Tag Archive | Gap Analysis

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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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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