Paul Writer launches Innovative Marketer Dialogue,
Video interview series with CMOs highlights marketing best practices

Anisha Motwani
Director & CEO
Max Life Insurance

 

 

On Big Data, Mobile and Social and how is it being used by your organization?

We’ve been one of the pioneers in insurance space in data analytics, we’ve realized that this is a very unique category, it’s the only product which actually stays with you in all your life stages. You could buy it at a certain age, you may not be around but the product stays. It’s a product that comes into affect even after your death. It’s a different kind of passive category, its not a very actively engaged category where the customer is really interested in keeping track of what is happening to his product or knowing/understanding more of it. You buy it once and then it stays till eternity during which there are no instances and triggers where you feel the need to connect unless there is some renewal premium that you need to pay and realize you’ve forgotten to pay or perhaps need to know the date of payment due. The question is how do you actually use analytics in this kind for this kind of mindset?

One of the things we use analytics very intelligently for is the whole risk profiling of the customer. The customer having bought it once is supposed to retain and stay with the policy and to do that he has to continuously keep re-investing in paying premiums, renewal premiums. To understand customers we do risk-profiling and we analyze the propensity of customers to renew or surrender. We were one of the early ones who developed advanced models that will tell us the risk profile of these customers on the basis of various different variables like geography, income, demographics etc. On the basis of that we are easily able to understand whether a particular customer is going to be persistent, will he pay the next premium or not? What are the chances that he may pay occasionally and drop out? He may be a forgetful customer. Therefore to understand this, we use analytics very intelligently

We have got three different categories of customers and the action plan for each of them is very different. There is the low risk customers (First category) who we know will pay and there isn’t too much effort on following up that is required on this category but on the high risk customers ( Second category), we have a dedicated call center to remind these customers “It is in your best interest to continue with the policy and pay up.”

The third category, where we use analytics widely is the customers with a propensity to re – purchase. This is a category which doesn’t stick to fulfilling one need. For instance, you could’ve bought your first policy for your child but you can also buy your next policy for your retirement needs purely as a savings product for buying insurance cover for death protection. It’s a category that fulfills multiple needs and therefore you can buy multiple products from us.

Data tells us that an average person in mature countries actually buys 5.2 policies from an insurance companies and is considered ideal. The question is how do we go back to the same customer? So we analyze the propensity to re-purchase models’ that will tell us who is the customer that has the propensity to buy again because we don’t want to be chasing everybody, it’s a wasted cost and a wasted time-effort which business cant afford so therefore we analyze through intelligent segmentation done on the basis of customer’s propensity to re-purchase.

We also run analytics not just on our customer database but also on our agent’s database. In a category that is so dependent on the sellers and their effort which are the agents or the advisors who will be persistent with you and who are the ones who have the chance of leaving you midway. Therefore we use an agent retention model. Those are the categories where we actually use analytics very widely but of course there are other areas where we are using risk-profiling and risk-modeling as well. There are multiple applications that we have for data analytics which are very relevant for business for us.

On the social media front, we use analytics and today we have a very large social media community, we’ve got more than 1 million people engaged with us through three different communities that we have – there’s an ‘iGenius Child’ community which is engaging on the subject of parenting, we’ve got ‘Khushiyon Ki Planning’, another community which is engaging on the subject of milestone. If you want to have a successful milestone in life, you need to plan for it in advance so this is what ‘khushiyon ki planning community’ is all about. There’s another community that is interested to know more about insurance products and insurance category on the whole which is very specific and customized to insurance.

Through these three communities you know the profile of these customers, what is the subject that they are interested to talk about, how do we get people to actually come and facilitate these conversations? There is a scientific way in which we go about it and we have a complete content plan and a content calendar for the year available with us. Based on the calendar, we plan interventions and we engage with our customers.

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