Customer Engagement

Here at Bluewolf, we go a few steps further with customers than most. More than just attentive service, we are obsessive about the customer experience. For us, customer obsession is about how you organize your resources and build your culture around the customer, and how your resources in turn organize their efforts around the customer. Customer engagement is how you create and deliver the best customer experience without question. Name the top five companies in your opinion for customer engagement and experience, right now. Chances are, at least three of the following made your list:

• Amazon
• Google
• Apple
• Disney
• Xbox (Microsoft)

There is a reason these companies land at the top of the heap every time customer engagement comes up, and it's not because they are the best or biggest companies in the world, although they certainly are leaders in their respective market segment. Walmart dominates the retail market and Exxon/Mobil rules the oil and gas industry, but they aren't even close to making this list. Companies like the five listed have a large, loyal customer base because their primary concerns are the customer journey and the experience their customers have every step of the way. People trust and rely on Google to such an extent that the entire Internet seems to implode if its search engine is down for two minutes. As we know, this doesn't happen often, and the fact that it's fixed in such a minuscule amount of time is impressive, which only serves to increase customer engagement because we all know they can be relied upon.

We take customer attention more seriously than most organizations, but others are recognizing the value of true customer obsession and are trying to do the same. Let's take a moment to explain what we mean by customer obsession. Customer obsession and customer engagement are central tenets of the customer-driven enterprise. It goes far beyond the idiotic clichés about the customer being always right or the customer being number one. In an agile enterprise, the customer is everything all the time. This chapter explains how to become truly customer obsessed, why you want to, and why it is so critical for success in today's economy.

If you haven't realized it yet, the old ways of competing don't apply. The battle for customers is won based on your ability to engage customers completely. That's why we aren't shy about customer obsession.

Have you ever really thought through the incredible customer moments that occur each time you walk into an Apple Store? Almost the moment you enter, you are greeted by an employee who is not only equipped to answer any question you have about Apple's products, but can check you out on the spot using the iPad they're carrying. No lines, no paper receipts—just a direct, one-on-one interaction that is simple, fluid, and quick. That's a customer-obsessed, agile company that knows how to engage the customer fully, and Apple is extremely successful by almost any measure. (Historical note: When the late Steve Jobs announced his intentions to open retail stores in 2001, his announcement was met with tepid enthusiasm. Today, Apple Stores generate $16 billion annually and boast the highest revenue per square foot of any retailer.) But unfortunately, customer engagement isn't easy. Companies fumble opportunities to engage customers every day.

A leading telecom player, for instance, seems prone to blowing it lately from a customer standpoint. They keep popping up in the news, and not in ways that show them in the best light. For example: A customer's home was lost to a fire, and the provider delayed canceling his subscription (due to the customer's inability to provide his account number) until considerable media exposure and pressure. Rather than having a customer engagement mentality in place that would have enabled them to handle this smoothly, they stumbled when they encountered an extreme situation where they needed to put the customer first.

It could have been so easy to do right by the customer to preserve and even advance the relationship (remember the lifetime value of a customer). Basic employee training on tone, approach, and the handling of unique requests could have prevented this and other similar situations, especially those where employees exhibit customer-inappropriate behavior.

Or maybe you heard the story of the athletic clothing retailer, where the company chairman commented that some women's bodies don't work for their clothing. While the chairman may have been expressing his honest opinion, it was neither sensitive nor appropriate. Following this incident, the company also banned customers who had sold their merchandise on eBay from buying products online by blacklisting their IP addresses. Apparently, it took numerous news stories and customer complaints in the very public forum of Facebook to get them to change their policies. Rather than trying to connect with all of their customers, the company alienated many of them, including the women they thought their clothing suited.

Now, contrast this to the eastern state described previously. They listened to their customers' complaints and noticed the backlogs and delays. Granted, this department had to be threatened with a delay in their reimbursements, but they did the right thing by their customers and never ended up as the lead item in a Facebook timeline or on the front page of The New York Times.

Still, the reality is that most businesses are not fully customer focused. This is bad for customers, but it can be good for business managers like you who understand the importance of customer focus and are ready to do something about it. Besides, it makes more competitive sense than trying to match suicidal low prices.

Actually, most businesses subscribe to all the correct clichés like “the customer is always right” or “the customer comes first,” never bothering to check what customers want, need, or even what they think. These managers have a product or service they think is good and provides value, therefore it must be true. They never hold themselves to a customer experience litmus test, and they don't want to know because then they might have to change their thinking, take remedial actions, or spend money.

Customer Experience 101

The problem: Customer experience is complicated, multidimensional, and you're not the boss. The customers control the relationship, not you. The funnel algorithm that has served the business for so long (Figure 5.2) is no longer enough. Customer experience is the sum of all experiences a consumer has with a supplier of goods or services over the duration of the relationship with that supplier. Today, you're responsible for the experience people have with your brand before they even become a customer and for as long as they remain a customer. Again, think about how much of the lifetime value of the customer you want.

