Not All Customer Experience Variation is Equal: Use Control Charts to Identify Actual Changes in the Customer Experience
Variability in customer experience scores is common and normal. Be it a survey of customers, mystery shops, social listening or other customer experience measurement, a certain amount of random variation in the data is normal. As a result, managers need a means of interpreting any variation in their customer experience measurement to evaluate if the customer experience is truly changing, or if the variation they are seeing is simply random.
One solution to this need is control charts. Control charts are a statistical tool commonly used in Six Sigma programs to measure variation. They track customer experience measurements within upper and lower quality control limits. When measurements fall outside either limit, the trend indicates an actual change in the customer experience rather than just random variation.
To illustrate this concept, consider the following example of mystery shop results:
In this example the general trend of the mystery shop scores is up, however, from month to month there is a bit of variation. Managers of this customer experience need to know if July was a particularly bad month, conversely, is the improved performance of in October and November something to be excited about. Does it represent a true change in the customer experience?
To answer these questions, there are two more pieces of information we need to know beyond the average mystery shop scores: the sample size or count of shops for each month and the standard deviation in shop scores for each month.
The following table adds these two additional pieces of information into our example:
|Month||Count of Mystery Shops||Average Mystery Shop Scores||Standard Deviation of Mystery Shop Scores|
Now, in order to determine if the variation in shops scores is significant or not, we need to calculate upper and lower quality control limits, where any variation above or below these limits is significant, reflecting an actual change in the customer experience.
The upper and lower quality control limits (UCL and LCL, respectively), at a 95% confidence level, are calculated according to the following formulas:
x = Grand Mean of the score
n = Mean sample size (number of shops)
SD = Mean standard deviation
Applying these equations to the data in the above table, produces the following control chart, where the upper and lower quality control limits are depicted in red.
This control chart tells us that, not only is the general trend of the mystery shop scores positive, and that November’s performance has improved above the upper control limit, but it also reveals that something unusual happened in July, where performance slipped below the lower control limit. Maybe employee turnover caused the decrease, or something external such as a weather event was the cause, but we know with 95% confidence the attributes measured in July were less present relative to the other months. All other variation outside of November or July is not large enough to be considered statistically significant.
So…what this control chart gives managers is a meaningful way to determine if any variation in their customer experience measurement reflects an actual change in the experience as opposed to random variation or chance.
In the next post, we will look to the causes of this variation.
For many brands, this pandemic represents a moment of truth with their customers. Moments of truth are specific experiences of high importance, where a customer either forms or changes their opinion of a brand in meaningful and lasting ways. Customers are stressed. They feel uncertainty, fear and, frankly, exhaustion. This uncertainty and fear drives customers to seek shelter from resources they trust. Brands which become a trusted resource, which provide comfort, true comfort, in the face of this crisis have an opportunity to not only do the right thing, but cement their customers’ relationship with the brand. On the other hand, brands which fail to do so, risk destruction of their customer relationships.
Perhaps the most important way brands can respond to the moment of truth presented by this crisis is showing true care for: customers, employees, and the community.
Additionally, it is imperative that customers feel safe. Based on current science, in-person interactions can be relatively safe if followed within CDC and public health guidance including risk mitigation efforts such as: physical distancing, masks, ventilation, length of exposure, and hand washing & sanitizer.
Using these previous posts as a foundation, we can now address the implications of the pandemic on customer experience measurement.
So…. what does all this mean in terms of customer experience measurement?
First, I like to think of the customer experience measurement in terms of the brand-customer interface where customers interact with the brand. At the center of the customer experience are the various channels which form the interface between the customer and institution. Together, these channels define the brand more than any external messaging. Best-in-class customer experience research programs monitor this interface from multiple directions across all channels to form a comprehensive view of the customer experience.
Customers and front-line employees are the two stakeholders who interact most commonly with each other in the customer-institution interface. As a result, a best practice in understanding this interface is to monitor it directly from each direction: surveying customers from one side, gathering observations from employees on the brand side, and testing for the presence and timing of customer experience attributes through observational research such as mystery shopping.
Measure Customer Comfort and Confidence
First, fundamentally, the American economy is a consumer confidence driven economy. Consumers need to feel confident in public spaces to participate in public commerce. Customer experience researchers would be well served by testing for consumer confidence with respect to safety and mitigation strategies. These mitigation strategies are quickly becoming consumer requirements in terms of confidence in public commerce.
The American economy is
driven by consumer confidence.
