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:
- 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.
- Quadrant 2: Areas with high correlations to loyalty and high performance. These are service attributes to maintain.
- Quadrant 3: Areas with low correlations to loyalty and low performance. These are service attributes to address if resources are available.
- 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:
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
Kinesis CEM 
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