Customer Innovations: Creating Experiences that Drive Measurable Business Results

Are you losing too many customers or sales opportunities?    Are you experiencing too much negative word of mouth?    Are customers’ expectations changing faster than your company’s ability to stay ahead of the competition?    Do you have trouble aligning the efforts of intermediaries in order to deliver for the customer?    Are customers behaving in a way that constrains or undermines your efficiency and profitability?    Are all your efforts just leading to “better sameness”?

Over the past couple of years, I’ve covered an extensive array of topics focused on how companies can address these issues.  In this post, I’d like to take the liberty of  describing the type of work we do and the unique tools we use in the process.

My colleagues and I at Customer Innovations have a 25 year track record helping leading organizations create experiences that improve the acquisition, retention, and profitability of customers.  In the course of our work, we’ve demonstrated bottom line results of 10-25% in the form of increased retention, incremental sales, reduced acquisition costs, positive word of mouth, higher price realization, and improved productivity of customer-facing operations.   Most of our work has been with organizations that create experiences across complex networks of “customers” including consumers, agents, brokers, retailers, and other influencers.

Our work generally takes the form of these types of efforts:

  • Rapid Revenue Retention. We quickly identify specific elements of the current experience that are leading to attrition, lost sales, negative word of mouth, and unproductive customer behavior.   Intensive 10-12 week efforts often lead to $10 – $100 million in benefits.
  • Accelerating Sales From the “Outside In”. Rather than starting with the internal structure, processes, tools, and training, we start with a deep understanding of how and why your customers buy and then focus improvements on shifting buying behavior.
  • Creative Customer Insight. Without breakthrough customer insight, design efforts can only produce “better sameness.”  We have a unique approach to surfacing customers’ latent motives, beliefs, needs, and priorities in a way that informs the creation of highly evocative and profitable products, services, and experiences.
  • Signature Experience Design. We design, deliver, and engage customers in experiences that capture their attention and influence the actions they take.  These evocative experiences are structured to tell a meaningful and influence customer behavior using a set of differentiated “signature experience” elements.
  • Aligning Effective Employee and Intermediary Experiences. We help create the specific employee and intermediary experiences required to ensure that those who work directly or indirectly with your customers reinforce the intended evocative experience.

We Have a Unique Technology for Creating Experiences that Influence Customer Behavior

Traditional touch-point oriented approaches rarely deliver more than “better sameness” because they focus on how the organization delivers an experience rather than on deeply understanding how people actually have experiences and how those experiences influence behavior.   Customer Innovations has a unique approach and toolset for designing evocative experiences that positively and profitably influence behavior. 

  • Experience MinerTM – Traditional “voice of the customer” approaches are insufficient for understanding the largely subconscious processes that influence customers’ desires, preferences, emotional states, choices, and behavior. Based on 25 years of cognitive and behavioral research, the Experience MinerTM toolset helps surface, analyze, and measure the ways customers think about, feel about, and act on their experiences.
  • Experience DesignerTM – The output from Experience MinerTM feeds our structured Experience DesignerTM toolset that guides every step of the experience ideation, concept development, specification, and blueprinting processes.  Experience DesignerTM also incorporates an integrated experience-chain framework that helps specify and design the specific employee and intermediary experience interventions required to generate the intended customer experience.
  • Experience EconomicsTM – It’s exceptionally easy to deliver an uneconomic experience.  Most organizations simultaneously over-invest in elements of the experience that don’t matter to customers and under-invest in elements that have significant influence on customer behavior.  The Experience EconomicsTM toolset helps companies find the optimal investment point based on the influence that individual and collective experience design elements and service levels have on the financial performance of the business.

I’ll continue to expand on these tools in upcoming posts.   In the meantime, you might want to check out the following links:

If you’d like any more information, just post a reply or send me a note at fcapek (at) customerinnovations (dot) com.   Cheers, Frank

Choice Architecture: Designing Experiences that Influence Customer Behavior

Well-designed experiences influence behavior.   A well-designed customer experience can influence customers to return for additional purchases, spend more money during each purchase, and tell lots of other potential customers about the experiences they’ve had with your business, etc…    In addition, a well-designed customer experience can influence customer behavior in a way that decreases the cost of service.   For example, the experience can be designed to increase the likelihood the customer will place an order or look for service on the web rather than calling the call center.  Additionally, I’m doing an increasing amount of work with energy companies who traditionally haven’t paid much attention to customer experience.  However, many of those companies are now focused on designing services and experiences that influence customers’ conservation and consumption behavior.

In order to keep things simple, classical economics has always assumed that people act based on a relatively stable set of preferences.  However, in real life, this is far from true.  People typically don’t know what they want until they see it… they construct their preferences and work through decisions as they understand their alternatives in context.  Subtle differences in the design of that context can have a significant impact on the decisions customers make.  In fact, research in the areas of cognitive psychology and behavioral economics has shown that…

…small and seemingly insignificant contextual details have a major impact on people’s behavior.

For Example….

…How Including an Irrelevant Choice Can Influence Customers to Spend More?

