Measure the Customer Experience in an Integrated Cross Channel Environment
Success in retail banking requires meeting customers with the correct channel for the customer’s waypoint in that journey.
A waypoint is a point of reference when navigating a journey.
Not all waypoints are equal. Customers prefer different channels based on the waypoint in their customer journey. As a result, different channels have assumed different roles in the customer journey. The challenge for customer experience managers is to provide an integrated customer experience across all waypoints.
Kinesis’ research has identified specific roles for each integrated channel in the customer journey:
|Mobile||– Transaction Tool|
|Web||– Primary Role: Research Tool|
– Secondary Role: Sales & Transfers
|Contact Center||– Help Center|
– Source of Advice
|Branch||– Sales Center|
– Source of Advice
The mobile channel is seen by customers as a transaction tool; the website’s role is broader, as a research, transaction and sales channel; contact centers are primarily a help center; and the branch is primarily a sales and advice channel.
This post offers a framework to measure individual channels in a way that will provide both channel specific direction in managing the experience, as well as benchmarking each channel against each other using consistent measurements.
Two CX Risks: Exposure and Moments of Truth
In designing a customer experience measurement program, it is instructive to think of the omni-channel experience in terms of two risks: exposure and moments of truth.
Exposure risk is the frequency of customer interactions within each channel. Poor experiences in channels with high frequencies are replicated across more customers resulting in exposing more customers to poor experiences. Mobile apps are the most frequently used channel. According to our research, customers use mobile banking apps 24 times more frequently than visiting a branch. Mobile banking has most exposure risk. Websites are used by banking customers 16 times more frequently than a branch; followed contact centers, used 2.3 times more frequently than branches.
Moments of Truth
Moments of truth are critical experiences with more individual importance. Poor experiences in a moment of truth interaction lead to negative customer emotions, with similarly negative impacts on customer profitability and word of mouth.
Routine transactions, like transfers or deposits, represent low moment of truth risk, problem resolution or account opening are significant moments of truth.
Exposure & Moment of Truth Risk by Channel
Different channels represent exposure and moment of truth risk is different ways.
The mobile channel’s role is primarily a transaction tool. According to our research the mobile channel is the preferred channel for both transfers (58%) and deposits (53%). It, therefore, has the highest exposure risk and lowest moment of truth risk.
The website is a mixed channel between research, transactions and opening accounts. A plurality of customers (40%) consider the website their preferred channel to get information, followed by transfers (33%) and opening accounts (31%). As a result, the web channel has a mix of exposure and moment of truth risk.
The contact center is primarily viewed as a channel for problem resolution (51%), followed by an advice and information source (27% and 23%, respectively). It represents low exposure risk and elevated moment of truth risk.
Finally, the branch is the primary a source for advice and account opening (53% and 51%, respectively). With infrequent use and high impact customer experiences, the branch has very low exposure risk, and significant moment of truth risk.
Understanding Exposure and Moments of Truth Risk to Inform CX Measurement
This concept of risk, along exposure and moments of truth, provides an excellent framework for informing customer experience measurement.
Digital channels with high exposure risk should be tested thoroughly with usability, focus groups, ethnography and other qualitative research to ensure features meet customer needs and are programmed correctly. Once programmed and tested, they need to be monitored with ongoing audits.
Channels with higher moment of truth risk are best monitored with post-transaction surveys, mystery shopping and the occasional focus group.
|Exposure Risk||Moments of Truth|
|Design Focus Groups|
|Post Transaction Surveys|
Integrated CX Measurement Design
When measuring the customer experience across multiple channels in an integrated manner, we recommend gathering both consistent measures across all channels, as well as measures specific to each channel. Each channel has their own specific needs; however, consistent measures across all channels provide context and a point of comparison.
Cross-channel consistency is key to the customer experience. Inconsistent experiences confuse and frustrate customers, and risk erosion of the brand value.
The consistent cross-channel measures Kinesis prefers to use are measures of the brand personality and efficacy of the customer experience.
|Brand Personality||Efficacy of the Experience|
Likelihood of Referral
Brand Personality: To measure brand personality, Kinesis asks clients to list five adjectives that describes their brand personality. Then we simply ask customers if each adjective described the customer experience. We also ask clients to give us five statements that describe their desired brand, and measure the experience with an agreement scale. For example, a client may desire their brand to be described by the statements: We are committed to the community. We would then ask respondents the extent to which they are in agreement with the statement: We are committed to the community. These measures of brand adjectives and brand statements provide managers of the customer experience a clear benchmark from which to evaluate how each channel reflects the desired brand personality.
