Doug Camplejohn
(00:01)
Hello, everyone. Welcome to this week’s episode of Revenue Renegades. Today, I’m excited to welcome Linda Lian, the CEO and co-founder of Common Room. Linda, welcome to the show.
Linda Lian
(00:11)
Thanks, Doug. Excited to be here.
Doug Camplejohn
(00:14)
We always start by asking about the founding story. How did you originally come up with the idea for Common Room?
Linda Lian
(00:21)
If you look at my LinkedIn, I’ve had a very horizontal and leapfrogging career. I started in finance, which led me to become an early-stage investor. That’s where I got excited about developer tools. It was the heyday of the rise of the cloud and modern DevOps movements.
A persistent theme in my career has been the desire to get into the trenches, moving from finance roles to being directly involved in building and taking products to market and creating customer value.
I got the opportunity to move from being an early-stage investor at Madrona Venture Group in Seattle to leading product marketing at AWS for some of the fastest-growing tooling lines at the time, like serverless and containers. As a student of the open-source distribution model, I saw how developers were on the cutting edge of changes in sales. Twenty years ago, sales was about building a fleet of reps, cold-calling lead lists, and targeting accounts. At AWS, I saw users finding software, evaluating it on their own, and reading reviews from trusted peers. By the time they asked for a sales call, 80 to 90% of the sales process was already complete.
Coming from developer tools, I saw incredible tools for application developers, including visibility, monitoring, and activation capabilities for application health. Yet, there was a lack of visibility and intelligence on the customer journey funnel. I thought, if apps are one piece of what keeps a B2B company alive, what about the customers and their journey? Why is it so dark and outdated? My service line was growing 300% year over year, with many developers engaging with us, but Salesforce CRM would have old notes from sales reps about calls with people who no longer worked there. I wanted to solve this problem.
From day zero, our vision has never changed: we want to transform how organizations connect with people. Focusing on people as primitives has been a crucial architectural decision, enabling us to build a strong data foundation for the new AI world and powering many differentiated solutions on our platform.
Doug Camplejohn
(04:00)
That’s really interesting. The overarching vision remained the same, but the entry point, if I understand correctly, was through communities and then evolved. Can you talk about where that started and how it evolved?
Linda Lian
(04:15)
Common Room is an AI-native platform that helps go-to-market teams know who to reach out to, when, and with a personalized message that will convert. When we set out to build the platform, we asked ourselves: what’s the one engagement signal that’s important to organizations but often overlooked? To me, that was dark social—unowned and owned digital properties like Twitter, LinkedIn, GitHub, and forums. If you’re a user-based organization, you always have a forum or community, with questions and troubleshooting happening not just with existing customers but across the entire funnel. For example, a LinkedIn post about your latest feature release can be one of the earliest awareness and engagement signals you get from a prospect.
We set out to capture all engagement happening in these siloed channels and unify them into a central place. We’re a COVID-era company, built during a time when all sales and marketing activity moved digital. Community and DevRel teams were on the front lines of this new frontier, but everyone was anonymous and didn’t understand the impact of their work on the customer journey or business outcomes. We focused on these dark social signals.
We asked: who would find these signals most useful? Initially, we targeted community and DevRel teams, but as we evolved, sales leaders began asking for more—product usage signals, third-party signals like champions who change jobs, technographic and firmographic signals, and unique niche signals only accessible through AI-powered scrapers. The evolution was organic, expanding our enrichment capabilities and the personas we serve, from ABM to DemandGen, enabling more teams to take action on these insights.
Doug Camplejohn
(08:12)
That makes sense. Expanding the persona and use cases exploded the opportunities for the platform. As part of this journey, do you evaluate data sources for your customers, or do they choose their own?
Linda Lian
(08:45)
We’ve done a lot of discovery and talk to customers daily about this pain point. The story of ops and RevOps has been a lot of manual effort to unify data points so the field can take action. A big part of that undifferentiated lift is gathering data. There are enrichment providers—when we started, Clearbit was the gold standard, but now there are many options.
Most ops professionals want to focus on strategic conversations, not manual enrichment. We abstract the heavy lifting by offering prescriptive, out-of-the-box enrichment setups. The most typical are Gmail de-anonymization, industry-leading signal capture, and now firmographic and technographic data, where AI assists with more niche data points through web scraping.
Another set of data, historically handled by reps, is account research. Millions are spent on sales enablement to help reps understand complex buyer maps or strategic wedges. AI is unlocking huge value here. Our research agent, RoomieAI, centrally configures all the data points reps care about—competitors, product offerings, engineering team growth, strategic initiatives from earnings calls—and serves them up. We call this scaling tribal knowledge. The best reps do this consistently, but now we can even out that insight and context for the whole field, driving productivity.
Doug Camplejohn
(11:49)
I saw a post recently where Clay seemed to block you from an event. It sounds like your approach is to do the heavy lifting for customers, while Clay is more of a roll-your-own approach. Is that fair?
