FLIP: Auditing a Survey, Segmenting a Market
Critique of a flawed questionnaire, a four-cluster hierarchical segmentation, and segment-specific certification strategies for FLIP's professional development product.
Reviewing the questionnaire.
Read the questionnaire in Appendix 2 carefully. Like Anand, I have concerns. There are issues with the construction of the questions and the scales used to collect responses.
- The first two questions are used as filters, which may narrow the data and create biased responses.
- The questionnaire assumes that only people who are actively pursuing professional certifications should take it, which may overlook the people who may not need those certifications.
- The questionnaire also has a class ranking question, which may make some respondents uneasy.
- This is unnecessary on a questionnaire and does not represent everybody with the top 10% or top 25% answer.
- Having a "neither" option may be unfair for respondents because it represents the entire bottom 75%, which is very broad.
- They should create more options such as Bottom 50%, top 30%, prefer not to say.
- And they should also explain why they need this information, as it seems a little irrelevant.
- Every question should also have a "Not applicable" option.
Cluster analysis.
Running a cluster analysis (without discriminant analysis) on the data, there are four clusters here. This is visible by looking at the dendrogram and segment profiles.
Cluster 1, Rookies (42% of population)
- Students who are about to or have recently graduated with very limited working experience.
- They are likely trying to enhance their resumes and will work in finance in the future.
Cluster 2, Seasoned employees (38% of population)
- People who are in the workforce and have decent work experience.
- They are focusing on their certifications and trying to get more relevant work in their field.
Cluster 3, Veterans (10% of population)
- Employees who have a lot of work experience and do not engage with extra activities.
Cluster 4, Specialists (10% of population)
- Employees that have a lot of BFS experience and prioritize comfortable e-learning.
Re-running with discriminant analysis.
When running a cluster analysis with discriminant analysis, the tool flagged a high-collinearity warning. Several variables (B-school = Crème De La Crème, Major Specialization = Marketing, Minor Specialization = Finance, Minor Specialization = Systems, UG Degree = BCom CA, and Percentile in Class = Top 10 Percentile) were removed because of high collinearity with variables already present in the report.
| Option | Selection |
|---|---|
| Clustering method | Hierarchical |
| Standardization method | None |
| Segments forced | 4 |
| Run discriminant analysis | Yes |
| Run classification analysis | Yes |
Next steps for FLIP.
My recommendations for FLIP include strategies to better target each segment.
- For the rookies, focus on improving their resumes and gaining certifications.
- For the seasoned employees, focus on certifications that improve current job skills and allow for potential job switching or job improvement.
- For the veterans, establish more specialization and convenience such as a more flexible schedule and online learning programs.
- For the specialists, focus on convenience and having self-paced e-learning courses.
I would also collaborate with more B-schools and make FLIP a well-known program. This can help because it makes FLIP certifications credible. Workshops, webinars, and informational sessions can help gain awareness.