On a recent podcast about these 5 rules, I shared a recent digital experience that was definitely on the “could use some work” side of the spectrum. It was Glasses Direct, which is where you order the frames you want with your prescription, and then they send you the glasses. The experience started to trigger some uneasy feelings when they asked me to put a credit card on my forehead and take a picture of it to send to them. They needed the photo since my prescription didn’t have my measurements on it. Ostensibly, they could figure out how to size the glasses based on the credit card’s image between my eyes.

The glasses were not cheap, so I was feeling uneasy about this credit-card directive. Moreover, the glasses were taking a long time; weeks it seemed to me. Meanwhile, while I was waiting, I had no email about my glasses’ progress but at least ten promotional emails from them hoping to sell me something else before I received my first order. (Later, I learned that they did send an email about my order, but I missed it.) To summarize my experience, Glasses Direct was a great idea for a business model, but the digital experience fell short of my expectations.

Since the pandemic, everyone’s doing a lot more of their customer business online, making digital transformation mission-critical these days. I used Glasses Direct for the first time during the pandemic, as I didn’t fancy contracting COVID-19 at the opticians. It is critical to remember that people are still people even when they’re interacting with a computer. These five new rules can help bring your digital experience in focus rather than ending up with a blurry vision.

The Five Rules for Designing a Great Digital Experience

1. Design in a digital “nudge.”
2. Analyze how customers really behave.
3. Design your experience to anticipate your customers’ needs.
4. Plan to evoke emotions and measure them.
5. Humanize technology.

Rule #1: Design a digital “nudge.”

Nobel-prize winning economist Richard Thaler and Cass Sunstein wrote a book called “Nudge” a few years back. They suggested that small changes we make in choices shift people in one direction or another. However, you don’t force people in a direction; instead, the way you present the options with subtle clues affects what they choose. So, to take this idea into the digital space, consider how you can influence your customers to behave the way you want them to act with the way you present your online interaction choices.

There are a few different ways to do this. For example, scarcity works to get customers to act fast. If you make an offer, always put a time limit on it. Giving an “expiration date” to the deal makes it scarce, which helps customers prioritize their buying decision. Disney used to do this with their movies. They would bring classic Disney cartoons from the 60s and 70s, like The Jungle Book or Dumbo, “out of the vault” so you could buy them—but only for the next six months. Then, they go back in the vault! Parents felt compelled to snap up these old cartoons for their newborn children, who wouldn’t watch them yet, just so that in a few years, the movies would be in their collection.

Scarcity is just one of the principles of the behavioral sciences you could use. You could also employ the effects of Social Proofing, which uses the reviews and comments to attract attention to your product. You could utilize the impact of Extremeness Aversion, which means that people usually like the middle option. By presenting your desired purchase as the moderate choice between a more expensive and elaborate offer and a pared-down, more affordable one, you can nudge people to do what you want. Also, don’t forget the whole area of first impressions and the esthetics of your experience. The way your site looks and how the product is featured can also nudge people in the right direction.

Rule #2: Analyze how customers really behave.

One thing I love about the digital space is you can measure everything. You have a better capacity to analyze what people are doing. You can measure where people have come from, where people are going, and even the hotspots on the screen. Having all that data enables you to make predictions.

Also, I like to test the tactics I use in a safe environment. You can test if you use this icon in one position how customers behave and then move it somewhere else and see what happens. Moreover, you can do these types of tests quickly.

Customer Science uses this blend of data, which you get in abundance with a digital experience, to see what people are doing. As you might recall, there’s a significant difference between what customers say and what customers do. The great thing in the digital environment is you can see what they do. You can also make (and test) one of these digital nudges and see the effect.

Amazon uses Customer Science because they have a great deal of data. Moreover, they know a great deal about me. I buy virtually everything on Amazon, from food to books and everything else. They know what I read on my Kindle and when I wake up because I use the Amazon Echo. They even know who’s come to my front door. Some people think it’s Big Brother-ish, and it is, but I think how they use it is ingenious, which leads me to the next rule…

Rule #3: Design your experience to anticipate your customers’ needs.

Given all that data you acquire for rule #2, here, in working with rule #3, you can use it to anticipate what customers will do next. Then, you can design your experience to play into that behavior. You are, in effect, beating customers to the punch and offering them an easier way to do what you want in your experience while at the same time improving the process for them.