Along the same lines, given the centrality of consumer confidence in our economy, measuring how customers feel about the mitigation strategies put in place by the brand is extremely important. Such measurements would include measures of appropriateness, effectiveness, and confidence in the mitigation strategies employed. We recommend two measurements: how customers feel about the safety of the brand’s in-person channel in general, and how they feel about the safety relative to other brands they interact with during the pandemic. The first is an absolute measure of comfort, the other attempts to isolate the variable of the pandemic, just measuring the brand’s response.
The pandemic is changing consumer behavior. This much is clear. As such customer experience researchers should endeavor to identify and understand how consumer behavior is changing so they can adjust the customer experience delivery mix to align with these changes.
Testing Mitigation Strategies
Drilling down from broader research issues to mystery shopping specifically, there are several research design issues that should be continued in response to the COVID-19 pandemic.
Measure Customer Confidence in Post-Transaction Surveys with Alerts to Failures: First, as economic activity waxes and wanes through this coronavirus mitigation effort, consumer confidence will drive economic activity both on a macro and micro-economic level. Broadly, consumers as a whole will not participate in the in-person economy until they are confident the risk of infection is contained. Pointedly, at the individual business level, customers will not return to a business if they feel unsafe. Therefore, market researchers should build measures of comfort or confidence into the post-transaction surveys to measure how the customer felt as a result of the experience. This will alert managers to potential unsafe practices which must be addressed. It will also serve as a means of directly measuring the return on investment (ROI) of customer confidence and safety initiatives in terms of the customer experience.
Measure Customer Perception of Mitigation Strategies: Coronavirus mitigation strategies will become typical attributes of the customer experience. Beyond simply testing for the presence of these mitigation strategies, customer experience managers should determine customer perceptions of their appropriateness, efficacy, and perhaps most importantly, their confidence in these mitigation strategies.
Gather Employee Observations of Mitigation Strategies: Frontline employees spend nearly all their time in the brand customer interface. As such, they have always been a wealth of information about the customer experience, and can be surveyed very efficiently. The post-pandemic customer experience is no exception.
First, as we discussed previously, employees have the same personal safety concerns as customers. Surveys of employees should endeavor to evaluate employees’ confidence in and comfort with coronavirus mitigation strategies.
Secondly, frontline employees being placed in the middle of the brand-customer interface are in perfect position to give feedback regarding the efficacy of mitigation strategies and the extent to which it fits into the desired customer experience – providing managers with valuable insight into adjustments which may make mitigation strategies fit more precisely into overall the customer experience objectives.
Independently Test for the Presence of Mitigation Strategies: All in-person channels across all industries will require the adoption of coronavirus mitigation strategies. Mystery shopping is the perfect tool to test for the presence of mitigation strategies – evaluating such strategies as: designed physical distancing, physical barriers between POS personnel and customers, mask compliance, sanitization, and duration of contact.
Alternative Research Sources for Behavioral Observations: Some customer experience managers may not want unnecessary people within their in-person channel. So the question arises, how can employee behaviors be measured without the use of mystery shoppers? One solution is to solicit behavioral observations directly from actual customers shortly after the in-person service interaction. Customers can be recruited onsite to provide their observations through the use of QR codes, or in certain industries after the event via e-mail. The purpose of these surveys is behavioral – asking the customers to recall if a specific behavior or service attribute was present during the encounter. From a research design standpoint, this practice is a little suspect, as asking people to recall the specifics about an event after the fact, without prior knowledge, is problematic. Customers are not prepared or prompted to look for and recall specific events. However, given the unique nature of the circumstances we are under, in some cases there is an argument that the benefits of this approach outweigh the research limitations.
Test Channel Performance and Alignment
The instantaneous need for alternative delivery channels has significantly raised the stakes in cross-channel alignment. As sales volume shifts to these alternative channels, customer experience researchers need to monitor the customer experience within all channels to measure the efficacy of the experience, as well as alignment of each channel to both each other and the overall brand objectives.
Finally, as more customers migrate to less in-person channels, customer experience researchers should endeavor to measure the customer experience within each channel. As more late adopters are forced by the pandemic to migrate to these channels, they may bring with them a completely different set of expectations relative to early adopters, therefore managers would be well served to understand the expectations of these newcomers to the alternative channels so they can adjust the customer experience to meet these new customers’ expectations.
As commerce migrates away from conventional in-person channels to alternative delivery channels, the importance of these channels will increase. As a result, the quality and consistency of delivery in these channels will need to be measured through the use of mystery shoppers. Some industries are going to be problematic, as their current economics do not currently support alternative delivery. With time however, economic models will evolve to support alternative channels.
This is a difficult time. It will be the defining event of our generation.
