Machine learning is the latest in a series of data-driven technology developments that are disrupting and transforming the Customer Experience, Marketing and Sales Analytics category of the Big Data and analytics (BDA) market. Stratecast|This report has identified more than vendors who supply solutions in this category.1 Competition will require each of them to develop or partner to deliver machine learning (ML) capabilities for lead scoring.
The basic idea is that ML algorithms, in the right hands and with the proper data, can enable more- informed gathering and evaluation (scoring) of marketing leads. The higher-level value proposition is that, if businesses apply machine learning in this way, they will be able to adjust their sales and marketing efforts to address customers and prospects with the highest propensity to purchase.
Machine learning algorithms have been used by academic and scientific researchers for decades to discover patterns in new data based on previously processed datasets. Now, vendors are commercializing these algorithms in cloud-based applications that combine ML with additional functions, new data sources, and user-friendly interfaces. Marketing departments can use these new solutions, which are essentially ML applications that have been trained with data on existing customers, to score sales leads based on their propensity to buy. The variety of ways in which ML- based lead scoring solutions are coming to market means that there truly is an option to satisfy every level of budget, analytic skill and marketing automation maturity.
- BDA 3-03
- Executive Summary
- Machine Learning for Lead Scoring
- Four Startups That Provide ML-Based Lead Scoring
- New Lead Sources, Old Software, and Vendors of Record
- How Ready Are Buyers and Sellers for ML-based Lead Scoring?