Tag Archive | Service Behaviors

Opposite Sides of the Same Coin: One Word Descriptions of the Customer Experience In Experiences with Both Positive and Negative Purchase Intent

What one word would a customer use to describe the experience at your bank?

Would your customer experience be described as professional, knowledgeable or informative, or would it be described as frustrating, disappointing, inexperienced or rushed?

One simple and elegant tool to get a picture of your customer experience is to ask customers what one word they would use to describe the customer experience.

Kinesis recently mystery shopped six major North American banks to evaluate the state of the sales and service process at these institutions and identify potential drivers of purchase intent in the customer experience. Shoppers were asked a mixture of closed-ended questions to evaluate the presence or frequency of specific behaviors, and open-ended questions to gather the qualitative impressions of these behaviors on the shoppers – in short the how and why behind what the shopper felt. Part of this research plan was to ask shopper to describe their experience with one word. Finally, to provide a basis to evaluate the effectiveness of each of these brand attributes, shoppers were asked to rate their purchase intent as a result of the visit. This purchase intent rating was then used as a means of evaluating which attributes tend to be used to describe experiences with positive purchase intent compared to those with negative purchase intent.

The descriptions we received from mystery shoppers ranged from professional, knowledgeable, and informative to disappointing, frustrating and rushed. This list of adjectives alone was interesting; however, the purpose of this research was to identify drivers of purchase intent, in part to differentiate experiences with positive purchase intent compared to those with negative purchase intent.

So…how did the customer experience in mystery shops that reported positive purchase intent differ from those that reported negative purchase intent? –OR- Specifically, what adjectives did shoppers use to describe the experience that created positive purchase intent compared to those that created negative purchase intent?

Shoppers who reported purchase intent used the following adjectives to describe the experience.

Adjective Pos PI

From this word cloud the drivers of positive purchase intent can be deduced.  Potential bank customers respond to bankers who are professional, informative, knowledgeable, friendly, pleasant, helpful and attentive.  What customers want is a banker who cares about their needs and has the ability to meet those needs.

Conversely, shoppers who reported negative purchase intent as a result of the customer experience used the following adjectives to describe the customer experience.

Adjective Neg PI

In comparison to the shops with positive purchase intent, the list of adjectives that describe shops with negative purchase intent is a little more nuanced.  Adjectives like frustrating and disappointing are illuminative but not necessarily actionable; while adjectives such as rushed, inexperienced, indifferent, and pushy provide clear direction with respect to elements of the customer experience that undercut purchase intent.

Bottom line: Customers want to do business with bankers who care about their needs and have the ability to satisfy those needs, and reject bankers who are inexperienced, indifferent, pushy or rush the customer through the transaction.

Two Sides of The Same Coin
Positive Purchase Intent Negative Purchase Intent
Professional

Informative/ Knowledgeable

Friendly

Pleasant

Helpful

Attentive

Rushed

Inexperienced

Indifferent

Pushy

When you look at these adjectives side by side, aren’t these opposite sides of the same coin?


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Not All Service Attributes Are Equal: Retail Bank Transaction Drivers of Loyalty

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.  In one study of the retail banking industry, a 5% increase in customer loyalty translated into an 85% increase in profits.[1]

Customer loyalty is driven by the entire relationship with bank.  Image, positioning, products, price and service all mix together in the customer’s’ value equation as customers make a continual decision to remain loyal.

What customer service attributes drive customer loyalty?

This article summarizes research into specific transaction service attributes with the intent of identifying which transaction attributes drive customer loyalty, and provides an analytical tool to help managers determine which attributes will yield the highest potential for ROI in terms of improving customer loyalty.

In order to determine transaction attributes which drive customer loyalty, Kinesis surveyed bank customers who had recently conducted a transaction at a branch.