For example, time is a significant resource for all of us. To conserve it, we want things to be easy, so we spend the least amount of time (and cognitive resources) on something that we can. If you can make things easier on your customer by understanding how they navigate a website and what needs they have that accompany a purchase, you are more likely to get customers to behave the way you want.

Don’t make your customer anticipate. Figure out what they would want and give it to them. Whatever you do, please don’t make them burn up their precious attention, trying to find the necessary information to make a decision. Make it easy for them to see what they need.

Moreover, you can use that information from Rule #2 to segment customers by behavior, which allows you to get even more specific about what they need for the experience to be easy. If you know that this type of customer usually behaves in a particular way, you can provide the information they need to improve the experience and get them to do what you want. Everyone wins in this scenario.

Rule #4: Plan to evoke emotions and measure them.

Around 18 months ago, I had a podcast about analyzing customers’ facial expressions during experiences. To summarize how the technology works, there is a camera positioned to record customers’ facial expressions during experiences, which you can later analyze to understand how customers feel at the moment. The types of signals that reveal the customer’s emotional state include micro-expressions, like eyebrows raising, lip pursing, or pupil dilation. The advantage is that you get a real-time report on how your experience makes people feel. So, for example, if glasses direct had been recording my face when I read the email about putting the credit card between my eyes, they would have known by my microexpression that I was surprised they asked (by my raised eyebrow) and doubtful that this would work (by my pursed lips).

In a digital experience, however, you usually can’t see anyone. You can hear somebody yelling at you in a store or see them stamping their feet, but online, not so much. The best way you can determine if someone is unhappy is if they leave the page just before check out or something. Or, maybe they get on the chatbot next, so you have that data to consider. In other words, it isn’t easy with digital experiences to know at the moment how customers feel.

However, that is even more why I think it is vital to get on board with Rule #4. If you make a deliberate plan to evoke a specific emotion—which can be feeling cared for or prepared or surprised and delighted—in your digital experience, then you have a better chance that those moments will have positive feelings rather than negative, even if you can’t record the microexpressions as they occur…yet.

Rule #5: Humanize technology.

The best way to introduce this rule is to give you an example. So, as I mentioned, I buy everything on Amazon, including a chef’s knife recently. Unfortunately, we dropped it on the floor, and the blade broke. I went online and saw there was a manufacturer’s warranty, so I began a chat. It was clear that I was dealing with an automated chatbot, which isn’t bad in itself, but it was noticeable. Then, when I reached a real human, the human asked me the same questions in the chat, which annoyed me.

My advice here is two-fold. First, mind the experience enough that you don’t ask people the same bloody questions twice. Second, it would be best to make that interaction with technology feel more “human” if possible.

We know from a former guest on our podcast, Shiri Melumad, assistant professor of marketing at the Wharton School, University of Pennsylvania that she has data that shows people respond differently on mobile phones than they do on their computers, albeit subtle differences. For example, people are more emotional on their phones because mobiles are more difficult to type into, so people get to the point rather quickly. However, these subtle differences might also be present in how people react when they think they’re talking to another human being versus thinking that they’re talking to a robot. Those differences and reactions would be essential to anticipate and manage in your digital experience.

We are not saying that you should use a bot or that people don’t like communicating with a bot. However, it is different, and it would be wise to determine if it’s the right kind of difference for the interaction. In other words, you should ask yourself at various points in the digital experience, would this interaction have a better emotional outcome for the customer if a human handled it?

Humanizing technology also means that you should not make customers feel that you are trying to avoid the human touch. I had that lousy type of avoidance experience with my cable company last week. (What a surprise!) I couldn’t get a human to talk to me. It felt like a nightmare, which is not the digital experience anyone is trying to design for customers.

These five rules will help you build an excellent digital experience. Try putting a digital nudge in the design to take advantage of all the concepts we have discussed in the behavioral sciences, and then see what your customers do. Moreover, use this data about customer behavior to understand what customers want or what they are trying to get and test to see what happens if you change it. Once you know these needs, try and design a digital experience that anticipates customers’ needs to make it easier for them to get what they want when they want it. Doing so will help your plan evoke the emotions you want customers to feel during your digital experience to tie to results that you measure. Finally, consider how your digital interaction comes across to customers and whether the human touch is in all the right places. All of these rules can help govern your digital experience, which, as we all know in 2020, is one of the only places your customers can have an experience at all.

