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How Does Big Data Hadoop Empower Retail Sector
Just a few years and big data Hadoop has made a really great impact on businesses. Let’s talk about the retail market a few years back when no big data was introduced.
Earlier, advertisers had to operate focus groups, consumer polls and panels, & in-store surveys so as to comprehend the success of a particular store or brand, its products and its marketing. In case any information was left unknown then it was essentially left up to guessing.
But, at present Hadoop offers the required technology and data pipeline for assessing consumers as individuals and building individual marketing campaigns consequently. Rather than the guessing work, or gambling and aspiring for success, businesses now are able to make observations on retail data & concentrate on the individual buyer. Not just it cuts back the time spent on researching, but it can reduce marketing budget considerably and helps ads to target right audience.
Components of Retail Analytics
Not just ad campaigns, but there are innumerable applications that can be developed using Hadoop, from analysing the consumer to analysing the brand. Below listed are the five common applications.
Build a Comprehensive analysis of the Customer: There are so many ways by which retailer interact with consumers such as newsletters, social media, in-store and so on. However, customer behaviour is unpredictable without Hadoop. This big data solution can store and correlate transaction data as well as online browsing behaviour. This helps businesses to recognise phases of consumer lifecycle to better boost sales, cut down inventory expenses and develop a loyal consumer base.
Measure Brand Sentiment: Studying brand internally can be sluggish, expensive and erroneous. With Hadoop, businesses are capable of gaining an unbiased outlook on consumers’ opinions of the brand as affected by advertising, product launch, news stories, competitor moves and in-store experiences.
It scans social networking sites like Twitter, Facebook, LinkedIn, etc, browser searches and other media for related keywords to give real-time snapshots of customer satisfaction & insight of the brand. By better understanding of consumers’ opinions, retailers can line up their customer outreach, promotions and products.
Localize & Customise Promotions: Hadoop is such a platform which can change your game plan by combining both historical and real-time streaming data. This helps retailers to localise as well as customise their promotions. Retailers who have mobile apps can send personalised push notifications to users based on the geo-locations. This will help customers know a specific product, deal or promotion in their locality.
Optimize Websites: Clickstream data is a significant division of big data marketing. It notifies retailers what consumers click on and bought or didn’t buy. But, storage for viewing & analysing these perceptions on other database is pricey or they just don’t have the ability for all data exhaust.
Apache Hadoop is capable of storing all the web logs and data for years and at low investment allowing retailers to comprehend user paths, run A/B tests, do basket analysis and prioritize site updates, therefore improving consumer conversion & revenue.
Redesign Store Layouts: The consumer in-store experience is the toughest for retailers to assess as there is no data accessible for their pre-checkout behaviour. But, it’s a known fact that store layouts put an important impact on product sales, hence sensors have been built to help bridge this gap in data. With the help of Hadoop a lot of data is stored, once analysed, this data can help retailer optimise their store layout and enhance the in-store experience. It also reduces cost.
This data storage and data processing framework is really a boon for retailers.
Hence, it becomes to embark upon big data hadoop training in Delhi or any other location that you want.
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