Linda Lian
(12:13)
That’s fair. I come from a developer background, and the ecosystem is co-opetition. We respect all vendors innovating in the space. We see three main problems in the modern lead funnel: pipeline capture and enrichment, orchestration of unified data, and activation by humans. Salesforce is not a great UI for modern lead prospecting, nor is it AI-native. We invest in creating a sales workbench—a purpose-built workflow for SDRs, AEs, AMs, CSMs, and all the humans who need to take action on data. We believe pipeline generation and selling are team sports—humans aren’t going away. Technology and AI should accelerate pipeline and sales efficiency, letting humans work smarter rather than hiring more people to work harder.
Doug Camplejohn
(14:31)
Salesforce is talking a lot about AI, but also hiring thousands more sales reps. On the other end, there are dozens of AI SDR companies saying you don’t need reps at all. How do you think about both ends of that spectrum?
Linda Lian
(15:06)
We’re not dogmatic—every business is unique, and needs change over time. We support AI SDR solutions on our platform. Our biggest differentiator is the quality of inputs—LLMs need great data, or you get AI spam. AI SDR is great in certain scenarios. Most of our customers are growing their sales teams and also considering AI SDR. At a $10 billion company, we helped move 150 reps to strategic upmarket accounts, using AI SDR for long-tail acquisition—organizations with fewer than 100 employees get an AI SDR experience, still informed by signals.
AI SDR works well for transactional, less consultative moments—executive buyers hitting your pricing page, inbound qualification, or when prospects are just looking for answers. For strategic accounts, we surface person-level intent signals—who to reach out to, when, and why—so humans can add context. AI drafts messages using these signals, saving reps from cobbling them together or missing them entirely.
Doug Camplejohn
(19:01)
We have a phrase at Coffee: “You can’t have good AI with bad data.” You epitomize this by bringing together rich internal and external sources and surfacing them in ways most reps never see. Outreach and SalesLoft unlocked the importance of multiple touches. Now, with so much available signal, the next generation is about harnessing and orchestrating it, surfacing it to reps.
Linda Lian
(19:56)
Exactly.
Doug Camplejohn
(19:58)
On the inbound side and AI SDR, Jacco from Winning by Design said if you have bad process and bad data, you’re just enabling a spam cannon. The inbound use case is interesting. How do you think about automating inbound versus having a human in the loop?
Linda Lian
(20:38)
It comes down to gaining insights and context from noisy data. Usually, it’s about ICP fit, persona fit, and account fit as the first barrier of prioritization. Most organizations aren’t there yet—they get a flood of inbounds, and the rep just handles it. Is it someone you should spend time with? Who knows? Many AI companies face the problem of too much awareness and inbound interest, which becomes existential as they scale.
Step one is deanonymizing Gmail well and understanding the 360-degree context of a person’s engagement and account fit. If it’s a good fit, a human handles it; if not, there’s another path.
Doug Camplejohn
(22:22)
You talk about right person, right message, right time. Can you share examples of customers using those plays successfully?
Linda Lian
(22:34)
Three plays stand out. First, social selling: if you have a brand, you’re likely on social media. Social signals convert to meetings at much higher rates than traditional channels, but you must act quickly because behavioral signals decay fast.
Second, website visits: solution pages show strong intent, but most organizations don’t have that signal set up for the field. It often gets lost in data warehouses.
Third, champions who move jobs: we track job history and know when someone changes jobs. When a long-time customer joins a new company, you can build on the existing relationship. People change jobs every two years, and most executive buyers spend most of their budgets in their first six months. That’s a great time to reach out.
Doug Camplejohn
(26:09)
On LinkedIn, are you talking about people liking or commenting on posts from executives or the brand and then engaging from there?
Linda Lian
(26:35)
Yes, it’s all of that. Customers put out ads on LinkedIn, and individuals engage. It could be company page posts, competitor or ecosystem listening, or engagement in Slack groups. Some customers have Slack communities with over 100,000 people, and understanding who’s in there is a huge opportunity.
Doug Camplejohn
(27:30)
So you’re eliminating the need to manually check who engaged across channels and instead surfacing it through Common Room?
Linda Lian
(27:51)
Exactly, and at the person level. For example, I can see that Doug liked our latest LinkedIn post, is in our Slack group, and just started a free trial. Before platforms like ours, that information was never served up cohesively to a rep.
Doug Camplejohn
(28:13)
On website visitors, are you referring to person identification? I recently saw a former LinkedIn CMO visit our site, and when I reached out, she was surprised and found it creepy.
Linda Lian
(28:39)
It’s about how you engage. For example, if someone visits your pricing page, that’s strong intent and a good reason to reach out. We recently closed a deal with a public company, and the CEO was the final signer. I saw him all over our website and emailed him, and he was surprised at how I knew. At the end of the day, so much information is already out there. The key is applying it appropriately and ensuring compliance with GDPR, SOC 2, and data privacy laws. We have a close partnership with LinkedIn and always operate within their constraints.