Efficacy of the Experience: Ultimately, the goal of the customer experience is to produce the intended result – results like loyalty, increased wallet share, or lower transaction costs. Kinesis has had success using three measures to evaluate the efficacy of the customer experience:
- Purchase Intent: Purchase intent is an excellent measure of efficacy of the experience. To measure purchase intent we ask respondents how the experience influenced their intention to either open an account or maintain an existing relationship with the financial institution.
- Likelihood of Referral: The use of measures of likelihood of referral, like NPS, as a proxy for customer loyalty is almost universally accepted, and as a result, is often an excellent measure of efficacy of the experience.
- Customer Advocacy: Beyond likelihood of referral, agreement with the statement, My bank cares about me, not just the bottom line, is an excellent predictor of customer loyalty.
Channel Specific Attributes
In addition to consistent cross-channel measurements, it is important to focus on channel specific customer experience attributes. While consistent measures across channels provide a benchmark to brand objectives, measuring specific service attributes provides actionable information about how to improve the customer experience in each specific channel.
In designing channel specific research features, ask yourself what specific service attributes or behaviors do you expect from each channel. The answer to these questions will depend on the channel and your brand objectives. In general, they typically roll up to the following broad dimensions of the customer experience:
Specific Channel Dimensions
|Digital Channels||Personal Channels|
For digital channels, the best specific attributes to measure are ones associated with appeal, identity, navigation, content/ presentation, value, trust. For personal channels, such as contact centers and branches, we find the best attributes are associated with dimensions of reliability, responsiveness, empathy, competence, and tangibles.
Not all waypoints in the customer journey are equal. Customer experience researchers need to consider the role of each channel in the customer journey and design measurement tools with both channel specific observations, as well consistent measures across all channels.
Integrated Digital First CX Model: Implications for CX Managers
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.
/Next, we will consider the implications of a digital first integrated environment for CX researchers.
A New Normal: Implications for Bank Customer Experience Measurement Post Pandemic – Stabilizing Relationships
Part 3: Onboarding Research: Research Techniques to Track Effectiveness of Stabilizing New Customer Relationships
As we explored in an earlier post, Three Types of Customer Experiences CX Managers Must Understand, there are three types of customer interactions: Planned, Stabilizing, and Critical.
Stabilizing interactions are service encounters which promote customer retention, particularly in the early stages of the relationship. It is incumbent on an integrated digital-first banking model to stabilize new customers, without relying on the local branch to build the relationship. It is important, therefore, to get the onboarding process right in a systematic way.
New customers are at the highest risk of defection, as they have had less opportunity to confirm the provider meets their expectations. Turnover by new customers is particularly damaging to profits because many defections occur prior to recouping acquisition costs, resulting in a net loss on the customer relationship. As a result, customer experience managers should stabilize the customer relationship early to ensure a return on acquisition costs.
Systematic education drives customer expectations beyond simply informing customers about additional products and services; it also informs new customers how to use services more effectively and efficiently – this is going to be critical in a digital first integrated strategy. Customers need to know how to navigate these channels effectively.
The first step in designing a research plan for the onboarding process is to define the process itself. Ask yourself, what type of stabilizing customer experiences do we expect at both the initial account opening and at discrete time periods thereafter (be it 30 days, 90 days, 1-year)? Understanding the expectations of the onboarding process will define your research objectives, allowing an informed judgment of what to measure and how to measure it.
Kinesis recommends measuring the onboarding process by auditing the performance of the process and its influence on the customer relationship from the bank and customer perspective.
Bank Perspective: Performance Audits
Performance audits are a type of mystery shop, and an effective tool to audit the performance of the onboarding process.
First, mystery shop the initial account opening (across a channels: digital, contact center and branch) to evaluate its efficacy and effectiveness. Be sure to link these observations to a dependent variable, such as purchase intent, to determine which service attributes drive purchase intent. This will inform decisions with respect to training and incentives to reinforce the sales activities which drive purchase intent.
