A Conjoint Analysis of the Indian Life Insurance Industry
Posted by Category: Analytics and Consulting, Business Analytics, Conjoint Analysis, Marketing, Primary Research.
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A Conjoint Analysis of the Indian Life Insurance Industry
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Why Conjoint Analysis?
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Conjoint Analysis (Srinivasan, V. – 1978) is considered far superior to any other research methodology of knowing consumer perception, and scope of new product launch. The main reason behind this is that this is one of those rare techniques that makes the customer makes real life trade-0ffs between available choices, and hence gives optimal results which can simulate real life conditions.
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To illustrate this point assume that you are conducting a survey of what features are most liked in a sports car using a Likert scale (a scale with 5 or 7 choices ranging from ‘Least Likely’ to ‘Most Likely’”), the consumer does not has to make any trade-offs, and all features from “Top Speed”, “Style”, “Performance”, “Maintainence” emerges out to be highly liked, and the manufacturer (who has got this survey conducted) is left clueless as to what he should focus on. Also for such ranking type scales the difference between the two ranks are equal. But in a real life situation the difference between the likings of different options are the same, which is never so in real life.
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The constant sum technique (in which you ask the respondents to divide a sum of 100 among all the given options) solves the above problems, but is too difficult for the respondents, and after some time they get so exhausted that the results marked in that condition looses its validity. Also it does not tell you how much the user is ready to pay for all these features. In short it only serves to give a fair bit of idea of likeness, and not purchase intentions of the user, and so any estimates of market share calculation, and gap analysis proves faulty.
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Besides solving all these problems, Conjoint Analysis also acts as the mother of all techniques as with this, in a single study we can get to know the following things at once:
- Consumer Perception of all the products of a given category
- Relative Importance of Different Features of a product to a consumer
- How much a consumer is willing to pay for each feature in a product
- The pricing strategy for a given range of product line up
- Gap Analysis in a given product Category
- Likely Market Share of a proposed new product
- The feature composition of a proposed new product
- The effectiveness of sales and marketing departments for an existing product
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Why Indian Life Insurance, Why Now, and Why for the Young Customers?
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I can throw many graphs and tables to prove the point that it is required, but that will only a waste of time for all my readers. I will not do anything till it does not makes business sense, and is also good for the overall society. On one hand we can see the youth of our age groups (who are in the ideal stage to start investing for the safety of their future) who are totally uninterested in all such policies (and really give a damn to the features of the policy, and the medium through which they are being targeted currently), and on another hand we have the Life Insurance Companies, which although understand the importance of the youth segment in their growth potentials, but are trying to pursue them with the same old products, same old mediums, same old positioning that we care a damn about (no doubt many of us are not interested in buying a policy).
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Also, the Insurance sector is going to be opened for foreign investors, and with the current financial state that most of the Life Insurance companies are (except LIC), its highly unlikely that any of the India Players will be able to compete with them if they don’t understand their consumers well, and are able to tap the huge, untapped youth life insurance market. Also for the young customers, although with the foreign companies (presuming they will invest heavily in Market Research) they will get the product that they want, but at a very high price point. So it makes complete sense to bridge this gap between the life Insurance companies and the youth now in the mutual interest of all.
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Now without wasting anymore of your time, we will head directly to the “Design of Experiment” used for this study in the next page ahead.
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Next (Design of Experiment) —>
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Last Page (Result – Conjoint – Indian Insurance) —–>
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