Discover how ADA supported a leading global ePharma company in India to achieve a 3% increase in conversion rates for their over-the-counter (OTC) products through the strategic application of Category Affinity Models.

The Challenge

As one of India's top ePharma firms, the client provides an extensive range of pharmaceutical services, including diagnostic laboratories, online doctor consultations, and surgery booking services. Despite their market leadership, the client faced challenges in their B2C OTC segment, particularly in achieving satisfactory conversion rates from push notifications.

To address this, the client sought to enhance both click-through rates and conversion rates by implementing targeted marketing strategies while optimizing advertising costs and improving the effectiveness of their campaigns.

The Strategy

1.Identifying Customer Affinity through Machine Learning Models

ADA developed a predictive model to determine customer affinity toward various product categories. This model generated scores indicating the probability of each customer purchasing from a specific category within the upcoming month.

The Execution

1.Data Preparation

Customer transaction data was analyzed to extract purchasing behavior insights. In parallel, clickstream data was collected to examine customer behavior on the client's digital platforms. By integrating both datasets, ADA created a comprehensive view of customer behavior to reveal actionable patterns.

2.Building the Classification Model

Through data analysis, key variables influencing customer decisions were identified. Historical data was used to train a monthly predictive model, which was subsequently tested on new data to ensure accuracy. This process enabled the generation of reliable affinity scores and targeted marketing recommendations.

The Results

Achieved a 2% to 3% increase in conversion rates from push notifications and activation channels.

Reduced advertising expenditure by 20%.

Improved customer experience by lowering the incidence of irrelevant or spam-like messages.

This case highlights how leveraging advanced data science and category affinity models can drive measurable business outcomes, helping ePharma companies boost performance, enhance customer engagement, and optimize marketing investments.