Beyond auditing the initial account opening experience, a performance audit of the onboarding process should test the presence and timing of specific onboarding events expected at discrete time periods. As an example, you may expect the following onboarding process after a new account is opened:
|At Opening||Internet Banking Presentation
Mobile Banking Presentation
Contact Center Presentation
|1-10 Days||Welcome Letter
Internet Banking Password
Overdraft Protection Brochure
Mobile Banking E-Mail
|30-45 Days||First Statement
Credit Card Offer
Auto Loan Brochure
Mortgage/Home Equity Loan Brochure
In this example, the bank’s customer experience managers have designed a process to increase awareness of digital channels, introduce the integrated layered service concept, and introduce additional services offered. An integrated research plan would recruit mystery shoppers for a long-term evaluation of the presence, timing, and effectiveness of each event in the onboarding process.
In parallel to auditing the presence and timing of onboarding events, research should be conducted to evaluate the effectiveness of the process in stabilizing the customer relationship by surveying new customers at distinct intervals after customer acquisition. We recommend testing the effectiveness of the onboarding process by benchmarking three loyalty attitudes:
- Would Recommend: The likelihood of the customer recommending the brand to a friend, relative or colleague.
- Customer Advocacy: The extent to which the customer agrees with the statement, “You care about me, not just the bottom line?”
- Primary Provider: Does the customer consider you their primary provider for financial services?
These three measures, tracked together throughout the onboarding process, will give managers a measure of the effectiveness of stabilizing the relationship.
Again, new customers are at an elevated risk of defection. Therefore, it is important to stabilize the customer relationship early on to ensure ROI on acquisition costs. A well-designed research process will give managers an important audit of both the presence and timing of onboarding events, as well as track customer engagement and loyalty early in their tenure.
In the next post, we will explore the third type of experience – experiences with a significant amount of influence on the customer relationship – critical experiences.
A New Normal: Implications for Bank Customer Experience Measurement Post Pandemic – Planned Interactions
Part 2: Research Tools to Monitor Planned Interactions through the Customer Lifecycle
As we explored in an earlier post, Three Types of Customer Experiences CX Managers Must Understand, there are three types of customer interactions: Planned, Stabilizing, and Critical.
Planned interactions are intended to increase customer profitability through the customer lifecycle by engaging customers with relevant planned interactions and content in an integrated omni-channel environment. Planned interactions will continue to grow in importance as the financial service industry shifts to an integrated digital first model.
These planned interactions are frequently triggered by changes in account usage, financial situation, family profile, etc. CRM analytics combined with Big Data are becoming quite effective at recognizing such opportunities and prompting action toward planned interactions. Customer experience managers should have a process to record and analyze the quality of execution of planned interactions with the objective of evaluating their effectiveness – regardless of the channel.
The key to an effective strategy for planned interactions is relevance. Triggered requests for increased engagement must be made in the context of the customer’s needs and with their permission; otherwise, the requests will come off as clumsy and annoying, and give the impression the bank is not really interested in the customer’s individual needs. By aligning information about execution quality (cause) and customer impressions (effect), customer experience managers can build a more effective and relevant approach to planned interactions.
Research Plan for Planned Interactions
The first step in designing a research plan to test the efficacy of these planned interactions is to define the campaign. Ask yourself, what customer interactions are planned through these layers of integrated channels. Mapping the process will define your research objectives, allowing an informed judgment of what to measure and how to measure it.
For example, after acquisition and onboarding, assume a bank has a campaign to trigger planned interactions based on triggers from past engagement. These planned interactions are segmented into the following phases of the customer lifecycle: engagement, growth, and retention.
Often it is instructive to think of customer experience research in terms of the bank-customer interface, employing different research tools to study the customer experience from both sides of this interface.
In our example above, management may measure the effectiveness of planned experiences in the engagement phase with the following research tools:
|Customer Side||Brand Side|
These post-experience surveys are event-driven, where a transaction or service interaction determines if the customer is selected for a survey. They can be performed across all channels, digital, contact center and in-person. As the name implies, the purpose of this type of survey is to measure experience with a specific customer experience.
Ultimately, employees are at the center of the integrated customer experience model.
Employee surveys often measure employee satisfaction and engagement. However, there is far more value to be gleaned from employees. We employ them to understand what is going on at the customer-employee interface by leveraging employees as a valuable and inexpensive resource of customer experience information.