One of my favorite recent examples comes from MIT Professor Dan Ariely.  (See Dan’s great book:  Predictably Irrational)  Dan came across the following advertisement for The Economist:

The Economist Subscription Options

The Economist Subscription Options

The ad offered three subscription options:

  • Electronic Only: $59
  • Print Only: $125
  • Electronic and Print: $125

Which of these options do you think people would choose?  Why would anyone choose the “Print Only” option rather than opting for the additional “FREE!” electronic subscription?  It seems very unlikely!  In fact, Ariely conducted a test with 100 Sloan School students and only 16 chose “Electronic Only” while 84 chose the “Electronic and Print” option.  No one chose the “Print Only” option! On the surface, this option seems totally irrelevant.  Why would you even offer it?   It turns out that something very interesting happens when this seemingly irrelevant option is eliminated.  When another 100 students were offered only two choices: “Electronic Only” and “Electronic and Print”, 68 chose “Electronic Only” while only 32 chose “Electronic and Print.”   

The presence of an irrelevant option influenced a more than 250% increase in customers choosing the more expensive alternative!!!

Ariely observed the following, “Thinking is difficult and sometimes unpleasant.” Cues that allow us to establish the relative value of various offerings, then, reduce the cognitive load or effort required to think about your options.  What the Economist offered was a no-brainer; while we can’t be certain that the print subscription is worth more than twice the electronic version, the combination of the two was clearly worth more that the print version alone.

Choice Architecture:  Designing Choices that Influence Customer Behavior

Customers always have choices.  Choice architecture is the deliberate design of both the choices and the context for those choices in order to influence a person’s behavior.  The most obvious, classic examples of choice architecture come from the design of retail stores and merchandise displays, restaurant menus and buffet lines, print and online catalogues, etc…  I got my start in customer experience 25 years ago designing store layouts, merchandise displays, signage, and promotions that increased customer profitability.   I’ve learned that there are three components that need to be addressed: 1) the Choice Design (the customer options including the information provided about those options), 2) the Choice Pathways… the sequence or placement of those choices in time and space, and 3) the Choice Environment including peripheral cues like signage, lighting, other people in privacy/public space, etc…

Let’s look at a simple illustrative case.  A well-designed restaurant menu can be a great example of choice architecture based on sophisticated menu psychology.   It turns out that there is a predictable Visual Choice Pathway people typically follow when they read a menu.  For example, when most people open a four page menu, their eyes go first to the top of the page on the right side.  A smart menu designer generally places one of the highest profitability items at the top of this page.  Then, most people’s eyes will move down towards the center of that same page.  An even smart(er) menu designer will put the most expensive item towards the center of the page… not because they think the customer will order it… but because it will tend to prime the customers’ expectations about what they’re likely to spend.  In most cases, customers will then look at the items immediately above and below the most expensive item.  Those two items immediately above and below the most expensive item are deliberately two of the most compelling selections on the menu… and are the most commonly ordered items designed to generate the most profit on the menu.  There have been numerous examples of restaurants that have been able to significantly shift their average ticket size based on the design of the menu.  (See:  Reading Between the Lines: The Psychology of Menu Design or Basics of Menu Psychology).

A similar thing happens in high end retail boutiques.  The sight of those $295 jeans (I still can’t believe it!) subtly prime the customer to feel that $125 jeans are a bargain.   The $295 jeans sell a lot more $125 jeans.  We’ve seen the same sort of thing in jewelry stores, hospitality companies, and many other diverse situations.

Although these examples are intriguing, it’s important to recognize that examples of choice architecture are literally everywhere.   For example:

  • The design of an election ballot is an example of choice architecture. Experiments have shown, if a candidate is listed first on the ballot, he may well get a 4% increase in votes.
  • When a doctor describes alternative treatments available to a patient, it is also an example of choice architecture. Research has shown that if a doctor says 90% of patients are alive five years after a certain procedure, far more people opt for that procedure than if the doctor says 10% of patients are dead five years after having it.

Choice architecture applies just about any product or service company that offers alternatives to their customers.   This can be anything from insurance companies that offer coverage options, banks that offer different financing or deposit products, business services firms that propose alternative approaches to their clients, etc…

Unfortunately, most companies don’t think about choice architecture effectively… actually in most cases, they don’t think about it at all.  Often a company will just throw a bunch of alternatives at their customers and count on the customers to sort it out.  As a result, they miss significant opportunities to drive additional revenue and profit.  The most important starting place is to understand much clearer how customers make decisions and design an experience that fits the way customers think (i.e.,  Design from the Mental Model of the Customer).  See:  Optimizing the Most Critical Elements of the Customer Experience: Customer Choices and Cognitive Ergonomics: Framing and Priming the Customer Experience.

This is an area that is getting an increasing amount of academic attention. Richard Thaler, Director of the Center for Decision Research at the University of Chicago Graduate School of Business, and Cass R. Sunstein are authors of the excellent book, Nudge: Improving Decisions About Health, Wealth, and Happiness (see also:  Designing Better Choices (LA Times Commentary) by Richard H. Thaler and Cass R. Sunstein).  Thaler and Sunstein provide several interesting examples of how organizations can improve the decision making effectiveness for their customers and employees.  This includes:

  • If we want to increase savings by employees, employers might … enroll them automatically in a 401k plan, unless they specifically choose otherwise.
  • If we want to increase the supply of transplant organs in the United States, we could assume that people want to donate, rather than treating non-donation as the default.
  • If we want to increase charitable giving, we could give people the opportunity to join a plan, in which some percentage of their future wage increases are automatically given to charities.
  • If we want to respond to the recent problems in the credit markets, we could design disclosure policies that ensure consumers can see exactly what they are paying and make easy comparisons amongst their possible options.