With respect to the transaction, customers were asked to rate the following service attributes:

  • Professional dress
  • Branch cleanliness
  • Prompt greeting
  • Greeting made customer feel welcome
  • Dependable and accurate
  • Prompt service
  • Willingness to help
  • Job knowledge
  • Interest in helping
  • Best interests in mind
  • Actively listened to needs
  • Ability of bank personnel to help achieve financial needs
  • Desire of bank personnel to help customers achieve financial goals
  • Commitment to community

The next step in the research is to capture a measurement of loyalty against which to compare these attributes.

Measuring customer loyalty in the context of a survey is difficult.   Surveys best measure attitudes and perceptions. Loyalty is a behavior based on rational decisions customers make continually through the lifecycle of their relationship with the bank.  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 the bank, or a new customer may be very satisfied and highly loyal.

Measuring customer loyalty in the context of a survey is difficult.   Surveys best measure attitudes and perceptions. Loyalty is a behavior based on rational decisions customers make continually through the lifecycle of their relationship with the bank.  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 the bank, or a new customer may be very satisfied and highly loyal.

Kinesis proposes a model for estimating customer loyalty based on two measurements: likelihood of referral and customer advocacy.  Likelihood of referral captures a measurement of the customer’s likelihood to refer the bank to friend, relative or colleague.  It stands to reason, if one is going to refer others to the bank, they will remain loyal as well.  Because customers who are promoters of the bank 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.  This concept of trust is perhaps more evident in the second measurement,: customer advocacy.  Customer advocacy is captured by measuring agreement with the following statement: “My bank cares about me, not just the bottom line.”  Customers who agree with this statement trust the bank to do right by them, and not subjugate their best interests to profits.  Customers who trust their bank to do the right thing are more likely to remain loyal.

Kinesis uses likelihood of referral, hereafter labeled “Promoter,” and customer advocacy, hereafter labeled “Trust,” to calculate an estimate of the customer’s loyalty.  Imagine a plot where each customer’s Promoter score is plotted along one axis and the Trust score plotted along the other.  Using this plot we can calculate the linear distance between the perfect state of the highest possible Trust and Promoter ratings.  This distance yields a loyalty estimate for each customer, where the lower the value, the higher the estimate of loyalty – low values are good.[i]

Trust Promoter Plot

See Using Promoter and Trust Measurements to Calculate a Customer Loyalty Index for a complete description of this methodology.

Calculating a loyalty index has value, but limited utility.  A loyalty index alone does not give management much direction upon which to take action.  One strategy to increase the actionably of the research is to use this index as a means to identify the service attributes that drive customer loyalty.  Not all service attributes are equal; some play a larger role than others in driving customer loyalty.

So…how does the research determine an attribute’s role or relationship to customer loyalty?  One tool is to capture satisfaction ratings of specific service attributes and determine their correlation to the loyalty statistic.  The Pearson correlation coefficient is a measure of the strength of a linear association between two variables.

Comparing the correlation of the above service attributes to this loyalty estimate yields the following Pearson Correlation for each attribute:

Pearson Coefficient

Want to help me achieve financial goals

-0.69

Commitment to community

-0.66

Ability to help achieve financial goals

-0.64

Best interests in mind

-0.60

Greeting made customer feel welcome

-0.56

Interested in helping

-0.56

Willing to help

-0.55

Prompt service

-0.51

Actively listened to needs

-0.50

Prompt greeting

-0.49

Dependable and accurate

-0.45

Professional dress

-0.42

Knew job Job knowledge

-0.41

Branch attractive

-0.39

Branch clean

-0.37

Note the Pearson values are negative; the loyalty estimate is an inverse, where lower values indicate a stronger estimate of loyalty.  As a result the stronger negative correlation translates into a correlation to our estimate of loyalty.

The four attributes with the highest correlation to loyalty are:

  1. Want to help me achieve financial goals,
  2. Commitment to community,
  3. Ability to help achieve financial goals, and
  4. Having my best interests in mind.

Two common themes in the top-four attributes are empathy and competence.  Bank customers value relationships with banks that care about their needs and have the ability to satisfy those needs.  Again, customer loyalty is driven by the entire relationship with bank.  However, in terms of transactional service, customers clearly value empathy and competency and will reward banks who deliver on these two attributes with loyalty.