The pandemic, and our reaction to it, is dramatically changing how humans interact with each other, and the customer experience is no exception. There is reason to suggests this difficult time could become a new normal. Managers of the customer experience need to understand the implications of the customer experience in the post-Covid environment, as the implications of the pandemic may never fully subside. Customer experience managers must consider the implications of this new normal, not only on the customer experience, but on customer experience measurement.
In summary, the most common cause of spread is believed to be airborne by inhaling virus particles exhaled into the environment. The infectious dose of a virus is the amount of virus a person needs to be exposed to in order to establish an infection. We currently do not know the infectious dose for SARS-CoV-2. Estimates range from a few hundred to a few thousand virus particles. One virus particle will not cause an infection. To be infected one must exceed the infectious dose by either being exposed to a cough or a sneeze. Absent coughs or sneezes, under normal activity one must be exposed to the virus over time to exceed the infectious dose.
This post draws ocorn the foundation of the first to discuss the implications of the pandemic on the customer experience.
Modern day customer experiences exist in a finely tuned ecosystem, where the dramatic changes as a result of the pandemic have off set the delicate balance, causing problems from supply chain disruptions to an immediate shift away from in-person channels.
Furthermore, the pandemic represents what I call a moment of truth regarding the relationship with customers. Moments of truth are specific experiences of high importance, where a customer either forms or changes their opinion of a brand in meaningful and lasting ways. How brands respond to moments of truth, particularly in this time of global crisis, will strengthen or weaken the customers’ relationship to the brand.
Moments of truth are specific experiences of high
importance, where a customer either forms or changes
their opinion of a brand in meaningful or lasting ways.
Customers are stressed. They feel uncertainty, fear and, frankly, exhaustion. Ongoing concern for personal safety, education of children, and the well being of loved ones is exhausting. This uncertainty and fear drives customers to seek shelter from resources they trust. Brands which become a trusted resource, which provide comfort, true comfort, in the face of this crisis have an opportunity to not only do the right thing, but cement their customers’ relationship with the brand. On the other hand, brands which fail to do so, risk destruction of their customer relationships.
Care for all Stakeholders
Perhaps the most important way brands can respond to the moment of truth presented by this crisis is showing true care for stakeholders in the brand: customers, employees, and the community.
Care for Customers
Brands must communicate care for customers. Drawing on a personal example, March of 2020 was a particularly worrisome time for me. At that time, the Seattle area was considered one of the epicenters of the outbreak, mandatory stay at home orders where being introduced – fear ruled – fear driven by uncertainty; uncertainty with respect to the safety of myself and loved ones; uncertainty with respect to the financial future; uncertainty with respect to the state of the entire globe.
Amidst all this uncertainty and fear I received an email from Citigroup entitled “Covid-19. Let us know if we can help.” It communicated personal care for me, encouraged alternative channel use: online, mobile and 24/7 contact center assistance, and contained links to CDC guidance.
A week later the campaign continued with an update on the actions Citigroup was implementing based on the pandemic; again, educating me to digital tools available, offering personal assistance if needed.
Two and a half months later, in June, I received an email expressing “heartfelt thanks” for adapting to changes and remaining loyal. It described ways Citigroup was assisting with a variety of COVID-19 relief, specifically introducing a partnership with celebrity chef Jose Anres’ World Central Kitchen Campaign distributing meals in low-income neighborhoods in big cities like New York, and monitoring the globe for food shortages elsewhere. This not only demonstrated care for me personally, but care for the community.
Care for Communities
Citigroup’s donations to the World Central Kitchen campaign is one example of care for our communities. There are countless examples of brands offering community support.
- A beer brewery, Brewdog, shifted production away from beer to hand sanitizer.
- A Spanish sports retailer donated scuba masks to hospitals.
- EBay offered free services to small business forced to switch from brick-and-mortar to ecommerce to keep their small business afloat – pledging $100 million in support of this endeavor.
Care for Employees
Employees are important. They animate the brand and drive customer loyalty – particularly in moments of truth like these. Research has determined that in many retail and service environments, there is a positive correlation between employee satisfaction and employee retention as well as customer loyalty. They are not immune from the fear and the stress of this crisis. Additionally, frontline employees spend all their time in the brand-customer interface. They are the personal representatives of the brand.
Additionally, given these front-line employees spend the majority of their time in the brand-customer interface, they tend to have a level of understanding about the customer experience that management often misses.
As a result, it is incumbent on brands to attend to the stresses employees are under, demonstrate concern, and develop communication channels for employees to feed customer experience intelligence to management.
I’ve always been an advocate of meeting customers in their preferred channel; meeting them where they are today and delivering a seamless experience. Obviously, over the recent decades there has been a migration from in-person channels to increasing self-directed, alternative channels. The pandemic has immediately accelerated this shift. Be it telehealth, online banking, in-home instruction of our children, or a restaurant delivering through UberEats, providers of all types now face increasing pressure to bring their business to their customers’ homes.
