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: Customer Preferences for Financial Service Provider
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.
Next, to inform decisions about digital delivery, we will investigate customer preferences specific digital banking features. What do customers what from the digital channel?
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.
Business Case and Implications for Consistency – Part 4 – Consistency and the Outsized Influence of Poor Experiences
In earlier posts we discussed the business case for consistency, primarily because consistency drives customer loyalty and the causal chain from consistency to customer loyalty.
This post continues to explore the business case for consistency by considering the influence of poor experiences.
To start, let’s consider the following case study:
Assume a brand’s typical customer has 5 service interactions per year. Also assume, the brand has a relatively strong 95% satisfaction rate. Given these assumptions, the typical customer has a 25% probability each year of having a negative experience, and in four years, in theory, every customer will have a negative experience.
As this case study illustrates, customer relationships with brands are not defined by individual, discrete customer experiences but by clusters of interactions across the lifecycle of the customer relationship. The influence of individual experiences is far less important than the cumulative effect of these clusters of customer experiences.
Consistency reduces the likelihood of negative experiences contaminating the clusters of experiences which make up the whole of the customer relationship. Negative experiences, regardless of how infrequent, have a particularly caustic effect on the customer relationship. A variety of research, including McKiney’s The Three Cs of Customer Satisfaction: Consistency, Consistency, Consistency, has concluded that negative experiences have three to four times the influence on the customer as positive experiences – three to four times the influence on the customer’s emotional reaction to the brand – three to four times the influence on loyalty, purchase intent and social sharing within their network.
In our next post we will discuss inter-channel consistency.
Business Case and Implications for Consistency – Part 3: The Causal Chain from Consistency to Customer Loyalty
In an earlier post we discussed the business case for consistency, primarily because consistency drives customer loyalty. This post describes the causal chain from consistency to customer loyalty.
Brands are defined by how customers experience them, and they will have both an emotional and behavioral reaction to what they experience. It is these reactions to the customer experience which drive satisfaction, loyalty and profitability.
There is a causal chain from consistency to customer loyalty. McKinsey and Company concluded in their 2014 report, The Three Cs of Customer Satisfaction: Consistency, Consistency, Consistency, that feelings of trust are the strongest drivers of customer satisfaction and loyalty, and consistency is central to building customer trust.
For example, in our experience in the banking industry, institutions in the top quartile of consistent delivery are 30% more likely to be trusted by their customers compared to the bottom quartile. Furthermore, agreement with the statements: my bank is “a brand I feel close to” and “a brand that I can trust” are significant drivers of brand differentiation as a result of the customer experience. Again, brands are defined by how customers experience them. In today’s environment where consumer trust in financial institutions is extremely low, fostering trust is critical for driving customer loyalty. Consistency fosters trust. Trust drives loyalty.
In our next post we will continue to explore the business case for consistency by considering the influence of poor experiences.
Business Case and Implications for Consistency – Part 1: Why We Value Consistency
Humans value consistency – we are hard wired to do so – it’s in our DNA.
It is generally believed that modern humans originated on the Savanna Plain. Life was difficult for our distant forefathers. Sources of water, food, shelter were unreliable. Dangers existed at every turn. Evolving in this unreliable and hostile environment, evolutionary forces selected in modern humans a value for consistency – in effect hard wiring us to value consistency. We seek security in an insecure world.
In this context, it is not surprising we evolved to value consistency. While our modern world is a far more reliable environment, our brains are still hard wired to value consistency.
The implication for managers of the customer experience is obvious – customers want and value consistency in the customer experience. We’ve all felt it. When a car fails to start, when the power goes out, when software crashes we all feel uncomfortable. A lack of reliability and consistency creates confusion and frustration. We want to have confidence that reliable events like starting the car, turning on the lights or using software will work consistently. In the customer experience realm, we want to have confidence that the brands we have relationships with will deliver consistently on their brand promise each time without variation in quality.
Customers expect consistent delivery on the brand promise. They base their expectations on prior experience. Thus customers are in a self-reinforcing cycle where expectations are set based on prior experiences continually reinforcing the importance of consistency. This is the foundation of customer loyalty. We are creates of habit. The foundation of customer loyalty is built on the foundation of dependable, consistent, quality service delivery.
While we evolved in a difficult and unreliable environment, our modern society is much more reliable. Our modern society offers a much more consistent existent. Again, it’s a self-reinforcing cycle. Product quality and consistency of our mass production economy has reinforced our expectations of consistency.
