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Case Studies

1. Retail Company in Latin America with 10 Stores Uses Analytics to Improve Sales

Problem :

The customer wanted to understand the needs of their customers in real time and map it to their store offerings, manage their inventory, shelf-placing and optimize the supply chain. Sales were sometimes lost due to online prices offered which were lower than store prices and demand surges.

Solution :

IndustryARC Analytics offered a custom dashboard based solution which offers recommendations on the products to be stocked and the optimum prices at which different products can be priced. For this initiative we pulled data from the POS, inventory/warehouse estimates, online demand parameters through social media and mapped it with historic sales/demand numbers and used data analytics to give a unique tool which helped solve the problem.

Bottom-line :

The client was better able to address customer needs, stay ahead of competition and get real-time recommendations on strategies for pricing and stocking at their stores. Sales increased by 10% over a 6 month period since the solution was implemented across all 10 stores of the retail client.

2. Improvement of Recommendation Engine for an Asian E-commerce Company

Problem :

The company is an e-commerce service provider of more than 8000 items related to electronics, accessories and other items and is relatively new. It had a growing user database with MAU’s increasing by 15% every month and revenues by 3%. It wanted to increase both the stats by making changes to the recommendation engine.

Solution :

IndustryARC studied the purchase and browsing patterns of the company and used overall trends in the market on a global scale. Further in-depth study was done via A/B testing on live users to get a better trend analysis curve. The site functionality was then changed and the recommendation engine was updated to use predictive analytics on products.

Bottom-line :

User interaction time on the site increased by almost 30% and overall sales also increased 17% in the second month itself.

3. Speeding up the Sequencing and Interpretation of Genomics in a Indian Research Organization

Problem :

The institute is a multi-disciplinary research and development organization and is working in mapping the human genome sequence, identifying markers and building its in-house genome database. The data being produced in its research efforts is increasing tremendously and is now in the range of Terabytes. The institute wanted to use analytics to store, analyze and interpret data it already has and is in the process of collecting.

Solution :

IndustryARC used big data analytics to completely overhaul the storing of data coming from DNA sequencing machines. The comparative database where disease markers and input live data is compared, analyzed has also been changed. The entire project has been executed in a record time of 3 months.

Bottom-line :

Data storing and processing times have been reduced significantly. Queries are served 10 times faster than before.

4. Real Time Data Analytics for Power Utility Provider in Europe

Problem :

The company which is a mid-tier Power and other utilities provider in Europe wanted to better analyze the energy usage patterns of its customers, for better pricing and peak time supply efficiency.

Solution :

IndustryARC used the data usage patterns of consumers in a sample locality of 100 households. Data usage in peak and off hours was analyzed and this data was compared, superimposed with other external influencing factors like holidays, weather, seasons etc to make a robust predictive analytics based pricing/supply model.

Bottom-line :

Real-time data from the smart meters where installed is being used in tandem with the prediction engine to help the company plan its supply chain efficiently and help save costs.