The announcement of Salesforce Einstein at Dreamforce has focused marketers’ attention on artificial intelligence (AI) and its ability to interpret complex data and act on it. For business-to-business (B2B) marketers, the success or failure of AI rests on its ability to provide measurable increases in business metrics, like lead volume, lead conversion, sales acceleration and pipeline.
Artificial Intelligence for B2B is Built on Predictive Analytics
The core capabilities of AI already exist for B2B marketers, with predictive analytics and data management by Leadspace. Predictive analytics is the backbone of AI’s ability to find new leads, identify decision makers inside target accounts to enable account-based marketing (ABM) and provide scoring and segmentation for more effective marketing automation campaigns.
B2B Marketers Need a Complete View Across All Their Marketing Channels
While Salesforce Einstein will be a powerful tool for B2C marketers and sales acceleration, according to Doug Bewsher, CEO of Leadspace and former CMO of Salesforce, “B2B marketers need a complete solution that works across multiple channels, in their existing marketing stack.”
Leadspace Customers Get ROI from AI for B2B Marketing Today
Leadspace’s more than 120 customers, including seven of the world’s 10 largest enterprise software companies, get that today.
"When marketers talk about artificial intelligence for B2B, they usually mean the ability to automate the process of finding, scoring and segmenting the best leads to reach the right decision makers,” said Jason Seeba, Head of Marketing for BloomReach.
“That's exactly what we've been doing at BloomReach for three years with Leadspace."
On-Demand Data is Key to Successful AI for B2B Marketing
Leadspace also provides a key element for AI success lacking in other solutions: on-demand data, updated in real time. The Leadspace Virtual Data Management Platform aggregates data from across the open and social web, as well as proprietary databases and a customer’s own CRM.
“Bad data is the Achilles heel of AI,” said Bewsher. “AI is only as good as the data available to it. Marketers who want to get the full benefit of AI need to address their data problems first, or they’ll see the same diminishing returns as with traditional marketing automation.”