[i] The mathematical equation for this distance is as follows:

Loyalty Index Equation

Where:

T = Trust rating

P = Promoter rating

ST = Number of points on the Trust scale

SP = Number of points on the Promoter scale

 


[1] Heskett, Sasser, and Schlesinger The Service Profit Chain, 1997, New York: The Free Press, p 21


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Call to Action: Using Gap Analysis to Put Loyalty Index into Action

For most service industries the business attribute with the highest correlation to profitability is customer loyalty. It is, therefore, very important to gather a measurement of customer loyalty. However, simply calculating a loyalty index is not enough. Estimating customer loyalty is important, and an obvious first step; however, alone – without any context – is not very useful.

What’s needed is a methodology to transition research into action, and identify clear paths to maximize return on investments in the customer experience. What managers need is a tool to help them prioritize the service behaviors on which to focus improvement efforts. One such tool is an analytical technique called Gap Analysis.

Gap Analysis compares performance of individual service attributes relative to their importance, providing a frame of reference for prioritizing which areas require attention and resources.

To perform Gap Analysis, each service attribute measured is plotted across two axes. The first axis is the performance axis. On this axis the performance of each attribute is plotted. The second axis is the importance axis. Each attribute is assigned an importance rating based on its correlation to the loyalty index. Service attributes with strong correlations to loyalty are deemed more important and service attributes with low correlations are deemed less important.

This two-axis plot creates four quadrants:

Gap Analysis Loyalty

  1. Quadrant 1: Areas with high correlations to loyalty and low performance.  These service attributes are where there is high potential of realizing return on investments in improving performance.
  2. Quadrant 2: Areas with high correlations to loyalty and high performance.  These are service attributes to maintain.
  3. Quadrant 3: Areas with low correlations to loyalty and low performance.  These are service attributes to address if resources are available.
  4. Quadrant 4: Areas with low correlations to loyalty and high performance.  These are service attributes which require no real attention as their performance exceeds their importance.

To illustrate this analysis methodology, consider the example below with the following service attributes:

Performance

Loyalty Correlation

Appearance/cleanliness of physical facilities

4.9

0.37

Appearance/cleanliness of personnel

4.8

0.42

Perform services as promised/right the first time

4.8

0.62

Perform services on time

4.9

0.54

Show interest in solving problems

4.9

0.61

Willingness to help/answer questions

4.7

0.55

Problems resolved quickly

4.4

0.56

Knowledgeable employees/job knowledge

4.6

0.41

Employees instill confidence in customer

4.7

0.52

Employee efficiency

4.7

0.58

Employee courtesy

4.9

0.56

Employee recommendations

4.8

0.53

Questioning to understand needs

4.9

0.45

Plotted on the above quadrant chart, they yield the following chart:

Gap Example

In this example, problems resolved quickly, employee efficiency, willingness to help, employees instill confidence are the four behaviors with relatively high correlations to the loyalty index and relatively low performance  As a result, improvements in these attributes will yield the highest potential for ROI in terms of improving customer loyalty.

Using gap analysis, managers now have a valuable indicator to identify service attributes to focus improvement efforts on.  Directing attention to the attributes in Quadrant I should have the highest likelihood realizing ROI in terms of the customer experience improving purchase intent.

Related Article: Using Promoter and Trust Measurements to Calculate a Customer Loyalty Index


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It’s Personal: Retail Banking Sales and Closing Behaviors That Drive Purchase Intent

There is continued discussion about the branch’s role in the future of banking.  The current consensus is it will continue to evolve from a transactional center to a sales center.  Banking is a professional service.  To avoid commoditization and selling on features other than rates and fees, a professional and effective sales process is required.

Our research into the efficacy of the branch sales process has identified several service and sales attributes that drive purchase intent.  (See the insert below for a description of the methodology).

This article focuses specifically on closing behaviors, attempting to identify best practices in terms of driving purchase intent.