To hear more about this idea in more detail, listen to the complete podcast here.

Colin Shaw is the founder and CEO of Beyond Philosophy, one of the world’s leading Customer experience consultancy & training organizations. Colin is an international author of six bestselling books and an engaging keynote speaker.

Follow Colin Shaw on Twitter @ColinShaw_CX

The post The 5 Rules for Designing a Great Digital Experience appeared first on Beyond Philosophy.

Customer Science is the fusion between technology (mainly AI), behavioral science, and data.

Let’s break it down a bit more, starting by defining science. Professor Ryan Hamilton is the only scientist I know. Fortunately, he is also the co-host of our podcast, The Intuitive Customer, and we discussed what Customer Science is on a recent episode. Professor Hamilton explained that science is a rigorous identification and measurement of phenomena, leading to understanding it systematically and then presenting it with a causal link or a theory. Science doesn’t say we know for sure that we will be right, but it does say when we get new information, we know more than when we started. I agree.

So, I ask you, is your company good at the rigorous identification of customer experiences in a systematic way that you can explain with a theory? I am sure most of you will say no because most businesses don’t. When I look at organizations today, the vast majority have neither rigor nor an in-depth understanding of customers and their experiences. Moreover, most organizations do not look at a rational, emotional, subconscious, and psychological level of a Customer Experience, which is vital to understanding customer behavior. These organizations can go into incredible depth using science in other areas like products, finances, operations, and so on, but not customers. Therein lies the problem. Without this in-depth understanding of customer behavior, organizations can’t interpret the data or adequately train their AI.

For example, I talked to a client and asked him if he had any client research in a specific area. He said he did—from seven years ago. I thought, “Blimey! That is a lifetime ago! The world has changed drastically in the last seven months, let alone seven years!” When I asked to see data on how a customer feels and which specific emotions they were evoking with their present experience, my client did not have any data on these areas either. Without this information, how can a business claim to have a rigorous identification of Customer Experiences systematically or explain customer behavior with a causal link? However, that doesn’t bother me nearly as much as the fact that they don’t even realize it is necessary. But I digress…

As I mentioned before, Customer Science is an embryonic idea. When you google Customer Science, it doesn’t yield many results. There are a few out there, but not an overwhelming amount. Customer Science is not fully defined; it’s more of a fusion between technology, Customer Experience, and behavioral science.

It reminded me of 2002 when I first started talking about getting into Customer Experience. Back then, Customer Experience(CX) was still solidifying as a concept. I spent most of my time in the first five years educating people on what CX was and what it meant. Moreover, it morphed into all kinds of areas and focused over 18 years as different opinions surfaced and changed the conversation. Customer Science is here now, at the beginning of this journey into meaning.

“Nothing is more powerful than an idea whose time has come.” -Victor Hugo

Data Collection is the First Step Toward Customer Science

A vast reservoir of Customer Data exists for science to rigorously identify and explain. Take Amazon, for example.

I love Amazon just as much as I love Apple (which, as many of you know, is a lot). I have a couple of Echo Dots in the house, shop on the site and the pantry, use their entertainment options, etc. This means that Amazon knows when I get up and when I go to bed, what I like to listen to, what I want to eat, what I like to do with my free time, and everything else.

Amazon can consolidate and aggregate all this data, apply what they know about customer behavior, and understand my buying behavior. Amazon knows what I buy when and how much and, perhaps most importantly, they can see where they can influence my behavior. The difference between Amazon and many other companies is using this data to understand their customers at a behavioral science depth. They have a division called Amazon Science. What I love about Amazon Science is this division is all about “customer obsession.” Also, they refer to their team as “our scientists.”

Is your company customer-obsessed, and do you employ scientists to look at customer behavior based on the data you have collected? Again, the majority of you will answer no. However, what would be possible if you used that data for segmentation by customers’ buying habits, hobbies, values, and spending amounts, too? It would be a powerful package.

In other words, with all the technology and the data, you can apply the rigor of science to it to explain why people are doing things, and then employ those findings to get people to buy more. Voila! Customer Science.

Reinventing What Already Exists

Do you remember what life was like before the iPhone? I do. You could take a digital picture, talk or text on the phone, listen to digital music, check your email, and shop on the internet, just like you do today. However, we did all these things on separate devices. The iPhone brought them all together, and the advantage was the integration. The consolidation of functionality makes them more potent than they were as individual devices.

