Perspective on Market Research Study Sampling in India

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India is a really big country for any researcher…

Let me Introduce India to you…

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Map Visual: http://www.economist.com/content/indian-summary

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35 States & UTs

640 districts

7,935+ towns

640,867+ villages

1.2billion individuals

247million householdsMap Visual: http://www.economist.com/content/indian-summary

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As a researcher my three key challenges been:

- To know the actual size of the universe, and size of the cell and the number of members in the final homogenous cell

- To draw appropriate random sample from that cell

- To project/correct the findings back to the population

- Then, infer it with/without enough local knowledge

Map Visual: http://www.economist.com/content/indian-summary

Ideally, how many homogenous cells the country (universe) should be divided in to for capturing the diversity (sampling & weighting) and fully understand it (infer)?

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33,600 cells of Urban India =

35S/UT * 8TC * 5SEC * 6Age * 2Gender * 2Language

37,800 Cells of Rural India =

35S/UT * 3VC * 3DT * 5SEC * 6Age * 2Gender * 2Language

Can be any number, but a valid argument can be:

But realistically, that’s utopian and may be unnecessary…

Map Visual: http://www.economist.com/content/indian-summary

Most of the mass product and service marketers (who are research savvy) have a pan India reach – a distribution network that reaches out to many towns and villages, if not complete India More than 50% business of these marketers’ business

probably come from beyond the top 8 to 10 cities Consumption growths are also higher on cities beyond the

top 8 to 10 cities

All mindshare creation effort (advertising/promotion) by mass marketers today is pan India (spends on geo-locations is possible only if advertiser is very heavy on print, else TV is all pan India)

Then, why are regular market research studies (tracking) limited to just 8 to 10 cities for most of the product/service categories?

Some more points to ponder

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Big budget nation representative studies NSSO: 88 Geographical Regions – Stratified random

Sampling NCAER (CMCR): Stratified Random Sampling IRS: Probability proportionate to size (PPA) - Sample

allocated proportionate to 12 years+ Universe of a geographic unit

National Family Health Survey

Regular Market Research/ Smaller studies/ Monthly Tracking Judgmental, Quota Sampling by Target Group Sometimes post survey correction weighting on 1 or 2

variables with universe estimates from IRS

Some of the sampling practices

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Big Question 1:

What is better, natural (gen. pop.) proportion of users & intenders vs. TG wise quotas?Quota sampling sessions in schools always start with “it is not a advisable method, avoid as much as you can?

Why do we need quota… no reason other than to have “an analyzable base for a segment”?

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Big Question 2:

Why 100 to 200 sample per town?How can 100 sample be representative for a 3million+ population town?

Even after collecting 200 odd sample with what confidence one will analyze the data at an Individual town level to take inferences, especially in India where there is a lot of diversity?

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Is there a more practical way of dividing India?Before that let’s understand India a little more…

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Percentage of urban population is good enough indicator for clubbing of towns together as high level homogenous groups with varied access to infrastructure, social development and consumerism

However all 100,000+ population towns can’t be similar

Urbanization in India

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As per 2011 census there are 47 towns# (1 million+ population towns) accounting for 116 million population accounting for around 30% of all Indian Urban population

Let’s not forget about the growth of 1million+ towns

13Juxt for whoever interested (Public) # Source: http://en.wikipedia.org/wiki/List_of_most_populous_cities_in_India

The emergence of small agglomerates such as these is changing the urban setting in respect of rural access to services. Goods and service facilities are coming nearer to the consumer, and services of new kinds are emerging, inducing a diversification of jobs, notably in construction, food supply and processing, and groceries.

Emerging agglomerates of India

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In some much-urbanized regions, such as Tamil Nadu, the average maximum distance to the nearest city is already only 6 km and will drop to 5.6 km in 2011. For 2011, we can expect 12.3 km for Madhya Pradesh (13.7 km in 2001), 9.2 km for Gujarat (10.2 km in 2001), and 8.1 km for Andhra Pradesh (8.8 km in 2001).

Territorial network is bringing urban agglomerations closer to towns

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Is town class a substitute to town selection for smaller and regular studies?Possibly yes… but not the way Indian Census divides it… various studies provide us enough clue for right course of action.

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Smaller studies can still remained urban focused yet bring in relatively better national representation with even 2000 odd sample, if a at a segment level roughly 377 (95% confidence level & 5% error margin) sample is collected then we can collect sample for 6 town classes instead of 6 to 8 towns

We must not mix up all the 1,000,000 population towns as one and try to group them in 3 sub-groups 30 lakh+ (3mn+) (Top 10 Towns, if required they should

be studied individually) 10lakh to 30lakh (1 to 3million) (37 more towns) 5lakh to 10lakh (0.5 to 1 million) (45 more towns)

1 to 5 lakh towns (404 more towns) Below 1lakh population towns (7531 more towns)

Way forward for typical small sample study

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2,880 cells of Urban India =

4Z * 6TC * 5SEC * 6Age * 2Gender * 2Language

1,440 Cells of Rural India =

4Z * 3VC * 5SEC * 6Age * 2Gender * 2Language

An easier, practical and manageable way for national representative sampling would be:

Or depending on objective & budget we can reduce the no. of cells further…

Map Visual: http://www.economist.com/content/indian-summary

Thank youwww.juxtconsult.com www.getcounted.net

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