They not only provide intelligence into the customer experience, but also evaluate the level of support within the organization, and identify perceptual gaps between management and frontline personnel.
|Overall Satisfaction Surveys
Overall satisfaction surveys measure customer satisfaction among the general population of customers, regardless of whether or not they recently conducted a transaction. They give managers valuable insight into overall satisfaction, engagement, image and positioning across the entire customer base, not just active customers.
|Digital Delivery Channel Shopping
Be it a website or mobile app, digital mystery shopping allows managers of these channels to test ease of use, navigation and the overall customer experience of these digital channels.
|Transactional Mystery Shopping
Mystery shopping is about alignment. It is an excellent tool to align the customer experience to the brand. Best-in-class mystery shopping answers the question: is our customer experience consistent with our brand objectives? Historically, mystery shopping has been in the in-person channel, however we are seeing increasing mystery shopping to contact center agents.
In the growth phase, we measure the effectiveness of planned experiences on both sides of the customer interface with the following research tools:
|Customer Side||Brand Side|
Awareness of the brand, its products and services, is central to planned service interactions. Managers need to know how awareness and attitudes change as a result of these planned experiences.
|Cross-Sell Mystery Shopping
In these unique mystery shops, mystery shoppers are seeded into the lead/referral process. The sales behaviors and their effectiveness are then evaluated in an outbound sales interaction.
These shops work very well in planned sales interactions within the contact center environment.
|Wallet Share Surveys
These surveys are used to evaluate customer engagement with and loyalty to the institution. Specifically, they determine if customers consider the institution their primary provider of financial services, and identify potential road blocks to wallet share growth.
Finally, planned experiences within the retention phase of the customer lifecycle may be monitored with the following tools:
|Customer Side||Brand Side|
|Critical Incident Technique (CIT)
CIT is a qualitative research methodology designed to uncover details surrounding a service encounter that a customer found particularly satisfying or dissatisfying. This research technique identifies these common critical incidents, their impact on the customer experience, and customer engagement, giving managers an informed perspective upon which to prepare employees to recognize moments of truth, and respond in ways that will lead to positive outcomes.
Employees observe firsthand the relationship with the customer. They are a valuable resource of customer experience information, and can provide a lot of context into the types of bad experiences customers frequently experience.
|Lost Customer Surveys
Closed account surveys identify sources of run-off or churn to provide insight into improving customer retention.
|Life Cycle Mystery Shopping
If an integrated channel approach is the objective, one should measure the customer experience in an integrated manner.
In lifecycle shops, shoppers interact with the bank over a period of time, across multiple touch points (digital, contact center and in-person). This lifecycle approach provides broad and deep observations about sales and service alignment to the brand and performance throughout the customer lifecycle across all channels.
Comment tools are not new, but with modern Internet-based technology they can be used as a valuable feedback tool to identify at risk customers and mitigate the causes of their dissatisfaction.
Call to Action – Make the Most of the Research
For customer experience surveys, we recommend testing the effectiveness of planned interactions by benchmarking three loyalty attitudes:
- Would Recommend: The likelihood of the customer recommending the bank to a friend, relative or colleague.
- Customer Advocacy: The extent to which the customer agrees with the statement, “My bank cares about me, not just the bottom line?”
- Primary Provider: Does the customer consider the institution their primary provider for financial services?
For mystery shopping, we find linking observations to a dependent variable, such as purchase intent, identifies which sales and service behaviors drive purchase intent – informing decisions with respect to training and incentives to reinforce the sales activities which drive purchase intent.
As the integrated digital first business model accelerates, planned interactions will continue to grow in importance, and managers of the customer experience should build customer experience monitoring tools to evaluate the efficacy of these planned experiences in terms of driving desired customer attitudes and behaviors.
In the next post, we will take a look at stabilizing experiences, and their implications for customer experience research.
Translate Research to Action with a VOC Table
Ask any group of satisfaction researchers and consumers of satisfaction research about the largest problem facing the research industry, most likely, the lack of actionability (or usefulness of the research) will be the most common concern raised. All too often, research is conducted, reports produced and bound into professional looking binders which end up gathering dust on a shelf some place, or if you’re like me, providing excellent use as a door stop.
What is missing is a strategy to transition research into action, and bring the various stakeholders into the research process.
Managers and researchers alike are faced with the difficult task of determining where to make investments, and predicting the relative return on such investments. One such tool for transforming research into action is the Voice of the Customer (VOC) table.
A VOC Table is an excellent tool to match key satisfaction dimensions and attributes with business processes, and allow managers to make informed judgments regarding which business process will have the most return in terms of satisfaction improvement.
