Taking the Big Data Challenge to Transform Retail Industry

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Big Data analytics

The retail industry has seen massive transformation in the last ten years, coping with the advent of new technologies and marketing platforms. Today, the retail industry is using 33% of the overall data available to organizations, projecting a growth of 3.5 percent every year until 2022.

In this article, we blow the lid off all the trends in Big Data analytics in the retail industry and how leading companies are leveraging data and machine learning algorithms to devise their own retail and omni-channel marketing strategies.

Customer Behaviour Analytics

If 2010-2015 belonged to the online ecommerce destinations, 2015-2018 belonged to social media advertising platforms like Facebook, YouTube, Instagram and Twitter. Deeper, data-driven analytics dug out from Mobile, Social Media communications, email campaigns, tele-calling and website form submissions can be integrated with Structured and Unstructured datasets to segment customers into potential buyers and loyalists.

To understand customer behaviour and shopping patterns across markets and geographical regions, retail marketing teams and ecommerce giants rely on a team of well-trained Big Data experts.

In-Store Digital Experience

Earlier, a customer would be welcomed to a website by a simple homepage that would showcase products as they were. Today, every customer sees what he/she is searching for. This smart search is possible due to the higher focus on delivering personalization in a contextual manner. The Big Data Online training programs are specifically designed to understand these:

  • Audience Data from Advertising campaigns
  • People-Based Marketing Data
  • In-Store personalization data

Data engineers rely on Big Data and Intelligent algorithms to integrate cross-selling buyer patterns with the historical data from various point-of-sale gathered from –

  • Websites
  • Mobile apps
  • Referral systems
  • Brick and Mortar stores

Predictive Intelligence for Increasing Product Sale

Retailers- online and offline, are relying no Predictive Intelligence to plan marketing strategies that help them sell more products in less time, thereby affecting the profit lines drastically.

Here are some applications of Big Data-driven predictive intelligence that retailer leverage:

  • Consolidate data points from recommendations and reviews, and presenting them to probable buyers
  • Forecast trends and plan the Big-Day sales
  • Tracking weekday sale to plan the best day of the week/month/quarter, and measure inventory levels to respond to market demands automatically
  • Relying on social media tools to build ‘Sentiment Analysis’ of what products customers speak more often and how they want to buy.

Competition Analytics

What’s the best way to sustain business apart from increasing your profit margins?

It would be to track what your top competitors are doing. Big Data online training enables data engineers to put data-driven insights at the heart of corporate strategy. The intelligent analysis is based on past and present performance of how retail strategies worked, keeping in mind the future predictions and dynamic intent of customers.

New data sources logged in from social media transactions and email communications are adding 200GB data every day, bringing an unprecedented wealth of data for competitive advantage in the ever-expanding retail industry.

Are you ready for the Big Data challenge?

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