In short, for closing behaviors to be effective, the banker must first demonstrate competence and sincere concern for the customer’s best interests and needs.  Closing behaviors without this predicate can be very dangerous to the sale.

What are the most common closing behaviors?

In our observational research of 100 retail banking presentations, key closing and presentation behaviors were observed in approximately two thirds of the sales presentation.

Express interest in your business or make feel valued as a customer

70%

Ask for the business or some commitment to action

70%

Discuss products in terms of benefits designed to meet needs

68%

Make comment expressing value of banking with the bank

63%

Asking for the business and making the shopper feel valued as a customer were the most common, followed closely by discussing products in terms of benefits designed to meet needs, and finally by expressing the value of banking with the bank.

Which behaviors are most effective?

To answer which of these four behaviors are most effective, let’s look at their relationship to the mystery shoppers purchase intent as a result of the sales presentation.

Closing Chart 1

Of these four behaviors, expressing interest or making the customer feel valued as a customer has the strongest relationship to purchase intent. This behavior was present 3.6 times more frequent in shops with positive purchase intent relative to those with negative purchase intent.

What drives feeling valued as a customer?

Now, let’s take a look at the most significant behavior.  What drives feeling valued as a customer?  What caused shoppers to feel valued?  To gain insight into this, Kinesis asked shoppers an open-ended question regarding how the banker expressed interest in their business.  An analysis of the responses to this question is instructive.

When these responses are grouped by theme they generally group into four themes:

Closing Chart 2

Looking at these comments with respect to whether or not the shopper reported positive purchase intent, two of these themes have a positive relationship to purchase intent: personal attention (45% for positive purchase intent compared to 0% for negative) and concern for needs (43% in shops with positive purchase intent compared to 11% for shops with negative purchase intent).

Comments with POSITIVE relationship to purchase intent.
How expressed interest/Made feel valued as customer…

Positive Purchase Intent

Negative Purchase Intent

Personal/ Full Attention/ Not Rushed

45%

0%

Sincere/ Best interests in mind/ Concern for needs

43%

11%

The other two behaviors have a negative relationship to purchase intent. One of these is both significant and instructive.

Comments with NEGATIVE relationship to purchase intent.
How expressed interest/made feel valued as customer…

Positive Purchase Intent

Negative Purchase Intent

Offer to open account/ Effort to get business

6%

61%

Informative/ Answered questions

17%

50%

A more overt effort to get the business, including opening the account, was present ten times more often in shops with negative purchase intent (61%) compared to positive purchase intent (6%).  An effort to ask for the business without appearing to have the customer’s best interests in mind or giving the customer personal attention will not drive purchase intent.  While asking for the business is an important part of any professional sales presentation, when doing so, the ground needs to be prepared by making the customer feel you have their best interests in mind.  Otherwise, the banker can seriously undermine the presentation.

As branches continue to evolve from a transactional to a sales center, it is important not to divorce service from sales.  Good sales is good service.  The sales behavior with the strongest relationship to purchase intent is expressing interest in the customer and making them feel valued.  The most effective way to make customers feel valued and interested is to provide them your full attention and sincerely demonstrate concern for the customers needs and best interests.

Visit the next article in this series.   Beyond Needs Analysis: Asking Motivation Questions to Drive Purchase Intenthttp://bit.ly/11sK9vG

 

———–

Methodology

To evaluate the state of the in-branch sales process, Kinesis mystery shopped 100 branches among five banks with significant North American footprints.  Among the objectives of the study were to:

1) Define the sales process among different institutions.

2) Evaluate the effectiveness of specific sales behaviors.

Shoppers were asked a mixture of closed-ended questions to evaluate the presence or frequency of specific behaviors, and open-ended questions to gather the qualitative impressions of these behaviors on the shoppers – in short the how and why behind what the shopper felt.  Finally, to provide a basis to evaluate the effectiveness of each sales behavior, shoppers were asked to rate their purchase intent as a result of the visit. This purchase intent rating was then used as a means of evaluating what behaviors tend to be present when positive purchase intent is reported as opposed to negative purchase intent.

