Learn from your customers history and turn your data into insight. Let the data work for you!

Better decisions are made with accurate data. PREDICT provides deeper business insights with tools for data blending and accuracy to help you retain customers, spot trends and increase revenues.

Features:

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Actively engage EVERY customer

PREDICT helps you to know churn probability and find patterns in existing data associated with the predicted churn rate.

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Increase Customer engagement multifold on your store with PREDICT

Increase your ROI and improve Customer experiences with the Advanced Store Analytics features of PREDICT.

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Strategize your future with PREDICT

PREDICT allows you to spot trends and make the right business decisions to stay ahead of fierce market competition.

Case Study

Churn Predictive Analysis for a Retail Giant

Challenges

Client had been noticing a significant reduction in its online sales for a while and needed a desperate measure to address this issue. Futurism was selected for its outstanding contribution in solving similar problems for similar domain. We identified the following business challenges:

  • 30% downfall in their order placement.
  • 55% decrease in number of returning customers.
  • Customers were leaving from the payment page without completing the transaction.
  • 15% Increase in product returns.
  • 5. No tools to predict the reasons for all the above problems
Dimensions Solution

Futurism provided end to end services to address this problem including requirement gathering, analysis, program design, and development and testing and showcased various outcomes on powerful dashboards.

  • Data gathering from existing data sources
  • Data cleansing performed as per business requirements
  • Data file was imported into R for building various models
  • Data were differentiated into 2 parts- test data set for testing and train data set for evaluating model
  • Removed unnecessary attributes from data that were not necessary for the model
  • Executed various models on data for finding the appropriate model to find out the best use case for predictive analysis
  • Figured out important attributes that were responsible for people churning out
  • Various Reports and Dashboards were created using Power BI Desktop tool
  • Reports and Dashboards were published on cloud power BI service
Results
  • 60% increase in order placement.
  • 40% increase of returning customers.
  • Successful redirection of appx. 82% customers to successful payments
  • 35% reduction in returns.
  • Based on our recommendations (Dynamic Coupons, deep social integrations etc.) increased user engagements by 50%