A VOC Table supports this transition from listing the key survey elements on the vertical axis, sorting each attribute by an importance rating. On the horizontal axis, a complete list of business functions is listed. At this point, the researcher and manager match business process/functions with key survey elements and make judgments regarding the extent to which the business function influences key survey element (in the enclosed example, a dark filled-in square represents a strong influence, an unfilled square represents a moderate influence, while a triangle represents a slight influence.) A numeric value is assigned to each influence (typically, a value of ‘four’ for a strong influence, ‘two’ for a medium influence, and ‘one’ for a weak influence). For each cell in the table, a value is calculated by multiplying the strength of the influence by the importance rating of the survey element. Finally, the cell values are summed for each column (business function) to determine which business functions have the most influence on customer satisfaction.
Consider the enclosed example of a VOC table. In this example, a retail mortgage-lending firm has conducted a wave of customer satisfaction research, and intends to link this research to process improvement initiatives using the attached VOC Table. The satisfaction attributes and their relative importance, as determined in the survey, are listed in the far left column. Specific business processes from loan origination to closing are listed across the top of the table. For each cell, where satisfaction attributes and business process intersect, the researchers have made a judgment of the strength of the business process’s influence on the satisfaction attribute. For example, the researchers have determined proper document collection to have a strong influence on the firm’s ability to perform services right the first time, and a weak relationship for willingness to provide service. For each cell, the strength of the influence is multiplied by the importance. The sum of the values of each cell in each column determines the relative importance of each business process in influencing overall customer satisfaction.
In the example, the loan quote process and clearance of underwriting exemptions are the two parts of the lending process, which have the greatest influence on customer satisfaction, followed closely by an explanation of the loan process. The other three aspects of the loan process of significance are document collection, application, and preliminary approval. The least important are document recording and credit and title report ordering. The managers of this hypothetical lending institution now know what parts of the lending process to focus on to improve customer satisfaction. Furthermore, in addition to knowing which specific events to focus on, they also know, generally speaking, which improvements in the loan origination process will yield more return in terms of customer satisfaction than improvement in processing, underwriting, and closing. As all the loan origination elements have comparatively strong influence on satisfaction.
Customer Experience Measurement in the Coronavirus Age
Earlier in this three-part series we discussed the mechanism and risk of SARS-CoV-2 infection, and the implications of the pandemic on the customer experience.
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.
Customer Experience Measurement in the Coronavirus Age: Implications for Customer Experience
Earlier in this three-part series we discussed the mechanism of infection and risk of SARS-CoV-2 infection.
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.
In the next post, we will build off the foundation of the previous two posts to address the implications of the pandemic on customer experience measurement.
 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.
Customer Experience Measurement in the Coronavirus Age: The Mechanism and Risk of Infection
From Zoom happy hours, canceled events, concerns over how best to educate our children, economic disruption, and caring for the victims, the SARS-CoV-2 pandemic, and the resulting public heath requirements are changing our lives in ways both big and small, superficial and tragic. The customer experience is certainly no exception. Writing about effects of the pandemic, while it unfolds, is a unique challenge – as we are learning more about the virus, its health effects, mitigation strategies, and overall effects on society in real time. Things change daily and we are all learning on the fly here. This series of blog posts is an early attempt to discuss the effects of the pandemic on customer experience research.
Before we begin, let me stress one thing. I am a market researcher who specializes in evaluating the customer experience. I am not an epidemiologist or doctor, and I have no training or experience in public health. As a result, I will refrain from expressing scientific or medical theories or opinions of my own. Any virus related conclusions or opinions expressed in this series of posts will be from credible sources and cited in footnotes. If at any point it appears I am drawing medical or scientific conclusions of my own, it is unintentional, and should not be regarded as such.
The need for managers of the customer experience to understand the implications of post-SARS-CoV-2 environment will most likely survive the immediate pandemic. Changes in customer experience management will probably assume a more permanent nature. First, this novel coronavirus may never go completely away, but rather become endemic in our society, meaning it could be a constant presence. Second, recent history suggests SARS-CoV-2 is not the only novel-corona virus we are going to face in the coming decades. Currently there are seven know coronaviruses that infect humans – prior to 2003 there were only four. In a relatively short period of time, three new coronaviruses have jumped from animals to humans. The number of known coronaviruses to which humans are susceptible has nearly doubled in 17 years, so it does not require a great leap of the imagination to conclude this is not the last novel virus we will need to deal with.
