Name: Inside the Room: Q1 2026 Product Release Updates
Uploaded: 2026-02-04T19:16:08.141Z
Duration: 36 min
Description: Inside the Room: Q1 2026 Product Release Updates

Transcript for "Inside the Room: Q1 2026 Product Release Updates": Alright. Good afternoon, everyone, or I guess I guess good morning to those, all around the world. Thank you so much for joining us. My name is Adam Harris. I'm a product marketer here at Common Room. And today, I just wanna welcome you all both live and for those who are watching the recording afterwards. Today, we're gonna talk about some really awesome product releases that we have here at Common Room and maybe a little bit of a hint at what's coming with Common Room as well. But before I get ahead of myself, I would like to introduce Viraj, who is our cofounder and chief tech chief technology and product officer. Viraj, would you like to introduce yourself? Yeah. Thanks for setting this up, Adam, and hello to all of our customers and future customers. I'm glad to share more about stuff we've built and stuff we're planning to build. So thanks again for joining. Fantastic. So a few housekeeping items before we move on into the meat of the presentation, but just I wanna remind everyone that we will have a question and answer session at the end of the webinar. You can submit your Q and As on the tab to the left of your screen actually, sorry, to the right of your screen as you're staring at your screen. You can submit your questions there, and we will sort and answer them as appropriate. If there are any questions that we do not get a chance to answer within the time allotted, we will we can follow-up with you afterwards as well. And once again, the recording for this session will be available about twenty four hours after the event has concluded, and we'll be able to we'll be able to take a quick look at, or you'll be able to take a quick look at everything that's going on and, re replay it. Alright. So let's go ahead and jump in. First and foremost, once again, Viroj Moni and Adam Parish, you are two, wonderful presenters here today. I wanna open up by talking a little bit about the trends and themes that we're seeing here in the market. You know, as a product marketer, Viroj is kind of having his ear very close to the ground for the problems and the scenarios that our customers are are encountering every day. We've really divided it up into three big, you know, themes that we're seeing. The first thing being is that, data quality is really holding back a lot of revenue teams. And we can get into that, and we'll have an answer for that later on in in the program. The second is that I think all of us are feeling this, but go to market AI is at an inflection point, especially in regards to trust among sellers, and we're seeing that through adoption. We're seeing that through what tools they're using. We're seeing that through what questions customers are asking us. And lastly, you know, kind of the recognition that AI needs to be fully accessible for all team members. Can't be siloed off into separate teams. Can't be siloed off into just separate use cases. But, like, really good AI is just, across the board accessible. And so with that, Viraj and the product team and our leadership team at Common Room have have set forth these three product innovation pillars that we are building towards in 2026. And, Viraj, if you wanna go into a little more depth as to, like, what these three pillars mean and kind of a little a little bit of a previous, what these will look like later on. Whoop. There we go. Yeah. For sure. You know, we all have seen how AI has helped everybody get more efficient and do more. The foundation of really good outcomes with AI is having solid data. You do not want poison pills that are gonna make data bad data cause AI to hallucinate or generally give conflicting insights. And so the most important thing for any delivery platform that promises AI driven outcomes is being built on a solid data foundation. Common Room from the beginning has spent a lot of time and energy making sure that the data we provide to customers is the best possible using state of the art ML models in the early days and AI tools now. We continue to invest here in a way that blends, you know, best of first, second, and third party signals and data, but also ensuring that the data is accurate and high quality. We'll talk a little bit about some of the features we've delivered and some of what's on the road map that brings this to life. But as a commitment to our customers, this is something that we take pretty seriously in terms of, you know, having a team that constantly monitoring the data ecosystem, monitoring data in our own system. That way, y'all don't have to incur the burden of, you know, changing your tooling or revisiting new data vendors or worrying about contracts and costs and all that fun stuff. So that's that's gonna be a continued focus, and that's where we have some pretty exciting things to announce that we'll talk about soon. The second pillar really is becoming the place where your you and your company are going to for sales outcomes. And then when you think about what that looks like in 2026, what does AI native prospecting look like? How do you operationalize signals with speed to lead using all the right insights at the right time? Some of the Spark features that we released have just been extremely impactful to customers. So we have plans to continue down that trend and really make sure that all your prospecting needs