 


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Same-Branch Deposit Growth & The Customer Experience

It seems like only yesterday the branch was history. Do you remember twenty years ago when everyone predicted the death of the branch in favor of alternative delivery channels? How things have changed.

Now, the branch is seen as critical to delivering value to not only customers but shareholders as well. Now it appears branches and, more specifically, same-branch deposit growth is a key driver of shareholder value. First Manhattan Consulting Group has determined that other than return on equity and revenue-per-share growth, same-branch deposit growth is the strongest driver of total shareholder return. Furthermore, they quantify this relationship, concluding that 60% of the variance in shareholder return is explained by organic retail deposit growth. The shares of institutions with higher same-branch deposit growth tend to trade at higher multiples-to-earnings than institutions with lower same-branch deposit growth rates.

With the understanding that same-branch deposit growth is a key driver of shareholder value, Kinesis has endeavored to test and understand the relationship, if any, between the customer experience and same-branch deposit growth. We have determined that both purchase intent and same-branch deposit growth appears to be strongly associated with behaviors associated with reliability, empathy, and assurance.

To test the relationship between same-branch deposit growth, Kinesis has conducted thousands of mystery shops of a broad spectrum of institutions ranging in size from community banks with two branches to very large institutions with branch networks in the thousands. To conduct this test, Kinesis used a measurement instrument based on the five-dimensional SERVQUAL model, which defined the customer experience by the following five-dimensions: tangibles, reliability, responsiveness, empathy and competence.

The specific objectives of this analysis were to:

1) Test specific service behaviors/attributes against purchase intent to determine which behaviors, if any, appear to correlate with purchase intent.

2) Evaluate the relationship between the presence of these behaviors and branch deposit growth.

3) Test the efficacy of a mystery shop scoring system and branch deposit growth.

Kinesis first worked to test the relationship between elements of the customer experience and purchase intent, and to determine key drivers of purchase intent in the customer experience. As part of the solution to achieve this end, Kinesis asked each shopper, how the experience would have influenced their intention to purchase had they been an actual customer. Responses to this inquiry were collected on a 5-point scale ranging from “significantly increased” to “significantly decreased” the intention to purchase. Furthermore, immediately following this purchase intent rating, Kinesis asked each shopper to explain why they rated purchase intent as they did.

To help assure the validity of the analysis, two independent analysis plans were applied to the purchase intent data. First, the open-ended comments regarding why the shopper rated their purchase intent as they did were grouped according to common themes and according to the purchase intent rating. Second, the balance of the responses to the mystery shop questionnaire was cross tabulated by the purchase intent rating to determine which specific behaviors correlated most closely with purchase intent.

The results of this first part of the analysis plan revealed the following:

Once a shopper enters the branch, branch personnel clearly drive purchase intent. Over two-thirds (69%) of the reasons given for positive purchase intent are the result of branch personnel, only about one-in-five (18%) were product related, while 8% were due to the branch atmosphere.

The branch personnel driven elements include: generally positive, friendly service (26%), product knowledge/informative/confidence in the personnel (16%), attentive to needs/interest in helping/personalized service (14%), and professional/respectful/not pushy employees (10%). Prospective customers want confidence and trust not just in the bank, but also in the people who are the human face of the institution.

The second part of the analysis plan revealed very strong correlations between the following behaviors and purchase intent:

  • Friendly & Courteous
  • Greeting
  • Interest in Helping
  • Discuss Benefits & Solutions
  • Promised Services Get Done
  • Accuracy
  • Professionalism
  • Express Appreciation
  • Personalized Comment (i.e., How are you?)
  • Listen Attentively

Kinesis then grouped these highly correlated behaviors into the five-dimensional SERVQUAL model and found they group into three of the five-dimensions (reliability, empathy, and assurance) as follows:

  1. Reliability: Promised Services Get Done; and Accuracy
  2. Empathy: Interest in Helping; Discuss Benefits & Solutions; Personalized Comment (i.e., How are you?); and Listen Attentively
  3. Assurance: Friendly & Courteous; Greeting; Professionalism; and Express Appreciation

Intuitively, this result makes sense, beyond the basic requirement of reliability; customers also want to interact with bank personnel who have empathy (care about their best interest) and assurance (the knowledge and courtesy of employees and their ability to convey trust and confidence).

