The migration away from the branch channel that started decades ago has accelerated in recent years – aided by the confluence of the pandemic and technical advances. Banks now operate in an age where it is possible to deliver a seamless integrated digital first retail banking delivery model. Such a digital first business model needs to accomplish two objectives in the digital space: it must foster trust and deliver personalization.
Kinēsis’ research into issues of trust and personalization, suggests there is much work financial institutions need to do to achieve the objective of fostering trust and delivering personalization. Nearly as many customers do not trust their primary financial institution as those who do. Meanwhile digital channels exhibit a weaker relationship between trust and satisfaction compared to non-digital channels.
Customer perceptions of trust and satisfaction with their primary financial institution vary greatly based on what they value in the relationship with a financial institution. Importantly, for managers of the customer experience, what customers value in a relationship with a financial institution also reflects channel preference and selection.
Understanding customer segments should inform channel management.
In our research, Kinēsis segmented survey respondents into four groups based on their answers to a battery of questions regarding which retail financial services are most important to them. This segmentation grouped respondents into four attitudinal segments which we describe as follows:
|Show Me The Money|
These customers seek financial value from financial institutions. They are significantly more likely than other respondents to feel value for money and competitive rates and fees are most important when doing business with a financial service provider.
These customers value personalized service from their financial service providers. They tend to feel the most important attributes of a financial service provider are personalized service with polite and knowledgeable staff, providing quick and efficient service and fast resolution to any issues.
Customers who grouped into this segment are were more likely to value a broad range of products, loyalty programs, ethical and sustainable business practices, recommendations and an appealing brand.
|Don’t’ Make Me Wait|
These customers value efficiency. Almost exclusively they respond quick and efficient service and fast resolution to any issues are most important to them.
Let’s explore how customer attitudes and values can reflect themselves in trust, satisfaction and behavior.
Trust in Financial Institution
Customers who value products and services have stronger trust in their primary financial institution, while those who value efficiency display weaker trust.
When asked the extent to which they agreed with the following statement, “My primary financial institution looks after my long-term financial wellbeing.” Customers who value products and services professed the strongest agreement with this statement, and were significantly more likely to agree with this statement compared to customers who value efficiency.
Satisfaction with Financial Institution by Channel
Customers who value products tend to be more satisfied, while customers who seek financial value tend to be less satisfied.
In general, automated channels appear to have higher satisfaction compared to personal channels. Customers expressed the highest satisfaction for mobile apps and the lowest satisfaction for contact centers.
Preferred Channel to Open Account
Customers who want quality products and services are significantly more likely to want to use a mobile app to open an account, as opposed to visit a branch.
About half of the respondents preferred to open an account at a branch, about one-third would prefer to use the website, while only one in ten would prefer a mobile app to open an account. The customer segment most likely to find appeal in using the mobile app are those who value products and services.
Preferred Channel for Problem Resolution
The contact center is the preferred channel to resolve a problem, followed by the branch.
Customers who want quality products and services are significantly more likely to want to use a mobile app to resolve a problem, as opposed to visit a branch.
Preferred Channel for Information
When asked how they prefer to get information, a plurality of customers prefer to use the website, followed by the contact center.
Customers who seek service quality are significantly more likely than financial value seekers to want to visit a branch to get information.
Preferred Channel for Advice
It is clear most customers still prefer the branch when seeking advice. Seeking advice is a type of transaction we refer to as a moment of truth, with high importance on the relationship with the customer, and it’s clear a little hand holding is appreciated across all segments.
Customers who seek service quality are significantly less likely than others to want to visit a website to seek financial advice.
Preferred Channel for Funds Transfer
The majority of customers prefer mobile apps to websites for funds transfers.
Customers who seek quality products or services are significantly more likely to prefer mobile apps to transfer funds, compared to those who seek service or efficiency.
When segmenting customers by what they value in a financial institution, differences begin to appear between customer segments in both measures of trust, satisfaction and behavior.
Customers who value products and services tend to trust and be more satisfied with their primary financial institution. This most likely reflects the transition from a branch centric model to a digital first model. Customers who are product oriented are less likely to require personal attention. Not surprisingly, these customers are also more likely to use a mobile app to complete a variety of transactions.
Preference for financial value and efficiency do not appear to have significant behavioral differences, however, attitudinally, they display different feeling of trust and satisfaction. Customers who value efficiency display weak trust in their primary financial institution; while those who seek financial value are generally less satisfied with their primary financial institution.
Customers who value service quality are most likely to be left behind in a switch from a branch distribution channel to a digital first deli very model. These customers represent 25% of all bank customers. They are less likely to use a website and app and more likely to visit a branch.
