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:
| Channel | Preferred Role |
| 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
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 Usability Tests Ongoing Audits | Post Transaction Surveys Mystery Shopping Focus Groups |
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.
Consistent Measures
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 |
| Brand Adjectives Brand Statements | Purchase Intent Likelihood of Referral Customer Advocacy |
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 |
| Appeal Identity Navigation Content/ Presentation Value Trust | Reliability Responsiveness Empathy Competence Tangibles |
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.
Not All Customer Experience Variation is Equal: Common Cause vs. Special Cause Variation
Variability in customer experience scores is common and normal. Be it a survey of customers, mystery shops, social listening or other customer experience measurement, a certain amount of random variation in the data is normal. As a result, managers need a means of interpreting any variation in their customer experience measurement to evaluate if the customer experience is truly changing, or if the variation they are seeing is simply random.
In a previous post, we proposed the use of control charts as a tool to track customer experience measurements within upper and lower quality control limits, giving managers a meaningful way to determine if any variation in their customer experience measurement reflects an actual change in the experience as opposed to random variation or chance.
Now, managers need to understand the causes of variation, specifically common and special cause variation. Common and special cause variation are six sigma concepts, while most commonly used in industrial production, they can be borrowed and employed to the customer experience.
Common Cause Variation: Much like variation in the roll of dice, common cause variation is natural variation within any system. Common cause variation is any variation constantly active within a system, and represents statistical “noise” within the system.
Examples of common cause variation in the customer experience are:
- Poorly defined, poorly designed, inappropriate policies or procedures
- Poor design or maintenance of computer systems
- Inappropriate hiring practices
- Insufficient training
- Measurement error
Special Cause Variation: Unlike the roll of the dice, special cause variation is not probabilistically predictable within the system, as a result it does not represent statistical “noise” within the system, but is the signal within the system.
Examples of special cause variation include:
- High demand/ high traffic
- Poor adjustment of equipment
- Just having a bad day
When measuring the customer experience it is helpful to consider everything within the context of the company-customer interface. Every time a sales or service interaction within this interface occurs the customer learns something from the experience and adjusts their behavior as a result of the experience. Managing the customer experience is the practice of managing what the customers learn from the experience and thus managing their behavior in profitable ways.
A key to managing customer behaviors is understanding common cause and special cause variation and their implications. Common cause variation is variation built into the system: policies, procedures, equipment, hiring practices, and training. Special cause variation is more or less how the human element and the system interact.
See earlier post:
Use the Right Research Tool: Avoid NPS with Mystery Shopping
Net Promoter Score (NPS) burst on the customer experience scene 15 years ago in a Harvard Business Review article with the confident (some might say over confident) title “The One Number You Need to Grow.” NPS was introduced as the one survey question you need to ask in a customer survey.
Unfortunately, I’ve seen many customer experience managers include NPS in their mystery shopping programs, which is frankly a poor research practice.
The NPS methodology is relatively simple. Ask customers a “would recommend” question, “How likely are you to recommend us to a friend, relative or colleague?” on an 11-point scale from 0-10.
Next, segment respondents according to their responses to this would recommend question. Respondents who answered “9” or “10” are labeled “promoters”, those who answered “7” or “8” are identified as “passive referrers”, and finally, those who answered 0-6 are labeled “detractors”. Once this segmentation is complete, the Net Promoter Score (NPS) is calculated by subtracting the proportion of “detractors” from the proportion of “promoters.” This yields the net promoters, the proportion of promoters after the detractors have been subtracted out.
The theory behind NPS is simple. It is used as a proxy for customer loyalty. Loyalty is a behavior, surveys best measure attitudes, not behaviors. Therefore customer experience researchers need a proxy measurement for loyalty. NPS is considered an excellent proxy for loyalty under the theory that if one is likely to put their reputation at risk by referring a brand to others, they are more likely to be loyal to the brand. In contrast, to those who are not willing to put their reputation at risk are less likely to be loyal.
Fads in customer experience measurement come and go. The NPS fad has been particularly stubborn. Mostly because the theory behind it is intuitive, it is a solution to the problem of measuring loyalty within a survey, and it is simple. I personally think it was oversold as the “one number you need to grow.” Overselling it as the one number you need to grow doesn’t do justice to the complexities of managing the customer experience, nor does one NPS number give any direction in terms of how to improve your NPS score. An NPS score alone is just not very actionable.
