitous and cheap. So it’s really hard to steal a march on your competition to gain market advantage through hardware.
But in process we have access to an almost infinitely variable set of competitive advantages if we can adapt and leverage them. This is what Predictive Decisions promises to do in my view. With analytics and algorithms running at the speed and scale of technology rather than that of a person’s brain, a vendor can process huge numbers of variables and synthesize solutions that result in content, products or offers that are relevant to each customer.
But, don’t be confused, this isn’t about the offer or content—this amounts to building custom processes for each customer on the fly at the exact moment the process is needed. I know lots of vendors, and maybe even Salesforce, will disagree with me but the most important output of products like Predictive Decisions is not the recommendation whatever form it takes. What’s most important is that the system, by generating a unique process for each customer, remains authentic to the situation.
I use authentic when others might be comfortable with personal or similar words. But there is no such thing as personal anything when dealing with a set of algorithms; if the algorithms are good, they generate a facsimile of reality and that’s authenticity. Truth be told, most customers don’t want personal relationships with every vendor and attempting the personal might even hinder what ought to be a straightforward and professional interaction. That’s why I use authentic.
When my shopping experience is over, I am not having a beer with the associate or the computer. My highest goal is to interact with someone or something that gets me and therefore enables my success and that’s all about process. So congrats to Salesforce on yet another product release but this one isn’t about technology, it’s all about process and Salesforce customers should be glad about that.