Emotional Well Being
As observed earlier, this pandemic is a moment of truth between many brands and their customers. In our experience, customers primarily want three things from a provider: 1) empathy, 2) care/concern for their needs, and 3) competence. We see this constantly. Customers want to do business with brands that empathize with them, care about their needs, and are capable of satisfying those needs in a competent manner. Brands that seek to attend to the emotional needs of their customers during this moment of truth will earn the loyalty and positive word-of-mouth of their customers.
In-Person Precautions and Mitigation Strategies
While the pandemic has accelerated an ongoing transition to alternative channels, some industries require an in-person experience. Based on current science, in-person interactions can be relatively safe if followed within CDC and public health guidance outlined in the first part of this series:
- Physical Distancing: Estimates of exposure time all assume close personal contact. Physical distancing decreases the likelihood of receiving an infectious dose by putting space between ourselves and others – current recommendations are 6 feet.
Furthermore, many in-person transactions can now be done touch free. I recently had to rent a car, and was pleased to meet the rental attendant outside holding a tablet. The attendant took down all my information, I never had to touch or sign anything. In a different transaction, requiring a signature, I was offered a single use pen to keep.
- Masks: Masks are a core tool to provide physical distancing between individuals. Masks do not primarily act as a filter for the wearer, but suppress the amount of droplets an infected person can spread into the space around them. This reduces the risk that others will exceed the infectious dose of the virus.
- Ventilation: Well ventilated areas disperse virus particles making it less likely a dose exceeds the infectious limits. Like my car rental agency, brands should endeavor to provide well ventilated spaces for employees and customers to interact – not only to protect customers but employees as well.
- Length of Exposure: Finally, brands should design service encounters to be as time efficient as possible. Again, the CDC advises a 15-minute exposure limit for close personal contact. Social distancing through physical distance, masks, and ventilation should increase this safe exposure limit. However, strategies should be implemented to make service encounters as brief as possible. For example, if you require information from your customers as part of the service interaction, collect this required information online or over the phone prior to an appointment. This could help to make customers and employees safer and more comfortable.
- Hand Washing & Sanitizer: Hand washing and sanitization is the primary defense against transfer infections.
Putting it All Together
Putting all this together, let’s look at an industry Kinesis has the most experience with. Kinesis’ largest practice is in the banking and financial services industry. Recently the American Bankers Association (ABA) released the results of an industry survey regarding publically announced responses of US banks to the pandemic. 
Many banks are applying some of the concepts discussed above in creative ways. A review of a random selection of banks reveals the following responses ranked from most common to least common:
- Enhanced deep cleaning and disinfecting of work spaces;
- Implementing social distancing in work spaces, including branches;
- Encouraging use of alternative delivery channels, such as mobile and internet banking;
- Personalized assistance to customers negatively impacted by the pandemic;
- Increased donations to charity/ partnering with the local community to mitigate the effects of the pandemic;
- Allowing employees to work remotely if possible;
- Limiting access to branches (closing branch lobbies, limiting hours, appointment only banking);
- Paid time off for employees to self-quarantine or to care of school age children;
- Rotating schedules of customer-facing staff to reduce risk (one institution has applied a 10 days on 10 days off policy); and
- Educating customers of pandemic related fraud/scams.
 Geddes, Linda. “Does a high viral load or infectious dose make covid-19 worse?” newscientist.com, March 27, 2020. Web May 14, 2020.
 “America’s Banks Are Here to Help: The Industry Responds to the Coronavirus.” ABA.com, April 29, 2020. Web. May 19 2020.
Previously, we discussed the implications of inter-channel consistency for researchers, and introduced a process for management to define a set of employee behaviors which will support the organization’s customer experience goals across multiple channels.
This post considers the implications of intra-channel consistency for customer experience researchers.
As with cross-channel consistency, intra-channel consistency, or consistency within individual channels requires the researcher to identify the causes of variation in the customer experience. The causes of intra-channel variation, is more often than not at the local level – the individual stores, branches, employees, etc. For example, a bank branch with large variation in customer traffic is more likely to experience variation in the customer experience.
Regardless of the source, consistency equals quality.
In our own research, Kinēsis conducted a mystery shop study of six national institutions to evaluate the customer experience at the branch level. In this research, we observed a similar relationship between consistency and quality. The branches in the top quartile in terms of consistency delivered customer satisfaction scores 15% higher than branches in the bottom quartile. But customer satisfaction is a means to an end, not an end goal in and of itself. In terms of an end business objective, such as loyalty or purchase intent, branches in the top quartile of consistency delivered purchase intent ratings 20% higher than branches in the bottom quartile.