While NPS is an excellent loyalty proxy and has a lot of utility is a customer experience survey, it is not an appropriate tool to use in a mystery shopping context. Mystery shopping is a snapshot of one experience in time, where a mystery shopper interacts with the representative of the brand. NPS is a measure of one’s likelihood to refer the brand to others. The problem is the likelihood to refer the brand to others is almost never the result of a snapshot in time. Rather, it is a holistic measure of the health of the entire relationship with the brand, and as such does not work well in a mystery shop context where the measurement is of a single interaction. As such, NPS is a measure of things unrelated to the specific experience measured in the mystery shop; things like: past-experiences, overall branding, alignment of the brand to customer expectations, etc.
Now, I understand the intent of inserting NPS in the mystery shop. It is to identify a dependent variable from which to evaluate the efficacy of the experience. NPS is just the wrong solution for this objective.
There is a better way.
Instead of blindly using NPS in the wrong research context, focus on your business objectives. Ask yourself:
- What are our business objectives with respect to the experience mystery shopped?
- What do we want to accomplish?
- How do we want the customer to feel as a result of the experience?
- What do we want the customer to do as a result of the experience shopped?
Once you have determined what business objectives you want to achieve as a result of the customer experience, design a specific question to measure the influence of the customer experience on this business objective.
For example, assume your objective of the customer experience is purchase intent. You want the customer to be more motivated to purchase after the experience than before. Ask a purchase intent question, designed to capture the shopper’s change in purchase intent as a result of the shop.
Now, you have a true dependent variable from which to evaluate the behaviors measured in the mystery shop. This is what we call Key Driver Analysis – identifying the behaviors which are key drivers of the desired business objective. In the example above we want to identify key drivers of purchase intent.
I like to think of different question types and analytical techniques as tools in a tool box. Each is important for its specific purpose, but few are universal tools which work in every context. NPS may be a useful tool for customer experience surveys. It is not, however, an appropriate tool for mystery shopping.
Best Practices in Mystery Shop Program Launch: Communication of Expectations
In a previous post we introduced the importance of proper program launch.
Best in class mystery shop programs clearly communicate behavioral expectations to frontline employees. There should be no surprises in mystery shopping.
Brands have personality. Brand personality is a set of characteristics associated with the positioning, products, price and service mix offered by a company. Launch the program by communicating your desired brand personality. While branding is a complicated mix of product, price, positioning and place, it often falls on the frontline employees to make the brand real in the perception of the customers – to animate the brand. It is, therefore, critical that employees’ service behaviors be aligned with the brand personality. Start the mystery shop program launch with a clear description of your desired brand personality.
After communication of the brand personality, the next step is to define what specific sales and service behaviors you expect from employees as ambassadors of the brand. Create a list of behavioral expectations by asking yourself the following questions:
- What specific service behaviors do we expect?
- When greeting a customer, what specific behaviors do we expect from staff?
- When meeting with customers after the greeting, what specific behaviors do we expect?
- If a phone interaction, what specific hold/transfer procedures do we expect (for example asking to be placed on hold, informing customer of the destination of the transfer)?
- Are there specific profiling questions we expect to be asked? – If so, what are they?
- What closing behaviors do we expect? How do we want employees to ask for the business?
- At the conclusion of the interaction, how do we want the employee to conclude the conversation or say goodbye?
- Are there specific follow-up behaviors that we expect, such as getting contact information, suggesting another appointment, or offering to call the customer?
- What other specific behaviors do we expect?
Remember the goal is to ensure employees animate the brand. Each behavior expected should support this end.
Ultimately it is a best practice to give employees a copy of the actual questionnaire and shopper guidelines. Best in class mystery shop questionnaires are composed of a mixture of objective behavioral observations and subjective impressions and comments.
The objective observations of behaviors form the backbone of the program. They measure and motivate the specific sales and service behaviors expected from employees. These observations must be both objective and empirical, answering the question, was a specific behavior observed or not?
Rating scales are the most common means of collecting subjective impressions. Measures of how the shopper felt about the experience. They add both a qualitative and quantitative perspective to the objective behaviors, as well as provide a basis for interpreting their importance.
