Folks,
Based on queries and comments received in class today re the project, let me try to quickly putup stuff that IMHO mertits wider dissemination.
1. Let me rush to clarify that no great detail is expected in the supply side Q.
As in, you're not expected to say - "XYZ should offer an FD [fixed deposit] with a two year minimum lock-in offering 8.75% p.a.".
No.
Saying "XYZ should offer FDs in its product portfolio." is sufficient.
2. Make the assumption that the sample adequately represents the target population - of young, urban, upwardly mobile professionals.
3. Yes, data cleaning is a long, messy process. But it is worthwhile since once it's done, the rest of the analyses follow through very easily indeed, in seconds.
4. It helps to start with some idea or set of conjectures about a set of product classes and a set of potential target segments in mind, perhaps. One can then use statistical analyses to either confirm or disprove particular hypotheses about them.
5. There is no 'right or wrong' approach to the problem. There is however a logical, coherent and data-driven approach to making actionable recommendations versus one that is not. I'll be looking for logical errors, coherency issues, unsustainable assumptions and the like in your journey to the recommendations you make in phase III.
Hope that clarifies.
Sudhir
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