Today’s information technology continues to reinforce our desire for consistency. However, it adds an additional element of customization. Henry Ford, the father of mass production, famously said of the Model-T, “You can have any color you want as long as it’s black.” Those days are gone. Today, we expect both consistency and customization.
In the next post, we will explore the business case for consistency.
Two Questions….Lots of Insights: Turn Customer Experience Observations into Valuable Insight
Customer experience researchers are constantly looking for ways to make their observations relevant, to turn observations into insight. Observing a behavior or service attribute is one thing, linking observations to insight that will maximize return on customer experience investments is another. One way to link customer experience observations to insights that will drive ROI is to explore the influence of customer experience attributes to key business outcomes such as loyalty and wallet share.
The first step is to gather impressions of a broad array of customer experience attributes, such as: accuracy, cycle time, willingness to help, etc. Make this list as long as you reasonably can without making the survey instrument too long.
For additional thoughts on survey length and research design, see the following blog posts:
Click Here: Maximizing Response Rates: Get Respondents to Complete the Survey
Click Here: Keys to Customer Experience Research Success – Start with the Objectives
The next step is to explore the relationship of these service attributes to loyalty and share of wallet.
Two Questions – Lots of Insight
In our experience, two questions: a “would recommend” and primary provider question, yield valuable insight into the relative importance of specific service attributes. Together, these two questions form the foundation of a two-dimensional analytical framework to determine the relative importance of specific service attributes in driving loyalty and wallet share.
Research has determined the business attribute with the highest correlation to profitability is customer loyalty. Customer loyalty lowers sales and acquisition costs per customer by amortizing these costs across a longer lifetime – leading to some extraordinary financial results.
Measuring customer loyalty in the context of a survey is difficult. Surveys best measure attitudes and perceptions. Loyalty is a behavior not an attitude. Survey researchers therefore need to find a proxy measurement to determine customer loyalty. A researcher might measure customer tenure under the assumption that length of relationship predicts loyalty. However, customer tenure is a poor proxy. A customer with a long tenure may leave, or a new customer may be very satisfied and highly loyal.
Likelihood of referral captures a measurement of the customer’s likelihood to refer a brand to a friend, relative or colleague. It stands to reason, if one is going to refer others to a brand, they will remain loyal as well, because customers who are promoters of a brand are putting their reputational risk on the line. This willingness to put their reputational risk on the line is founded on a feeling of loyalty and trust.
Any likelihood of referral question can be used, depending on the specifics of your objectives. Kinesis has had success with both a “yes/no” question, “Would you refer us to a friend, relative or colleague?” and the Net Promoter methodology. The Net Promoter methodology asks for a rating of the likelihood of referral to a friend, relative or colleague on an 11-point (0-10) scale. Customers with a likelihood of 0-6 are labeled “detractors,” those with ratings of 7 and 8 and identified as “passive referrers,” while those who assign a rating of 9 and 10 are labeled “promoters.”
In our experience asking the “yes/no” question: “Would you refer us to a friend, relative or colleague?” produces starker differences in this two-dimensional analysis making it easier to identify which service attributes have a stronger relationship to both loyalty and engagement.
Similar to loyalty, customer engagement or wallet share can lead to some extraordinary financial results. Wallet share is the percentage of what a customer spends with a given brand over a specific period of time.
Also similar to loyalty, measuring engagement or wallet share in a survey is difficult. There are several ways to measure engagement: one methodology is to use some formula such as the Wallet Allocation Rule which uses customer responses to rank brands in the same product category and employs this rank to estimate wallet share, or to use a simple yes/no primary provider question.
Using these loyalty and engagement measures together, we can now cross tabulate the array of service attribute ratings by these two measures. This cross tabulation groups the responses into four segments: 1) Engaged & Loyal, 2) Disengaged yet Loyal, 3) Engaged yet Disloyal, 4) Disengaged & Disloyal. We can now make comparisons of the responses by these four segments to gain insight into how each of these four segments experience their relationship with the brand.
These four segments represent: the ideal, opportunity, recovery and attrition.
Ideal – Engaged Promoters: This is the ideal customer segment. These customers rely on the brand for the majority of their in category purchases and represent lower attrition risk. In short, they are perfectly positioned to provide the financial benefits of customer loyalty. Comparing attribute ratings for customers in this segment to the others will identify both areas of strength, but at the same time, identify attributes which are less important in terms of driving this ideal state, informing future decisions on investment in these attributes.