Purchase intent and satisfaction with the experience were both measured on a 5-point scale.
Again, it is incumbent on customer experience researchers to identify the causes of inconsistency. A search for the root cause of variation in customer journeys must consider processes cause variation.
One tool to measure process cause variation is a Voice of the Customer (VOC) Table. VOC Tables have a two-fold purpose: First, to identify specific business processes which can cause customer experience variations, and second, to identify which business processes will yield the largest ROI in terms of improving the customer experience.
VOC Tables provide a clear road map to identify action steps using a vertical and horizontal grid. On the vertical axis, each customer experience attribute within a given channel is listed. For each of these attributes a judgment is made about the relative importance of each attribute. This importance is expressed as a numeric value. On the horizontal axis is a exhaustive list of business processes the customer is likely to encounter, both directly and indirectly, in the customer journey.
This grid design matches each business process on the horizontal axis to each service attribute on the vertical axis. Each cell created in this grid contains a value which represents the strength of the influence of each business process listed on the horizontal axis to each customer experience attribute.
Finally, a value is calculated at the bottom of each column which sums the values of the strength of influence multiplied by the importance of each customer experience attribute. This yields a value of the cumulative strength of influence of each business process on the customer experience weighted by its relative importance.
Consider the following example in a retail mortgage lending environment.
In this example, the relative importance of each customer experience attributes was determined by correlating these attributes to a “would recommend” question, which served as a loyalty proxy. This yields an estimate of importance based on the attribute’s strength of relationship to customer loyalty, and populates the far left column. Specific business processes for the mortgage process are listed across the top of this table. Within each cell, an informed judgment has been made regarding the relative strength of the business process’s influence on the customer experience attribute. This strength of influence has been assigned a value of 1 – 3. It is multiplied by the importance measure of each customer experience attribute and summed into a weighted strength of influence – weighted by importance, for each business process.
In this example, the business processes which will yield the highest ROI in terms of driving the customer experience are quote of loan terms (weighted strength of influence 23.9), clearance of exemptions (22.0), explanation of loan terms (20.2), loan application (18.9) and document collection (16.3).
Inconsistent treatment based on certain demographic characteristics is illegal. The Civil Rights Act of 1964 prohibits discrimination in almost all privately owned service industries based on race, color, religion, gender, or national origin. Other industries, such as retail banking, have additional regulatory requirements.
Beyond this legal risk, managers must be aware of the significant risk to the reputation of the brand posed by discriminatory practices.
Managers may seek comfort in the knowledge that their company’s policies and procedures are not to refuse service to anyone. However, this overt discrimination is just a small part of the risk associated with discrimination. Beyond overt discrimination, which is extremely rare, there are two other categories of discriminatory practices: disparate impact and disparate treatment.
Disparate impact is the result of policies or business practices which have an unequal impact. A restaurant with a policy to require prepayment for meals from one demographic group and not another is an example of disparate impact.
Disparate treatment is differences in treatment that originate at the customer-employee interface. Disparate treatment does not necessarily need to be a conscious act. It can be an unconscious pattern or practice of different treatment that the employee is not even aware of. The use of name, offering promotional material to a customer of one group as opposed to a customer on another group are all examples of disparate treatment.
Now, observing differences is treatment is not necessarily proof of discrimination. Human behavior, after all, is variable. There is a certain amount of normal variation in all service encounters. The trick is to determine if disparate treatment observed represents a pattern or practice of discrimination. Fortunately statistics has the answer, we use statistical tests of significance to determine both if observed differences in treatment are the result of actual discriminatory practices and the likelihood that any one member of a protected class will be treated differently than a member of another protected class. It should be noted, however, that regulatory agencies set the bar much higher. Many do not necessarily rely on statistical testing. In their view, any single case of disparate treatment is evidence of discrimination.
In a future post we will discuss the implications for customer experience researchers in testing for disparate treatment.
Inconsistent customer experiences are a significant threat to customer loyalty. In a previous post, we observed the casual relationship between consistency in the customer experience and feelings of trust and loyalty.
Consistency drives satisfaction. It is extremely common to see a correlation between intra-channel consistency and performance. Consider the following scatter plot from Kinesis’ research, which plots bank branch customer satisfaction by the variation in branch customer satisfaction:
As this plot demonstrates, consistency correlates with quality. Branches with higher customer satisfaction ratings are also the most consistent. In our customer experience research proactive we see this time and time again.
Additionally, this plot also demonstrates that top-line averages of customer satisfaction can be misleading. The bank in this plot had an average customer satisfaction rating of 93%. However, many branches fall well below this top-line average, resulting in an incomplete picture of the customer experience. Customers do not experience top-line averages; they experience the customer experience one interaction at a time at the local business unit level.
