Using Big Data for Strategic Communications

Once upon a time, the marketing department was data-starved and decision-making was largely about following the Marketing Head's gut-feel which in turn was influenced by 'trends' of the time.

Now, as the tsunami of Big Data shifts this decision-making to led-by-data and further to overloaded-by-data, strategy seems to take a backseat. But it doesn't have to be that way.

1. Find the Highest Common Factor, not the Least Common DenominatorMost upselling and cross-selling is based on what was searched and bought recently. This is standard data analysis and cross-tabulation at play. While that is good for incremental sales, it does little to grow large-scale business.

Instead, in a market like India, where the potential to grow the pie is still big, we can use data to solve larger business problems - to go beyond sales pitches, and find behavioural triggers.

For example, online retail seems to be battling slow growth beyond cash-on-delivery. Here, big data can help collate first gifting items purchased for delivery to other addresses - these purchases would automatically push consumers to go for some mode of pre-payment, instead of cash-on-delivery. And once they have experienced this mode, they are ripe for a complete shift away from COD.

Once these ideas are discovered, the appropriate ones can be elevated for ad campaigns too. For example: what if in this ad for Amazon, big data could provide the most correct item to purchase? Perhaps sales growth can see a steeper trajectory.

2. Redefine your segmentation criteriaIn absence of data, segmentation is usually done with geography and demographic variables - age, gender, etc. But with big data, these very factors can be challenged. What if, more than geography (small town / large town / metro), the 'life-stage' of the customer (single / married / married with kids) defined his / her purchase behaviour?

3. Redefine your competitionIn MBA classes, we were told of Coca-Cola's big growth story that came from redefining competition as 'all beverages'. Similarly, using big data, we can redefine our brand's competition based on time and money - instead of just product category. As brands move from mere products to experience (and want to charge a premium for it), this becomes interesting as well as critical.

What do you think?
Any stories to share on Big Data?