While empirical behaviors are the backbone of the shop, many of Kinēsis’ clients consider open-ended comments the heart of the shop. Subjective open-ended questions should reveal valuable insight into understanding exactly how the shopper felt about the experience.
There should be no surprises in mystery shopping. Customer-facing employees should understand exactly what behaviors are being measured, and how shoppers are to interpret these behaviors in terms of completing the questionnaire.
In a subsequent post we will discuss communication of program administration.
No Surprises in Mystery Shopping – The Importance of Proper Program Launch
There should be no surprises in mystery shopping. When investments in mystery shopping fail to achieve their potential, it is often because those who are accountable for the results, the front-line employees and their direct managers, were not properly introduced to the program.
Improper positioning and introduction of the program risks creating internal resistance. Front-line personnel may interpret mystery shopping as something akin to Orwell’s Big Brother – interpreting it as a distrustful management checking up on their employees. They may see the mystery shop program solely as a means of realizing financial rewards, rather than more intrinsic rewards such as being better at their profession, and as a result game the system by frivolously disputing shops. This internal resistance often manifests itself in the form of excessive disputes, questioning everything, wasting hours of time reviewing security films, and playing a game of indentifying the shopper – almost always phantom shoppers (actual customers who are not mystery shopping them). All this internal resistance creates an unnecessary distraction from realizing the brand’s customer experience goals.
Key to launching a successful mystery shopping program is communication, positive communication of: behavioral expectations of employees, guidance regarding internal program administration, and instruction on how to use the results to improve performance. There should be no surprises in mystery shopping, surprises create resistance and kills buy-in.
Position mystery shopping as a win-win. Position it that mystery shopping is designed to help the employee by making them better at their jobs. Employees want to succeed. They want to be good at their jobs. Leverage this desire to succeed in obtaining buy-in from the frontline.
It is, therefore, critical to ensure employees throughout the organization are fully informed and have bought into the program before it is launched. Pre-launch communication should include:
- definition of the brand
- description of the employees’ role as ambassadors of the brand
- list specific behaviors expected of employees (including a copy of the mystery shop questionnaire)
- answering procedural questions of how to communicate program related issues
- training employees how to read mystery shopping reports
- Finally, how to use the information effectively, including and how to set goals for improvement.
Proper launching of a mystery shop program is critical to its success. Starting on the right foot positions mystery shopping in the minds of customer-facing personnel as a positive tool to help them become better at their jobs – and offers real benefits to them both in terms of rewards as a result of the shop, but also intrinsically as it reinforces sales and service behaviors that will benefit them throughout their career.
Communication is key – again, there should be no surprises in a mystery shop program.
In a subsequent post we will discuss communication of expectations.
It’s Personal: Drivers of Member Purchase Intent as a Result of the Branch Experience
What do potential members want as a result of a visit to your branch? Or, perhaps more importantly, what drives potential members to want to open an account as a result of a visit to your branch?
To answer these questions, Kinesis conducted research into the efficacy of the branch sales process and identified several service and sales attributes that drive member purchase intent. In our observational research of 100 credit union new account presentations, mystery shoppers were asked to describe what impressed them positively as a result of the visit to the credit union. Excluding the branch atmosphere, the five most common themes contained in these open-ended comments were:
- Interest in Helping/ Personalized Service/ Attention to Needs,
- Professional/ Courteous/ Not Pushy,
- Friendly Employees, and
- Product Knowledge of/ Confidence in the Representative
To understand the relative importance of these behaviors with respect to purchase intent, shoppers were asked to rate their purchase intent as a result of the presentation. Kinesis used this rating to group these shops into two groups (those with positive and negative purchase intent) and compared the results of these two groups to each other. Of these positive impressions, three have strong relationships to purchase intent. They are present with greater frequency in shops with positive purchase intent compared to those with negative purchase intent.
|
Reason for Positive Purchase Intent |
Relative Frequency Positive to Negative Purchase Intent |
| Product Knowledge of/ Confidence in the Representative | 2.7 |
| Interest in Helping/ Personalized Service/ Attention to Needs | 2.5 |
| Friendly Employee | 2.3 |
The representative’s product knowledge was cited 2.7 times more frequently in shops with positive purchase intent compared to shops with negative purchase intent. Similarly, attention to needs and personalized service was present 2.5 times more frequently in shops with positive purchase intent compared to those with negative purchase intent. Finally, shoppers were 2.3 times more likely to cite the friendliness of branch personnel in shops with positive purchase intent relative to negative.