are met directly in common rooms platform. And then to echo what Adam was saying, right, making AI work in a way that serves in the entire go to market team. We're pretty focused on making reps way more productive and efficient in their jobs. Obviously, making sure that the dev ops team that sets everything up for different parts of the go to market organization can leverage AI, and then bringing AI to marketing as well is part of our plan for 2026. Fantastic. Yeah. So I love those three themes, solid data foundation. Obviously, that's important to everyone on this call. The second is, really becoming that system of record and, like, making us the central hub for for prospecting and focusing on the outcomes associated with it. Like, AI for AI's sake is useful to no one, then making sure that AI is available to everyone within the go to market organization. So moving forward thanks so much for that, Baraj. I think it's really helpful to hear your perspective. And once again, you know, given all the conversations you have with customers and with prospects and with industry peers, like, understanding and amalgamating everything that we as a as a marketer are experiencing right now. So moving right along, you know, what I wanna say or what I wanna focus on to a certain extent is, you know, everything that we've delivered thus far in this quarter, but also what is coming. So to give you a little bit of a preview over the next few slides is a quick overview of the initiatives that we've shipped our customers. Miraj, I'm gonna ask you for a couple of your favorites. I think the these favorites, as as you have expressed them is, you know, our premium phone enrichment as well as room AI Spark, something you alluded to just a few minutes ago. But, like, that's that's been, not surprising, but, like, hugely impactful for especially for our our rep workflows. And then further on, we're going to dive deeper into three new initiatives for Common Room or three new introductions for Common Room. First is the introduction of org three sixty, the second being kind of improved technographic signals with, improved technographic signals with our partner with Buyercaddy, and lastly, talking about data agent. So as we move forward, Viroj, once again, a quick recap. You know, there's two things that you really wanted to hit upon in here. So first, premium bone enrichment. You know, what what's the deal with full enriched, Viroj? Yeah. Full enrich is one of our, partners that we onboarded, last quarter, and customers have been seeing incredible outcomes in terms of just their ability to reach the right people at the right phone numbers. What full language does is a very similar model to what Common Room does with person three sixty, but obviously focuses on phone numbers. And because of our relationship with them, we're able to extend that as a add on at pretty attractive pricing. So if you haven't looked at it, definitely check it out. We're working on, adding some free credits for all of our customers to play with this as well. The idea here is a lot of information about customers is dynamic, and phone numbers is one of those, like, really dynamic pieces that's easy to get stale, but really valuable when it's current and accurate. And so that's where we work closely with full end rates to make sure that if you purchase this add on, you have the ability to get on demand the best contact information for prospects or existing customers as needed. Yeah. And, like, the precision associated with, like, just finding the right phone number is, you know, Yeah. We hands, again, down. you know, because because we have a data team that spends a lot of time evaluating, we spend, you know, a lot of time evaluating various different vendors before partnering with full enrich and are very confident of the data we provide here. Fantastic. And second, anti powered research and activation, Rumi AI. You know, this was announced back in, October, I believe. And, you know, obviously, it seems like it's been you know, we're we're in 2026 now. But if you could talk a little bit about the successes that our customers have had with Roomie AI, especially, like, kind of some of the real time Slack alerts, we'd love to hear your perspective on, like, the impact that this has made within our customer environments. This has been a sleeper hit. Well, not not really sleeper from our perspective because we put a lot of energy into it. But the key here is giving customers insights about a contact that don't just give you summary information or here's their title or here's their LinkedIn profile or whatever. It actually tells you what they did that is important relative to your business, both at the person level and at the account level. So if someone hits your website, if they've also done a few other things in other signals, Spark is able to compile all of that into really crisp summaries for you that help you understand who this person is, but more importantly, why you should reach out to them now, how you should reach out to them. And the other transformational thing here is it gives you a lot of account context that includes not just a party signal or, like, information about the company, information from your own systems about the state of this account. Yeah. You know, if there are previous updates around closed loss or closed won or upcoming renewal or champion changes or any notes you've made from previous calls, it'll synthesize all of that and bring it into a crisp summary of here's why you should act, here's