In change of marketing gear, Maruti using analytics to reach 2020 sales target

It’s one thing to talk big data, and quite another to let analytics gathered from databases of large businesses help with actual prospecting exercises.

India’s passenger vehicle major Maruti Suzuki India Ltd (MSIL) is setting out to achieve a yearly sales target of two million vehicles by 2020.

Significantly, it’s aiming to achieve 10 per cent of that target through database marketing.

With the help of its regional dealer networks and call centres, Maruti Suzuki’s active customers number about 6.5 million.

But the company has a database much larger than that – 15 million customers in all, out of which 12 million have been mapped as ‘unique’.

And so far, database marketing has accounted for about five per cent of the brand’s total sales every year.

The analytics-led customer relationship management (ACRM) leads to Maruti Suzuki running an average of 2,000 targeted regional campaigns in a year with over a lakh cars sold incrementally through database marketing over the last three years. The company collects data from a range of business transactions such as sales, service, exchange, insurance, and customer profiling along with the data on its dealer management system. All of this data runs on a private cloud analytics architecture that helps design sales strategy.

Maruti Suzuki has been at it since 2008. Sanjeev Handa, Vice-President – Marketing, MSIL, lays out the findings: 45 per cent of Maruti’s current customers are first-time buyers, 28 per cent are repeat customers, while another 27 per cent are looking to buy a second car. “When this seed germinates, the fruit we want from the tree is more Maruti. That’s what the efforts are for,” Handa declares.

While there’s not much historical data on first-time buyers, what gets captured on the remaining 55 per cent of customers helps gather insights from when a prospect is due for changing a car to whether their children are at college, the latter being an opportunity to acquire another customer. Moreover, workshop data helps spot accidental or damaged cars, yet another opportunity for sales.

Insights gathered from MSIL databases led to a “successful” geo-specific campaign run in Punjab to push the sales of Alto 800, for example. Customers that have owned an old model of Alto and Alto K10 for over 4.5 years, running over 30,000 kilometres with an insurance claim of over ₹7,000 were identified.

“Our target customers there were on one hand aged 26-35 years and salaried, and on the other, over 55 years and retired, both groups having active transactions with us for a year prior to the campaign. Through our dealers and call centres, we generated over 150 prospects from that exercise,” explains Handa.

In Pune, a similar campaign to generate sales of Ciaz, Maruti Suzuki found that customers between the ages of 26-75 years who owned either an SX4, Dzire or a Swift for over 5.5 years were more likely to upgrade to a higher end sedan. This outreach yielded about 100 prospects out of which about 50 per cent customers purchased the Ciaz.

On the target of two million by 2020, Handa says, “I wouldn’t say we’re being bullish by aiming for 10 per cent of that number but there’s definitely an advantage in using insights from data to sell and service better.”

Maruti Suzuki is reportedly on track to sell 1.3 million cars this fiscal. Besides spending approximately ₹8-10 crore per year on analytics, the company will be attempting to expand the scale of the ACRM project year-on-year.

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