Thaler and Sunstein describe three key elements that are important to designing a choice architecture that leads to better results for individuals and society:

  1. Default Design. Whatever you chose as the default option has the highest likelihood of being selected.  For example, the states that have organ donation as the default option when individuals get a drivers license have a much higher acceptance rate.  In fast food restaurants, highly profitable combo meals have become the default option… customers often need to explicitly ask for just the burger. Design architects need to pay careful attention to the default option.
  2. Providing Feedback. People respond to feedback about their decisions.  For example, in some markets electric utilities are starting to provide specially designed bulbs (called orbs) that glow red as homes use higher levels of energy.  These devices have influences customers consumption behavior and have proven to reduce energy use during peak periods by 40% in Southern California. (find reference and make sure I’m using the right terminology)
  3. Anticipating Errors. People make mistakes and it’s possible to design a choice architecture which anticipates these mistakes and thus leads to better outcomes.  Thaler and Sunstein have been promoting the example of “Save More Tomorrow” programs, which help employees set aside future pay hikes for retirement. “Save More Tomorrow is based on the same principle of expecting error,” he said. “We ask people if they want to commit now to saving more later, because all of us have more self-control in the future. The first company that adopted it tripled savings rates, and the program is now spreading.”  They also use the example of the Paris subway card, which allows users to insert it into an electronic turnstile in any of four ways to gain entrance to the subway.  Compared that to most payment kiosks in which there are 4 possible ways to insert your credit card… only one of which will work.

This is a topic with a lot of subtlety and power… if you’re looking for additional practical insights, feel free to post a reply or get in touch.  In summary…

If you offer customers options and you don’t think about choice architecture…

…you are almost certainly missing significant opportunities to improve profitability.

Framing and Priming the Customer Experience

I’ve gotten accustomed to taking my car to the Jiffy Lube near my house.  Over the 30 years that I’ve been driving, I’ve had the full range of good and bad experiences with auto service shops.  However, this Jiffy Lube has a distinctive and effective way of interacting with me regarding the cost of my service.  At the end of each visit, they bring me over to a terminal that we can look at together – side by side; they walk me through each of the service elements that were performed along with the cost of each service; then they apply a series of discounts to the individual services, as well as, loyalty discounts that consistently bring my total cost down to about 60-70% of sum of the individually itemized costs.   I have always walked out of that particular Jiffy Lube feeling like I’ve saved money and that they appreciate my business.    I’ve also always walked out feeling like many of the companies I advise could learn a lot from that relatively simply but very well designed and deliberate interaction.

This interaction is an example of category of experiential design levers called framing effects.  Rather than just presenting the price, Jiffy Lube framed it in a way that highly influenced my experience of saving money.  There are a wide set of framing effects that influence how people interpret and evaluate their experiences.  For example, consider the following two scenarios:

  1. You live around the corner from an electronics store that carries the new computer speakers you’ve been looking at for $100.  You also learn that a discounter, located ten miles from your house, has a special on the same speakers for half price: $50. Do you drive the 10 miles?
  2. You live near an electronics store that carries the new computer you’ve wanted for $2000. Ten miles from your house, another store is carrying the same computer for $1950… a savings of $50.  Do you drive the 10 miles?

As you might guess, research has shown that many customers who would make the drive for scenario 1 might not for scenario 2.  On a rational level, this makes little sense since the value of the drive is identical:  $50.  However, a $50 savings on a $100 item is framed differently than a $50 savings on the much more expensive item.

If you consider how we process the experiences we have, it’s easy to see that it’s far from rational or logical.  Our experiences are highly influenced by subconscious shortcuts that have an enormous influence on how we think, feel, and act.  Many of these shortcuts lead to apparent contradictions with what you’d expect from a more rational decision maker.  This post will cover some of the tools for positively influencing both the quality and profitability of the customers’ experience.

Pioneering behavioral economists Daniel Kahneman and Amos Tversky conducted extensive research into framing effects.  One of the other frames they studied involves loss aversion.  For example, if you were offered a gamble with a 10% chance of winning $95 and a 90% chance of losing $5… would you take it?  Most people would not.  Now suppose you were offered the chance to buy a $5 lottery ticket for a 10% chance of winning $100.  Many of the people that rejected the first alternative would accept the second despite the fact that the expected value of each alternative is exactly the same:  $5.  However, the alternative that involves voluntarily paying $5 rather than taking a chance of “losing” $5 is framed differently.

Loss-aversion framing also contributes to the fact that many customers do not make purely rational decisions regarding insurance.  For example, the expected value of many insurance policies is generally in the neighborhood of 50-60%.  You might compare this to the return on putting your money into a slot machine… an expected value of 90%.  In general, the most economically rational decision is to self-insure to the extent possible and only buy insurance as necessary to cover catastrophic events.

In addition to framing effects, another influence lever in the design of the customer experience is priming.  Priming involves activating an association in memory just before a person completes an action or task.  In an interesting experiment, also conducted by Kahneman and Tversky, subjects were asked to provide the last four digits of their social security number.  They were then asked to estimate the number of doctors in Manhattan.  Very surprisingly, the estimates that subjects gave were positively correlated with the last four digits of their social security number; people with high social security numbers gave higher estimates and people with lower social security numbers gave lower estimates.

In a similar experiment, subjects were asked the last two digits of their social security number and then asked what they would be willing to pay for a consumer product (e.g., bottle of wine, wireless computer keyboard, video game).  Similarly, the price customers were willing to pay was positively correlated with the (random) digits of the customers’ social security number.  For example, subjects with social security numbers in the bottom 20% priced a bottle of Cotes du Rhone wine at $8.64 versus subjects with social security numbers in the top 20% who priced the same bottle at $27.91.  (See: “Tom Sawyer and the Construction of Value” by Dan Ariely, George Lowenstein, and Drazen Prelec).

