Advertising genius, John Wanamaker famously said, "Half the money I spend on advertising is wasted; the trouble is I don't know which half." Decades later, this statement rings true across advertising and marketing and may even have inspired much of the innovation driving predictive analytics, data science, machine learning, and its application to marketing.
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A key factor to success in demand generation is ensuring lead qualification teams are not only fed enough leads, but are also able to quickly sift through leads and spend time on those most likely to turn into business. Unfortunately, like Wanamaker, lead qualification teams often find that half their leads are worthless but they don’t know which half; all resulting in wasted time and effort chasing down phone leads that are not interested in your offering or perhaps are not a good fit for your product.

This is one area where utilizing predictive analytics can provide great insight. While traditional lead scoring (scoring leads based on demographic and behavioral data) is certainly an aspect one should continue to track; it is only half the story. Predictive lead scoring, an item commonly found on a marketers’ wish list, takes scoring to the next level by not only looking at demographic and behavioral data but also identifying key signals and trends in historical pipeline and sales reports. By marrying revenue and behavior data, marketers can develop a predictive model to score leads on attributes and actions in addition to their likelihood to turn into closed business.

The predictive model can then be applied to new leads and passed along to the lead qualification team, enabling them to identify which leads are worth pursuing. This helps drive higher efficiencies in the lead qualification team in turn driving higher more qualified lead volume.

The benefits of predictive analytics in marketing and sales are hard to ignore. According to Aberdeen Research, sales and marketing organizations that use predictive analytics witnessed a 76% higher click-through rate and double the sales lift from marketing campaigns than firms that did not. Dell showcased predictive analytics beyond compare; its marketing team cut the number of leads sent to sales by half while doubling sales productivity and revenue!

Much like a storm, predictive analytics has the capability to alter everything in its path. Apart from predictive scoring, predictive analytics can play a significant role all along the buying funnel right from lead generation to tailored messaging to predicting upsell and cross-sell opportunities.

What about you? Let us know how your marketing team has utilized predictive analytics to increase leads and efficiency by leaving a note in the comments section.

 

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