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:
- Quadrant 1: Areas of high importance and low performance (where there is high potential of realizing return on investments in improving performance).
- Quadrant 2: Areas of high importance and high performance. These are service attributes to maintain.
- Quadrant 3: Areas of low importance and low performance. These are service attributes to address if resources are available.
- 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.
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.