Good sales people understand how priming creates an “anchor point” that affects a customer’s subsequent decisions.  If I’m selling men’s suits, the first suit I’ll show a customer will be well above the price I’d expect the customer to pay.  As I show the customer that suit, I’ll make sure the customer knows that I’ll find something that meets their needs, so as not to scare them away.  However, in most cases, the higher the price of the first item I show, the higher the customer will end up paying for the item they eventually choose.

In working with a leading retailer, we looked at the impact of signage on drawing customers into the store and influencing their eventual purchase.  We found that signs signaling a lower price at the store entrance would draw customers into the store while progressively higher priced signs as the customer moved further into the store increased the chances that customers would be willing to pay for higher priced items.

Several years ago, I had the chance to work with Christine Boskoff, who was one of the most successful high-altitude mountain climbers in the world and the owner of the leading outdoor adventure travel company named Mountain Madness.  Her question was how to improve word of mouth about Mountain Madness in order to attract new clients.  The recommendation I developed with her was that, on the last day of each trip, there should be a final celebration involving a ceremonial round of “storytelling.”  In this storytelling ceremony, each participant would have a chance to share the personal story of their adventure, what it meant to them, and what their most positive takeaways were.  The act of telling their own story, in addition to listening to the stories of others, has a powerful effect to prime and prepare clients with the “personal legends” they’ll share with others when they get home.  In the course of telling and retelling these legendary stories the most compelling aspects are typically “sharpened” while any of the less positive or inconsistent aspects are “leveled” in order to fit with a more compact storyline.

Framing and priming effects operate at a predominantly subconscious, reactive level and can have a significant impact on the perceived quality and actual profitability of the customer experience.  For more information on how customer process the experiences they have see:   Designing for Customers’ Reactive, Deliberative, and Reflective Experiences.

Before I go, I’ll leave you with one final priming example:

You have exactly five seconds, not a second more, to multiply:

2 x 3 x 4 x 5 x 6 x 7 x 8

Write down your answer.  Now, ask a friend to multiply, again in exactly five seconds:

8 x 7 x 6 x 5 x 4 x 3 x 2

Now, compare the two answers.  Besides the fact that you both got the answer wrong (the answer is 40,320), you should notice that your answer is smaller than your friends.  If you’re like most people, you started out multiplying 2 x 3 x 4 to get 24… x 5 to get 120… then ran out of time and had to quickly estimate the rest… but didn’t multiply by enough.  Your estimate was primed by the 120.  On the other hand, your friend probably started multiplying 8 x 7 to get 65… x 6 to get 390… before running out of time and having to quickly estimate the rest… but he too didn’t multiply by enough.  His estimate was primed by the 390.

Optimizing the Most Critical Elements of the Customer Experience: Customer Choices

From a business perspective, the most critical elements of the customer experience involve the choices that customers make:  the choice to buy; the choice to recommend; the choice to continue as a customer.  In practice, most organizations have insufficient insight into how customers consider their alternatives and make choices.  Even worse, many organizations do things that complicate customers’ decisions and create barriers to profitable customer behavior.  In this post, I will provide several frameworks that can help companies understand how their customers decide and inform how to design an experience that removes barriers to profitable customer behavior.

Rational economic theory makes the assumption that:  the more choices customers have, the better.  Certainly, there are several kinds of experiences where an extensive set of options increase the likelihood that customers will be satisfied.  These include:

  • Preference Matching Experiences, in which customers initiate the experience knowing what they are looking for.  For example, if they walk into a video store looking for a particular title, the greater the selection, the more likely they’ll walk out satisfied.  If they go to dinner with a diverse group of friends, all wanting to order their favorite meal, the more items on the menu, the more satisfied people in the group will be.
  • Exploratory Search Experiences, in which customers are “foraging” for novel alternatives that match their unique or even idiosyncratic interests.  The ability to search for and find novel choices similar to other choices they’ve enjoyed in the past are a significant part of the appeal of “long tail” providers like Netflix, Amazon, Apple’s i-Tunes, etc…

However, not all experiences are Preference Matching or Exploratory Search Experiences.  A growing amount of evidence suggests that, in most cases, people have a difficult time managing complex choices.  As the attractiveness of product or service alternatives rises, people experience conflict and, as a result, may put off making a decision, choose the default option, or simply opt out.  Research suggests that as the number of alternatives increases, people simplify their decision making processes by relying on heuristics, they tend to consider fewer alternatives, and process a smaller fraction of the available information regarding those alternatives.

Emerging neuroeconomic research supports a more information-processing approach based on bounded rationality.  This research demonstrates that decision makers have limitations based on both their level of motivation and their capacity for processing information; including limited working memory and computational capabilities.  The fact is, people today are overwhelmed with activities, information, and choices.  The challenge has become how to manage this complexity and keep things simple.  Evidence supports the conclusion that “choice overload” can be a barrier to profitable customer behavior.

In one representative experiment, conducted by Iyengar and Lepper, consumers shopping at an upscale grocery store were presented with a tasting booth that displayed either a limited selection (6) or an extensive (24) selection of different flavors of jam.  The experimenters measured both customers’ initial attraction to the tasting booth and their subsequent purchase behavior.  While the extensive choice booth attracted more customer attention, customers presented with the limited set of choices were 10 times more likely to make a purchase.  Customers that sampled from the limited choice booth made a purchase 30% of the time versus only 3% of the time from the extensive choice booth. Leading companies are really starting to understand this.  P&G, for example, reduced the number of versions of Head and Shoulders shampoo from 26 to 15, and, in turn, experienced a 10% increase in sales.

