Marketing ops ·
Snowflake drives 150%+ more sales-qualified pipeline with Mutiny ABM personalization
The problem
Snowflake's ABM team needed to drive engagement at thousands of target accounts each quarter at scale, requiring laser-focused processes and tight alignment between marketing and hundreds of sales people.
Workflow diagram · grounded in source
1
Intent signal identification
trigger
“they surface information about prospect searches that align with a new Snowflake feature. And then run broader campaigns against those themes, as there's a clear seed of intent”
2
Multi-source data integration
integration
“The tools that send information to Snowflake are Mutiny, Bombora, RollWorks, and LinkedIn, allowing them to take action on data they can't get elsewhere”
3
Engagement scoring model
validation
“Casey's team created a scoring model to track engagement and measure their advertising success within Snowflake. The model includes email clicks, website visits, and other first-party data to give a wholistic view of the buying journey”
4
Bi-weekly AE alignment meetings
human_review
“at a bare minimum: ABMers are meeting every two weeks with each AE and their SDR”
5
Personalized landing page deployment
output
“Snowflake uses Mutiny to deploy 1:1 website personalization for their target accounts. These personalized landing pages can contain: The target company's name, Specific features highlighted based on sales conversations, Relevant CTA to b…”
Reported outcome
Snowflake achieved an 80% increase in average customer value and 150% more sales-qualified pipeline by combining personalized website experiences with coordinated SDR strategies.
Reported metrics
average customer value (ACV)80%
Sales qualified pipeline150%+
Reported stack
MutinyBomboraRollWorksLinkedIn
Frequently asked questions
What did this team achieve with this AI workflow?
Snowflake achieved an 80% increase in average customer value and 150% more sales-qualified pipeline by combining personalized website experiences with coordinated SDR strategies.
What tools did this team use?
Mutiny, Bombora, RollWorks, LinkedIn.
What results were reported?
average customer value (ACV): 80%; Sales qualified pipeline: 150%+ (source-reported, not independently verified).
How is this marketing ops AI workflow structured?
Intent signal identification → Multi-source data integration → Engagement scoring model → Bi-weekly AE alignment meetings → Personalized landing page deployment.