This pandemic and its predicted aftermath represent a moment of truth for customers and their relationship to the brand. In an uncertain and risky environment, customers will be even more likely to build relationships with brands they trust. Forward thinking managers of the customer experience will respond by building more mechanisms to monitor customer perceptions of safety within the in-person channel and fulfillment via expanded alternative channels.
Mechanism of Infection
What we know now is the virus appears to spread primarily through person-to-person contact, via people in close contact with each other or to a lesser extent secondary transfer off contaminated surfaces.
SARS-CoV-2 survives on most surfaces. Touching an infected surface and touching your eye, nose or mouth represents a risk of infection by transfer. Although, recent guidance from the CDC suggests transfer is not a significance mode of transmission. That being said, high touch surfaces such as door handles, elevator buttons, POS machines, and bathroom surfaces, should still be considered a potential risk for transfer infection. However, the main mechanism of infection is via close personal contact.
When an infected person coughs, sneezes, talks or performs any other activity exhaling air, respiratory droplets are produced. These droplets can land on the mouths or noses of people nearby, or in some circumstances, hang in the air in an aerosol form and be inhaled into the lungs. Current evidence suggests most individuals with mild to moderate symptoms can be infectious up to 10 days after symptom onset. Further complicating this picture, it appears individuals without symptoms can be infectious even without knowing they are infected themselves.
In order for customer experience managers to make informed choices about the customer experience in the post-Covid age, it is important to understand the mechanism of infection. The infectious dose of a virus is the amount of virus a person needs to be exposed to in order to establish an infection. The infectious dose varies depending on the virus (the flu can cause infection after exposure to as few as 10 virus particles, others require exposure to thousands of particles to establish an infection). Currently, the infectious dose of SARS-CoV-2 is not understood with any precision; however, some experts estimate it at a few hundred to a few thousand virus particles.
Like fire needs three things to burn (oxygen, fuel and heat), in my layman’s expression, three factors dictate Covid-19 transmission: activity, duration and proximity.
Different activities release different amounts of virus particles into the environment. On the far end of the spectrum, a cough or sneeze releases about 200-million virus particles. Furthermore, the force of a cough or sneeze can aerosolize these particles (thus allowing them to hang in the air for a long time), or travel across a room in an instant. On the other end of the spectrum, breathing normally releases about 20 virus particles per minute, but with less force than a cough or sneeze. As a result, the particles expelled by breathing will tend to be expelled at a slower speed and travel a shorter distance. Speaking releases about 200 viral particles per minute.
These rates of exposure are important in terms of understanding the time required to exceed the infectious dose threshold. Consider the following formula:
The time required to be infected, assuming close proximity with no precautions, is the infectious dose divided by the rate the virus particles are expelled.
Assuming an infectious dose of 1,000 virus particles, very close proximity to someone speaking (close enough to inhale all the particles released by the speaker) would require 5 minutes to exceed the infectious dose:
Similarly, very close proximity to someone breathing normally would require a ten-fold increase in exposure (50 minutes):
Obviously, a single cough or sneeze with 200-million virus particles will instantly exceed the 1,000 particle threshold.
Again, currently, we do not know the infectious dose – estimates range from a few hundred to a few thousand virus particles. Therefore, the data is insufficient to determine the exact duration of time to acquire an infection. However, public health authorities do provide guidance.
Risk of Infection
The Centers for Disease Control and Prevention (CDC) advises, that for close contact with an individual in a non-healthcare setting, 15 minutes can be used as a threshold for the time to acquire an infectious dose (note: subsequent to the date of this blog post, the CDC’s guidance has been updated from 15 consecutive minutes to 15 non-consecutive minutes in total over a 24-hour period).
Since currently we do not know SAR-CoV-2’s infectious dose, the key take away is an individual is not going to be infected by a single virus particle. However, we are not free from risk. We, as a society, are going to need to weigh the risks. This will take the form of everyday people making everyday decisions about the risks they are willing to accept – both to themselves personally, and to society as a whole. “Nothing is without risk, but you can weigh the risks. . . . It’s going to be a series of judgment calls people will make every day,” as Dr. William Petri a professor of infectious disease at the University of Virginia Medical School, told the Washington Post. 