Member experiences which focus on personal attention, interest in helping, personalized service, professional, courteous and friendly encounters drive purchase intent as a result of a visit to a credit union.
Best Practices in Mystery Shop Scoring
Most mystery shopping programs score shops according to some scoring methodology to distill the mystery shop results down into a single number. Scoring methodologies vary, but the most common methodology is to assign points earned for each behavior measured and divide the total points earned by the total points possible, yielding a percentage of points earned relative to points possible.
Drive Desired Behaviors
Some behaviors are more important than others. As a result, best in class mystery shop programs weight behaviors by assigning more points possible to those deemed more important. Best practices in mystery shop weighting begin by assigning weights according to management standards (behaviors deemed more important, such as certain sales or customer education behaviors), or according to their importance to their relationship to a desired outcome such as purchase intent or loyalty. Service behaviors with stronger relationships to the desired outcome receive stronger weight.
One tool to identify behavioral relationships to desired outcomes is Key Driver Analysis. See the attached post for a discussion of Key Driver Analysis.
Don’t Average Averages
It is a best practice in mystery shopping to calculate the score for each business unit independently (employee, store, region, division, corporate), rather than averaging business unit scores together (such as calculating a region’s score by averaging the individual stores or even shop scores for the region). Averaging averages will only yield a mathematically correct score if all shops have exactly the same points possible, and if all business units have exactly the same number of shops. However, if the shop has any skip logic, where some questions are only answered if specific conditions exist, different shops will have different points possible, and it is a mistake to average them together. Averaging them together gives shops with skipped questions disproportionate weight. Rather, points earned should be divided by points possible for each business unit independently. Just remember – don’t average averages!
Work Toward a Distribution of Shops
When all is said and done, the product of a best in class mystery shop scoring methodology will produce a distribution of shop scores, particularly on the low end of the distribution.
Mystery shop programs with tight distributions around the average shop score offer little opportunity to identify areas for improvement. All the shops end up being very similar to each other, making it difficult to identify problem areas and improve employee behaviors. Distributions with scores skewed to the low end, make it much easier to identify poor shops and offer opportunities for improvement via employee coaching. If questionnaire design and scoring create scores with tight distributions, consider a redesign.
Most mystery shopping programs score shops according to some scoring methodology. In designing a mystery shop score methodology best in class programs focus on driving desired behaviors, do not average averages and work toward a distribution of shops.
Mystery Shop Key Driver Analysis
Best in class mystery shop programs provide managers a means of applying coaching, training, incentives, and other motivational tools directly on the sales and service behaviors that matter most in terms of driving the desired customer experience outcome. One tool to identify which sales and service behaviors are most important is Key Driver Analysis.
Key Driver Analysis determines the relationship between specific behaviors and a desired outcome. For most brands and industries, the desired outcomes are purchase intent or return intent (customer loyalty). This analytical tool helps mangers identify and reinforce sales and service behaviors which drive sales or loyalty – behaviors that matter.
As with all research, it is a best practice to anticipate the analysis when designing a mystery shop program. In anticipating the analytical needs of Key Driver Analysis identify what specific desired outcome you want from the customer as a result of the experience.
- Do you want the customer to purchase something?
- Do you want them return for another purchase?
The answer to these questions will anticipate the analysis and build in mechanisms for Key Driver Analysis to identify which behaviors are more important in driving this desired outcome – which behaviors matter most.
Next, ask shoppers if they had been an actual customer, how the experience influenced their return intent. Group shops by positive and negative return intent to identify how mystery shops with positive return intent differ from those with negative. This yields a ranking of the importance of each behavior by the strength of its relationship to return intent.
Additionally, pair the return intent rating with a follow-up question asking, why the shopper rated their return intent as they did. The responses to this question should be grouped and classified into similar themes, and grouped by the return intent rating described above. The result of this analysis produces a qualitative determination of what sales and service practices drive return intent.
