Previously, we discussed the implications of inter-channel consistency for researchers, and introduced a process for management to define a set of employee behaviors which will support the organization’s customer experience goals across multiple channels.
This post considers the implications of intra-channel consistency for customer experience researchers.
As with cross-channel consistency, intra-channel consistency, or consistency within individual channels requires the researcher to identify the causes of variation in the customer experience. The causes of intra-channel variation, is more often than not at the local level – the individual stores, branches, employees, etc. For example, a bank branch with large variation in customer traffic is more likely to experience variation in the customer experience.
Regardless of the source, consistency equals quality.
In our own research, Kinēsis conducted a mystery shop study of six national institutions to evaluate the customer experience at the branch level. In this research, we observed a similar relationship between consistency and quality. The branches in the top quartile in terms of consistency delivered customer satisfaction scores 15% higher than branches in the bottom quartile. But customer satisfaction is a means to an end, not an end goal in and of itself. In terms of an end business objective, such as loyalty or purchase intent, branches in the top quartile of consistency delivered purchase intent ratings 20% higher than branches in the bottom quartile.
Purchase intent and satisfaction with the experience were both measured on a 5-point scale.
Again, it is incumbent on customer experience researchers to identify the causes of inconsistency. A search for the root cause of variation in customer journeys must consider processes cause variation.
One tool to measure process cause variation is a Voice of the Customer (VOC) Table. VOC Tables have a two-fold purpose: First, to identify specific business processes which can cause customer experience variations, and second, to identify which business processes will yield the largest ROI in terms of improving the customer experience.
VOC Tables provide a clear road map to identify action steps using a vertical and horizontal grid. On the vertical axis, each customer experience attribute within a given channel is listed. For each of these attributes a judgment is made about the relative importance of each attribute. This importance is expressed as a numeric value. On the horizontal axis is a exhaustive list of business processes the customer is likely to encounter, both directly and indirectly, in the customer journey.
This grid design matches each business process on the horizontal axis to each service attribute on the vertical axis. Each cell created in this grid contains a value which represents the strength of the influence of each business process listed on the horizontal axis to each customer experience attribute.
Finally, a value is calculated at the bottom of each column which sums the values of the strength of influence multiplied by the importance of each customer experience attribute. This yields a value of the cumulative strength of influence of each business process on the customer experience weighted by its relative importance.
Consider the following example in a retail mortgage lending environment.
In this example, the relative importance of each customer experience attributes was determined by correlating these attributes to a “would recommend” question, which served as a loyalty proxy. This yields an estimate of importance based on the attribute’s strength of relationship to customer loyalty, and populates the far left column. Specific business processes for the mortgage process are listed across the top of this table. Within each cell, an informed judgment has been made regarding the relative strength of the business process’s influence on the customer experience attribute. This strength of influence has been assigned a value of 1 – 3. It is multiplied by the importance measure of each customer experience attribute and summed into a weighted strength of influence – weighted by importance, for each business process.
In this example, the business processes which will yield the highest ROI in terms of driving the customer experience are quote of loan terms (weighted strength of influence 23.9), clearance of exemptions (22.0), explanation of loan terms (20.2), loan application (18.9) and document collection (16.3).
In a future post, we will look into the concepts of common and special cause variation, and another research methodology designed to identify areas for attention. Control charts as just such a tool.
Self-help resources typically take the form of a webpage housed on the mystery shop provider’s website or on an internal resource page. These resources provide a tutorial in the form of either a PowerPoint or video, reinforcing to stakeholders many of the subjects already discussed: definition of the brand, behavioral service expectations, and a copy of the questionnaire.
These self-help resources are also an excellent opportunity to introduce the mystery shop reports and how to read them (both on an individual shop basis and on an analytical level), and introduce concepts designed to identify the relative importance of specific sales and service behaviors which drive desired outcomes like purchase intent and customer loyalty.
Shop Results E-Mail
Upon distribution of the first shop, it is a best practice in launching a mystery shop program to send an e-mail to the supervisor of the employee shopped advising them of a completed shop, and containing either a PDF shop report or access to the shop via an online reporting tool.
The content of this e-mail should be dependent on the performance of the individuals shopped. If a shop is perfect, the e-mail should congratulate the employees on a perfect shop. If a shop is below expectations, it should inform the employees, in as positive way as possible, that their performance was below expectations and set the stage for coaching. It should remind employees that it is not the performance of this first shop that counts, but subsequent improvement as a result of the shops.
Depending on the timing of shop e-mails, some clients prefer the shop to be sent as soon as it clears the provider’s quality control process, while others prefer shops be held and released in mass at the end of a given shopping period (typically monthly). If the e-mail is sent at the end of a given period, this is an excellent opportunity to identify top performers who received perfect shops as a means of both recognizing superior performance, and motivating other employees to seek similar achievement.
