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Common Room x The Signal
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Hey y’all! 👋
My goal with The Signal is to explore the future go-to-market playbook and the infrastructure that runs it.
I’ve been following Common Room for a few years now. And it’s been fun to watch them evolve from a community intelligence product to popularizing signal-based selling, and now building out a platform to be the system of intelligence for GTM teams. I’ve gotten to know the team and continue to be impressed with the caliber of talent they’ve been able to attract, and the direction they’re heading. I think Kevin is one of the best marketers in the GTM tech space. And picking up Florin to run their SDR Team was a ninja-level move. I know several other people there who are also world-class.
Common Room is building a comprehensive platform—from signals to scoring to AI SDR workflows—for teams to run a modern go-to-market motion, without stitching together a dozen point solutions.
A lot of the new tooling (and even foundation models) require a technical user, like a GTM Engineer. But, sales reps are not GTM Engineers and don't want to fiddle with tooling. And, many companies would prefer to not have to hire GTM engineers and rebuild their entire stack (rightfully so). Instead, they want an intuitive product that helps achieve outcomes. That’s Common Room’s vision: create an incredibly flexible and powerful platform, that gets outcomes, without requiring a GTM Engineer to use it.
That’s why I’m excited to share this Deep Dive with you today, on Common Room.
Here's what we'll cover in today's post:
The Unified Foundational Data Layer
Actions > Insights
Signal Stacking
AI-Driven Signal Capture + Orchestration + Activation
Enterprise-Readiness
Looking Forward: Supporting the Nuanced GTM Motions of Tomorrow
Let's dive in.
The Unified Foundational Data Layer
The go-to-market tech stack has evolved significantly over the past few years. We've gone from basic email automation to sophisticated signal-based selling, and now LLMs/GenAI and agents. But with this evolution comes a problem: data fragmentation. Most companies are swimming in signals spread across multiple tools, creating (even more) silos that make it hard to build a coherent picture of buyer behavior. And, I believe, this problem will only get worse over time, not better.
Common Room's thesis starts with a foundation that's simple and powerful: you need to unify both the signals and who's behind them—the companies and people generating those signals—into, what they call, a “customer journey graph.” That foundational layer becomes critical for running a modern go-to-market machine, which includes AI, automation, signal-based plays, and micro-campaigns. For these motions to work, you need the 'who' and the context (eg: 1st, 2nd, and 3rd party signals and data) to take action.
Better data in = better outputs. This has always been the case in GTM. But, this is especially true in the era of AI, agents, and automation.
And they aren’t building yet another point solution. Common Room is building towards a full, integrated platform. Similar to how Rippling consolidated HR and IT systems (see: Parker’s concept of a “compound startup”), Common Room is building a workspace that pulls together signals (plus marries those signals to a unified, enriched individual record) that would otherwise live in separate tools: website activity, product usage, job change alerts, traditional intent data, content engagement, plus signals you can pre-configure for AI to go "hunt" for across internal and public web like 10-Ks, financial statements, competitors, user frustration, etc.
(This value prop is especially compelling in today's cost-conscious environment because it allows for consolidation of the tech stack.)
The result? A single pane of glass that eliminates data silos and provides a comprehensive view of each account and contact, prioritized for you, with the context of why, and a suggested next best action.
Actions > Insights
Having “intent” data is one thing. Making data actionable is another thing entirely.
I’ve always had a very deep belief that salespeople don't care about “insights.” They care about taking action. It’s why I’ve always had doubts about traditional marketing intent solutions (my Turing test: SDRs and AEs never rave about these tools).
Intent data providers focus on delivering insights to marketers. But, Common Room is designed with the frontline seller in mind. For every high-intent signal, reps can see the full context. Things like: why an account scored highly, what specific actions triggered the alert, and who to target in the account (legacy ABM players give you company-level, but not person-level information, which makes it ~useless for sellers).
Common Room gives you three levels of automation (“crawl, walk, run,” if you will):
Manual - Prioritized account/contact lists (with full context)—based on likelihood to convert to pipeline—for reps to work through.
Co-pilot (aka semi-automated) - One-click actions to add contacts (one-off, or even in bulk) to sequences while maintaining human touch.
Full autopilot (aka AI SDR) - Completely automated workflows for repetitive, proven plays.
I haven’t seen a full AI SDR that entirely replaces SDR teams (yet). But, I do think there are certain use cases, or segments of your market, where a fully automated workflow (aka an AI SDR) makes sense (I expand on this topic in this piece: Should You Buy an AI SDR?). The TLDR: a low-ACV, high-TAM segment is a great place to consider deploying an AI SDR.
