Big Data Analytics to supercharge Sales !!


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 In the post-recession slow growth world, profitability is back on the agenda. Customers have more information at hand than sellers; organization should not rely on gut feeling to sell. Sales agents often spend much time on the prospects who are not likely to buy or who won’t buy enough products. What they need is to have the real time information at their fingertips of who is the customer, what are their intentions, interactions, transaction history to make a profitable impact at the first moment of truth.

With today’s advances in every field of life, most of our interactions as customers or vendors get recoded through digital world and we create humongous data points. The data that is generated in this fashion is massive in volume, comes from multiple sources and in multiple formats such as audios, videos, chats, text messages, picture files, system logs, social media posts like tweets, fb posts etc.

Current CRM or database systems are not designed to take this huge amount of data, of variety of formats and process it to show trends and establish correlations, efficiently.
Big Data has emerged to handle such demands and have been greatly responsible of many success stories at large organizations such as Google, Cisco, MetLife, Wal-Mart,, Forbes etc.

We all know the great example of Amazon using Big data of massive click streams and historical purchasing data from over 150+ million customer accounts, tie that up with over 1.5 billion items in their retail catalog and more than 200 fulfillment centers around the world to produce an improved world class recommendation engine for personalized sale to each customer.

Intel on the other hand developed a big data analytics predictive engine to identify which resellers have greatest potential for high volume sales.
Wal-Mart is using Big data to increase their sales by creating Social Genome to reach customers or friends of customers by analyzing their social footprints.
Salesforce had acquired ExactTarget to make every customer interaction a personalized relationship.

CustomerMatrix is helping organizations by collecting all the structured and unstructured data available there combined with prescriptive analytics to create action alerts to increase revenues.
Infer combined internal company data with external data such as employee count, social presence, job openings, company size etc and built personalized predictive models to score each lead to convert to have most revenue impact.
Retailers are using customer’s smartphone signals and in-house surveillance camera video streams to see where customer go in their stores, which products they look at, to design better product placements and encourage customers to stay longer and buy products.

It will more prudent to use Big data analytics to increase sales by gathering customer feedback even before the sale.  By following the customer on his/her 3 stage decision making journey from trigger (compel him to look for the solution to his problem), research (become as knowledgeable about customer’s problem & solutions as possible) & purchase (make an impression on customer as thought leader & trusted advisor to his problem) stage, sales teams can supercharge the sell.

Republished with author's permission from original post.

Sandeep Raut
Sandeep Raut is Founder and CEO at Going Digital.He is ranked in top 10 global influencers and thought leaders in Digital Transformation.


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