Calibrating SEC Classifications In Terms Of Relative Purchasing Power
India is far too complex a market with multiple determinants of consumption behaviour, that no single consumer classification system works well for all kinds of product categories, and for all kinds of strategies. Income is one basic classificatory system which we have discussed earlier. The SEC (socio Economic Classification) system for classifying consumers is a favourite and, some would argue, more robust alternate system used by marketers and market analysts to classify consumers based on their propensity to consume. More robust because it is closely correlated with income, and easy to accurately elicit from respondents, no matter how poor or illiterate they are. The Urban SEC system (classes A to E) is based on the occupation and education of the head of the household, while the rural SEC (R1 to R4) system is based on the education of the head of the household and the type of house lived in.
There is however one problem with SEC classification that income does not have. In the case of income, it is intuitively easy to quantify the purchasing power of each income class; and, as discussed in the previous article on income, while this may not be a valid absolute measure of income, it is a very reliable measure of relative income across different classes, allowing us to compare them usefully. To compare the purchasing power of each SEC class by going back to income distributions of each social class member would defeat the purpose of having an alternate categorization method that was free of the problems of income measurement. Therefore, spurred by the core idea of socio economic classification that all variables used must be easy to elicit and easy to verify, the team at Hansa Research has developed two simple yet forceful constructs, one that works at an aggregate level and the other that works at a category level. Both use data from their IRS study. IRS is a twice a year survey conducted by Hansa Research for the Media Research Users Council, MRUC. IRS 2005 had a sample size of 2,42,118 households from an all India sample.
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The aggregate level index called Households' Potential Index (HPI), |
HPI uses consumption / ownership of a whole host of durables, packaged goods, services and demographics, to construct a simple aggregate index of how much purchasing power a household exhibits. (See table). The concept underlying the index is simple - households owning or using a low penetration item or having a less popular demographic characteristic (like high education levels) get a higher score for that. The scores are then aggregated across all items and a HPI score arrived at for the household. Thus in place of income, we have a sort of "consumption" / "ownership" / "characteristics" based index which is a measure of purchasing power. Again, the score for any category is simply done, eliminating all judgement. It is the reciprocal of the penetration of the category in the total universe. Thus if 70% have a television, then television ownership in a household generates a lower score on power / potential (1/70), but if only 10% have an air conditioner, then air conditioner ownership in a household gets a higher score (1 / 20). The raw scores aggregated across all items included in this index are then normalized on a 1 to 1000 scale. Further, within a broad category, premium versions of it as treated differently - example, a black and white TV, a colour TV and a flat screen TV.
Based on this HPI score, the relative purchasing power of each SEC is as below
For the first time, on a sensible common scale the rural SECs and the urban SECs have been compared. This eliminates the differences in how they think about income (since these types of income surveys measure respondent's perception of their own income, without any cross checks). |