As the industry transitions to a digital first delivery model, managers of the customer experience will need to pay close attention to the customers who value personalized service and human interaction in the customer journey to foster both trust and satisfaction.
In previous posts to this five-part series on building an integrated digital-first service model we discussed:
- Matching different waypoints of the customer journey to the channels best suited for the specific waypoint;
- Customer preferences for a financial service provider; and
- What customers want from digital channels.
A waypoint is a point of reference when navigating a journey. Not only do the customer journeys take place across a multiple channels, but they take place across multiple transactions or waypoints.
An integrated digital channel strategy must be founded on understanding how specific channels match up to specific waypoints in the customer journey. In the first installment of these series there is a discussion of this issue. The understanding that different transactions match different channels is the whole point of an integrated strategy.
Currently, not every digital channel is a match for every customer need. Digital channels with higher a frequency of visits are increasingly the day-to-day face of the institution. The exposure risk of these channels is high, and managers of the customer experience must make sure digital channels are well programmed and tested to manage this exposure risk. Currently, however, customers prefer to match digital channels for low moment of truth interactions such as transfers, deposits, and researching information. In terms of satisfaction, these digital channels outperform the non-digital; however, they play on a very different playing field. Customers interact with branches and contact centers much less frequently, and assign lower satisfaction ratings to these channels. But when they do use these channels, it is much more important. Customers match these non-digital channels to high moment-of-truth interactions such as seeking advice, problem resolution, and opening an account.
Advances in artificial intelligence will no doubt close some of the moment of truth gaps between digital and non-digital channels, but for now, there still is a role for branches and contact centers. Closing these gaps between digital and non-digital channels will require attention to both personalization and trust. Again, people want banks to care about their needs and have the ability to meet their needs and solve their problems.
What do customers want from a bank?
Overall, customers value efficiency and personalized service from their primary financial institution. As we’ve seen, the most appealing service attributes to customers are:
• Online and mobile services
• Quick and efficient service
• Fast resolution of any issues
• Ability to manage my accounts in ways that suit me
• Polite and knowledgeable staff
It is important to note, this list includes both digital and personal channels. Customers value an integrated approach.
ROI Potential of Digital Banking Attributes
Investments in timely information, financial value, and cyber security assistance have the most potential for return on investment. The digital banking attributes with the highest potential for ROI in terms of appeal to customers and increasing their trust are:
• Alerts about upcoming direct debits
• Alerts about upcoming overdrafts
• Offers and perks from places shopped often
• Cyber security assistance
Further, investments in personalized information have the highest potential for fostering customer trust. Customers do not find the following attributes particularly appealing relative to other attributes; however, they do offer high ROI potential in terms of increasing customer trust:
• Budget information
• Savings tips
• Balance updates
Ultimately, success or failure of any integrated digital first strategy will require banks to achieve something that has eluded them so far – that is to scale personalization.
Video banking seems an obvious solution to scale personalization. However, while the potential of their adoption of this channel, in the age of Zoom, is delayed. According to our research only 4% of bank customers have used video banking. However, of those consumers who have used video banking, all of them trust their primary financial institution, and felt it looked after their financial wellbeing. This suggests video banking could be well received, and deepen the overall relationship with the customers.
In previous posts to this five-part series on building an integrated digital-first service model we discussed matching different waypoints of the customer journey to the channels best suited for the specific waypoint.
Beyond the overall CX at the institution level, we also researched CX attributes specific to the digital channel. In an effort to identify digital features to prioritize in digital channel design, Kinēsis investigated both the appeal and trust of various digital banking attributes.
Timely information, cyber security, and financial value are the most appealing digital banking features.
Digital Attribute Appeal
The following chart displayed the relative appeal of digital service attributes on a 5-point scale:
Timely information about overdraft and upcoming direct debits alerts received two of the top three appeal rankings (4.2 and 4.0, respectively). Assistance with cyber security threats, and offers and perks from places shopped often round out the top four.
The next tier of five attributes, with average appeal ratings of 3.3 to 3.0, contain themes of information and personalized advice:
• Personal financial reports and analytics/ Dashboards
• Savings tips based on my spending patterns
• Balance updates until my next payday
• Tips to act more sustainably based on my behavior
• Budget information based on spending
Chatbots and gamification (making the app more fun with elements of game playing, such as badges, points, etc), round out the bottom two attributes.
Digital Attributes & Trust
To add context to the digital attribute appeal ranking, we asked consumers if each of the attributes would increase their trust in the financial service provider.
