Big Data has been gaining in prominence in recent times. For businesses that are experiencing difficulties in making Big Data work in reality, their first step should be to understand the challenges in decoding this Big Data. At Marketing Analytics Conference 2013, the focus point was not to understand the importance of Big Data, but the difficulties and complications in segmenting this data.
According to Arindam Banerjee, Professor, IIM Ahmedabad, “There are three key questions before a marketer starts consuming big data for their products’ overall development. Can we merge new data to traditional ones? Can we build faster decision support models? And can we systematically segment the data to augment predictive model?” The emergence of Big Data in the age of social media has thrown a sea of opportunities for brands and marketers to inspect products’ performance and to understand product’s lifecycle and next version through the conversational data. Banerjee added, “The living room conversations have shifted to our screens and are on record. It’s huge, it’s full of consumer preferences and also this meaty information is muddled with a lot of irrelevant information.”
The discussions segmented this data into three parts, which were – market data, behavioural data and decision making data. While the market data is sourced from agencies, behavioural data might come from social media channels and data registered at the time of purchase can come from the Point of Sale (POS). Big Data analytics never allows the merger of the above three as all of them come from disparate sources. How to draw an inference then? Where can one find a predictive model coming out of this data?
E-retailers have a definite advantage in drawing a line for this kind of data as they have each consumer’s behaviour and consumer movement recorded via clicks on their websites. The problem of disparate sources is not a cause for any worry to the e-retailers. Speaking on how big data has helped Healthkart, its Co-Founder and Managing Director, Prashant Tandon said, “Big Data has helped us break some of the myths around marketing, such as e-shopping is a ‘metro culture’. We realised that it is not true. The numbers coming from smaller cities and rural areas counts to 34 per cent and 25 per cent, respectively. That is more than 50 per cent coming from non-metros. With this data, none of the e-retailers can overlook the importance of semi-urban and rural markets.”
The importance of Big Data has already been understood by the marketers, but why are they standing on the cross roads? Deepak Taneja, Head - Digital Marketing & E-commerce, Nokia India disclosed that the colour yellow was chosen to be the face of their brand’s flagship phone, Lumia 1020, due to the figures coming from the consumers saying yellow is their favourite colour for a phone. This might sound like an example of usage of Big Data, but only to a minimal extent.
Data driven marketing will not be applauded for coming up with results for the masses but only when it can segment and infer distinctive and personalised results for every single consumer. Big Data will take marketing to the smartest distinction, but as of now it is yet to become big enough for marketers.