Account-based marketing tools—marketers love them, sales reps hate them.
Why? Because ABM tools show (often vague) buying signals from accounts, not the people behind them.
This works for marketing teams. They can use account-level intent to power scoring models and blanket target accounts with ads.
But sales teams can’t action on it. Account scores lack context. Account research eats up valuable time. And reps are left to fish for the right prospects within each account.
Still, the promise of ABX is possible for sales.
Here’s how organizations like Notion, Apollo GraphQL, and Zapier turn account-level intent into actionable insights with Common Room.
Solve account scoring mysteries
Problem
Account-level intent is often used as an input for scoring models, telling reps which accounts to focus on first.
But these scoring models are black boxes. Reps have zero context for why an account should be prioritized or how past activity should influence outreach.
Solution
Our customers use signal-based lead and account scoring to make account rankings useful in the field.
Accounts are scored based on every available buying signal, not just obvious behaviors like form fills and email opens. More importantly, reps can hover over any score to see exactly why an account was ranked that way and drill down into the account to get a holistic view of the actions powering the score.
Common Room’s signal-based scoring creates contextual lead and account scores based on machine learning-enriched fit and behavioral data. Scores—and the context behind them—are refreshed daily using your custom rules, parameters, and weighting.
Beyond fit criteria that shows an account matches an ideal customer profile, reps get full visibility into web visits, product usage, social engagements, and any other activity associated with an account.
Using calculated fields, our customers can also power account scores based on the volume of a particular signal, like companies posting a high number of relevant job listings.
This makes it easy for our customers to prioritize which accounts to go after and tailor outreach based on granular actions and attributes.
Strategy
Notion uses signal-based lead and account scoring to give reps a 360-degree view of accounts within their book of business.
Instead of tabbing back and forth between tools to piece together a view of accounts, team members get all the info they need—including precise product usage data—in one place.
Reps quickly prioritize accounts based on ICP fit, dig into account-level behaviors across channels, and drill down to find economic buyers.
“Common Room shows all interactions that prospects had with Notion content across different channels,” said Felipe Fernandez, Enterprise BDR. “I managed to book two meetings in an hour with this strategy by simply calling the prospects and personalizing the pitch a little bit.”
Results
Improving account prioritization and visibility helped Notion generate 30% more meetings per rep per month.
“What once took hours and multiple tools to gather—product usage, job changes, social interactions—is now immediately available,” said Pratyusha Ram, GTM Systems. “Most importantly, it's helping us generate more pipeline!"
Speed up account research
Problem
Account research is crucial to crafting compelling messaging. It’s also a huge time suck.
Reps spend hours researching accounts to build a POV, identify purchase decision-makers, and personalize messaging.
Solution
Our customers use Common Room to auto-capture and centralize account context from across all first-, second-, and third-party data sources.
Job changes, job listings, news events—everything reps need to build a business case is served up on a silver platter.
Common Room’s AI-powered signal capture automatically fetches contact, account, and activity data from your first-, second-, and third-party data sources. Our machine learning algorithms process this data and turn it into structured outputs for team members to access, analyze, and action on.
Reps also use our GenAI research agent—RoomieAI™—to conduct account research at speed.
They simply ask RoomieAI any org-level question they have and get the results immediately, no screen switching necessary. RoomieAI will search the internet—including earnings calls and 10-K releases—to break down product lines, competitive analysis, user sentiment, and more.
Common Room’s research agent scours the open web to answer any account-level research questions that need answering. Out-of-the-box and custom prompts let you instantly spotlight key information to power outbound, from earnings calls and annual financial statements to user sentiment and product feedback.
This makes it easy for our customers to quickly get up to speed on target accounts and inform their outreach strategy.
Strategy
Apollo GraphQL uses Common Room’s always-on signal capture to gather account context and spotlight lookalike accounts.
Reps get a personalized view of every account—from firmographic details to cross-channel behaviors—right where they work.
And real-time alerts make sure reps are notified about any account activity they care about instantly.
“Every customer’s journey is different,” said Aisha Nins, GTM Program Manager. “No sale is exactly the same, but with all these signals embedded in Common Room, we can identify trends across the board to understand what an ideal customer looks like and where there are opportunities to engage.”
Results
Streamlining account research helped Apollo GraphQL drive 26% of qualified leads.
“Common Room gave us visibility into multiple signals to identify new, relevant stakeholders—as well as their activity across several platforms—to target new leads and gain insights into accounts sales reps couldn’t see before,” Aisha said. “We made Common Room the hub for all the signals that would point to an ideal customer profile.”
Auto-surface contact-based intent
Problem
Account-level intent tells you which organizations to go after, not which people.
There’s no way for reps to know which individuals are behind an account-level intent signal or whether they’re the right fit.
Solution
Our customers use Common Room’s identity resolution and waterfall enrichment engine—Person360™—to automatically reveal the people behind different intent signals.
In addition to account-level context, Person360 provides names, job titles, work histories, contact information, cross-channel activities, and more in one unified profile. Economic buyers, ideal personas, and other key contacts are automatically spotlighted.
Common Room’s out-of-the-box identity and enrichment engine uses machine learning models to automatically deanonymize contact and account activity, merge cross-channel signals into unified profiles, and fill in the blanks with rich contextual data.
In cases where account-level activity is all reps have to go on, our customers use Prospector to surface the right stakeholders.
Reps simply input their criteria for prospects at an account—like job title and location—and Prospector returns a list of all individuals who match. Better yet, this process can be automated from end to end using intelligent workflows.
Common Room’s prospecting agent retrieves prospects and companies from a proprietary, constantly refreshed database of more than 200 million B2B contacts and accounts based on your custom filtering criteria. These people and organizations are then enriched via machine learning-powered models.
This makes it easy for reps to quickly find and follow up with the right people within each account.
Strategy
Zapier uses Person360 and Prospector to zero in on above-the-line buyers within accounts.
This allows reps to focus on prospects with economic buying power, as well as find solid candidates for multithreading.
Reps simply filter their views of accounts for director-level stakeholders and above.
“Common Room gives me a view of all the important contacts at one company,” said Strategic Account Manager Cathy Du. “All the info I need is all in one place and easy to sort through. It helps me find important contacts to outreach, understand who they are, and prioritize who’s most relevant.”
Results
Simplifying person-level prospecting helped Zapier increase meetings booked by 31% in 3 months.
"Reaching the right stakeholders is critical to building a repeatable sales motion and increasing ACVs,” said Vice President of Sales and Customer Success Nalin Vahil. “Our teams had to jump back and forth between multiple tools to do that, and we were still missing key insights. With Common Room, we can identify the right stakeholders faster."
Make account scores practical, accelerate account research, and reveal the people behind the buying signals.
That’s how Common Room customers turn account-level intent into actionable insights.
Trade old ABM for real ROI with Common Room
Get started for free or get in touch to see how Common Room’s AI-powered customer intelligence platform helps you capture, enrich, and take action on every buying signal.