Opportunity – Disengaged Promoter: This customer segment represents an opportunity. These customers like the brand and are willing to put their reputation at risk for it. However, there is an opportunity for cross-sell to improve share of wallet. Comparing attribute ratings of the opportunity segment to the ideal will identify service attributes with the highest potential for ROI in terms of driving wallet share.
Recovery – Engaged Detractor: This segment represents significant risk. The combination of above average share of wallet, and low commitment to put their reputational risk on the line is flat out dangerous as it puts profitable share of wallet at risk. Comparing attribute ratings of customers in the recovery segment to both the ideal and the opportunity segments will identify the service attributes with the highest potential for ROI in terms of improving loyalty.
Attrition – Disengaged Detractor: This segment represents the greatest risk of attrition. With no willingness to put reputational risk on the line, and little commitment to placing share of wallet with the brand, retention strategies may be too late for them. Additionally, they most likely are unprofitable. Comparing the service attributes of customers in this segment to the others will identify elements of the customer experience which drive attrition and may warrant increased investment, as well as, elements that do not appear to matter very much in terms driving runoff, and may not warrant investment.
By making comparisons across each of these segments, researchers give managers a basis to make informed decisions about which service attributes have the strongest relationship to loyalty and engagement. Thus identifying which behaviors have the highest potential for ROI in terms of driving customer loyalty and engagement. This two-dimensional analysis is one way to turn customer experience observations into insight.
Guest Return Intent Drivers in the Restaurant Experience
The business attribute with the highest correlation to profitability is loyalty. Loyalty lowers sales and acquisition costs per guest by amortizing these costs across a longer lifetime – leading to some extraordinary financial results. However, the question remains, what service attributes drive guest loyalty?
To answer this question from a behavioral standpoint Kinesis conducted 400 restaurant mystery shops with the purpose of determining which service attributes/behaviors drive guest return intent. Forty-six service attributes were observed across five dimensions of the guest experience: environment, food & beverage quality, greeting, personal attention and timing of food and beverage delivery.
The attributes measured grouped into these five dimensions as follows:
- Table maintained appropriately throughout the meal
- Dining room clean, organized and well maintained
- Exterior building, parking lot, walkways and planters clean
- Silverware, china, glassware and your table clean
- Men’s restroom clean and stocked with supplies
- Lighting fixtures clean and working
- Lobby area clean and organized
- Menus clean and in good condition
- Women’s restroom clean and stocked with supplies
- Bar clean, organized and well maintained
- Room temperature level comfortable
Food & Beverage Quality
- Entrees presented attractively, and tasted good
- Appetizer presented attractively, and tasted good
- Drinks attractively presented, and tasted good
- Dessert presented attractively, and tasted good
- Greeting made feel welcome
- Prompt greeting
- Staff members greet with a friendly smile as being seated
- Thanked and encouraged to visit again
- Ask specific questions about your experience upon leaving
Service: Personal Attention
- Server attentive and prompt throughout the meal
- Server discuss the beverage menu, suggest an item or ask about your preferences
- Server discuss the appetizer menu, suggest an item or ask about your preferences
- Server promote daily specials
- Host carry on a conversation as being seated
- Server discuss the beverage menu or ask about preferences
- Receive appetizer in a timely manner
- Manager engage guests in conversation
- Server smiling and enjoying time with all the guests
- Acknowledged by a server in a timely manner
- Attentive to needs while in the bar area
- Server discuss the dessert menu, suggest an item or ask about preferences
- Server knowledgeable and confident when responding to questions
- Manager present
- Server try and entice you to order their favorite appetizer(s)
- Resolve any service, food or beverage issues
- Food and beverage service timed well
- Receive entrees in a timely manner
- Receive starter soup/ salad in a timely manner
- Receive appetizer in a timely manner
- Manager engage guests in conversation
- Receive drink orders in timely manner
- Receive dessert in a timely manner
- Cashed out in a timely manner
- Acknowledge and get order in a timely manner
- Drinks arrive in a timely manner
In order to determine the relationship of these attributes to return intent, Kinesis asked mystery shoppers if, based on the guest experience, they intended to return to the restaurant. This independent variable was then used as a basis for cross-tabulation to determine the frequency with which the behaviors were observed in shops with positive return intent and negative return intent.
