Data analytics for retail business

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Data Analytics for Retail Business | Top Golang Web Development Business Problem Retail industry is among top other industry segments realising the need of data driven business. Retailers who use predictive analytics achieve 73% higher sales than those who have never done it. Retailers are opting for Analytics solutions to study customer behaviour and thereby increase profitability and sales. Client is looking for a Big Data analytics solution that will pull data from different sources to determine: 

Know what customers are most likely to buy in advance

Determine the highest price a customer will pay for a product

Target recommendations and promotions

Practise better price management

Reduce fraud

Improve supply chain management

Enhance business intelligence

Business Solution We developed a Big Data analytics platform using Golang, Python , and Hadoop to pull data from TeraData. The Platform can produce Analytics based on Historical Data, and at the same time, it offers Predictive Analytics based on Hadoop Data storage. The client has a Data volume turnover of 900GB annually. This Data is in the form of Structured as well as Semi-structured Data which is sourced from Products, Customers, Departments, Orders, Transaction, Purchase History, and much more. Our Data Analytics solution collects, stores and analyses data collected from SQL Server (Client Database Server) by scheduling job to pull relevant data. Deciphering this massive amount of data the platform can determine: Dynamic Pricing 

This analytical platform has a great advantage in dynamic pricing as it responds to the competitive market rapidly by changing the prices of its products every 2 minutes (if required)

Clickstream Analysis


Click Stream analysis defines the pages the visitor visits on a website. Further it tracks the path visitor takes to reach to the final page to make a purchase. This helps businesses to reduce the steps and enhance usability. Enhanced usability results in minimizing the customer drop-outs.

Social Media Analysis 

Customer sentiment analysis helps business owners knowing the positive and negative feedbacks of the customers using their products. These feedbacks are captured from social medias and gives business owners the insights of any difficulties customers are facing and take necessary actions to improvise.

360° Customer Analysis 

Customer Satisfaction is the key for retailers to boost their sales. Retailers can leverage their businesses using data analytics solution. Our data analytics solution assist retailers in analysing the consolidated data captured from POS, online transactions, social media awareness and customer service centers.

Fraud Detection and Prevention The predictive/ Big Data Analytics platform thus provides the Client with crucial information. This prediction aids them in taking accurate actions to avoid frauds.

Business Benefit 

Customer Satisfaction

Increase sale

Data Processing time down to 1 week & even daily

Mainframe Cost Saving

Identify new product opportunities within our current market

Build unique customer profiles & personas in order to match solutions to specific customer needs

Improve brand image of our company

Avoid offer spam

Source: https://www.qwentic.com


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