# Lead scoring model lifts sales conversion by 20%

> Private equity-backed price comparison and switching service · Retail & Consumer

A price comparison and switching service wanted to point its finite outbound sales team at the highest-value leads. QuantSpark's propensity model delivered a 20% increase in conversion rate.

## At a glance

- **20%** increase in conversion rate

## What was the problem?

The service wanted to increase monthly sales by improving outbound conversion. It needed to rank and prioritise its lead base so that limited sales-team capacity was directed at higher-value prospects across categories such as energy, insurance and telecoms.

## What did QuantSpark do?

QuantSpark began by mapping the mechanics of the sales funnel to ensure the modelling was optimised for practical impact, then constructed a modelling dataset and analysed the individual drivers of lead value. Using advanced SQL and machine-learning algorithms, the team iterated through scenarios and configurations to converge on the strongest predictor of valuable leads, implemented the model within the client's systems and processes, and designed a testing framework to monitor performance over time.

## What changed?

After a month of live testing, the scoring algorithm was rolled out across the entire outbound sales funnel. The testing and reporting framework measured a 20% increase in conversion rate. Additional insight from the model was used to tailor call strategies for leads with particular profiles, driving further incremental gains.

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Canonical page: https://quantspark.ai/case-studies/lead-scoring-propensity-model-price-comparison
More about QuantSpark: https://quantspark.ai/llms.txt