Machine learning and retail - a perfect match.

The background.

A major player in the Spanish retail sector, with an extensive network of stores and a substantial customer base, identified the potential to enhance insurance sales within its technology product offerings. Recognizing the value of a focused and specialized approach, they partnered with Transcom to develop a dedicated insurance phone sales service. 

This strategic collaboration aimed to not only boost the volume of insurance policies sold but also achieve greater operational efficiency and cost savings. By leveraging Transcom's expertise in customer engagement and telemarketing, the retail giant sought to unlock new revenue streams and optimize its insurance sales process.

The solution.

A robust historical dataset was compiled over a three-month period, with all pertinent lead variables meticulously defined and documented. Subsequently, rigorous statistical analysis was undertaken to discern the interrelationships among variables. Following extensive testing of various ML algorithms, the optimal predictive model was selected.

Outbound strategies were then formulated, assigning each lead a sales priority number generated by the automated ML algorithm. The dialer system has been configured with the necessary OB strategies to optimize contact rates and sales conversions. The sales conversion results are continuously monitored, with the ML algorithm undergoing monthly retraining to ensure peak performance.

The results.

Our efforts yielded some impressive outcomes: we saw a noticeable boost in how quickly products were flying off the shelves, with a 22% increase in sales. Over just three months, we managed to generate an additional 30,000 euros in revenue. And to top it off, we were able to streamline our processes and reduce the overall cost of sales by 15%. All in all, it's been a successful period of growth and optimization.

The success of this ML initiative has already yielded promising new business opportunities. The development of innovative services based on ML design principles is currently under consideration.