Project Overview

Our client contacted us with the need to identify and prioritize potential clients to optimize their sales process.
They were looking for a solution that would allow them to focus on leads with the highest probability of conversion, thus reducing associated costs.

Project Objective

SAMA's objective was to develop a lead scoring model based on Machine Learning that would classify and prioritize leads according to their probability of conversion, providing our client with a competitive advantage in their sales process.

Methodology Used

We combined advanced analysis techniques and ML to transform raw data into actions on the most promising leads.

Process and Analysis

We analyzed historical sales and behavior data to identify patterns and characteristics in clients that were key to identifying buyers.

We used algorithms to develop a predictive model capable of assigning a score to each lead based on their probability of conversion.

We conducted exhaustive tests and continuous adjustments to ensure the model provided accurate and useful predictions.

Results Achieved

Our lead scoring model allowed the company to identify and prioritize clients with a higher probability of conversion, resulting in a significant increase in the sales success rate.

The implementation of the ML model not only improved the efficiency of the sales team but also provided a valuable tool for strategic decision-making in future marketing campaigns.

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