Traditionally retailers have made ad-hoc efforts to reduce customer churn by modifying pricing or marketing campaigns based on assumptive predictions.
Using Big Data analytics retailers can now discover patterns in customer data that allows them to give a ‘churn’ score to a segmented customer base. With the tools to effectively ascertain a customer’s lifetime value based on attributes like browsing history, purchase history and social media activity, retailers can confidently tailor programmes to improve service, loyalty and retention.
Retailers are under mounting pressure from the sheer number of competitors in the Omni-channel world. They need dynamic, demand-based intelligence to initiate promotions and deliver their products to consumers at the right price, in the right place, at the right time.
Big Data analytics allows retailers to implement a flexible pricing strategy using real-time intelligence. It allows them to forecast, execute, measure and automate to compete more profitably.
Patients can get basic parameters checked by themselves at home and that would transmit data to their health center wirelessly. Algorithms analyze the data and flag patterns that indicate a high risk of readmission, alerting a physician.
For e.g: Patients with congestive heart failure have a tendency to build up fluid, which causes them to gain weight. Rapid weight gain over a 1-2 day period is a sign that something is wrong and that the patient should consult a doctor.
Assessing risk of commercial loans, through various channels and business involved.
For e.g: a company dealing in mining might be affected by multiple aspects mostly due to government regulation, court rulings or any other type of activities which might be going on with the corporate. It also depends on weather conditions or any other environmental conditions which might affect business.
Dynamic analytics of competitor pricing data.
Accurate demand forecasting by customer segment for optimized capacity.
Improved yield management through automated inventory control and fare rules.