Optimize sales processes and increase conversion rates by leveraging advanced analytics

Background

Our client is Belgium’s number one vehicle distributor, with a market share of around 21% and 1.2 million vehicles on the road. They import and distribute vehicles, spare parts, and accessories, and have a strong network of independent dealers across the country, plus 20 corporate-owned locations.

Technology partners

Python

Challenge

The interaction between a car dealer and a potential customer is decisive for successful sales. The effort invested in the potential customer is a crucial factor in converting the sales opportunity. The aim of this project was to identify "hot leads," defined as a customer with a high likelihood of purchasing a vehicle within three weeks of visiting a showroom.

Approach

- Create a propensity model to score and identify high potential customers. - Identify top factors that determine predictive lead scores to uncover what is driving the best leads. - Deliver valuable information related to the current sales opportunity, such as source (web, showroom, etc.), brand, model, and whether a test drive was requested. Combine this information with CRM data like gender, age, address, and enriched demographic data. Make scores accessible to Sales representatives via other applications already existing within the company (i.e. CRM & apps)

Key results

01
Deliver valuable, high intent leads to the sales representatives
02
Significant and demonstrable increase in conversion rate of leads compared to the current approach
03
Increase in sales volume

Benefits

The sales team can now benefit from an optimized sales process, leveraging their knowledge of the model drivers to increase customer conversion rates and ultimately increase sales. The business can also optimize sales representatives' time by managing the amount of effort invested on a potential sale.

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