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Customers don't tell marketers much but most of the information they need is present in the data recorded during the sale. However, most Indian companies fail to exploit valuable customer data effectively. Right now one would be probably sending out one common communication to all the customers - do you really think they are all alike Imagine getting a call one morning from one of your best customers to say that she is leaving. Or from another to say that she is likely to respond positively to your next promotion. Or still another to say that she will buy your product even if you raised its price by 5 per cent.

Customers don't reveal, but there are chances of having enough data about them to predict their behavior to a fair degree of accuracy.

People will be surrounded by valuable customer data, whatever industry it maybe. Several companies are discovering that they have actually been sitting on a goldmine and have started reaping the benefits of analyzing and using the data productively.

While data analytics is not new in the West, most marketers in India still lag behind in effectively mining data for marketing purposes. This is an attempt to de-mystify data analytics so we can make a beginning in leveraging customer data effectively.

Let's look at a few key industries and explore what could be done with the data that get generated by them.

Financial Services:

Whether it's an insurance product, a mutual fund, a credit card or a banking service, there are volumes of data that get captured. They pertain to loans taken by the customer, the time she took to repay them, the deposits she has with you, the degree of risk she is willing to take, the kind of purchases she makes on her credit card, her credit history. You also know how long she has been your customer, who else in her family has an account with you.

Telecommunications:

Like in financial services, you are already capturing detailed data - which plan the customer is on, what kind of calls she makes - local, national, international; their duration and time, the monthly spends. You could layer this with profile information captured through a questionnaire - is she a student, a working mother, a travelling salesman or a senior executive

Upon analysis, you can break down your customer base into six or seven segments and tailor your communication, the medium, offers, pricing and plan according to the new segments that emerge. Right now, you are probably sending out one common communication across your customer base - do you really think they are all alike

B2B:

The relative number of transactions here are fewer while values are higher. Customers can be categorised according to type of industry, geography, value of orders, and mode of payment, and in other ways that are unique to your business. Historical records can throw up the categories of customers you should be focusing your resources on.

Retail:

In this business, as in the FMCG industry, tracking customers was deemed impossible given the sheer volume and complexity of transactions involved. Now, though, several retail outlets capture customer data as part of their loyalty programmes.

From having looked at the loyalty programmes of four large retail groups it emerges that the data captured is inadequate. In most cases, all that is captured is amount spent and number of visits. Crucially, the kind of products bought is missing.

The programme is purely a mechanism to `bribe' the customer to keep returning to accumulate points that can translate to goodies of some kind in the future. Little or no analysis is done to inspire differential communication or offers, nor any attempt made to predict the kind of products the customer will buy in the future. This amounts to under-utilising the power of the loyalty programme.

Pharma:

Medical representatives have been the best users of data from any marketing segment. They are quick to figure out the set of doctors they need to spend their scarce resources of time on. They know who their high-, medium- and low- value customers are and focus their efforts accordingly. Unfortunately, all this is done intuitively. The knowledge resides in their heads and is lost when they move. Rarely is it transferred to the corporate level where it can be consolidated and analysed.

FMCG:

Given the millions of transactions between customers and the company across multiple channels, is it really worth attempting to capture customer data Consider this statistic:

For a large FMCG brand it was found that 67 per cent of its revenues in the city came from just 17 per cent of households. Does it make sense, therefore, to identify these households so that the company can communicate directly and relevantly with them Or should it continue to spend crores of rupees on mass media advertising across the entire market It is an expensive and time-consuming task but imagine if in about five years just 5 per cent of these households can be identified. That's almost 20 per cent of your revenue-generating households which you know personally.

Understanding how to apply the data in any industry is an ongoing challenge. To tease useful information out of the database, we need to apply analytical techniques. These could include profiling techniques, statistical analysis (including regression and cluster analysis) as well as econometric models that forecast outcomes based on trends. Much of the data required to build these models is hidden in your database or can be obtained from third-party sources.

Let's look at just a few of the analytical tools that are available.

Not all customers are created alike. Some are clearly more valuable than others. You need to determine who are the customers that matter and who to ignore. A tool called the Differential Marketing (DFM) Triangle helps us segment customers into three or more categories according to their value to the company.

The DFM triangle, however, gives us just one dimension of the relationship - the value - and is only partially accurate in determining a course of action. It does not tell us how loyal customers are, or in other words, what their share of wallet is. This we determine using a tool called Value Spectrum, which allows us to arrive at the strategy to use according to the degree of value and loyalty that the customers display which segments of customers have the greatest potential value and therefore need to be protected from poaching by competition, which customers should be targeted for greater share of their business from competition, which customers are truly loyal and can be increased in value, and importantly, who should be ignored. This can be potentially a chunk of your customers who otherwise might be getting the same treatment and share of your marketing money as your best prospects.