Calculate fit. No formulas required.
Octave goes beyond technographics and firmographics for trustworthy qualification based on business pains, business model, and unique fit for your use cases.
Thousands of users at leading companies including
Rules-based scoring gives you an illusion of control.
Carefully calibrated rules crumble when they meet reality. Octave’s native understanding of your ICP helps you qualify accounts — not just for a product, but for specific use cases and sales plays.
Flexible and open qualification
Octave improves on rules-based scoring with a granular understanding of your ICP.
Transparent
Review the reasoning behind each qualification decision.
Portable
Build your own scoring agents using Octave's qualification logic, or start with out-of-the-box Managed Agents.
Expandable
Have 100 use cases across 5 products? Octave can qualify one lead across all of them.
Qualify your TAM for multiple use cases
Qualify your TAM in natural language
Describe the business characteristics that make an account a fit. Octave examines unstructured data like call transcripts and web research for evidence of those attributes.
Qualify your TAM for multiple use cases
Octave shows you not only which accounts to pursue first, but which of your motions, products, and use cases are the best fit for each one.
Start with Octave's ready-made qualification agent
Use a Managed Agent to qualify leads and accounts without building your own. Follows best practices for lead and account qualification, is production-ready with an API endpoint and native integrations, and sends to Clay, Common Room, your data warehouse, and more.
Scores you can trust
You have to write perfect rules
Deterministic scoring requires you to assign the perfect worth to actions and attributes. These values should differ based on lead & account context, but can't.
Rules are optional
Company news, CRM history, technographics, firmographics, call transcripts, LinkedIn profiles, product usage data — Octave synthesizes it all and compares it to your ICP definition.
Scoring logic gets stale
Once you write rules and assign values, who stays on top of maintenance over time? Markets move, but rules don't follow.
No rule maintenance
Octave's self-learning capabilities update your context graph as strategy evolves so qualification reflects your latest definitions.
A score doesn't tell reps what to say
Ranking leads doesn't explain which products to lead with and what messages to deliver.
Get a plan and message
Qualify each account against hundreds of products, use cases, and capabilities, with tailored messaging based on fit.
Techno & firmographics don't reveal pains
Most scoring data points don't reveal the problem a buyer needs to solve.
Qualify on business pain
Find specific needs in unstructured sources such as call transcripts, including details standard company fields miss. Qualify with unique business models and uncommon pains.
Find fit in any market
Call transcripts
Find specific needs in unstructured sources that standard company fields miss.
Product telemetry
Usage signals that show how an account actually behaves.
Same-day account research
News, jobs, and launches, pulled fresh at scoring time.
LinkedIn profiles
Person-level evidence for buying committee fit.
CRM history
Past activity and outcomes already sitting in your system of record.
Firmographics & technographics
The standard fields, used as one input rather than the whole score.
Our previous HubSpot rules-based scoring system wasn't always reliable. With Octave, our lead scoring is spot on. I can trust that a 9 out of 10 is a very good lead we should go after, and that we can skip a 3. Before Octave, our CRM was garbage in, garbage out… Now, we have Octave scoring as the filter for new leads, or can score thousands of leads and delete anything under a certain score. So I know I can trust the data I use.
We needed to figure out how many companies in our TAM met our target criteria. But our ICP definitions were quite complex. We couldn't just score with +/- 5 points based on industry and size. We needed an agent to understand a company's business, then infer fit for all our products. Octave let us score in that way.
With Octave, we can qualify new leads based on call transcripts, processing 200/day.
Octave always has fresh context when it scores – it plays nicely with our data infrastructure to get rich first-party and third-party data. We built a full data spine in BigQuery that feeds Octave's qualifying agents with 96 columns of enrichment: product usage signals, CRM history, Common Room activity, technographics, product signals, the works. We use Octave Managed Agents to build person-level qualifying agents across five personas, in addition to account-level qualifying agents.
Octave gave us a way to model the nuances of our ICP and apply that contextual intelligence across our entire prospect ecosystem at scale.
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