why it's important, and here's some recommended next steps. Like, ultimate context. Right? Like, I think all of us have used tools that are that can give you research at the account level or can, you know, you know, do basic summarization from a web, from a, from stuff that you that you've crawled from the, pulled from the web. But, like, that really fully contextualized research and insight is quite frankly really cool. Like, I use it myself as product marketer, understanding before I hop on calls with customers. So once again, a sleeper hit, but perhaps not from but perhaps not from our side as you said. Like, we put a ton of work. The engineering team has done a phenomenal job of connecting those dots all across the common room platform to give you that context. So alright. I think the the other key here is we will push this where your reps can get visibility. So, you know, if you work on a Slack, if you work on a email, if you're in product. So the goal here really is to give you this information at your fingertips in the. Chrome extension. Absolutely. Alright. Moving right along. So we have three new announcements that we have released over the last six weeks within Common Room. We're gonna hit each of those, here, here coming up. So first up is updates to account based flows and profile updates with org three sixty. Now this is a this is a meaty update for us. And, Raj, you know, I think for for a lot of our customers on the call, like, what the heck is org three sixty? Why is it important? How is it going to impact their workflows? And I I'd say the last question is, you know, how is it going to impact the outcomes that they can experience within Common Room as well? Yeah. You'll be hearing a lot more about org three sixty as we bring it online for both new and existing customers. But the way to think about this is org three sixty is bringing person three sixty at the account and company level. The outcome customers get here is you will be able to mirror exactly your account hierarchies that come from your CRM while making sure that you can layer on real world signals independent of how you organize accounts or how you route opportunities in your CRMs. So imagine being able to score, build plays, or prospect at any for any account regardless of how you organize it. As an example, Hulu and ESPN are subsidiaries of Disney. Right? Mhmm. Some companies may treat Disney as one single entity and one single account assigned to one rep. Many companies will have, you know, Hulu assigned to one rep and ESPN assigned to another and Disney Resorts assigned to a third. What org three sixty lets you do is you can build plays based on your your unique assignment criteria. You can score your unique assignment criteria. You can prospect within these. We will tell you which of your contacts belong to which of these subaccounts. But then signals that exist in the real world, things like job postings live on Disney's website or news that involves Disney, but maybe specifically ESPN or Hulu or prospecting within this even if prospects say they work at Disney but are in the ESPN organization. All of that becomes possible now to give you complete clarity and fidelity for how your business systems work, but all of the power of common room. And then, you know, you have ultimate flexibility. You wanna operate at the account level. You wanna operate at the organization level. And we're bringing this throughout our stack all the way from building place, through doing research, through scoring, and so on. Yeah. That's fantastic. And and to summarize that is ensuring the common room works seamlessly with how our customers wanna work. Right? And then being able to pull in all the insights and all the all the actions that you expect at the person level, bring that up to the account and the organization level as well and compile once again, as we were talking about before, compiling those insights and kind of contextualizing them across. And, ultimately, you know, you you said the term outcomes before, and you've you've said it multiple times, since, Barag, but making sure that the outcome associated with anything any action that we take within common room is the outcome that a customer wants, not something that you have to go back through and rehash. Not something you have to go back through and then fix multiple times, but it just it just works. Yeah. I mean, there's an element of magic to it. One of our early adopter customers was actually that's that's how they described it. It's like, hey. I don't know how this works, but it's just, like, some magic that we've never seen before in another tool. No. And that's the goal. You know? Our goal isn't to bother customers about how this works in the back end or how it's implemented. It really should mirror how your business thinks about running your business and. then sprinkle all of the signal magic as needed. Yeah. And I see a question in the chat. This is Salesforce first, but we will be bringing it to other CRMs as well. That's wonderful. But, yeah, thanks for answering that question from Kate. Alright. Next up, technographic samples with buyer, Caddy. So insights into the prospects. Tech stack, What I'd love to understand from you, Viraj, is how can technographic signals add that critical context to augment other signals and enrichment sources? Like, what is what is bringing this technographic layer into our signal our our signal foundation mean to our customers? Yeah. We we're really excited about this partnership as well. You know, a