Shafi Kamalbasha

Data Analyst @ Avira

Shafi is a data science enthusiast working passionately towards gaining business relevant insights from the data while constantly trying to find the right questions to ask. Currently he is working as Specialist Data Analyst in the Data Analytics and Insights team at Avira. At his job, he has led several analytics projects for Customer Acquisition, Retention, Lifetime Value modelling, marketing cost optimization, etc. His interest in data science piqued, back in 2010, when he was part of a 4-person team tasked with the Indian Government project of translating scientific documents only available in English to Hindi with the help of machine learning. Shafi holds degrees in MSc. Business Consulting with specialization in Business Intelligence from HFU, Germany and Bachelors of Engineering in Information Technology from Amrita University, India.

Tackling the Price Optimization Problem in Avira

Pricing is a crucial element of our business. It affects the Customer Lifetime Value and the Customer Acquisition Costs, among many other variables. Higher prices can negatively influence retention, and at the same time, lower prices can also affect the bottom line of the business. Finding the right pricing strategy is a hard problem. In this talk, we are going to present the algorithmic framework Avira uses to find the optimal pricing strategy.

We define the optimization problem on three variables: list price, discount, and presentation. Customer experiments are planned and executed using Bayesian Optimization approach. The outcomes of the experiments are enhanced using simulations to assess its global effect on the business. For example, how different list prices affect the customer lifetime value.

We illustrate this framework, with the real business case of finding the optimal discount for our most prominent product - Avira Prime.