To evaluate the link between the customer experience, and the above behaviors, to the bottom line, Kinesis compared mystery shop results to same-branch deposit growth using publicly available deposit data from the FDIC. This analysis determined that branches with above average frequencies of reliability, empathy and assurance behaviors experienced 26% stronger three-year branch deposit growth rate than branches with low frequencies of these behaviors.

Finally, to evaluate the efficacy of the mystery shop scoring methodology, mystery shop scores were compared to branch deposit growth. This analysis revealed branches with above average mystery shop scores experienced a 78% greater branch deposit growth compared to those with below average mystery shop scores.

Our research and experience leads us to the conclusion that there is a link between the customer experience and such critical financial metrics such as same-branch deposit growth. With an understanding of which attributes drive this relationship, managers can now focus training, incentives and other management techniques on reinforcing empathy and assurance among its personnel, and make a financial case to all stakeholders (management, employees and shareholders) that the customer experience does drive financial performance.


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Closing the Gap: Prioritizing Investments in Customer Service

Probably the most common problem facing the customer experience researcher is the actionability or usefulness of the research.  All too often, while there may be lots of data available, managers lack methodologies to transition research into action, and identify clear paths to maximize return on investments in the customer experience.

This is particularly true with mystery shopping.  When done correctly, mystery shopping can be a valuable tool.  However, often managers collect data about the service behaviors of their employees, but lack a clear means of identifying which behaviors to focus improvement efforts on, or identifying service attributes have the most potential for ROI.

What managers need is a tool to help them prioritize the service behaviors on which to focus improvement efforts.  One such tool is an analytical technique called Gap Analysis.

Gap Analysis compares performance of individual service attributes relative to their importance, providing a frame of reference for prioritizing which areas require attention and resources.

To perform Gap Analysis, each service attribute measured is plotted across two axes.  The first axis is the performance axis.   On this axis the performance of each attribute is plotted.  The second axis is the importance axis.  Each attribute is assigned an importance rating based on its correlation to purchase intent.  Service attributes with strong correlations to purchase intent are deemed more important and service attributes with low correlations to purchase intent are deemed less important.

This two-axis plot creates four quadrants:

  1. Quadrant 1: Areas of high importance and low performance (where there is high potential of realizing return on investments in improving performance).
  2. Quadrant 2: Areas of high importance and high performance.  These are service attributes to maintain.
  3. Quadrant 3: Areas of low importance and low performance.  These are service attributes to address if resources are available.
  4. Quadrant 4: Areas of low importance and high performance, these are service attributes which requ
    ire no real attention as their performance exceeds their importance.

To illustrate this concept, consider the following example quadrant chart where seven service quality attributes are plotted according to their performance and importance.  The “cross-hairs” defining the quadrants are the mid-point (or average) of both the importance and performance measures.  In this case the mid-point of the performance measures is 74%, and the mid-point of the importance axis is 2.9.

According to this example, two service attributes reside in the first quadrant (high importance and low performance).  These attributes are introduce product or service by using targeted question and mention any other product or service.  These two attributes, therefore, are the two that should be focused on first, as improvements in these should yield the most ROI in terms of improving purchase intent.

Gap Analysis Quadrants

No attributes are in the second quadrant (high importance and high performance), and one attribute, offer further assistance, resides in quadrant three (an area to address if resources are available).  The remaining four attributes reside in the fourth quadrant, where performance exceeds importance, and therefore do not require any immediate attention.

In this example, the manager now has a valuable indicator regarding which service attributes they should focus their improvement efforts.  Directing attention to the attributes in Quadrant 1 should have the highest likelihood realizing ROI in terms of the customer experience improving purchase intent.


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