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.
Research without call to action may be interesting, but in the end, not very useful.
This is particularly true with customer experience research. It is incumbent on customer experience researchers to give management research tools which will identify clear call to action items –items in which investments will yield the highest return on investment (ROI) in terms of meeting management’s customer experience objectives. This post introduces a simple intuitive mystery shopping analysis technique that identifies the service behaviors with the highest potential for ROI in terms of achieving these objectives.
Mystery shopping gap analysis is a simple three-step analytical technique.
Step 1: Identify the Key Objective of the Customer Experience
The first step is to identify the key objective of the customer experience. Ask yourself, “How do we want the customer to think, feel or act as a result of the customer experience?”
- Do you want the customer to have increased purchase intent?
- Do you want the customer to have increased return intent?
- Do you want the customer to have increased loyalty?
Let’s assume the key objective is increased purchase intent. At the conclusion of the customer experience you want the customer to have increased purchase intent.
Next draft a research question to serve as a dependent variable measuring the customer’s purchase intent. Dependent variables are those which are influenced or dependent on the behaviors measured in the mystery shop.
Step 2: Determine Strength of the Relationship of this Key Customer Experience Objective
After fielding the mystery shop study, and collecting a statistically significant number of shops, the next step is to determine the strength of the relationship between this key customer experience measure (the dependent variable) and each behavior or service attribute measured (independent variable). There are a number of ways to determine the strength of the relationship, perhaps the easiest is a simple cross-tabulation of the results. Cross tabulation groups all the shops with positive purchase intent and all the shops with negative purchase intent together and makes comparisons between the two groups. The greater the difference in the frequency of a given behavior or service attribute between shops with positive purchase intent compared to negative, the stronger the relationship to purchase intent.
The result of this cross-tabulation yields a measure of the importance of each behavior or service attribute. Those with stronger relationships to purchase intent are deemed more important than those with weaker relationships to purchase intent.
Step 3: Plot the Performance of Each Behavior Relative to Its Relationship to the Key Customer Experience Objective
The third and final step in this analysis to plot the importance of each behavior relative to the performance of each behavior together on a 2-dimensional quadrant chart, where one axis is the importance of the behavior and the other is its performance or the frequency with which it is observed.
Interpreting the results of this quadrant analysis is fairly simple. Behaviors with above average importance and below average performance are the “high potential” behaviors. These are the behaviors with the highest potential for return on investment (ROI) in terms of driving purchase intent. These are the behaviors to prioritize investments in training, incentives and rewards. These are the behaviors which will yield the highest ROI.
The rest of the behaviors are prioritized as follows:
Those with the high importance and high performance are the next priority. They are the behaviors to maintain. They are important and employees perform them frequently, so invest to maintain their performance.
Those with low importance are low performance are areas to address if resources are available.
Finally, behaviors or service attributes with low importance yet high performance are in no need of investment. They are performed with a high degree of frequency, but not very important, and will not yield an ROI in terms of driving purchase intent.
Research without call to action may be interesting, but in the end, not very useful.
This simple, intuitive gap analysis technique will provide a clear call to action in terms of identifying service behaviors and attributes which will yield the most ROI in terms of achieving your key objective of the customer experience.
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:
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.
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.
These days, post-transaction surveys are ubiquitous. Brands large and small take advantage of internet-based survey technology to evaluate the customer experience at almost every touch point. Similarly, loyalty proxy methodologies such as Net Promoter (NPS) are very much in vogue. However, many NPS surveys are fielded in a post-transaction context (potentially exposing the research to sampling bias as a result of only hearing from customers who have recently conducted a transaction), and are not designed in a manner that will give managers appropriate information upon which to take action on the research.
At their core, loyalty proxies are brand perception research – not transactional. We believe it is a best practice to define the sample frame as the entire customer base, as opposed to customers who have recently interacted with the brand. Ultimately, these surveys are image and perception research of the brand across the entire customer base.
Happily, this perception research offers an excellent opportunity to gather customer perceptions of the brand, compare them to your desired brand image, as well as measure engagement or wallet share. An excellent survey instrument to accomplish this is a survey divided into three parts:
- Loyalty Proxy: Consisting of the NPS rating or some other appropriate measure and 1 or 2 follow up questions to explore why the customer gave the NPS rating they did.
