Marketers who use predictive analytics in their demand generation process are more likely to achieve their objectives, according to the results of a recent study conducted by B2B predictive marketing platform Radius, in conjunction with Demand Metric.
Of the 295 respondents surveyed, less than one third (30%) reported having a B2B demand generation process that meets objectives well. However, when predictive analytics are applied, process performance improved, meeting objectives more than half of the time (55%).
"Our research found a strong relationship between the use of predictive analytics and the efficacy of demand generation processes," said Jerry Rackley, Chief Analyst for Demand Metric, in a release. "When predictive is part of the demand generation picture, the entire process performs better. This finding provides a compelling reason for B2B marketers to look at enabling their demand generation with predictive technology."
Other key findings from the survey include:
- Effective demand generation and the successful application of predictive analytics are often hampered by poor data quality. More than 80% of study participants with an "ineffective" demand generation process reported that data quality has a moderate to significant impact on marketing campaigns or sales efforts.
- Marketers primarily targeting enterprise companies are more actively engaged in analyzing their data than those focused on midmarket and SMB leads. According to the study, 75% of companies that target enterprise leads analyze their data to find revenue opportunities with new or current customers, compared to only 38% of those targeting small companies.
- More study participants claimed to understand predictive analytics well (44%) than have actually implemented or used it (11%).