We used Machine Learning and Predictive Analytics to help a worldwide automotive conglomerate score and prioritise leads​

The Results

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The Execution

The Malaysian sales team of a worldwide automotive conglomerate lacked propensity scoring and conversion predictive model which ineffective marketing and inefficient sales follow-up due to lack of visibility on which leads were most likely to convert.​

To address this, ADA implemented Consumer Data Platform (CDP) to unify the data from various systems and implemented a high accuracy propensity scoring model with machine learning and predictive capabilities.​​

Based on the propensity scores and conversion probability, the client segmented the leads for different personalised marketing campaigns and sales prioritization, leading to better marketing and sales synergy and focusing efforts on the high-potential leads. This resulted to improved customer experience and increased sales conversions.​

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