- Image perception: consisting of 3 or 4 questions to determine how customers perceive the brand.
- Engagement/Wallet Share: consisting of 3 or 4 questions to determine if the customer considers the brand their primary provider, and to gauge share of wallet of various financial products & services across the brand and its competitors.
This research plan will not only yield an NPS, but it will provide insight into why the customers assigned the NPS they did, evaluate the extent to which the entire customer base’s impressions of the brand matches your desired brand image, as well as identify how the brand is perceived by promoters and detractors. This plan will also yield valuable insight into share of wallet, and how wallet share differs for promoters and detractors.
Such a survey need not be long, the above objectives can be accomplished with 10 – 12 questions and will probably take less than 5 minutes for the customer to complete.
In a subsequent posts, we will explore each of these 3-parts of the survey in more detail:
Historically, bank contact centers have served primarily as service hubs, serving customers who call for information or are seeking assistance dealing with a problem in need of resolution. As banks continue to transition into an omni-channel model where customers can interact with the institution across a broad spectrum of channels, the contact center is transitioning into a sales hub, where customers who have researched a product online may still want to speak with a person prior to completing the purchase. As a result, contact center agents will require a new set of sales skills.
To help understand some of the new skill sets required of contact center agents as they transition from a service to sales role, Kinesis conducted mystery shops of six institutions with national scope to identify what customer experience attributes will yield the most ROI in supporting this sales role.
Our conclusion is customers want empathy and competence. They want agents who both care about their needs and can satisfy those needs.
Kinesis performed an analysis of purchase intent to identify the attributes with the most potential for ROI in supporting a sales role. We asked shoppers to rate the experience across a spectrum of service attributes on a 5-point scale where 1 is poor and 5 is excellent; as well assigning a purchase intent rating on a similar 5-point scale. We then cross tabulated the results by purchase intent to identify which attributes have the largest gap between shops which reported positive purchase intent and those which reported negative purchase intent.
Confidence in the Agent, valuing as a customer, interest in helping and explain the products in understandable terms are the four attributes with largest gaps between shops with positive purchase intent and negative, followed by professionalism and job knowledge. Friendliness/courtesy was the attribute with the smallest gap. While friendliness is important, when it comes to driving purchase intent, the attributes with the largest gaps are those related to care and competence. Customers want agents who care about their needs, and are capable of delivering on those needs.
Previously, we also explored the relationship of specific sales and service behaviors to purchase intent.
Cross Tabulation By 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 how they could assist||100%||98%|
|Hold||Increased Purch Intent||Decreased Purch Intent|
|Ask permission to be placed on hold first||85%||73%|
|Give the reason for being placed on hold||100%||88%|
|Give an estimate of how long you would be on hold||56%||27%|
|If the actual hold time exceeded the estimate, representative returned to the call to of the status||88%||50%|
|Thank for holding upon returning||96%||81%|
|Transfer||Increased Purch Intent||Decreased Purch Intent|
|Explain the reason for the transfer||99%||98%|
|Ask permission to transfer||84%||65%|
|Stay on the line until the transfer was answered by another representative||53%||33%|
|If hold time exceeded 60 seconds, return to explain delay and ask if you want to continue to hold.||35%||7%|
|Service||Increased Purch Intent||Decreased Purch Intent|
|Use name at least once during the call||66%||44%|
|Use proper grammar||11%||96%|
|Allow customer to speak first and finish your thought||99%||93%|
|Clarify all requests prior to processing the transaction||100%||80%|
|Maintain a friendly demeanor and pleasant voice throughout the call||100%||91%|
|Describe products or services in a manner that was easy to understand||100%||70%|
|Suggest additional products and/or services||71%||34%|
|Avoid bank jargon or other technical financial terms||100%||95%|
|Ask for business||88%||47%|
|Conclusion||Increased Purch Intent||Decreased Purch Intent|
|Thank for calling||98%||92%|
|Ask how else they could assist||95%||65%|
|Thank for choosing the institution||92%||66%|
|Mean Attribute Ratings||Increased Purch Intent||Decreased Purch Intent|
|Interest in Helping||4.9||3.8|
|Explaining products in understandable terms||5.0||3.9|
|Level of confidence in the representative||4.9||3.2|
|Valuing as a customer||4.9||3.5|