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Lead Scoring

To maximise the number of leads your business turns into customers, you need to be able to qualify them flawlessly. That’s something that artificial intelligence and machine learning can do with a very high degree of accuracy, finding patterns and indicators within your lead data that you couldn’t otherwise spot.

The Challenge

Knowing who to sell to, and more importantly focussing on the right prospect, can have a dramatic impact on sales performance. However, qualifying and scoring leads has traditionally been left to salespeople with rudimentary scoring systems, and even the judgment and experience of the best salesperson and the most insightful scoring system are imperfect, ultimately resulting in inaccurate lead ratings and fewer conversions.

The Process

Peak uses machine learning technologies to study your customer and lead data. In this way, we develop a deep understanding of what makes a good lead and a good customer for your business. We then provide a score which rates the probability that each lead will become a customer and are able to push this data back into our customers CRM systems to enable them to work seamlessly with the outputs of our algorithms. We can do this at any stage of the sales cycle, to optimise the entire process.

The Techie Bit

We start by ingesting existing data from your systems and matching it to Peak's proprietary datasets. Supervised classification algorithms, including tree-based models, generalised linear models and ensemble methods, are used to build a predictive lead scoring model that segments leads by different traits. Integrated into your systems, the model functions in real-time to predict which leads are most likely to result in successful outcomes for your business.

The Results

By spotting the patterns and indicators in your lead data that would otherwise have been left undiscovered, our machine significantly increases the accuracy of your lead scoring. Ultimately, this means better targeting of leads by your salespeople and more leads becoming customers.

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