How to Calculate the ROI of Predictive Lead Scoring

With content marketing, freemium products, and list-buys, marketers are generating more leads than ever before — but only a fraction of them are good prospects. Predictive scoring solutions like Infer help filter out the noise by programmatically researching every lead and identifying high-potential MQLs. That not only saves sales reps time, but just as important, it gives you an objective way to measure lead quality.

We’re continuously documenting best practices in order to provide a framework for measuring the ROI of a predictive scoring initiative. One approach that lends a lot of clarity to this process is to look at three simple metrics — your number of sales reps, your average cost per rep, and your percentage of bad leads. With this information, you can quantify the cost of wasting effort on bad leads.

ROI_01However, cost savings is only one way to measure the impact of predictive scoring. Most companies want to quantify the top-line impact as well. By looking at your average leads per month, conversation rate and revenue per opportunity, you can understand the potential revenue increase you’re likely to see from predictive scoring.

ROI_02To help you justify an investment in predictive lead scoring, we’re excited to introduce our new Predictive ROI Calculator. This new tool will allow you to plug in these few figures and instantly see the impact predictive scoring could have on your business.

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Sean Zinsmeister

Sean Zinsmeister

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Senior Director of Product Marketing at Infer Sean crafts the positioning, messaging and overall go-to-market strategy for Infer’s trove of next-generation predictive sales & marketing products. Once a satisfied Infer customer himself, Sean joined Infer from Nitro, where he developed and led an award-winning global marketing team.