Forward-thinking customer experience brands will consider how individuals and society as a whole weigh these risks and build customer experiences around both customer expectations and responsible civic commitment. The pandemic represents a moment of truth between brands and their customers. Building responsible and safe customer experiences will become a core driver of trust in the brand.
Some factors individual consumers and customer experience managers will need to consider as we weigh these risks include: 
Distance: At a minimum the environment and activity should allow for 6 feet separation to be maintained.
Duration: The duration of the activity should be short enough to minimize infection risk, considering the specific activity (breathing, talking, singing, etc) and other mitigation efforts (distance, masks, ventilation, etc).
Ventilation: Indoor venues should be well ventilated. Outdoor venues are naturally well ventilated and, therefore, safer.
Masks: Mask wearing by individuals will inhibit the spread of virus particles in the air. The CDC recommends wearing cloth face coverings in public settings where other social distancing measures are difficult to maintain (e.g., grocery stores and pharmacies). Masks are less of a filter to protect the wearer, but they inhibit the spread of virus droplets in the air by the wearer – masks protect others.
Transfer Risk: Customers and employees should avoid unnecessary contact with high touch objects or surfaces, disinfecting surfaces and hands with hand sanitizer.
In the next post, we expand on this discussion of infection risk and mitigation strategies and look at the implications of these on the customer experience and customer experience management.
 “Nothing Like SARS: Researchers Warn The Coronavirus Will Not Fade Away Anytime Soon” npr.org, June 11, 202. Web. August 13, 2020.
 Fred Hutchinson Cancer Research Center. Dr. Amitabha Gupta “Fred Hutch and Covid-19.” August 4, 2020. Video, 10:15. https://www.youtube.com/watch?v=iaa40DflvOk&feature=youtu.be.
 Skinner, Michael. “expert reaction to questions about COVID-19 and viral load” sciencemediacentre.org, March 26, 2020. Web. May 13, 2020.
 “How COVID-19 Spreads.” CDC.gov, May 21, 2020. Web. May 21, 2020.
 “How COVID-19 Spreads.” CDC.gov, May 21, 2020. Web. May 21, 2020.
 “Transmission of SARS-CoV-2: implications for infection prevention precautions.” who.int, July 9, 2020. Web. August 13, 2020.
 Geddes, Linda. “Does a high viral load or infectious dose make covid-19 worse?” newscientist.com, March 27, 2020. Web May 14, 2020.
 Bromage, Eric. “The Risks – Know Them – Avoid Them.” Erinbromage.com, May 6, 2020. Web. May 13 2020.
 “Public Health Recommendations for Community-Related Exposure.” CDC.gov, March 30, 2020. Web. May 15 2020.
 Shaver, Katherine. “Wondering what’s safe as states start to reopen? Here’s what some public health experts say.” Washingtonpost.com, May 15, 2020. Web. May 15, 2020.
 Shaver, Katherine. “Wondering what’s safe as states start to reopen? Here’s what some public health experts say.” Washingtonpost.com, May 15, 2020. Web. May 15, 2020.
 “About Masks.” CDC.gov, August 6, 2020. Web. August 14 2020.
Implications of CX Consistency for Researchers – Part 3 – Common Cause v Special Cause Variation
Previously, we discussed the implications of intra-channel consistency for researchers.
This post considers two types of variation in the customer experience: common and special cause variation, and their implications for customer researchers.
The concepts of common and special cause variation are derived from the process management discipline Six Sigma.
Common cause variation is normal or random variation within the system. It is 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, on the other hand, is not random. It conforms to laws of probability. It 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
What are the implications of common and special cause variation for customer experience researchers?
Given the differences between common cause and special cause variation, researchers need a tool to help them distinguish between the two. Researchers need a means of determining if any observed variation in the customer experience is statistical noise or a signal within the system. Control charts are a statistical tool to make a determination if variation is noise or a signal.
Control charts track measurements within upper and lower quality control limits. These quality control limits define statistically significant variation overtime (typically at a 95% confidence), which means there is a 95% probability that the variation is the result of an actual change in the customer experience (special cause variation) not just normal common cause variation. Observed variation within these quality control limits are common cause variation. Variation which migrates outside these quality control limits is special cause variation.
To illustrate this concept, consider the following example of mystery shop results:
This chart depicts a set of mystery shop scores which both vary from month to month and generally appear to trend upward.