Finally, this e-mail should reinforce superior shop performance by reminding front-line employees and managers of the rewards earned by successful shop performance.
This e-mail should be modified for all subsequent waves of shopping and be used as a cover letter for distribution of all future shops.
Additional e-mails may be sent to notify employees and their managers of specific events, such as: perfect shops, failed shops, shops within a specific score range, or shops which identify a specific behavior of an employee like a cross-sell effort.
Post Shop Call/ Presentation
Similar to the kickoff presentation, after the first wave of shopping, it is a best practice to conduct a post shop presentation, again by conference call or WebEx. The purpose of this presentation is to present the reports available, discuss how to read them, and – most importantly – take action on the results through coaching and interpreting call to action elements built into the program. Call to action elements designed to identify which behaviors are most important in terms of driving purchase intent or loyalty.
Loyalty. There is almost universal agreement that it is an objective – if not the objective – of customer experience management. It is highly correlated to profitably. It lowers sales and acquisition costs per customer by amortizing these costs across a longer lifetime – leading to extraordinary financial results. In retail banking a 5% increase in loyalty translates to an 85% increase in profits.
Loyalty is Emotion Driven
Banks often see themselves as transaction driven; delivery channels are evaluated on their cost per transaction. As a result, there is a lot of attention given to and investment in automated channels which reduce transaction costs and at the same time offer more convenience to customers. Win-win, right? The bank drives costs out of the transaction and customers get the convenience of performing a variety of transactions untethered by time or space. However, while transaction costs and convenience are important, loyalty is often driven by an emotional connection with the institution. An emotional connection fostered by interaction with actual employees at moments of need for the customers –moments with a high level of emotional importance to the customer – moments of truth.
Moments of truth are atypical events, where customers experience a high emotional energy in the outcome (such a lost credit card, loan application, or investment advice). In one study published in McKinsey Quarterly, positive experiences during moments of truth led to more than 85% of customers increasing wallet share by purchasing more products or investing more of their assets (Beaujean et al 06)
Impersonal alternative channels lack the ability to bind the customer to the institution. It’s the people. Effective handling of moments of truth requires frontline staff with the emotional tools or intelligence to recognize the emotional needs of the customer and bind them to the institution.
Previously we discussed the concept of “moments of truth” where some experiences in the customer journey have far greater importance than others. These moments of truth represent increased risk and opportunity to leave a lasting emotional impression on the customer; a lasting impression with significant long-term implications for both customer loyalty and wallet share. The purchase and sales experience is one such moment of truth. One study published in McKinsey Quarterly has determined that the purchase experience of financial services motivated 85% bank customers to purchase more financial products or invest more assets with the institution. (Beaujean et al 06)
We also introduced the concept of defining emotions using two dimensions of mood: valence (positive or negative) and arousal. Again, as we previously observed, modern research into brain activity during the decision process suggests that decisions are made within the brain before we are consciously of them. Emotions provide a short cut to acting on decisions, and rational thought appears to justify decisions after they are made on the subconscious level.
So…given that emotions play a key role in financial decisions, what are the emotions bankers encounter as part of the sales experience?
The emotions financial service customers experience vary by customer, financial need, circumstance and product/service sought, however the emotions a prospective customer may experience include:
• At Ease/Satisfied
So…what do we do with this enlightenment?
First, knowing that people are motivated to maintain positive emotional states and change/mitigate negative emotional states, it is important for the banker to recognize the prospective customer’s emotional motivation and offer solutions which will achieve either of these ends.
Kinesis has conducted research into purchase intent as the result of financial service sales presentation which may be instructive. Click here for this research.
Time and time again, in study after study, we consistently observe that purchase intent is driven by two dimensions of the customer experience: reliability and empathy. Customers want bankers who care about them and their needs and have the ability to satisfy those needs. Specifically, our research suggests the following behaviors are strongly related to purchase intent:
Interest in Helping
Discuss Benefits & Solutions
Promised Services Get Done
Friendly & Courteous
Both empathy and reliability require employees with Emotional Intelligence. These are employees with a positive outlook and a, strong sense of self-empowerment; self regulation; awareness of feelings (both their own and customers); master of fear and anxiety and the ability to tap into selfless motives.
Sales presentations are moments of truth with the potential to leave a lasting impression on the customer with significant long-term implications for both customer loyalty and wallet share – with obvious financial benefits for the institution. We’ve found that branches with above average frequencies of behaviors associated with reliability and empathy experienced a 26% stronger three-year branch deposit growth rate than branches with low frequencies of these behaviors.
Next, we’ll take a look at moments of truth in the context of problem resolution.