Mirroring the appeal rankings, cyber security and timely information have the highest likelihood of increasing trust in the financial institution.
Cyber security assistance and alerts about overdrafts and upcoming direct debits increased trust for just about 19 out of 20 customers.
Only about 4 in 10 customers felt chatbots or gamification would increase their trust in the financial institution.
In order to provide CX managers context to make informed decisions about which digital attributes to prioritize, the trust and appeal rankings of each attribute are plotted on the quadrant chart below. Each of the quadrants below labeled (Q1 – Q4) are defined by the average appeal and trust rankings. Those in quadrant 1 (Q1) have higher than average appeal and trust, while those in Q4 have lower than average appeal and trust.
Investments in timely information, financial value and cyber security assistance have the most potential for return on investment.
With higher than average trust and appeal ratings, alerts about upcoming direct debits and overdrafts, offers and perks from places shopped often and cyber security assistance are the four digital attributes positioned to yield the highest return on investment in terms of appeal and trust.
Personal financial information such as analytics/dashboards, budget information, savings tips, and balance updates have below average appeal, however higher than average trust implications, and therefore should be prioritized next.
Tips to act sustainably, chatbots and making the app more fun with gamification have both below average appeal and they do not appear to have strong associations with trust of the institution, and therefore should be prioritized last.
In a previous post to this five-part series on building an integrated digital-first service model we discussed matching different waypoints of the customer journey to the channels best suited for the specific waypoint.
In an effort to help CX managers make informed decisions regarding their overall service mix, Kinēsis asked consumers to rate an assortment of financial service CX attributes with respect to their importance, as well as the relationship between the importance of these attributes and the customers’ trust that the financial institution looked after their financial wellbeing.
Efficiency and personalized service are the most important dimensions of the customer experience.
The following chart displayed the frequency customers stated each attribute was important to them when doing business with a financial service provider. To force respondents to consider only attributes which were important to them, they were only allowed to select up to five attributes.
Again, efficiency and personalized service are the most important dimensions of the customer experience. The most frequently cited service attributes surround themes of efficiency (online and mobile services, quick and efficient service, fast resolution to any issues) and personalized service (polite and knowledgeable staff, and ability to manage accounts in ways that suit me), followed by polite and knowledgeable staff, the ability to manage accounts in ways that suit the customer, and competitive rates and fees.
Attribute Value & Trust in Institution
The least frequently cited attributes surrounded products and the brand (customer loyalty programs, broad range of quality products, recommendations of appropriate products & services and appealing brand).
Beyond the appeal of each attribute, Kinēsis investigated their relationship to trust in the financial institution.
While brand appeal, recommendations of appropriate products & services and a broad range of quality products were cited with the least frequency in terms of their importance, customers who cited these attributes as important were more likely to trust their primary financial institution. While customers are not as likely to include these three attributes in their list of top-5 important attributes, brand appeal, recommendations of appropriate products & services and a broad range of quality products do appear to have a positive relationship to trust in the institution.
What started decades ago as a migration away from the branch channel has accelerated during the Covid-19 pandemic – aided by technological advances that were not available just a few years ago. This confluence of the pandemic and technical advances is culminating in an age where it is possible to deliver a seamless integrated digital first retail banking delivery model. Such an integrated delivery model is based on the understanding that customers have different needs at different moments in their customer journey. This delivery model matches channels strategically to these different needs at the correct moment for the customer.
Customer Journey Waypoints
A waypoint is a point of reference when navigating a journey. Not only do the customer journeys take place across a multiple channels, but they take place across multiple transactions or waypoints as well. To investigate how customers navigate digital and personal channels, Kinēsis researched customer channel preferences for six different customer journey waypoints: opening an account, problem resolution, seeking advice, getting information, making a deposit, and transferring funds.
Two CX Risks: Exposure & Moments of Truth
Business is often a process of balancing risks. The customer experience is no different. Managers of an integrated delivery model should be aware of the two primary risks they face: exposure and moments of truth. Exposure risk is the sheer frequency of customer encounters in the channel. Poor experiences in a high exposure channels spread this poor experience across more customers. Moments of truth are critical experiences with more individual importance of the waypoint. Poor experiences in a moment of truth interaction lead to negative customer emotions, with similarly negative impacts on customer profitability and word of mouth.
Waypoints and Channel Preferences
The foundation of an integrated digital first CX model is based on matching the best suited channels based on the needs of both the customer and the institution. Customer channel choice is not uniform. Rather, customers select channels they deem appropriate based on the waypoint of the customer journey they find themselves. For customers conducting a transfer or deposit, mobile apps are the most popular channel (preferred by 58% and 53% of the customers, respectively). Customers seeking information have a broader range of preferred channels, but a plurality (40%) prefers to seek information via the website. The contact center’s preferred role is problem resolution (51%); while the branch is preferred to both seek advice and open an account.