Finally, Key Driver Analysis produces a means to identify which behaviors have the highest potential for return on investment in terms of driving return intent. This is achieved by comparing the importance of each behavior (as defined above) and its performance (the frequency in which it is observed). Mapping this comparison in a quadrant chart, provides a means for identifying behaviors with relatively high importance and low performance – behaviors which will yield the highest potential for return on investment in terms of driving return intent.
Behaviors with the highest potential for return on investment can then be inserted into a feedback loop into the mystery shop scoring methodology by informing decisions with respect to weighting specific mystery shop questions, assigning more weight to behaviors with the highest potential for return on investment.
Employing Key Driver Analysis gives managers a means of focusing training, coaching, incentives, and other motivational tools directly on the sales and service behaviors that will produce the largest return on investment. See the attached post for further discussion of mystery shop scoring.
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:
Environment
- 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
- 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
Service: Timing
- 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% |
| Prompt greeting | 93% | 76% |
| 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% |
| Manager present | 43% | 31% |
| 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 | ||
| Dimension | Attributes | Difference |
| 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.
Contact Center Behavioral Purchase Intent Drivers: Empathy & Competence
As bank contact centers transition from service hubs to sales centers. It is instructive to investigate which service attributes and behaviors will yield the most ROI in terms of driving sales through the contact center channel.
Beyond the attributes measured in the previous post, Kinesis also performed mystery shop observations of specific behaviors across six institutions with national scope to determine their relationship to purchase intent.
Greeting Behaviors
While the importance of a good first impression is true, across the four greeting behaviors measured, there does not appear to any significant differences between shops with positive purchase intent and shops with negative purchase intent.
| Greeting | Increased Purch Intent | Decreased Purch Intent |
| Greet by identifying the name of the institution | 99% | 97% |
| Greet by identifying themselves | 100% | 97% |
| Ask name | 78% | 71% |
| Ask how they could assist | 100% | 98% |
This is mostly due to the high rate of performance across these greeting behaviors. Greetings are strong across all shops regardless of purchase intent.
Service Behaviors
With respect to broader service behaviors, the behaviors with the largest gaps between shops with positive purchase intent and those with negative purchase intent are: suggesting additional products and asking for the business (each with about 2 times as many shoppers who experience positive purchase intent observing these behaviors compared to shoppers who experience negative purchase intent). Use name, use of understandable descriptions and clarity of speech round out the next three.
Hold & Transfer Behaviors
When the shopper was placed on hold, five behaviors were measured. Of these, giving an estimate of how long the customer will be on hold, and returning if the hold time exceed the original estimate to advice of the status of the call were the behaviors with the strongest relationship to purchase intent. Again, both with about 2 times as many shoppers who experienced positive purchase intent observing these behaviors compared to shoppers who experienced negative purchase intent.
Additionally, five transfer behaviors were measured. Of these, the behavior with the strongest relationship to purchase intent by far is returning to explain any delay after 60 seconds. With five times as many shoppers who reported positive purchase intent observing this behavior relative to those who reported negative purchase intent.
Call Conclusion
Finally, at the conclusion of the call, asking how else the agent could be of assistance and thanking the shopper for choosing the institution were the two behaviors with the strongest relationship to purchase intent.
Of the behaviors measured, a couple of common themes tend to be present in the behaviors with strong relationships to purchase intent. The behaviors with strong relationships to purchase intent tend to deal with the themes of personalized service and valuing the customer.
These behaviors with strong relationships to purchase intent group into these two themes as follows:
Personalized Service/Empathy
- If transfer hold time exceeds 60 seconds, explain delay and ask if customer wants to continue (this behavior 5 times more likely in shops with positive purchase intent compared to negative)
- Give estimate of hold time (2.1 times more frequent in shops with positive purchase intent compared to negative)
- If hold exceeds estimate, return with status update (1.8 times more frequent)
- If transfer, stay on line until completed (1.6 times)
- Use of name (1.5 times)
- Ask how else could assist (1.5 times)
Valuing Customer
- Suggest additional products or services (2.1 times more frequent in shops with positive purchase intent)
- Ask for business (1.9 times)
- Thanks for choosing the institution (1.5 times)
To maximize purchase intent, focus agents on behaviors which personalize the service in an empathetic manner (care for the customer and their needs) and value their business.
Click here for a cross-tabulation of the raw data by purchase intent.
Kinesis CEM 