It’s the same idea of consolidation with the concept of Customer Science. The term is a repackaging of existing theories—Customer Experience, AI, technology, cloud, 5G’s potential for data collection, Customer Experience Management, and the behavioral sciences’ psychological concepts—in a new way. It’s not wrong to repackage, either. If making an old idea new again makes people excited about it, and the old theory is a sound and important one, I am all for it.

Another significant influence on the idea is that organizations feel pressure to change. The marketplace has changed drastically over the pandemic. The increasingly widespread adoption of cloud computing, digital transformation, and 5G fuel the fusion of these ideas and encourage organizations to embrace them. Customer Science presents an opportunity to test our theories against our data using increasingly advancing tools to explain customer behavior and improve what we do.

We aren’t there yet. There is no Customer Science lab hard at work, optimizing the way to foster customer-driven growth. The concept is nascent, little more than a label at the moment. However, it’s a label with potential, and perhaps even an idea whose time has come.

The iPhone was also an idea whose time had come. Apple did pull the existing technology together to address a saturated phone market with a unique and advanced approach. Perhaps, in time, Customer Science can do the same for business.

The INTERPRETATION of Data is the Next Competitive Battleground

We all know we have masses of data. The issue is not the collection of data but instead the interpretation of data that is the issue. Behavioral scientists can look at data and interpret customer behavior to see patterns. The Apples and the Googles of this world recognize that there are patterns within the data. They also know if they look at the data differently with more advanced thinking, they can uncover what the customer really wants. Most organizations do not have this capability.

The evidence of this opinion lies in the company’s segmentation. Data enables improved segmentation. When you look at people’s psychological attributes, like their personality characteristics, lifestyle, interests, and social classes, you can infer something about their behavior. However, few organizations do this. Most segment their customers into large, medium, and small, or other such basic segmentation, which isn’t nearly enough differentiation, and certainly doesn’t include any rigor or explanation.

When you look at people’s psychological attributes, like their personality characteristics, lifestyle, interests, and social classes, you can infer something about their behavior. However, few organizations do this.

The opportunity is in science. Firms that have taken a scientific approach, as Amazon does with their data. Amazon has developed theories about customers and tested them to see if they work. Google runs thousands of A/B Tests every year to see what works and what doesn’t. They collect data, develop theories, test the hypotheses, and then develop new ideas based on their findings.

I am baffled by companies that invest millions of dollars based on a hunch rather than research. Sure, you can invest in whatever you want; it’s your money. But even if you do succeed, it’s more luck than anything else—and one day, your luck is going to run out.

However, if you can predict what the customer wants by examining the data through a behavioral sciences lens, you can see what customers want. Moreover, you know what they want even when they might not know themselves.

Unfortunately, many firms don’t have the data to examine. If you count yourself among them, our Emotional Signature® Research determines what emotional engagement you have currently with your customers and how you could gain more. Moreover, it’s research, not a “hunch.”

Customer Science is the Future for Customer Growth Analysis

It is also important to remember that the world is a messy place. With a non-scientific approach to business, which almost all companies take, it can be challenging to know whether your efforts were successful or not. Sure, there are outliers where a business makes a small adjustment to the process and ends up with 300% growth, or, to the contrary, a 50% loss in sales. However, it’s more likely that sales and the Net Promoter Score (NPS)® go up by five percent, but your competition also went up or down a little bit, or the market got more competitive or any other host of influences. With a non-scientific approach, it is difficult to know what change affected sales the most.

I am hopeful that if business embraces the idea of Customer Science, it will result in much more fundamental changes in the approaches that people take to managing Customer Experiences, as well as cultural differences about how we make decisions and evaluate success. Perhaps most importantly, it gives you the rigor and to identify and measure whether what you are doing is creating customer-driven growth—so you can keep doing it for more.

To hear more about this idea in more detail, listen to the complete podcast here.

Colin Shaw is the founder and CEO of Beyond Philosophy, one of the world’s leading Customer experience consultancy & training organizations. Colin is an international author of six bestselling books and an engaging keynote speaker.

Follow Colin Shaw on Twitter @ColinShaw_CX

The post What is Customer Science? Is This the Next Wave of Change? appeared first on Beyond Philosophy.