The following table illustrates these different channel preferences for different waypoints in the journey, as well as overlaying channel use, satisfaction and the moment of truth potential for each waypoint:
The above table illustrates the current state of the integrated digital first business model. The digital channels, with the most exposure risk, are the primary customer choice for waypoints which represent low moment of truth risk.
• Automated transactions such as transfers and deposits are preferred with an app.
• The website serves as both an information center, and to a lesser extent transactional center.
• The contact center’s primary role is problem resolution, and as a result carries significant risk in terms of moments of truth.
• The branch is where customers come to seek advice as well as initiate or deepen a banking relationship by opening an account.
Again, managers of the customer experience should be cognizant of both their risk in terms of exposure and moments of truth. With an average of nearly one visit every other day, poorly executed mobile experiences represent significant exposure risk, yet the nature of these transactions represent low moment of truth risk. Fortunately, 88% of customers are satisfied with their financial institution’s app, with a near super majority of customers describing themselves as very satisfied. The branch and contact center have the opposite risk profile. With, respectively, an average of just 7 and 17 visits annually, they do not represent a significant exposure risk. However, both the contact center and the branch represent significant risk with respect to encountering moments of truth. While digital channels are the daily face of the institution, when faced with a moment of truth, customers appear to prefer a see a real face, or hear a comforting voice. Customers interact with branches and contact centers much less frequently – but when they do – it is important. In this light, the relative dissatisfaction with these channels (average satisfaction 4.2 and 4.0, respectively) relative to apps and websites (average satisfaction 4.5 and 4.4, respectively) is cause for concern. The computers appear to be out performing the people – but they perform on an easier playing field.
The current environment with pandemic-related disruptions has pushed most customers into accelerating digital adoption. However, there is an element of trust missing with digital delivery. As most customers shy away from digital channels when their need advances up the moment of truth scale. Trust will be key in deepening digital relationships.
Momentum toward digital banking has been building for decades as emergent technologies, aided by the pandemic, increase the utility and use of digital channels. This confluence of the pandemic and technical advances is culminating in an age where it is possible to deliver a seamless digital first integrated retail banking business model.
Such an integrated delivery model is based on the understanding that customers have different needs at different moments of their customer journey. This delivery model matches channels strategically to these different needs at the correct moment for the customer.
Neither size nor a focus on technology provides an advantage in terms of the overall customer experience. The evidence strongly suggests, being closer to the customer, and matching different waypoints of the customer journey to the channels best suited for the specific waypoint is the best CX model:
• Automated transactions are preferred with an app.
• The website is best positioned as an information center, and to a lesser extent transactional center.
• Problem resolution in customers’ minds is the contact center’s primary role.
• Customers visit a branch to seek advice or open an account.
In future installments of this five-part series, we will:
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.
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.
In a previous post, we proposed the use of control charts as a tool to track customer experience measurements within upper and lower quality control limits, giving managers 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.
Now, managers need to understand the causes of variation, specifically common and special cause variation. Common and special cause variation are six sigma concepts, while most commonly used in industrial production, they can be borrowed and employed to the customer experience.
Common Cause Variation: Much like variation in the roll of dice, common cause variation is natural variation within any system. Common cause variation is any variation constantly active within a system, and represents statistical “noise” within the system.
Examples of common cause variation in the customer experience are:
- Poorly defined, poorly designed, inappropriate policies or procedures
- Poor design or maintenance of computer systems
- Inappropriate hiring practices
- Insufficient training
- Measurement error
Special Cause Variation: Unlike the roll of the dice, special cause variation is not probabilistically predictable within the system, as a result it does not represent statistical “noise” within the system, but is the signal within the system.
Examples of special cause variation include:
- High demand/ high traffic
- Poor adjustment of equipment
- Just having a bad day
When measuring the customer experience it is helpful to consider everything within the context of the company-customer interface. Every time a sales or service interaction within this interface occurs the customer learns something from the experience and adjusts their behavior as a result of the experience. Managing the customer experience is the practice of managing what the customers learn from the experience and thus managing their behavior in profitable ways.
A key to managing customer behaviors is understanding common cause and special cause variation and their implications. Common cause variation is variation built into the system: policies, procedures, equipment, hiring practices, and training. Special cause variation is more or less how the human element and the system interact.
See earlier post:
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.
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.
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.