That means thinking of customers as actual people, not transactions; as people whose decisions are based largely on emotional factors and, as far as you're concerned, on their experience with your brand. Simply providing a 360-degree view of your customer won't help you understand them as people. That's the old way—and it never really worked, anyway.

The new way is to build an understanding of the customer on a data foundation and then use that data to feed your employees with predictive customer moments. These would prescribe their next best action based on truly using predictive models to drive customer engagement.

The best way to determine what data needs to be captured is to use customer journey mapping. You have to understand not just the customer life cycle (Figure 5.3) but also map out each and every touch point a customer has with your business. This will enable you to assess your strengths and weaknesses around the customer connection. Customer journey and experience mapping consists of seven steps:

1. Select a specific customer to map.
2. Identify the high-level customer life cycle phases.
3. Map the step-by-step customer journey.
4. Map customer touch points.
5. Add customer attitudes and emotions.
6. Define internal supporting structure.
7. Identify opportunities.

Once you have created a visualization of that journey, you'll be able to design solutions that are targeted at improving specific moments to achieve better outcomes.

How Customers Buy

Do you ever wish customers could simply be cogs in your consumption machine? You could push a button and they would buy over and over again. Unfortunately, they are not cogs in your consumption machine or anyone else's. They are people with thoughts and feelings, trying to balance rational and emotional actions. Despite weighing the pros and cons, conducting research, making checklists, and following all the dutiful buying behaviors, most decisions are made based on emotional factors, which are influenced by their experience with a brand.¹

In a paper titled “Emotion and Decision Making,” researchers Lerner, Li, Valdesolo, and Kassam observe that a revolution in the science of emotion has emerged in the last few decades, bringing about the potential for a paradigm shift in decision theories. The research reveals that emotions constitute powerful, pervasive, and predictable drivers of decision making.²

Across different domains, important regularities appear in the mechanisms through which emotions influence judgments and choices. In the resulting paper, the researchers propose an integrated model of decision making that accounts for both traditional (rational-choice theory) inputs and emotional inputs, synthesizing scientific findings to date. In short, they write that in order to have anything like a complete theory of human rationality, we have to understand what role emotion plays in it. Today, we now recognize the crucial role contemporary science has begun to give emotion in decision research. Across disciplines ranging from philosophy to neuroscience, an increasingly vibrant quest to identify the effects of emotion on judgment and decision making is in progress.

Writing in Psychology Today in February 2013, Peter Noel Murray reported that emotion is a necessary ingredient to almost all decisions.³ When we are confronted with a decision, emotions from previous, related experiences affix values to the options we are considering. These emotions create preferences, which lead to our decision. As a result, emotions are the primary reason why consumers prefer brand name products. Why else, he asks, would we pay more for brand name products when many of the products we buy are available as generic brands with the same ingredients and at cheaper prices?

Recent research shows that positive emotions toward a brand have far greater influence on consumer loyalty than trust and other judgments. As a result, consumers are taking their biggest cues from a brand's attributes as they experienced them. And this is why customer obsession and insistence on creating an outstanding brand experience for each customer are so important.

Changing the Historical Mind-Set

If you want your customers or prospects to do something different—like adopt you as a new provider—you have to change their historical mind-set. This is another way of saying get them to stop doing what they usually do and try something new. That same historical mind-set also stops them from adopting new ideas.

To get them to change, you have to offer an experience that is relevant, fresh, and better than what they have experienced previously. You identify what this experience might be by looking through the data you have been collecting about your customer and learning about their needs, expectations, and hopes. You don't even have to figure it out; if you just pay attention to the data you are collecting, the customers themselves will reveal what they would respond to.

Let's briefly digress to discuss data, because understanding its role will help you know your customer better and deliver better customer experiences, every time. It comes down to achieving a highly predictable, dependable customer experience.

Data science takes every customer interaction and identifies patterns that can be repeated and proactively acted upon. In short, data science enables an organization to get ahead of a customer's actions—to know what customers want even before they do. This powerful ability becomes the focal point for business intelligence and customer engagement strategies, allowing businesses to be more competitive and service oriented as they get closer to their customers than ever before.

The real goal of data science is to integrate the data throughout an organization's business process layer to both predict and provide prescriptive actions to employees who will take the most relevant and timely next step. Yet data science is not confined to empowering just the service and customer-facing employees; it cannot exist in a siloed environment. It must be integrated into the entire organization, prompting businesses to realign executives, employees, and processes around the customer and absorb insight-driven value propositions throughout.