The results of this cross tabulation is as follows:
|Environment||Shops with …|
|Positive Return Intent||Negative Return Intent|
|Table maintained appropriately throughout the meal||96%||73%|
|Dining room clean, organized and well maintained||100%||90%|
|Exterior building, parking lot, walkways and planters clean||100%||94%|
|Silverware, china, glassware and your table clean||98%||94%|
|Men’s restroom clean and stocked with supplies||96%||91%|
|Lighting fixtures clean and working||98%||95%|
|Lobby area clean and organized||100%||98%|
|Menus clean and in good condition||99%||97%|
|Women’s restroom clean and stocked with supplies||93%||92%|
|Bar clean, organized and well maintained||99%||98%|
|Room temperature level comfortable||95%||94%|
|Food & Beverage Quality||Shops with …|
|Positive Return Intent||Negative Return Intent|
|Entrees presented attractively, and tasted good||98%||58%|
|Appetizer presented attractively, and tasted good||97%||88%|
|Drinks attractively presented, and tasted good||97%||88%|
|Dessert presented attractively, and tasted good||97%||97%|
|Greeting||Positive Return Intent||Negative Return Intent|
|Thanked and encouraged to visit again||95%||63%|
|Ask specific questions about your experience upon leaving||35%||8%|
|Greeting made feel welcome||93%||70%|
|Staff members greet with a friendly smile as being seated||60%||44%|
|Service: Personal Attention||Positive Return Intent||Negative Return Intent|
|Server attentive and prompt throughout the meal||93%||45%|
|Server discuss the beverage menu, suggest an item or ask about your preferences||80%||43%|
|Server discuss the appetizer menu, suggest an item or ask about your preferences||68%||33%|
|Server promote daily specials||64%||33%|
|Host carry on a conversation as being seated||70%||41%|
|Server discuss the beverage menu or ask about preferences||63%||35%|
|Manager engage guests in conversation||73%||47%|
|Server smiling and enjoying time with all the guests||97%||73%|
|Acknowledged by a server in a timely manner||96%||73%|
|Attentive to needs while in the bar area||92%||72%|
|Server discuss the dessert menu, suggest an item or ask about preferences||81%||65%|
|Acknowledge and get order in a timely manner||94%||80%|
|Server knowledgeable and confident when responding to questions||98%||86%|
|Server try and entice you to order their favorite appetizer(s)||64%||57%|
|Resolve any service, food or beverage issues||53%||67%|
|Service: Timing||Positive Return Intent||Negative Return Intent|
|Food and beverage service timed well||92%||51%|
|Receive entrees in a timely manner||92%||59%|
|Server promote daily specials||64%||33%|
|Receive starter soup/ salad in a timely manner||91%||60%|
|Receive appetizer in a timely manner||93%||65%|
|Receive drink orders in timely manner||96%||73%|
|Receive dessert in a timely manner||95%||77%|
|Cashed out in a timely manner||97%||81%|
|Acknowledge and get order in a timely manner||94%||80%|
|Drinks arrive in a timely manner||98%||85%|
Putting all this together, the ten attributes with the largest difference between shops with positive and negative return intent are:
|Top 10 Attributes|
|Service: Personal Attention||Server attentive and prompt throughout the meal||48%|
|Service: Timing||Food and beverage service timed well||41%|
|Food||Entrees presented attractively, and tasted good||40%|
|Service: Personal Attention||Server discuss the beverage menu, suggest an item or ask about your preferences||37%|
|Service: Personal Attention||Server discuss the appetizer menu, suggest an item or ask about your preferences||35%|
|Service: Timing||Receive entrees in a timely manner||33%|
|Service: Personal Attention||Server promote daily specials||31%|
|Greeting||Thanked and encouraged to visit again||31%|
|Service: Timing||Receive starter soup/ salad in a timely manner||30%|
|Service: Personal Attention||Host carry on a conversation as being seated||29%|
Of the ten attributed with the strongest relationship to return intent, five belong to the personal attention dimension, three belong to the timing dimension, the food & beverage quality and greeting dimensions round out the top ten with one attribute each.
Directing our attention from specific attributes to broader dimensions, the following chart shows the average difference in shops with positive return intent to shops with negative return intent:
Outside of the timing of food and beverage delivery, the dimensions of the customer experience with the strongest correlation to return intent are the greeting and personal attention, followed by food and beverage quality and the physical environment.
Beyond Loyalty: Engagement/Wallet Share
In two earlier posts we discussed 1) including a loyalty proxy as part of your brand perception research and 2) determining the extent to which your desired brand image is reflected in how customers actually perceive the brand.