As the complexity of the information and choice environment increases, people tend to simplify their decision making by relying on more simple rules of thumb or heuristics that reduce that complexity.  For instance, a study of the decision strategies of people presented with three, six, or nine alternatives revealed that 21% used an elimination strategy when presented with three options, 31% used an elimination strategy when presented with six options, and 77% used an elimination strategy when presented with nine options.

It’s helpful to consider a few basics regarding how people make decisions.  One way to look at it is that decision making can be characterized at four levels, based on the complexity of an individual’s goals and the intensity of their involvement:

  • Level 1 – Recognition-Based Decisions. This includes many of the quick and largely automatic, unconscious, or habitual decisions people make every day. When these decisions are made, the person does not pay much attention to attractiveness; they simply “know” from earlier experience what decision to make in a particular situation.
  • Level 2 – Simple Attractiveness-Based Decisions. This includes decisions made with reference to one or a few attractiveness attributes favoring the chosen alternative. These decision problems do not involve conflicts between attributes and often the solution is quite obvious the customer. These decisions may still be driven by habit or affect (feeling). They also may be made as quickly as Level 1 decisions.
  • Level 3 – Alternative-Based Decisions. These decisions involve choices between alternatives with either goal conflicts. In most cases, some attributes favor one alternative while some attributes favor other alternatives. Repeated decisions at Level 3 may become transformed to Level 2 or even Level 1. Most of the existing research addresses problems at this level.
  • Level 4 -Innovative Problem Solving Decisions. In these situations, alternatives are not fixed, nor is there a set of attributes that characterize these alternatives. At this level, creative problem solving is an important sub-process that leads to the generation of alternatives to be considered.

In most cases, customers would prefer to make decisions at the lowest possible level that yields a solution that meets their needs.  Customers can’t engage in alternative based evaluations or innovative problem solving as part of every experience.  In some ways, this contradicts the “buzz” on customer co-creation.  I’ve had smart people suggest that the whole idea of customer experience design is outdated because customers should just be able to design, configure, or co-create their own experiences.  I believe customer co-creation is one of those management concepts that is in the irrational exuberance phase.  There is certainly an important role for co-creation, however, across the wide range of experiences, the ability to navigate more of them on automatic pilot is the key to survival in the customers’ world of expanding complexity.

Researchers have compared customer expeiences that offer a limited, more psychologically manageable, versus an extensive, more psychologically excessive, number of alternatives and found that while experiences offering extensive alternatives may be initially perceived as desirable, they often create barriers to customers making choices and feeling satisfied with those choices after the fact.

Customers in extensive-choice situations tend to describe their decision-making process as being more enjoyable because of the wide-open opportunity it gives them but also more difficult and more frustrating.  In addition, extensive-choice participants report being more dissatisfied and having more regret about the choices they’ve made than did limited-choice participants.  This is particularly true in situations where customers feel they must make a choice for the objectively best option… rather than one that just reflects their unique personal preferences.

Understanding How Customers Make Decisions

Customers follow decision strategies that are dependent on the situation, their goals, and their persona. Rather than an invariant approach to solving choice problems, customers leverage a wide range of approaches, often developed on the spot.  Since decision makers generally cannot process all of the available information in a particular situation, they develop problem representations by filtering or restructuring the available information.  Hence, which information is selected for processing can have a major impact on their choices.

In general, it is not true that customers follow complex decision processes for complex, high involvement decisions.  In fact, as the complexity of the decision increases, the complexity of the decision process often decreases.  As decision situations become more complex, customers use rules of thumb or heuristics to reduce the complexity of the options and the information they must consider.  For example, options that are superior on the most prominent of a small set of attributes are favored as the decision task becomes more complex.

The decision process that customers follow and the options they select, will depend on the extent to which customers’ goals are:  minimizing the cognitive effort  required for making a choice, maximizing the accuracy of the decision, minimizing the experience of negative emotion during decision making, and maximizing the ease of justifying the decision, or some combination of such goals.

The way customers make choices is also highly dependent on the way their choices are presented or framed.  This creates a significant opportunity for providers that understand the psychology of their customers’ decision processes to present options in a way that improves the customer experience and drives additional revenue.  One of the ways to do this has to do with understanding customer attention.  There are two different types of attention:  voluntary and involuntary.  Voluntary attention is devoted to information perceived to relevant to the customer given their current goals.  Individuals will devote effort to examining information they believe will help them attain whichever goals are more heavily weighted in that situation.  However, attention also may be captured involuntarily by aspects of the environment that are surprising, novel, unexpected, potentially threatening, or extremely salient, thus exemplifying one aspect of accessibility.  For example, changes and losses may be particularly salient and particular problem representations may make certain aspects stand out and gain involuntary attention.  Thus, attention and selectivity can be influenced both by goal driven and more involuntary perceptual factors.

