The next generation marketing

M-commerce is the next best thing to work on. Now the problem is how we diagnose which ad to be placed with which user. This brings to a thought pondering exercise. Here are some golden rules:
1. Find out the social habits of the person through social networking sites
The social networking platform is a good site for diagnosing the basic needs of the person. The forums he uses, the forum he maintains or creates, his social image as presented- all this should give enough pointers to know about the character sketch of the person.

2. Find out the spending habits of the person through the credit card usage
Basically we are trying to find out if he is an impulsive buyer or a logical negotiator. The number of withdrawals from the ATM in terms of frequency and volume should give the nature of his spending. Any company would like to target more of the impulsive buyers, then ending up at the dead end of rationality.
3. Find out the social strata of the person through personal data
This gives the basic economic strata he is in for. The classes define the spending habits as well as the segmentation of the customers on the basis of the income of money.

4. Find out the surfing habits of the person
This leads to the specific ad that a person needs to target to.

5. Find out his hobbies and interests
Obviously, a person with a strong habit would like to spend more on the specific mobile ads.
Mostly in other countries, these things can be tracked via SSN of the country. But in India, these are fragmented. Here comes the concept and use of UID.
The following segmentation of customers can be done based on age, income, surfing habits and interests.
By age, we can see that 0-15, 16-22, 22-32, 32-50, 50-65, 65 and above can be a good segment based on rationality.
Similarly, income levels of 0-3.6, 3.6 to 6.0, 6.0 to 10.0, 10.0 to 18.0, 18.0 to above can be a good segment.
Also, surfing habits can be dumped using the database and then BI tools can be used to run the efficient method of maximum pages hit in a week to find out the surfing habits. If a person buys more things like gadgets online, ads should be of that nature. Simple reasoning would be used to target those specific customers. Similar trend is found suitable in the credit card usage for a person. More of the cause is devoted to the interest levels of that person.
Once the proper segmentation is done, the buying habits can be used to determine the ads for that particular person. More specific and meaningful ads to generate more revenue per volume of ads sent.
Again, the effectiveness in case of companies doing the same has to benchmark against each other from total revenue and revenue per volume of the ads sent.

One Comment

  1. It is true that m-commerce is the next big thing. There are more mobile subscribers than there are PC owners, and the very personal nature of mobiles may increase 'the annual value of goods and services transacted over mobile networks could reach $13 billion, or 7 percent of all e-commerce transactions' , within 3 years.( Analysys (a European telecom consultancy) report, "Mobile e-commerce," February 2000.)However, you have to take into account the disadvantages of limited bandwidth and end-system processing as well as a constrained user interface.Still, the uptake of mobile telephones is expected to continue. Nokia predicts that within three years people will use mobile telephones to access the Internet more often than they use personal computers.The advantages are obvious -the identity of a mobile user can be uniquely determine since mobiles are not usually shared. Operators can also detect a user’s exact location, enabling a whole range of new application.Now, to consider your idea of complementing m-commerce with social networking – market intelligence can be gathered from online communities, especially those who have teens as their target markets. The basic aim of any strategic marketer is to look for patterns so that the requirements of one customer defines that of a larger population, hence , the need of segmentation. The parameters might change, and the traditional segmentation variables might be rendered obsolete, but the future has arrived and we are in it.

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