company's tech stack gives you a lot of information about what they use, competitors, your own tools, when, you know, the the array of different tools a company uses. What is more important, though, is when changes occur in company's tech stacks. You know, company a brought on your competitor tool six months ago. What that means is in six months, they're gonna be do a renewal. Should you strategize about how to potentially convert them? Or, you know, an adjacent tool that your software works really well with has been deployed to all these different customers. Now here is your account list that you can give to reps to go prospecting to with really high confidence information about, you know, how a better together story works with some of these other tools. So bringing current information about this, but also layering in foreseen, last seen dates, as well as, like, the confidence measure of each different part of the stack, That's been really, really impactful to customers and has unlocked a bunch of different plays that they haven't even thought of before, Yeah. both competitive based plays, but also organic plays around how they can find companies that exhibit a need for the products they sell. Yeah. The I think the coolest thing for for me, at least, is the tech stack intensity, which is what I believe we and buyer caddy call it. And to your point earlier is, like, given that confidence, I think all of us have researched tech tech stack insights and, like but for an organization of any size, you you may have someone that's on a free trial, and it's only limited to one or two people within the entire organization. Or you have a provider that's rolled out across the entire org and has been embedded for years. Like, that difference as well is really important to know to understand where you may have a competitive edge, what what buyers are looking for. And so those types of signals, once again, kind of initial discussions with customers and the outcomes that they're seeing, it's been really powerful of, like, understanding that nuance associated, not just who has signed the contract or who has signed up for a free trial. So. And, like, every every company we partner with, you know, we did a pretty deep evaluation of this technology versus a bunch of others out there. And then the way we blend it into our existing set of tools. So, you know, we have others, data providers we use for this information already. So we do all the heavy lifting of. building out the ML models that blend in information from all of these vendors to give you kind of the best in class tech stack information. Fantastic. And a quick note, this is, you know, free to use for customers or for common room customers. It's not an add on here. It is just it, you know, literally just translates into the text text signals that you can find within your standard filters and segment building. So alright. Moving right along. This next one or this last one that we're going to talk about from a current release we just talked about last week or we just released last week, but it is data agent. And so, like, there's a there's a big rationale around, like, why CRM data hygiene is so important. And there are a bunch of alternative methods that people are using to help clean their CRMs, but we've rolled this out as a kind of as as a as a really wonderful solution to make sure that your data foundation is as clean and as is as clean as possible. So, Viroj, do you mind talking about, like, you know, why a AI is so data dependent? You've mentioned that beforehand, but, like, why and, also, like, why good hygiene is hard to maintain. I'm sure if if we have any rev ops folks on the call today, then, if if I say the word data hygiene, they their eyes twitch a little bit. But would love love some insights, why we built this? What if she's wanting, to a certain extent, whatever places, what what workflows and processes it replaces? Yeah. It's a it's a fun story on how why and how we build this. So we've always as part of having, you know, person three sixty and all three sixty, we've always been able to tell pretty easily when data in customer systems is stale or incorrect or when there's duplicates. And, you know, we reflect that in our product. So, for example, if you're looking at a contact profile, you'll see all the CRM links. You'll see a job history. You'll see valid and invalid emails. And as they started being leveraged across our customer base, we we got the we got requests from, like, DevOps teams around, hey. Can you export all this data to us so we can go clean up our CRM? Because clearly, you're seeing things that we aren't, you know, things like companies merging or acquisitions or rebranding, changing the domain names, etcetera. And so after we got a few of these, we figured, hey. Look. We have all of this information. Why not just make it available to customers in a self serve way that allows them to, you know, find duplicate accounts, find duplicate contacts, and allow them to merge it all or just clean up their own CRMs more effectively. Because, look, ultimately, everybody is gonna depend on high fidelity clean data. Obviously, we have the ability to operationalize it within common room, and this gives RevOps teams a great way to take all those person three sixteen or three sixteen sites that we can get, bring it to their own systems. So this is an early beta we announced a couple of weeks ago. Currently, all the we will show you all the duplicates and conflicts. You can download a report that helps you