What are the implications for managers of the customer experience?
The first implication for managers is the above observation that top-line averages can mislead. Top-line averages hide individual business units with both low and inconsistent customer satisfaction. Top-line averages come between management and customers, distancing managers from how customers actually experience the brand.
Secondly, variation must be managed at the cause. Intra-channel variation is almost always at the local business unit level. For example, a store with a high degree of variation in customer traffic will experience a high degree of variation in the customer experience if management does not mitigate the effects of the variation in traffic.
How to manage for consistency:
- Manage inconsistency at the cause
- Write a clear mission statement
- Use appropriate analytics
- Don’t silo analytics by channel
- Meet regularly with employees to share problems and potential solutions
- Focus on customer journey
Intra-channel consistency needs to be managed at the local level – individual stores and agents. Tools need to be available deep into the organization to allow managers at the lowest level of each channel to deliver a consistent experience.
Business Case and Implications for Consistency – Part 4 – Consistency and the Outsized Influence of Poor Experiences
This post continues to explore the business case for consistency by considering the influence of poor experiences.
To start, let’s consider the following case study:
Assume a brand’s typical customer has 5 service interactions per year. Also assume, the brand has a relatively strong 95% satisfaction rate. Given these assumptions, the typical customer has a 25% probability each year of having a negative experience, and in four years, in theory, every customer will have a negative experience.
As this case study illustrates, customer relationships with brands are not defined by individual, discrete customer experiences but by clusters of interactions across the lifecycle of the customer relationship. The influence of individual experiences is far less important than the cumulative effect of these clusters of customer experiences.
Consistency reduces the likelihood of negative experiences contaminating the clusters of experiences which make up the whole of the customer relationship. Negative experiences, regardless of how infrequent, have a particularly caustic effect on the customer relationship. A variety of research, including McKiney’s The Three Cs of Customer Satisfaction: Consistency, Consistency, Consistency, has concluded that negative experiences have three to four times the influence on the customer as positive experiences – three to four times the influence on the customer’s emotional reaction to the brand – three to four times the influence on loyalty, purchase intent and social sharing within their network.
Though it does not pre-assign seats or provide onboard meals and at times has a lengthy wait and check in process, consumers year in and year out rank Southwest Airlines at the top or near the top of customer service.
Why is Southwest consistently near the top?
There are many reasons. The most significant being alignment of customer experience to both their brand and customer expectations; however, I believe a key component of Southwest success in customer service is the emotional intelligence of their employees.
What is Emotional Intelligence?
Emotional intelligence is defined by four personality characteristics:
- A strong sense of self-empowerment and self regulation;
- A positive outlook;
- An awareness of feelings (both their own and customers); and
- A master of fear and anxiety and the ability to tap into selfless motives.
Each of these characteristics provide a clear benefit to the customer experience:
|Personality Characteristic||Benefit to the Customer Experience|
|Self-Empowerment and Regulation||Make Decisions in the Moment
|Constructive Responses to Challenges|
|Awareness of Feelings||Empathy and Better Communication with Customers
|Master of Fear/Anxiety and Selfless Motives||Express Feelings of Empathy and Caring|
Leading customer experience brands position the employee to constructively respond to challenges, make decisions in the moment, empathize with customers, and perhaps most important, not only feel but express feeling of care, concern and empathy to customers.
Much of the benefit of emotional intelligence is derived in “moments of truth” where some experiences in the customer journey have far greater importance than others. These moments of truth represent increased risk and opportunity to leave a lasting emotional impression on the customer; a lasting impression with significant long-term implications for both customer loyalty and wallet share. Perhaps the most common moment of truth is when something has gone wrong, the customer is unhappy or scared, and the relationship is at risk.
How do we build emotional intelligence?
First of all, emotional bonding cannot be scripted. Attempting to script such a connection will inevitably come off as hollow and insincere lacking authenticity and empathy, completely undermining the desired customer experience. Rather, emotional bonding must be a result of a spontaneous series of events that emerge from the emotional intelligence of employees.
The obvious starting point in building emotional intelligence is hiring frontline employees with the requisite emotional intelligence skills. Emotional intelligence can also be learned. However, it is a “soft” skill, unlike “hard” skills such as math; it can’t be taught in structured sessions. Rather, emotional intelligence is learned like almost all other human behaviors primarily though observation, experience and imitation.
Four Steps to Build Emotional Intelligence
Give people meaning in their work: Inspire frontline employees with a purpose beyond a paycheck. This clarity of purpose should include both what they are supposed to do and why they are supposed to do it.
