Our client, a leading online jewellery chain in India, aimed to identify and target website visitors who demonstrated a higher propensity to make purchases, with the goal of enhancing conversion rates.
Brandscapes Brew Insights:
- Data Mart Creation: We constructed a Data Mart offering a unified view of each customer. This included basic variables such as age, location, pages visited, events clicked, past transaction details, queries, and complaints. It also incorporated derived variables like the customer value index, engagement index, time spent on the website, and the number of media channels used.
- Ensemble Model Development: We condensed over 600 event and 40 transactional variables down to an efficient number of variable components. With these, we developed an ensemble prediction model for each segment using logistic regression, random forest, and support vector machine models. This model was designed to predict visitors with high sales potential.
Armed with insights from our model, the client segmented their website visitors and customized marketing activities for each group. These activities included offering greater incentives to those with lower purchase propensity scores, introducing subscriber retention offers, and assigning concierges to re-engage subscribers at risk of churn.
Our propensity model empowered the client to more effectively target their visitors. A significant outcome was the identification of 30% of visitors who made up 70% of the high purchase propensity segment. Our strategic approach and comprehensive analysis enabled our client to make informed decisions that significantly improved their e-commerce conversions. This case study is a testament to our commitment to helping clients navigate complex marketing challenges and achieve their business objectives.