Dynamic and Automated Micro-segmentation for highly effective targeted marketing

By Suman Mandal, Global Leader Advanced Analytics Banking Solutions, Virtusa Polaris

As organizations take the digital route, the fundamentals of mar­keting based on segmentation still remain relevant. Emails, SMS, app notifications need to follow the flow to be effective. However, data show that over 95 percent of people never bother to find out more about the product or offer when reached out through emails or notifications. That is mainly because the excess of unre­lated and irrelevant messages automatically switches off the customers’ interest. Organizations need to reach out to their (existing) customers less often when making an offer, but with more relevant content/messages/information. The abundance of both internal and external data makes it possible.

On an average, an organization usually run any­where between two to five carpet-bombing market­ing activities at a time. However, customers are being subjected to campaigns from multiple organizations. Flooded with choice, they pay attention only to those products or services that are most relevant to them. Micro-segmentation’s role is critical in terms of helping organizations find those smaller sets of people to whom a specific product or a specific functionality of a product is most important. Machine learning technology today allows doing this rapidly, dynamically, at massive scale and in a fairly automated fashion by mining massive amounts of data comprising of customers transactions, interactions, demographics along with data from exter­nal sources.

Improving targeted and direct marketing with micro-segmentation

For planned product launches, to boost revenue tar­gets for specific products or categories, or to counter competition, organizations come up with promotions such as “festivity themed discounts”, “spend-more-save-more” offers, etc. These target customers based on de­mographics, income bracket, or specific behaviour, e.g. transaction at a supermarket or an airline travel, etc. Planning and executing such activities take 2 – 6 weeks. Ask a marketer about the success rate of their last campaign and they’ll provide a number and also how they segmented and targeted the customers.

Let’s look at the success rates and also explore if technology can help.

In direct marketing, consistent above the industry average (3–4 per­cent) success rates (for conversion) could mean:

• The product/offer/promotion is unmatched with respect to its val­ue proposition and is supported by great sales, distribution, marketing, brand visibility and reputation, or

• The organization has an unusual way of measuring success and the success of a promotion need not necessarily have an impact on the revenues, or

• The customer base is very homo­geneous

Dynamic micro-segmentation approach can help in all the above cases. If the product is outstand­ing and well supported by sales, micro-segmentation can be used to find out – 1) Pockets of customers who are willing to pay a premium for customisation 2) Scope to re­duce/redistribute marketing mix(e.g. from paid media to earned media) 3) Optimise sales and distribu­tion strategy (e.g. tiered to flat or rewards programs).

To review the process involved in measuring success of promotions, defining success itself is extremely important. Success of a campaign can mean different things to dif­ferent people: from an expression of intent to buy through an actual purchase. A quick check of the re­ceivers of the offers (both those who bought into the offer and those who did not), as well as those who were not supposed to get the offer, can open up gaps in the execution process. Overestimating success in a promotion can be due to under­reporting of the number of people who received the offer-

Depending on how success rate is reported, it could vary from 20% to 5%.

Finally, in case the customer base is, in fact, homogeneous, the bank can launch a product category or brand targeting other types of customers. Micro-segmentation can help in this case extraordinarily well. Combin­ing information on existing custom­ers as well as “prospects” who ap­proach the organization, but do no end up buying, reveal white spaces/opportunities. Micro-segmentation can assist in finding these pockets of growth and help during the process of experimentation to find the suit­able “needs and products/services” matches.

Most organizations today have enough internal data as well as ac­cess to external data to micro-seg­ment their customer base to make more personalised, customised and relevant products, offers and ser­vices.

The technology is available to extract insights without writing elaborate queries. The impact and improvement that micro-segmen­tation can offer are equally high for banks enjoying high levels of success as well as the banks that find it dif­ficult to beat industry averages.

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