Design and data science must converge to deliver seamless, relevant, and hyper-integrated customer experiences—across channels, devices, and touch points—to reimagine the business and its entire workforce (see Figure 5.4). The result will be a customer-first business, which will bring success going forward.

What you need to do then is to focus on the customer experience from the beginning, and that means operating with a mind-set open to possibilities, not limits. At Bluewolf, we have an exercise we like to call “Art of the Possible.” By comparison many, if not most, companies operate according to a legacy mind-set. “Art of the Possible” is about moving beyond current practices and embracing new ideas to keep pace with customers and their ever-changing business environment.

Try this little mental exercise: Take your mission statement and replace your company's name with Google. Now, recreate your mission statement while imagining you have all of Google's resources at your fingertips. How does it look when you don't hold back and create a future freely and confidently? Take a step back and analyze how to achieve this reconceived mission, making note of which ideas and attitudes have to change in order to move forward. Often, it's not that companies lack the ability to make a change, but are caught up in old ways of thinking about their business and their customers.

What I'm really asking of you is to challenge yourself to think about the modern customer experience. This is not a one-time, static event you forget about next week. Customer expectations evolve rapidly based on their last, best experience. It's no longer enough to have continuous innovation—you have to provide instantaneous innovation to keep up with the pace of change. When you put customers first and constantly evaluate your business through their eyes, you'll be poised to adapt proactively, not reactively.

Berkshire Hathaway Travel Protection (BHTP)⁴ exemplifies this kind of customer-centric thinking center. The company tries to anticipate the needs of its travelers, especially when things have the potential to go wrong. BHTP's AirCare can repair travel mishaps, help locate lost luggage quickly, and even get customers access to the airport lounge. Live service to aid travelers is just a tweet, text, web chat, or call away. With the introduction of AirCare™ in May 2014, BHTP became the first travel-insurance company to address consumers' travel woes by offering a simple, fixed-benefit travel insurance product. It proved the value of a business model that predicts what its customers need, and builds its customer service around those needs.

I have said repeatedly in this book that technology is there to enable solutions, not the solution itself. But to perform this kind of innovation you must have the right tools. In Bluewolf's The State of Salesforce report, companies with both cloud governance and application life cycle management (ALM) were three times more likely to attribute revenue growth and two times more likely to attribute improved customer experience to their tool usage.

“Art of the Possible,” however, doesn't mean abandoning reality and building castles in the air. It's about being open-minded about realities and customer expectations to optimize them, not succumb to them. Then train yourself and your teams to become customer focused and positioned for success. Constantly ask yourself—where are your customers and opportunities right now, and where do the two meet?

The goal is to move your customers out of their current mind-sets. Sometimes this requires some persuasion; in other cases it may involve instantaneous innovation. The idea is to help them leave behind entrenched thinking that won't take them forward and lead them down a better path. To do that, you want to design things that are going to meet the customers' expectations, while knowing full well those expectations will be based on their last best experience. Still, this is not impossible; expectations evolve very rapidly. You can assist by creating experiences that are relevant and up to date. In effect, their last best experience could be the one they just had with you. That's where instantaneous innovation comes into play. You can make outstanding experiences for your customer any time, all the time. And you should.

Feeding Data into UX Design

Up until this point I have focused on data, but data is only part of the story. Great user experience (UX) design simply represents good data. If you don't know the data, you can't come up with even a passing design, never mind great design. The other thing about great UX design is that it doesn't require anything more of the customer than a normal, intuitive response. Steve Krug laid out the principle of this kind of design in his book Don't Make Me Think. Ostensibly about web usability, it really is about ensuring a top customer experience through intuitive design.

Always coming back to the customer, prescriptive design is about creating the use cases around a day in your customers' lives and knowing their journeys. Apply data to feed your design, which should be intuitive. If the action is not immediately obvious, it is not intuitive and therefore contrary to a positive customer experience.

Massive amounts of data, and the accompanying data architecture, have to be organized in such a way that they feed this type of design. Seen in the light of intuition, great design isn't big; it's small and streamlined. This isn't rocket science; to get to great design, step into the shoes of your end users, your customers. Figure out ergonomically what is most feasible in terms of the visual design for the user interface/user experience (UI/UX) and tell the story you've already captured in the data. If you need additional inspiration, Apple offers a wealth of great examples.

The true nature of customer engagement, notes Bluewolf UK's Director Vera Loftis in a December 2015 issue of Customer Experience, lies in understanding what customers need before they know they need it—not just resolving cases as they arise.⁵ The way you do this is through the combination of analytics, continual monitoring, and collecting customer behavior data. This enables you to predict when a customer is about to have an issue. The tools can alert your people charged with the customer to proactively reach out to a customer before the issue arises, or even communicate directly with the customer. Product or service incidents are inevitable, but going to your customers with a solution before they even know they have a problem is a great way to show them that you care about the issue at hand, and it automatically delivers a superior customer experience even if the initial issue was problematic.