Level 3 decision strategies can be characterized based on the overall amount of information considered, the selectivity or comprehensiveness of attributes that are considered, whether the customer focuses on their top down alternatives or bottoms up attributes, and whether the customer makes cross-attribute tradeoffs.  (See Bettman, James R., Mary Frances Luce, and John W. Payne, “Constructive Consumer Choice Processes“)  Common Level 3 decision strategies include:

  • Weighted Adding.  This consists of considering one alternative at a time, examining each of the attributes for that option, multiplying each attribute’s subjective value times its weighted importance and summing these products across all of the attributes to obtain an overall value for each option.  The alternative with the highest value would be the one that is chosen.  Because weighted adding involves extensive information processing and explicit tradeoffs, it is often considered to be more the most effective approach.  However, customers don’t generally follow this approach because it places significant demands on their working memory and computational capabilities.  Nevertheless, weighted adding is the decision model that underlies many of the techniques used by marketing researchers to assess preferences.  Note: An Equal Weight Strategy is a variation of Weighted Adding, in which there is an implicit assumption that each attribute is of roughly equal importance.
  • Most Important Attribute Selection.  This strategy provides a strong contrast to weighted adding:  the alternative with the best value on the most important attribute is simply selected (assuming there were no ties on that attribute).
  • Satisficing.  Involves finding the first “good enough” option.  Options are considered sequentially, in the order in which they are encountered.  The value of each important attribute for the current option is considered to see whether it meets some sort of cutoff level for that attribute.  If the attribute fails to meet the cutoff level, the option is rejected, and the next option is considered.  One implication of satisficing is that the option chosen can be significantly influenced by the order in which the options are encountered.
  • Elimination by Aspects.  Combines elements of both the most important attribute and satisficing strategies.  Elimination by aspects rejects options that do not meet a minimum cutoff value for just the most important attribute.  This elimination process may be repeated for the second most important attribute, with processing continuing until a single option remains.
  • Majority of Confirming Dimensions.  Involves alternatives that are processed as pairs, with the highest values of the two alternatives compared on each attribute, and the alternative with a majority of winning (better) attribute values is retained.  The retained option is then compared with the next alternative from the consideration set, and this process of pairwise comparison continues until all the alternatives have been evaluated and one option remains.
  • Feature Voting is a simple approach that just counts the number of good and bad features characterizing each of the alternatives and then selects the alternative with the greatest number of good and/or the fewest number of bad features.
  • Choice Heuristics.  Individuals often use a repertoire of rules of thumb or heuristics for solving decision problems.  These heuristics are acquired through experience, imitation, or training.  This could include customers that will “pick the second least inexpensive alternative (e.g., CD player, bottle or wine) from a brand whose name I recognize.”

Customers frequently use combinations of these strategies.  A typical combined strategy might have an initial phase in which some alternatives were eliminated and a second phase where the remaining options are analyzed in more detail.  One frequently observed strategy combination is an initial use of Elimination by Aspects to reduce the choice set to two or three options followed by a compensatory strategy such as weighted adding, to select among the remaining options.

 The Search for Dominance Structure

One very interesting decision models that appears to fit well with what customers frequently do is called the Search for Dominance Structure.  The key idea is that a decision maker will attempt to structure and restructure information about attributes in such a way that one of the alternatives becomes the obvious choice… because that alternative dominates the other alternatives on key attributes.  The to-be-chosen alternative has one or more clear advantages and all the major disadvantages of that alternative have been either neutralized or deemphasized.  (See:  Montgomery, Henry, “Decision Making and Action:  The Search for a Dominance Structure” in the book, “The Construction of Preference“)  This search for dominance appears to go through four phases:

  • Pre-editing typically occurs early in the decision process.  In this phase, the decision maker attempts to simplify the decision problem by selecting those alternatives and attributes that should be included in the representation of the decision situation.  There is ample evidence that decision makers attempt to simplify the decision by focusing on a limited subset of attributes, by rounding off information about attribute levels, and by screening out alternatives that fall short on important attributes.
  • Finding-a-promising alternative.  In this phase, the decision maker finds a candidate for his or her final choice.  An alternative that appears to be more attractive than other alternatives on an important attribute may be selected as a promising alternative.  When a promising alternative has been found the decision maker has formed a preference, albeit a temporary one, for a particular alternative.  Increasingly preferential attention is paid to this alternative.  The question is whether the decision maker can justify a decision to choose this alternative.  The question is dealt with in subsequent phases of the decision making process.
  • Dominance testing.  This implies that the decision maker tests whether the promising alternative dominates the other alternatives.  These tests could be more or less systematic or exhaustive.  If the promising alternative is found to be dominant, it is chosen and the decision process ends.  The fact that the decision maker manages to increase the support for the chosen alternative does not necessarily mean that the alternative dominates its rivals.
  • Dominance structuring.   If a violation of dominance if found, the decision maker continues to this phase, in which he or she attempts to neutralize or counterbalance the disadvantage(s) found for the promising alternative.  These attempts are based on various operations.  There are four dominance structuring operations:
    • The decision maker may deemphasize a disadvantage by arguing that the probability of the disadvantage is very low and that it could be controlled or avoided in one way or another.
    • Another possibility is to bolster the advantages of the promising alternative and in this way indirectly deemphasize the disadvantages.
    • In the cancellation operation the decision maker attempts to find dominance by canceling a disadvantage by relating it to an advantage that has some natural connection to the disadvantage in question.
    • Finally, the decision make may find a dominance structure by collapsing two or more attributes into a new, more comprehensive attribute.

It is also possible that the decision maker may restructure the problem in a way that reframes existing alternatives or creates new alternatives.  If the decision maker fails to find a dominance structure he or she may go back to the previous phase and make a new start in the search for dominance or he or she may postpone the decision, if possible.  Decision makers continue differentiating and structuring after the decision.  This is called consolidation and is important to reduce dissonance, disappointment, regret, etc…

There are numerous examples of how the customer experience can be tuned to match the way that customers’ actually make decisions.  For example, one of our health insurance clients was able to significantly increase client retention by reducing the number of renewal options offered to each client from over 100 to 4.  Previously, renewal packages sent to existing clients might be over 40 pages long.  In the new design, each client was offered four basic options:  same benefits as the current plan at a new price, same price for a minimal adjustment in current plan benefits, and two new plans at a marginal discount or increase compared to the current price.  For any given client, these four options represented the most likely renewal choices the client would consider.  As a result, the client received a one-page renewal summary that fit with their decision logic.