In empowering frontline employees to serve customers, brands should arm them with statements of general principles and values rather than scripted procedures, which undermine empowerment. Reinforce these principals often so in the instant, when they are in a moment of truth with a customer in need, they have an appropriate framework from which to resolve the issue – and bond the customer to the brand.
Most frontline employees want to help customers; however, their motivations may be varied. Leading customer experience brands allow their employees to discover their own motivations for looking out for the customer’s best interests.
Create learning opportunities through experience: Humans are programmed to learn through self-discovery. Self-discovery reinforces the learning process by instilling a sense of accomplishment or pride. These positive feelings associated with self-discovery are a strong psychological reward, which reinforces the learning process. While self-discovery is not a top-down process, managers can foster self-discovery through feedback, encouraging employees to reflect on their own successes and failures, and anecdotes about other employees. Case studies are not just for MBA students.
Align customer experience systems and processes: It is imperative that systems and processes support the emotional skills desired from employees. Systems and process must constantly reinforce the overall message of emotional intelligence and emotionally connecting with customers. In empowering employees to respond to moments of truth, management must strike a balance between financial considerations and the things that matter to the customer. Good customer experiences are not good because they are good; they are good because they are profitable; however, there is no benefit to being penny wise and pound foolish. Finally, processes need to be streamlined to give employees both the time and ability to rise to the situation.
Enlist leaders and mentors: Emotions are learned through modeling. Children don’t learn to react to certain stimuli just because a parent tells them what to feel. We learn how to react to certain situations through trial and error and observing role models. First, it is imperative that all managers and leadership model appropriate emotional skills. How can you expect emotional intelligence from the frontline if it doesn’t exist in leadership? Second, identify employees with the appropriate emotional skills and position them as role models within the organization.
Key to success of any customer facing brand is alignment of the customer experience to both the brand promise and customer expectations. Most of time, this is not difficult. Appropriate systems procedures and even automated delivery channels can achieve this end. However, in moments of truth, where there is a high degree of risk associated with the outcome of the experience, leading customer experience brands rely on an emotionally intelligent frontline staff to align the experience and bond the customer to the brand.
In an earlier post we explored how customers experience all aspects of their relationship with a brand through the lens of their emotional state, and observed that all brands must be prepared to meet each customer in their specific emotional state – be they happy, excited, depressed or angry.
Research has determined that, not surprisingly, people are motivated to maintain positive moods, and mitigate negative affective states. When feeling good we tend to make choices that maintain a positive mood. Customers in a positive mood are more loyal, and more likely to interpret information favoring a current brand. Meanwhile, people in negative affective states make choices that have the potential to change or, in particular, improve their moods.
A key to maintaining positive moods is arousal, or more specifically, the management of arousal. Let’s take a look at how arousal management influences consumer choice. Consumers in a positive mood prefer products congruent with their state of arousal. Excited or happy consumers want to stay excited or happy, while relaxed and calm consumers what to stay relaxed and calm. Consumers in a negative mood prefer products with the potential to change their level of arousal.
In considering the role of customer emotions in their relationship to a brand, it is important to understand the implications of customer emotions on design of the customer experience. It is impossible, of course, to plan every customer experience or to ensure that every experience occurs exactly as intended. However, brands can identify and plan for the types of experiences that impart the desired emotional state on the customer. It is useful to group these experiences into three categories of interaction with the customer: Stabilizing, Critical, and Planned.
Stabilizing interactions promote customer retention, particularly in the early stages of the relationship.
New customers are probably in a positive state of valence, with either a high state of arousal (happy/excited) or a negative state of arousal (relaxed/calm). Remember, people are motivated to maintain positive moods, therefore, the objective of these stabilizing interactions is to maintain this positive mood.
The keys to an effective stabilizing strategy and maintaining these positive moods are education, competence and consistency.
New customers are at the highest risk of defection. As customers become more familiar with a brand they adjust their expectations accordingly. It is important that expectations be set appropriately to eliminate conflict with reality. Conflict between expectations and reality early in the customer relationship runs the risk changing the customer’s mood from positive to negative. They are more likely to experience disappointment, and thus more likely to defect.
Education influences expectations, helping customers develop realistic expectations. It goes beyond simply informing customers about the products and services offered by the company. It systematically informs new customers how to use the brand’s services more effectively and efficiently, how to obtain assistance, how to complain, and what to expect as the relationship progresses. In addition to influencing expectations, systematic education leads to greater efficiency in the way customers interact with the company, thus driving down the cost of customer service and support.