Now, we expand the research plan to move beyond loyalty and brand perception, and investigate customer engagement, or the extent to which customers are engaged with the brand through share of wallet.
Comparison to Competitors
The first step in measuring customer engagement is capturing top-of-mind comparisons of your brand to competitors. There are many ways to achieve this research objective, perhaps the simplest is to present the respondent with a list of statements regarding the 4-P’s of marketing (product, promotion, place and price) and asking customers to compare your performance relative to your competitors.
The statements you present to customers should be customized around your industry and business objectives, but they may look something like the following:
- Their products and services are competitive
- They are more customer-centric
- They have lower fees
- They have better service
- They offer better technology
- They are more nimble and flexible
- They are more innovative
Similar to the brand perception statements discussed in the previous post, these competitor comparison statements can be used to determine which of these service attributes have the most potential for ROI in terms of driving loyalty, again, by cross tabulating responses to the customer loyalty proxy.
The next step in researching customer engagement is to determine if the customer considers you or another brand their primary provider. This is easily achieved by presenting the customer with a list of providers, including yourself, and asking them which of these the customer consider their primary provider.
Finally, we can tie industry comparisons to primary provider by asking why they consider their selection as a primary provider. This is best accomplished by using the same list of competitor comparison statements above, and asking which of these statements are the reasons they consider their selection to be the primary provider.
Similar to the brand perception statements discussed in the previous post, these competitor comparison statements can be used to determine which of these service attributes have the most potential for ROI in terms of driving loyalty, by cross-tabulating responses to these statements to the loyalty segments.
Image/Perception: A Mirror to Your Brand
In an earlier post we discussed including a loyalty proxy as part of your brand perception research.
Establishing and measuring loyalty proxies is important, but your brand perception research should not end there. Brand perception research should produce insight beyond loyalty. It should determine the extent to which customers impressions of the brand are aligned with your desired brand image. Additionally, perceptions of the brand among the most loyal and engaged customers should be compared to those who are deemed less loyal or engaged to identify opportunities to improve perceptions of the brand among customers at either risk of defection, or not fully engaged
In a subsequent post, we will address ways to measure engagement/wallet share.
The first step in measuring your brand perception is to define your desired brand. Ask yourself: if your brand were a person, what personality characteristics would you like your customers to describe you with? What adjectives would you want used to describe your brand?
In addition to describing your brand personality with adjectives, come up with a list of statements that describe your desired personality. For example, you may include statements such as:
- We are easy to do business with.
- We are knowledgeable.
- We are like a trusted friend.
- We are interested in customers as people, not just the bottom line.
- We are committed to the community.
So, we defined the brand in terms of personality adjectives and statements. Both will be used in designing the survey instrument.
The Survey Instrument
Unaided Top-of Mind
The first step in the survey instrument, is asking customers for their unaided top-of-mind perceptions of the brand. This will uncover the first thing that comes to customers’ minds about your brand prior to the effects of any bias introduced by the research instrument itself. There are many ways to capture unaided top-of-mind impressions. We like a simple approach, where you ask the customer for the one word that they would use to describe the company. This research question will yield a list adjectives that can be quantified by frequency and used to determine the extent to which customers top-of-mind impressions match the desired brand image.
After we have defined top of mind impressions of the brand, we recommend comparing brand perception to your desired brand identified in the brand definition exercise described above. This is a fairly simple process of presenting the customers with your list of brand personality adjectives and asking the customer which of these adjectives would the customer use to describe the company.
In a much earlier post we discussed using word clouds to interpret brand personality adjectives.
The next step in comparing the reality of brand perception to your branding goals is to ask the customers to what extent do they agree with each of the brand personality statements described above. As with the list of adjectives, this holds a mirror up to your desired image and measures the extent to which customers agree that you are perceived in the manner that you want to be.
Identifying Attributes with the Most ROI Potential
The value of these brand perception statements goes beyond just evaluating if you live up to your brand. Used in conjunction with the loyalty proxies discussed in the previous post, they become tools to determine which of these brand personality attributes will yield the most ROI in terms of improving customer loyalty. This is achieved with a simple cross-tabulation of agreement with these statements by customer loyalty segment. For example, if NPS is used as the loyalty proxy, then we simply compare agreement to these statements from promoters to detractors to determine which attributes have the largest gaps between promoters and detractors. Those with the largest gaps have the most ROI potential in terms of customer loyalty.