This amounts to what you might call a hyper-integrated customer experience. By contrast, an example of a disconnected experience, Loftis points out, is going into a store and being unable to return an item purchased online because the brand's website is a separate system. This is frustrating, inconvenient, and costly to the customer, which makes it potentially costly to the business, too. Brands need to ensure that they are delivering the same experience across all channels, devices, and touch points. This is what the savvy marketers call an omnichannel experience, where customers experience the same information and service no matter how they choose to do business with the company. With the omnichannel experience, customers can even mix and match communication channels and service people and still experience the same consistent, high-quality service. No matter where the customer is, the experience should be the same. Clean, accurate, consistent data can accomplish this. To understand the customer experience, start by identifying all customer touch points, mapping them to the appropriate data, finding the gaps, and filling them.

Emerging from all of this is the new customer experience. Forget about the 360-degree view. What you really want now is the predictive customer experience view. This isn't about who buys what, when, and where. It's about what's going to happen next. Then you position yourself to take prescriptive action to serve their needs before they're even aware of them. That requires setting up your systems to comb through every detail of available customer data, the data you have been collecting and analyzing to better know your customer. Now, analyze it again using the predictive algorithms that are becoming available, then rinse and repeat.

The road to predictive may seem daunting, but it's more than possible—it's necessary. Let's take a look at the seemingly out-of-the-box ways data and predictive algorithms can improve the customer experience with a discussion of the real-life story told in the best-selling novel Moneyball. If you're not familiar with the story, the Oakland Athletics' general manager Billy Beane dramatically improved the A's performance via data analysis. Beane took the on-base percentage data and used it to recruit and sign players who may not have had the most impressive field performance, but were able to get on base, score runs, and win ball games. This had a significant impact on the customer experience, as their higher performance created a better, more exciting game and atmosphere.

Data has the potential to impact everything about your business. Don't you want to figure out the right questions to ask so you can apply the Moneyball scenario and bring success to your own organization?

Get Personal

To paraphrase the messages regularly doled out to parents of teenagers: do you know where your customers are and what they want next? That's the customer challenge I call getting personal. Getting personal means creating a customer experience that is so relevant and appropriate to the customer and the situation that it had to be the result of deep, predictive insight, insight that is so attuned to the customer and the business's needs that it borders on intimate.

The goal of getting personal is to optimize the customer experience, which entails familiarity with a number of customer touch points such as inventory, customer life cycle, and customer experience mapping. And don't just stop with your direct customer. Extend your knowledge to the customer's customer wherever you can. Have you noticed that manufacturers of food products like Doritos advertise heavily to the consumers of those products? Their actual customers—the ones who order the products from the company—are large retailers or distributors. Just look at the extremely costly Super Bowl halftime ads. Costing several million dollars per 30 seconds of air-time, they are targeted to the end users of the products, not the organizations that actually buy the products from the advertiser.

On top of that, these advertisers spend millions of dollars more to research and get to know these end users as much, or more than, they know their actual direct customers. These heavy investments in market research and analysis make sure they are accomplishing the following:

1. Communicating effectively with their target markets,
2. Ensuring that the highly produced and expensive TV spots hit the right notes with the mass Super Bowl audience, and
3. Positioning themselves to deliver the experience these potential customers desire and now expect in terms of style, attitude, performance, and more. In the end, it comes down to establishing a personal relationship between the customer and the brand.

To make this work, establish your data architecture as the single source of truth about your customers: a deep, insightful repository of facts, customer opinions and attitude, sentiment, hopes, expectations, and more; past, present, and (predictive) future. Start with employee checkups and customer check-ins, but don't stop there. And please, don't send generic, bland surveys—they don't work.

Instead, put yourself into your employees' shoes—understand their daily journey and, in turn, how that affects the customer journey. If you never have, try Rep Rides, Bluewolf's day-in-the-life workshop explained in detail in Chapter 10. Here's an example where Rep Rides made a difference:

Art of the Possible

Can you do the same? Sure. Start by challenging your company to think beyond what is available, to what just might be possible. Strip outmoded mind-sets. Then engage with customer mind-sets toward business processes. That means capturing the current experience based on their last best experience. Then start innovating.

Finally, build on the customer experience, which is intimately tied to employee engagement—don't bother trying to optimize one without the other. And of course, make it personal and consistent. Remember, look through their eyes, not yours. Then expand on your strategy of information, understanding, empathy, and action. Sounds simple, huh?

People complain that I make it sound too simple, that I have drunk too deeply from the Kool-Aid of customer obsession. Needless to say, I don't agree. Just read through this book and try just one or two of the things I suggest. Then reach out to me at Bluewolf's headquarters in New York and give me your honest opinion.