As companies learn to process the flood of data from all sides, traditional models of marketing are slowly giving way to smarter, niche strategies. Firms are now using big data analytics to uncover highly profitable segments, changing their channel management strategy and sales plays. While Big data helps in identifying these micro-segmentation layers, AI is used to personalize their campaign efforts to reach out to this targeted audience, Madalasa Venkataram, Chief Data Scientist at TEG Analytics spoke on these lines at Cypher 2017, India’s most exciting analytics summit.
Big Data: the challenges around
There is no doubt that the amount of data that we have in the present time is beyond anyone’s imagination. However, with growing data, grows the problems around it. As Venkataraman lists, there are three major problem areas:
- Too much data: The challenges of grappling with the data and not knowing how to process it is a common problem organisations face and complain about.
- Too less information: While there is data in abundance, organisations fail to gather any meaningful information out of it.
- Inconsistent information: Varying information derived from data often leaves companies at wit’s end.
Citing examples, Venkataraman pointed how since time immemorial, the capability to process data has always been more than the data available at hand. What she intends to put across is the fact that big data means big processing power.
How can data influence sales, marketing analytics?
During her talk, Venkataraman speaks about the three major challenges that sales and marketing verticals of companies face.
Lack of personalisation towards customers: Companies are trying to make ends meet in order to bridge this gap using artificial intelligence and machine learning. Marketers need to have a single view of their customers because the platform for purchasing has changed.
The declining attention span: In the last 14 years, as Venkataraman cites, the attention span of customers has dropped to a meagre 8 seconds pushing marketers to deliver products that are relevant and has resonance with its users.
“Personalisation is what consumers crave and demand,” she added. Customers are increasingly moving towards personalisation and digital retail transformation is what the changing times demands.
Moreover, optimising channels at a very personal level is how big data helps sales and marketing verticals. The statistical techniques involved are several. It helps to target and delivering personalised services.
What is changing is the processing power and the time frame it needs for implementation of the product offered. Shortened turn-around time or rather to provide solutions real-time is almost what all organisations are working on.
Venkataraman concludes on the note that companies must learn how to use the data and the available tools to benefit both consumers as well and providers in order to answer the right questions with the right answers at the right time.
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