Critical interactions are service encounters that lead to memorable customer experiences. While most service is routine, from time to time a situation arises that is out of the ordinary: a complaint, a question, a special request, a chance for an employee to go the extra mile. We call these critical interactions “moments of truth.” The outcomes of moments of truth can be either positive or negative – they are rarely neutral.
Because they are memorable and unusual, moments of truth tend to have a powerful effect on the customer relationship. We often think of moments of truth as instances when the brand has an opportunity to solidify the relationship – earning a loyal customer, or risk the customer’s defection. Positive outcomes lead to positive states of valence (excited, happy, relaxed, calm) with greater wallet share, loyalty, and positive word word-of-mouth endorsements; while negative outcomes generate negative states (anger, frustration, depression); and result in customer defection, diminished share of wallet and unfavorable word-of-mouth.
We are in an era of automated channels. Automated channels are essential for meeting customer expectations and reducing transaction costs, but technical solutions are not, by themselves, able to drive an emotional connection between customers and the brand – particularly in moments of truth. Employees, emotionally intelligence employees, empowered to resolve the issue are critical in driving an emotional connection. In a future post, we will discuss the concept of Emotional Intelligence of frontline employees in handling moments of truth.
An effective customer experience strategy should include systems for recording critical interactions, analyzing trends and patterns, and feeding that information back to the organization. Employees can then be trained to recognize critical opportunities, and empowered to respond to them in such a way that they will lead to positive outcomes and desired customer behaviors.
Planned interactions are intended to increase customer profitability through up-selling and cross-selling. These interactions are frequently triggered by changes in the customers’ purchasing patterns, account usage, financial situation, family profile, etc. CRM analytics combined with Big Data are becoming quite effective at recognizing such opportunities and prompting action from service and sales personnel.
Customer experience managers should have a process to record and analyze the quality of execution of planned interactions with the objective of evaluating the performance of the brand at the customer brand interface – regardless of the channel.
The key to an effective strategy for planned interactions is appropriateness. Triggered requests for additional purchases must be made in the context of the customers’ needs and permission; otherwise the requests will come off as clumsy and annoying. By aligning information about execution quality (cause) and customer impressions (effect), customer experience managers can build a more effective and appropriate approach to planned interactions.
Customers experience all aspects of their relationship with a brand through the lens of their emotional state. Be they happy, excited, depressed or angry all brands must be prepared to meet each customer in their specific emotional state. It’s a challenge – but also an opportunity. Ultimately, loyalty is emotionally driven. Brands that can react to and manage customer emotions stand to reap the rewards of customer loyalty.
To understand the role of the customer’s mood in managing the customer experience, it is instructive to consider how two affective states work together to define mood. The following model tracks mood across valence (the extent to which the emotional state is positive or negative) and arousal (the extent to which the energy mobilization of the emotional state is experienced on a scale of active to passive or aroused to calm).
Together, these affective states of valence and arousal can define all human emotions. States of positive valence and high arousal are excited or happy; negative valence and low arousal are bored or depressed. States of positive valence and low arousal are calm and relaxed, and negative valence and high arousal are angry or frustrated.
Here is a detailed map of a variety of emotions across these two dimensions.
Research has determined that, not surprisingly, people are motivated to maintain positive moods, and mitigate negative affective states. When feeling good we tend to make choices that maintain a positive mood. Customers in a positive mood are more loyal, and more likely to interpret information favoring a current brand. Meanwhile, people in negative affective states make choices that have the potential to change or, in particular, improve their moods. For example, researchers have demonstrated a preference for TV shows that held the greatest promise of providing relieve from negative affective states. People in a sad mood want to be comforted, anxious people want to feel control and safety.
Key to maintaining positive moods is arousal or more specifically the management of arousal. Let’s take a look at how arousal management influences consumer choice. Consumers in a positive mood prefer products congruent with their state of arousal. Excited or happy consumers want to stay excited or happy, while relaxed and calm consumers what to stay relaxed and calm. Consumers in a negative mood prefer products with the potential to change their level of arousal. For example, in an experiment, participants were offered the choice of an energy drink or iced tea. The following chart illustrates participant’s preference by the state of arousal and valence:
Participants in a positive mood, preferred the drink congruent with their level of arousal, those in a positive low-arousal state preferred iced tea, and those in a positive high-arousal state preferred an energy drink. On the other hand, those in a negative mood preferred a drink incongruent with their energy state, those in a negative low-arousal state preferred an energy drink, and those in a negative high-arousal state preferred iced tea.
Understanding the role of arousal management in customers’ innate desire to maintain positive moods and mitigate negative moods has far reaching implications for just about every element of the customer experience from sales, to problem resolution, to customer experience design, hiring, training and customer experience measurement. In future posts we will explore these implications for each of these elements of the customer experience.