Doug Camplejohn
(30:51)
My last company was acquired by LinkedIn, and they have a stack rank of who’s violating their terms of service. If you think you’re not on that list, think again. It’s about how overt your actions are and how you impact the customer experience. Their mantra is members first, and it’s important to stay on the right side of that.
Linda Lian
(31:48)
Totally. We’re seeing vendors not passing AppSec, and AI, data, and privacy will be major topics in the coming years.
Doug Camplejohn
(32:04)
You mentioned RevOps. How do you see that role evolving?
Linda Lian
(32:27)
We see silos in go-to-market functions that need to be brought together. First, marketing and sales: marketing has its own view of the customer journey in legacy tools, while sales doesn’t value things like black box keyword intent as much. Our goal is to bring everyone into the same room, using person-level data rolled up to accounts. That unified data layer helps align teams.
The next silo is between RevOps and the field. RevOps has focused on cobbling data together and fixing data quality issues, but hasn’t been able to focus on driving sales efficiency and activation. AI can reduce manual toil and make unification, signal collection, and orchestration easier, enabling ops to become more strategic. We work with customers where ops and reps have different views of what should be done, and our goal is to bring those teams together.
Doug Camplejohn
(35:15)
The marketing and sales divide is as old as time. If you’re operating off different goals and data, alignment is impossible. I imagine you deal with technical and cultural challenges deploying your solution.
Linda Lian
(35:44)
Absolutely, especially in enterprises. We’re a technology provider and partner on change management, but this is a cross-functional effort.
Doug Camplejohn
(36:02)
There’s only so much therapy you can provide. Are there surprising or counterintuitive buyer signals companies overlook?
Linda Lian
(36:26)
Product usage signals are often misunderstood. More product usage doesn’t always mean more buyer intent. We found with some PLG companies that high usage can make customers less likely to talk to a human—they’re happy as is. However, when costs spike, that’s a great moment for a consultative approach, such as migrating to an enterprise product for better cost controls. Many companies are moving from transactional overage models to more consultative, strategic approaches with product signals.
Doug Camplejohn
(38:23)
Are those signals coming from tools like Amplitude and Segment, or do you use your own code?
Linda Lian
(38:33)
We mainly go through the data warehouse—Snowflake or BigQuery—as the ultimate source of truth. Data is then pumped into tools like Amplitude or Segment for specific use cases. Going to the source reduces our R&D burden for deep native integrations.
Doug Camplejohn
(39:14)
We’re almost out of time. Tell me about yourself—what do you do for fun?
Linda Lian
(39:24)
Outside of tech, I love everything non-tech: art, reading paper books, gardening, being in nature, and anything without a screen.
Doug Camplejohn
(39:58)
Nature comes up a lot in these answers. I’ve started color-coding my calendar to take calls while walking outside in Sausalito. Sunshine is nice.
Linda Lian
(40:01)
Yes, it’s beautiful. It puts into perspective what we’re building.
Doug Camplejohn
(40:25)
What’s something people would be surprised to know about you?
Linda Lian
(40:33)
I’m funny. I try not to take things too seriously, even with the ups and downs of startup life. I’m a risk-taker and hope it doesn’t get me in trouble, but you have to have fun.
Doug Camplejohn
(41:22)
All entrepreneurs are risk-takers, but not all have a sense of humor about it. Many think they have to be perfect or work 100 hours a week. The reality is, there are a few things you do as CEO that are really important, and if it feels like a grind, it’s not sustainable. My measure of success is for people to look back and say this was the most rewarding part of their career, not just financially but personally.
Linda Lian
(42:37)
Exactly. That’s what we’re all seeking to deliver to our teams.
Doug Camplejohn
(42:45)
Let’s geek out on products. Besides your own, what’s one product you love to use and why?
Linda Lian
(42:55)
It’s basic, but I’m obsessed with Stanley cups. The way it holds ice, the water volume, the coldness—it just works for me. The design flaw is it doesn’t fit in most car cup holders, and my husband hates it, but it’s about what it does to the water.
Doug Camplejohn
(43:18)
Amazing. I didn’t get the Stanley Cup fad at first, but many people have an emotional attachment to it. I appreciate when a product nails it.
Linda Lian
(43:50)
I was always dehydrated, but now I’m hydrated. It’s saving my life.
Doug Camplejohn
(44:01)
Stanley, thank you. Finally, how can listeners keep in touch with you and support Common Room?
Linda Lian
(44:08)
Check out our website, www.commonroom.io, for a demo or to chat with us. Follow me on LinkedIn—I post about modern go-to-market tactics, startup observations, and more. DM or connect with me there; I’m active.
Doug Camplejohn
(44:34)
I’ve sent you a connection request. Thank you, Linda. This has been a blast. I appreciate your time, and I know our listeners will get a ton of value from this conversation.
Linda Lian
(44:45)
Thank you, Doug.