In summary, from a business perspective, the most critical elements of the customer experience involve the choices that customers make:  the choice to buy; the choice to recommend; the choice to continue as a customer.  This post provided several frameworks that can help companies understand how customers decide.  As always, comments and suggestions are appreciated.

Novelty Seeking and the Design of Differentiated Experiences

Over millions of years of human development, our ability to predict has translated into our ability to survive.  We live in an inherently unpredictable world.  As a result, we have evolved a strong motivation to learn in a way that improves our predictions.  Not only does this motivation lead to a clear survival advantage, but, in a social setting, learning how to better predict other people’s behavior leads to small group cooperation and to attracting the fittest members of the opposite sex.  Our drive to predict leads to an overarching behavior – novelty seeking.

Brains want novelty.  This was first observed by Wilhelm Wundt, one of the founding fathers of the field of psychology, in the 19thcentury.  Wundt observed that the more complicated an experience is, the more a person will be stimulated by it.  Up to a certain level; at which point the experience starts to get overwhelming.  He described this diagrammatically as a bell-shaped curve, called the Wundt Curve, showing the state of arousal increasing as experiential complexity increases up to a point at which arousal starts to decrease as complexity continues to increase.

This explains why experiences with intermediate levels of complexity are generally the most pleasurable.  Why a movie whose plot is unpredictable, but not too unpredictable.  Why it’s pleasurable to listen to music that strikes a balance between predictability and novelty.  Why humor that helps us see things differently is inherently engaging.

Novelty seeking is actually hard-wired into the way your brain works.  Novelty seeking is stimulated by the neurotransmitter dopamine.  In a way, dopamine is the driver of all experience.  It works like a key for unlocking one of the most critical parts of your brain:  the striatum, which contains the highest concentration of dopamine receptors.  This is well described in two outstanding books: Greg BernsSatisfaction:  Sensation Seeking, Novelty, and the Science of Finding True Fulfillment and Read Montague‘s Why Choose this Book?  How We Make Decisions.

The striatum is where the interaction between you as an individual and the environment happens.  It works like a switching station with many inputs from other parts of your brain but limited capacity.  As a result, only a few signals can get through at any point in time.  What makes it through has to do with dopamine.  Dopamine is a chemical “reward” predictor that encourages your striatum to pay particular attention to novel input signals.  This interaction commits your motor system to a course of action, selected from the many different possibilities.  It produces your ability to decide what you want to do.

Doing something just past the edge of your predictability zone releases dopamine.  As a result, novel information flows through your striatum.  This, in turn, forces you to act on the information and, subsequently, reinforces the motivational system.

However, too much novel information creates an overload and a lack of attention.  The point at which too much information becomes… too much information… is related to the capacity of working memory.  It’s been demonstrated that people can maintain no more than 7+/- 2 chunks of information in working memory at any point in time.  By the way, this is why AT&T originally determined that telephone numbers should have 7 digits.

What are the implications for designing customer experiences?  For the past several years, we’ve been focusing our clients on the development of a small set of “Signature Experience Elements” that customers will perceive as a “difference in kind” and that fit with the overarching purpose of the organization.  Typically we design to no more than 5-7 Signature Elements that are aligned with the purpose or story the experience is trying to tell.  Sticking to this relatively small set of highly novel elements, it’s possible to create experiences that are closer to the optimum point of the Wundt Curve… (aka,  wundt-erful experiences).  The natural tendency for many organizations are to invest too heavily in a large number of incremental improvements that don’t stimulate the customers’ desire for novelty seeking.

For example, Whole Foods Market has a small number of signature experience elements that reinforce their “Whole Foods, Whole People, Whole Planet” positioning and are perceived by customers’ as a difference in kind.  These include:  organic food, artful food presentation, local growers, educational signage, novelty seeking selection, and premium pricing.

Another client example is a major jewelry store chain, whose brand story is “The Perfect Gift, Guaranteed.”  This company’s signature elements included:  a distinctive welcome, creative and consultative gift advice, coaching the customer on how to romance the gift, and a wow process for returns.  Each of these signature elements was designed to get the customers attention and contribute to them really internalizing the desired brand story.

In addition, predictable experiences lead to habituation.  Changes in happiness or satisfaction are driven by relative changes from our recent past.  This is why, as we adjust to any positive change in our circumstances, satisfaction or happiness fades.  Social psychologist Philip Brickman describes this as the hedonic treadmill; we need to seek higher levels of reward in order to maintain the same level of satisfaction.

Some sensations habituate more quickly than others.  For example, we tend to quickly get used to changes in their financial status.  A positive improvement in financial fortunes leads to a short term increase in the feeling of satisfaction followed quickly by a return to indifference.

This may be one of the reasons why structured loyalty or rewards programs tend to drive rational repeat purchase behavior but not necessarily higher levels of loyalty.  People habituate to rewards quickly when the rewards are relatively predictable.  However, I’ve observed that people respond more positively to rewards when the rewards are novel, unexpected, and authentic.

