The more data-driven marketing becomes, the easier it is for CMOs to attribute closed deals directly to their marketing programs.
But with so much information available they encounter a new challenge: knowing which tactics and strategies to prioritize when each bad decision can cost thousands in missed opportunities.
Predictive analytics is surging in popularity among marketing leaders. It combines several components of artificial intelligence (AI) to predict which prospects are most likely to become customers.
This technology eliminates a great deal of manual and redundant work from marketing and sales analytics, letting reps spend more time on high-value outreach and lowering chances that a calculation error will cost the company important deals.
You can use predictive analytics to identify your most promising prospects, build hyper-targeted segments, and personalize outreach at scale—often resulting in significantly increased conversion rates on inbound and outbound campaigns.
But not all predictive technology is equal. As more companies adopt it for marketing, the competitive edge shifts from whether you’re using it to how.
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