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Lead Scoring

Working the Right Leads with AI


Poor lead prioritization can have huge implications for sales and marketing with missed sales goals and demoralized sales teams and ruined collaboration. Poor lead quality drives burnout and high turnover in sales positions leading to extra costs for training and more sales staff on hand to generate the required pipeline. Traditional lead scoring methodologies rely on interest from the prospect to determine a score, but the interest level of the individual does not necessarily provide an indication of their ability to purchase.


AI based machine learning models can score marketing leads using a wider variety of factors and learn from those leads that ultimately became opportunities and those that created revenue. By looking at more information about customer behavior, company size, industry, etc., each lead can be evaluated and scored with sales representatives receiving a ranked list of leads for follow-up. AI can also provide reason codes for each lead so that sales knows the key factors that make the lead valuable. This optimized process insures that sales is working the highest quality leads available which drives faster ramp up from working on consistent leads, quota achievement, less turnover and overall lower sales costs.


The mission at is to democratize AI for all so that more people across industries can use the power of AI to solve business and social challenges. Across industries, marketing use cases drive significant use of products to solve key challenges including lead scoring, customer segmentation, offer optimization and content personalization. Marketing technology companies including G5 and trust technology to help them deliver innovative marketing solutions for their clients. H2O Driverless AI is an award-winning platform for automatic machine learning that empowers data science and technical marketers to scale machine learning efforts by dramatically increasing the speed to develop highly accurate predictive models.

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