I’m seeing companies use autopilot (eg: highly automated, personalized/relevant outreach) for SMB accounts and then manual/high-touch, human-in-the-loop (AI-augmented) for Enterprise accounts. Common Room has the flexibility to support any motion your team requires.
Signal Stacking
Kevin White, Common Room’s Head of GTM Strategy, talks a lot about the concept of “signal stacking.” I’ve come across this problem first-hand at multiple companies. This is where a lot of magic can happen, but it’s incredibly hard to hack together with the incumbent tools on the market. By the way, the best reps manually do this today, but it’s hard to train across a team, or ramp new reps into this behavior.
For example, you want to see when a target account has several free users who recently signed up, plus someone visited the technical docs on your website, and an exec just mentioned a relevant question on a social channel. Any one of these signals is sort of interesting in and of itself. But, when you stack them together, it’s very obvious that something interesting is happening at that company, and you should reach out (contextually) to these prospects asap. This is the sort of workflow that Common Room is enabling.
By the way, a resource I share with people all the time is Common Room’s “100+ Signals for Pipeline Generation” — it’s completely ungated (this is the way) so have at it!
And they make building these workflows very easy, without requiring deep technical expertise (or buying a course to learn how to use their product). Unlike other platforms, which can be powerful but challenging for non-technical users, Common Room has an intuitive visual interface that sales and marketing teams can learn in just a few minutes.
AI-Driven Signal Capture + Orchestration + Activation
At the highest level, Common Room helps with pipe generation in three ways:
Capture (who to target) → signal and intent capture + ID resolution.
Orchestrate (when to engage) → this would include scoring, setting up creative plays and segments so your reps can focus on the highest priority opps.
Activate (how to convert) → the sales workbench, integrations with existing tools (SEPs), and RoomieAI activate (personalized messaging).
Common Room is leaning into AI more lately, building "signal intelligence.” Their research agent—named, RoomieAI—can autonomously find relevant information about accounts and turn them into customized signals that are unique to every company (I think this is where the alpha will be in for GTM teams in the coming years). One example would be: finding primary competitors of accounts and suggesting an approach for how to position against those competitors. Again, these are completely bespoke signals (thanks to this magical new tool called, AI).
This isn't a traditional B2B database or generic LLM. It's purpose-built for go-to-market teams who need to identify specific buying signals across their target accounts.
Beyond research, Common Room's “activation agent” helps turn this rich context/signal into relevant messages. And, what makes it really useful is that these agents have access to both first-party data (from your CRM, data warehouse, etc.) and third-party signals, giving them more context than querying an LLM directly.
And if you want to get really wild, you can "daisy-chain" these AI agents. For instance (building on the ‘competitor’ signal example above), you could pull negative reviews from the competitors found, reference that in an outbound email generated by an agent, and automatically add to your sequencing tool of choice. The possibilities are endless.
Enterprise-Readiness
Common Room works with teams at large companies like Atlassian, Twilio, and Grammarly. These are organizations that have complex, fragmented data structures and lots of scattered data. And, equally as important, they require enterprise-grade features like governance and compliance (they have all the security review acronyms you can imagine).
Many of these enterprise companies would traditionally look to (expensive) intent data providers to help their GTM teams focus on the right accounts. But are now exploring Common Room to be able to take better action on the data provided.
And this enterprise focus is reflected in their platform's flexibility. Everything can be calibrated. From signal weights to scoring criteria. This gives teams the transparency and control they need to adapt the system to their specific business. And in turn, gives sellers transparent context, which builds trust, and adoption, and creates a beautiful virtuous cycle that improves the system.
Looking Forward: Supporting the Nuanced GTM Motions of Tomorrow
Common Room is building tooling that enables a nuanced go-to-market motion, which I think is the future. Buyers have more optionality, there is more data in the world, and the old playbook and tooling doesn’t work like it once did. The combination of these market forces creates a perfect storm for Common Room to exist.
And, as AI continues to transform go-to-market strategy, having clean, unified data becomes even more critical. Common Room's thesis is that by building the most comprehensive signal layer plus identity resolution, they'll enable the most sophisticated, targeted AI automations, that will run modern go-to-market teams. A product that is powerful enough to get outcomes, and puts the power and creativity of a GTM engineer in the hands of sales and demand gen managers.
If you’re building a modern GTM engine and struggling with noisy signals, it’s worth checking out Common Room to help your team efficiently drive more pipeline.
PS - Mention The Signal when you sign up and they’ll double your trial period (for free).
Thank you for your continued attention and trust—I do not take it for granted.
See you next time,
Brendan 🫡