Personal relationships tend to habituate more slowly.  The balance of predictability and novelty is an issue in long-term relationships.  After a long time together, two people get too good at predicting each others responses.  And they also become more certain that they “know” the other person’s underlying intentions.  This can be both comforting and highly constraining.   As people get to know each other, they may lose their sense of novel individuality.  People tend to believe that relationship harmony depends on stability and constancy.  This is an issue.  While novelty in a relationship may be inherently destabilizing, it is essential to the maintenance of any long-term relationship.  This is as true for business relationships and collegial relationships, as it is for married relationships.

In future posts, I’ll describe the implications of other neuromodulated processes (Harm Avoidance, Reward Dependence, and Persistence) that influence how people experience the world, as well as, provide guidance for the design of the most compelling customer experiences.

How Customers’ React to Violations of Justice

A couple of months ago, the Harvard Business Review carried a great article “Companies and the Customers Who Hate Them” by Gail McGovern and Youngme Moon.  In this article, the authors describe several situations where companies generate a significant portion of their profit by penalizing customers for bad behavior.  Examples cited by the authors include:

  • Video rental stores that generate a significant portion of their profits from late fees
  • Credit card companies that approve rather than decline over limit transactions and then charge the customer fees
  • Banks that present checks in reverse order of magnitude to increase the likelihood that more checks will be drawn against insufficient funds
  • Cellular providers that lock customers into lengthy contracts rather than creating loyalty through good service.

In addition to the examples cited in that article, there are no shortage of others including:

  • Car dealers that raise the price of popular models above list if there is a shortage.
  • Stores that raise the price of umbrellas when it’s raining or snow shovels when it’s snowing.

While leveraging antagonistic customer practices can generate higher profits in the short term, it also creates a competitive risk as customers can quickly migrate to more customer-friendly offerings from competitors as they arrive on the scene.

Potentially more important is a growing body of research that indicates customers will actively find ways to penalize companies they believe have treated them unfairly.  These penalties include defection and negative word of mouth (often using electronic means that now reach hundreds if not many thousands of other potential customers).

Customers intuitively and automatically sense when they are engaging in relationships that aren’t fair at some basic level.  The evolutionary path of the human brain has reinforced the development of instinctual, subconscious mechanisms for recognizing fairness in individual or group exchanges.  This capability dramatically improved the success of our hunter-gather ancestors who relied on cooperative group behavior for survival.  Every one of us has had emotional experiences of situations being “just not fair,” even if we have a hard time putting our finger on why we feel that way.  Usually our automatic emotional experience and resulting feeling of injustice happens before we can consciously label that feeling with some rational explanation or principal that tells us why it’s not fair.

One of the simplest ways to observe our instinctual fairness response is the Ultimatum Game.  This is a one-round bargaining game played by two people.  The first person, called the Proposer, is given a sum of money, say 100 dollars.  The Proposer then makes an offer to split some of the money with the second person, called the Responder.  The Responder can either accept the offer, in which case the two players each get their share, or reject the offer, in which case both players get nothing.  Since this is a one-round game, the only rational choice for the Responder is accept any non-zero offer.

However, the actual results of playing the game are very different.  In most cases, Responders reject non-zero offers that are perceived as “unfair” splits.  This experiment has been done across very different cultures and the results are essentially the same.  Non-zero offers are rejected at a rate that increases as the offer size decreases.  The overwhelming insight is the people feel an automatic, instinctual need to penalize unfairness even if that behavior involves a personal cost to them.

The Ultimatum Game is just the start.  There are a wide range of situations that reinforce the automatic drive that people have to penalize unfairness.  In essence, people are willing to spend their own capital (money, time, energy, etc…) to penalize others that treat them in ways that they perceive as unfair.  In his book “Passions Within Reason,” Robert H. Frank emphasizes that people “often do not behave as predicted by the self-interest model.”

The emerging field of neuroeconomics looks at the neuropsychological basis for decision making that does not follow rational economic theory.  It appears that our subconscious, automatic reactions to violations in social exchanges is handled by a particular area of the brain – the anterior insula.  Brain imaging of players in the Ultimatum Game demonstrate stronger activations in the anterior insula as the Responder is presented with increasingly unfair splits.  The anterior insula is also activated when people are shown objects and situations that they find disgusting.   This is one of the reasons why many people experience being treated unfairly as similar to feelings of disgust.

Across the research that’s been done in this area, three types of “justice” are important to consider in the customer experience:

  • Distributive justice. Does the customer perceive the outcome they received to be fair given either their perceived investment or what they believe has been received by other customers?
  • Procedural justice. Was the process that was used to arrive at the outcomes fair?  Did the customer see that their time was treated as highly valuable or did they believe they had to wait too long?  Were others who arrived after me served first?
  • Interactional justice. Was the customer treated fairly and with respect by the individuals that they encountered?

How different customers perceive, interpret, and evaluate violations in justice are personae dependent.  The basic components involved in understanding these different customer personae is covered in the post “Cognitive Ergonomics:  Designing Experiences that Fit the Customers’ Mental Model.”  For example, a customers’ temperamental orientation towards Harm Avoidance acts as an amplifier in automatic reactions to perceived violations of justice.  In addition, more Reward Dependent customer personae tend to react more strongly to perceived violations in Interactional Justice.  In general, the way you design interactions with customers have to be sensitive to the personae of the target customers.

Today customers 1) have an increasing ability to communicate their dissatisfaction with other customers and 2) base more of their purchase decision on word of mouth. Regardless of the company’s policy or the fine print on the back of the service agreement, if any company doesn’t design what they do to be highly sensitive to creating an experience that customers’ perceive as fair is just…  “roadkill waiting to happen.”