Customer experience researchers need to provide managers a means of determining if the month to month variation is statistical noise or some meaningful signal within the system. Turning this chart into a control chart by adding statistically defined upper and lower quality control limits will determine if the monthly variation is common or special cause.
To define quality control limits, the customer experience researcher needs to determine the count of observations for each month, the monthly standard deviation, and the average count of shops across all months.
The following table adds these three additional pieces of information into our example:
|Count of Mystery Shops||Average Mystery Shop Scores||Standard Deviation of Mystery Shop Scores|
To define the upper and lower quality control limits (UCL and LCL, respectively), apply the following formula:
x = Grand Mean of the score
n = Mean sample size (number of shops)
SD = Mean standard deviation
These equations yield quality control limits at 95% confidence, which means there is a 95% probability any variation observed outside these limits is special cause variation, rather than normal common cause variation within the system
Calculating these quality control limits and applying them to the above chart produces the following control chart, with upper and lower quality control limits depicted in red:
This control chart now answers the question, what variation is common cause and what variation is special cause. The general trend upward appears to be statistically significant with the most recent month above the upper quality control limit. Additionally, this control chart identifies a period of special cause variation in July. With 95% confidence we know some special cause drove the scores below the lower control limit. Perhaps this special cause was employee turnover, perhaps a new system rollout, or perhaps a weather event that impacted the customer experience.
Integrated Digital First CX Model: Implications for CX Researchers
In previous posts to this five-part series on building an integrated digital-first service model we discussed
An integrated delivery channel requires an integration of research methodologies to measure the customer experience. Researchers should think in terms of exposure and moments of truth as they monitor each waypoint in the customer experience.
Understanding Exposure & Moments of Truth Risks
Digital waypoints with high exposure risk should be tested thoroughly with usability, focus groups, ethnography and other qualitative research to ensure features meet customer needs and are programmed correctly. Once programmed and tested, they need to be monitored with ongoing audits.
Waypoints with higher moment of truth risk are best monitored with post-transaction surveys, mystery shopping and the occasional focus group.
Integrated Channel CX Measurement
When measuring the customer experience across multiple channels in an integrated manner, it is important to both gather consistent measures across all channels, as well as measures specific to each channel. Each channel has their own specific needs; however, consistent measures across all channels provide context and a point of comparison.
Here is what an integrated omni-channel research plan may look like:
Kinēsis recommends measuring each channel against a set of consistent brand attribute measurements. Brands have personality, and it is incumbent on CX researchers to evaluate each channel against the overall desired brand personality objectives. A channel disconnected from the institution’s brand objectives can do a lot of damage to the institution’s perceived image.
Kinēsis uses brand adjectives and agreement statements to measure customer impressions of the brand. Ask yourself, what 5 or 6 adjectives you would like customers to describe your institution. Then simply take these adjectives and ask customers if the adjectives describe the customer experience.
Next, ask yourself, what statements you would like the customer to describe their perception of the brand as a result of any interaction. Statements such as:
• We are easy to do business with.
• We are knowledgeable.
• We are interested in members as people, and concerned for their individual needs.
• We are committed to the community.
These statements can be incorporated into the research by asking customers the extent they agree with each of the statements.
Again, brands have personality. Brand adjectives and agreement statements are an excellent way to tie disparate research across multiple channels together with consistent measures of perceptions of the brand personality as a result of the experience.
Channel Specific Dimensions
Different channels have different service attributes; therefore, it is important to provide each channel manager with specific research relevant to their channel. Digital channels, for example, may require measures around: appeal, identity, navigation, content, value and trust. Non-digital managers may require measures such as: reliability, responsiveness, competence, empathy and the physical environment.
Efficacy of the Experience
Regardless of channel, all research should contain consistent measures of the efficacy of the experience. The efficacy of the experience is the institution’s ultimate objective of every customer experience. Ask yourself, how do we want the customer to feel or think as a result of the interaction?
Some examples of efficacy measurements include:
• Purchase Intent/ Return Intent: Kinēsis has a long history using this dependent variable, using purchase intent.
• Likelihood of Referral: Likelihood of referral measures (like Net Promoter Score) are generally accepted as a reliable proxy measure for customer loyalty.
• Member/ Customer Advocacy: The extent to which the financial institution is an advocate for the customer is best measured by using an agreement scale to measure the agreement with the following statement, “This bank cares about me, not just the bottom line.” Agreement with this statement is also an excellent proxy measurement for loyalty.