How Neo4j Grew Enterprise Leads by 157% with AI-Powered Campaigns and Offline Signals
Built by data scientists for data scientists, Neo4j Graph Data Science unearths and analyzes relationships in connected data to increase ML model accuracy and drive contextual AI - making better predictions with the data you already have.
The challenge
Neo4j, an industry-leading graph database technology provider, aimed to enhance the efficiency and growth of their advertising activities while maximizing their marketing budget. They sought to increase the volume of net-new enterprise leads.
The approach
Neo4j implemented a new AI based campaign type in Google Ads and supplied it with offline signals from their CRM. The new campaign type served ads across the entire Google inventory (Search, Display, Discovery, Gmail, YouTube) and optimized ad spend based on quality of the contacts entering the CRM.
Partnering with VertoDigital
With VertoDigital’s help, Neo4j implemented an offline conversion based on their enterprise ICP. The ICP Lead signals powered both smart bidding in Google Ads and cross-channel reporting in Looker Studio.
The results
Since implementing Performance Max campaigns, Neo4j reported improvements in both lead volume and quality through Google Ads. They achieved a 157% increase in new enterprise leads while reducing the cost per acquisition by 54%.
“VertoDigital helped us tap into the power of machine learning to find new customer prospects and grow our high-performing audience segments to drive ROI.”
—Lauren McCormack, Senior Manager, Digital and Marketing Automation
157%
Increase in net
new enterprise leads
54%
Reduction in cost per acquisition
of a net new enterprise lead
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