Scaling Data Science
LeadCrunch’s Data Science teams create Machine Learning models that help B2B Sales and Marketing teams find better prospects faster. Google, Oracle, Salesforce, and others utilize LeadCrunch to spend less time prospecting and more time with customers, accelerating sales cycles and driving revenue growth.
LeadCrunch depends on regular updates to their ML models to deliver better recommendations to customers. But existing processes made updating models slow and ineffective.
Bi-annual implementation of ML models
LeadCrunch’s Data Science team regularly updates and refines ML models, but with 10+ sub-models and an ever-evolving stack, implementation was slow. Deployment of new models only occurred a few times a year.
Tough to get an overview of experiments
Each model was managed differently, which was inefficient and made Prior to Verta, Data Scientists had difficulty gaining a holistic view of all of the experiments that were being run. This lack of insight further slowed the development of new models.
Maintaining models was a time-consuming process
Deploying and maintaining models often required large amounts of time and effort from LeadCrunch’s engineering team. But as a small company, these hours often weren’t available.
Having Verta is like having two additional data engineers on our team that can help support the data science team.”
ALEX QUINTERO, DIRECTOR OF DATA SCIENCE, LEADCRUNCH
MODEL PRODUCTION SPEED
IMPROVEMENT IN TTV
Verta provides LeadCrunch with a unified MLOps platform that addresses their most pressing deployment and operations issues.
Faster implementation of new ML models
Verta Inference allows LeadCrunch to easily deploy new models into production (batch, live, etc). “Previously, one of our main feature creation pipelines would take us 20 to 25 weeks,” says Alex Quintero, a Director of Data Science at LeadCrunch. “Once we brought Verta into the fold, that time cut in half. And it made it a lot easier to deploy and maintain our code.”
Accurate oversight of ML experiments
With model monitoring, experiment management, and a model registry, Verta’s MLOps platform supports the full model lifecycle. Verta’s intuitive experiment dashboard gave LeadCrunch’s Data Science teams confidence that they could get accurate, granular insights to the results of specific experiments.
Less time consumed by deployment and infrastructure
Verta freed LeadCrunch from the burden of worrying about deployment and infrastructure. “When you have a really small team like the one that we have, we can’t dedicate a lot of time and resources to the deployment of models,” says Brendan Homnick, LeadCrunch Sr. Data Scientist. “Verta takes all of that pain away.”
Before Verta, classifying our entire data universe would take days. Verta helped us redo our entire data universe in 20 minutes.”
JENNIFER FLYNN, PRINCIPAL DATA SCIENTIST, LEADCRUNCH
AI-enabled B2B Demand Generation
LeadCrunch helps B2B enterprises find the right prospects, faster. Sales and Marketing teams that use LeadCrunch’s Sales Development Platform spend less time looking for prospects and more time engaging with customers, accelerating sales cycles and driving revenue growth.