At Hansa Cequity, we believe Analytical Marketing  will be the biggest competitive advantage enterprises will have in the next decade or two. Successful enterprises of tomorrow will be the ones who can organize and leverage customer information at speed ,to optimize their marketing performance, increase accountability, improve profit and deliver growth. Hansa Cequity insights will bring to you trends and insights in this area and it's our way of sharing best practices so as to help you accelerate this culture and thinking in your organization. We call this kind of an approach Analytical Marketing and we will constantly bring in "best practices" for improving your capabilities in Analytical Marketing.

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The "Rural" in "Urban India"

  
  
  

India’s urban population grew from 290 million, in the 2001 census, to an estimated 340 million in 2008 (this is 30% of India’s population) & according to Mc Kinsey estimates this could go up to as high as 590 million by 2030. It took 40 years for India’s urban population to rise by 230 million (between 1971 & 2008) & India will add the next 250 million in half that time.

What kind of implications does this have for Marketers?

  1. Loyalty: There are very large rural audiences in urban areas in India. This is due to the huge migration that is consistently occurring-moving people from rural to urban areas. I would look to experiment here. Build relevance amongst this segment with loyalty applications that are completely voice based. I would look at loyalty applications that allow this population to use voice based applications to share credits across: transportation, education, & money transfer!
  2. On boarding for new customers: Banks, Telecom companies & other service organizations will rapidly get new customers who are just not familiar with their services. How do you get a customer to start using his debit card on POS without sufficient & relevant information?
  3. Growth of microsegments: need for analytics to study small consumer segments that may begin to display very different behaviour. As an example, youth in lower income household’s may take up Mobile banking in a much bigger way than what was traditionally thought-Marketers need to be watching this kind of behavior change very carefully. Especially Banks, Telecom & retail companies have data at a customer transaction level which will help them watch this kind of behaviour change using advanced analytics.
  4. Impact on Retail: Many years ago during my Retail experience, I found that many stores were impacted by what we called the cluster effect-a store in Hyderabad got many shoppers from Vijaywada, a store in Pune got in customers from Solapur etc. And these customers came in for short visits to the city & ended up spending big time! So they were valuable high ticket customers! All this happens because these visitors had friends & family working in the bigger cities. It would be interesting to see Retailers develop focussed databases to identify such prospects in partnerships with Travel companies?

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