Every time a company and a customer interact, the customer learns something about the company, and adjusts their behavior based on what they learn.
To explore this proposition, Kinesis conducted a survey of 500 consumers asking them to recall an experience with any provider that they found to be particularly positive or negative, and determined how these customer experiences influenced customer behavior.
Here is how respondents told us they changed their behavior based on the experience:
This post specifically addresses positive word of mouth as a result of the experience.
Respondents shared positive word of mouth a median 4.3 times as a result of their positive experience, compared to negative experiences, which were shared about 20% more often (median 5.2 times). In fact, they were more likely to share negative word of mouth across all mediums:
Word of Mouth as Result of Experience
|Friend or family (Excluding Online or Social Media)||
|Coworkers (Excluding Online or Social Media)||
|Online Social Media||
Customers are far more likely to share negative experience using online mediums. While they are about 1.2 times more likely to share a negative experience with a relative, friend or coworker via an off line medium, they are 1.7 times more likely to share negative experiences over positive via online mediums.
Again, every time a company and a customer interact, the customer learns something about the company, and changes their behavior based on what they learn. And, as this study shows, they certainly will share this experience with others. But what about the recipients of this word of mouth advertizing? How does one customer’s experience influence the behavior of others?
Approximately 90% of respondents said their purchase decisions were influenced positively (93%) or negatively (85%) by social media or word of mouth reviews.
With customer trust at an all time low, and social media providing a much more far reaching medium of person to person communication, positive word of mouth is becoming far more important in terms of defining the brand. Increasingly social media is becoming the media. With 9 out of 10 potential customers saying their purchase decisions are influenced reviews of others, it is increasing important that managers manage their customer experience to support and reinforce the brand.
Many banks conduct periodic customer satisfaction research to assess the opinions and experiences of their customer base. While this information can be useful, it tends to be very broad in scope, offering little practical information to the front-line. A best practice is a more targeted, event-driven approach collecting feedback from customers about specific service encounters soon after the interaction occurs.
These surveys can be performed using a variety of data collection methodologies, including e-mail, phone, point-of-sale invite, web intercept, in-person intercept and even US mail. Fielding surveys using e-mail methodology with its immediacy and relatively low cost, offers the most potential for return on investment. Historically, there have been legitimate concerns about the representativeness of sample selection using email. However, as the incidence of email collection of banks increases, there is less concern about sample selection bias.
The process for fielding such surveys is fairly simple. On a daily basis, a data file (in research parlance “sample”) is generated containing the customers who have completed a service interaction across any channel. This data file should be deduped, cleaned against a do not contact list, and cleaned against customers who have been surveyed recently (typically three months depending on the channel). At this point, if you were to send the survey invitations, the bank would quickly exhaust the sample, potentially running out of eligible customers for future surveys. To avoid this, a target of the required number of completed surveys should be set per business unit, and a random selection process employed to select just enough customers to reach this target without surveying every customer. 
So what are some of the purposes banks use these surveys for? Generally, they fall into a number of broad categories:
Post-Transaction: Teller & Contact Center: Post-transaction surveys are event-driven, where a transaction or service interaction determines if the customer is selected for a survey, targeting specific customers shortly after a service interaction. As the name implies, the purpose of this type of survey is to measure satisfaction with a specific transaction.
New Account & On-Boarding: New account surveys measure satisfaction with the account opening process, as well as determine the reasons behind new customers’ selection of the bank for a new deposit account or loan – providing valuable insight into new customer identification and acquisition.
Closed Account Surveys: Closed account surveys identify sources of run-off or churn to provide insight into improving customer retention.
Call to Action
Research without a call to action may be informative, but not very useful. Call to action elements should be built into research design, which provide a road map for clients to maximize the ROI on customer experience measurement.
Finally, post-transaction surveys support other behavioral research tools. Properly designed surveys yield insight into customer expectations, which provide an opportunity for a learning feedback loop to support observational research, such as mystery shopping, where customer expectations are used to inform service standards which are in turn measured through mystery shopping.
For more posts in this series, click on the following links:
- Introduction: Best Practices in Bank Customer Experience Measurement Design
- Mystery Shopping: Best Practices in Bank Customer Experience Measurement Design
- Leverage Unrecognized Experts in the Customer Experience: Best Practices in Bank Customer Experience Measurement Design – Employee Surveys
- Filling in the White Spaces: Best Practices in Bank Customer Experience Measurement Design – Social Listening
- A New Look at Comment Cards: Best Practices in Bank Customer Experience Measurement Design – Customer Comments & Feedback
- Customer Experience Measurement Implications of Changing Branch Networks
 Kinesis uses an algorithm which factors in the targeted quota, response rate, remaining days in the month and number of surveys completed to select just enough customers to reach the quota without exhausting the sample.