clean it up. And then we'd love feedback on how best to operationalize it. You know, we understand that CRM data is pretty sacred. You don't wanna willy nilly go edit it. And so as customers start to use this, we're soliciting feedback on how best to automate some of this cleanup. Should we tag duplicate accounts? Should we try and auto merge them? Should we just, like, allow for report downloads? All of the above. So as customers try this out, we're all ears in terms of how we can enhance this experience because our goal is to share the data we have with our customers so you can rely on it as well. We're gonna talk about it soon, but our MCP offering is in a similar vein. Right? Like, if you have other systems that you want to plug common room into, just drop our MCP server in there. Yeah. Fantastic. And once again, kinda to to summarize that is, you know, this is a problem that a ton of our rev ops our rev ops leads have talked to us about, and the alternatives that they're using is, you know, a lot of rules based cleanup, kind of, you know, going in, trying their best to clean, validation rules, dedupe rules. And what we constantly heard was that, like, they work okay, but they don't work well enough. And, like, the fidelity of data that CommRoom gives us or gives them, was at just that next level for making sure you're maintaining that proper, CRM hygiene and the fact that, like, CRM hygiene is an ongoing process. Right? Like, it's just it never ends. So as soon as as soon as you do a cleanup project, you know, a company merges, account go you know, a contact goes out of date, you have to start, you know, auditing that again and again and again. And that's that's, from our understanding, is the power behind data agents. It's always running in the background. It's always servicing what is right, what is wrong, what needs to be cleaned up. And we're excited about what the future holds from here. So alright. Thanks so much, Raj. Now moving forwards, what's next for common room? So we have, we're gonna talk at a high level about, you know, what we are imagining for the rest of 2026. And I'd love for you to give some some color commentary around like, what is Askcom Room anything? Like, what are we thinking around, you know, next generate next gen AI prospecting? And, you know, you just alluded to it, but, like, our MCP server. Like, there's a lot in here, Mhmm. but we'd love to get your your insight as to, like, what we're building directionally and and, Yeah. ultimately, what what what the customer outcomes we're looking for. This is continuing some of the wins we're seeing with Rumi, iSpark, being able to make a lot of those insights conversational so that, you know, when you get pulled into common room or a speed to lead contact, you will obviously get insights out of the box from our room AI research as well as Spark. But you might have other interesting strategies that you might wanna chat with AI about. And so what AskCommanything does is brings a chat surface into your contact or account that takes all the information we have, takes publicly available information, takes a data from all your signals, and then helps you answer any question you have specific to that contact or that account. And all of this remains compliant with AI policies. So, you know, we have ZDR, zero data retention policies that are important. So this is this is just like a handy way for reps to have a assistant experience always available to them within the common room surface and the Chrome extension, etcetera. Think of this as taking what room AI research and Spark do, but then making it interactive. Yeah. The next big bucket though is one I'm personally really excited about. We're making improvements to how prospecting works in common room so that parity with other prospecting tools or, you know, we have better data with them so we can easily outshine other prospecting tools. But our aspirations here are much broader. The we'll obviously share more as we have something to show, Yeah. but the value proposition and the use case here is, hey. How should prospecting look in a AI native world? You know, building an account list based on customer location or company size or company stage, total revenue, number of employees, or the tech stack. All of these are sort of the incumbent ways that prospecting works. And, obviously, we want common room to work best in class here. But that's not the way the future will be. AI just changes the game completely. You should be able to just get account lists based on a bunch of criteria that you didn't even think about. There's no need to define criteria. Or how do you identify the right people without needing to build out some sort of definition of account of contact titles or contact location or people who've changed jobs. All of that should just feel like magic. So that's the goal we're after with AI native prospecting, and I'm pretty excited. We have some early research that's yielding promising results, but I can't wait to bring that to customers. Yeah. And like you said, we'll we'll definitely talk about that more in a future iteration of this webinar, but, I'm excited about it as well and kind of, removing the shackles from kind of what our customers currently define as their prospecting motion. I think that's just super exciting. So you wanna wrap us up with a little bit about MCP server and, like, what we're envisioning there, Raj? Yeah. For sure. So we have apps that we plan to publish on OpenAI's JetGPT store as well as for Anthropix Cloud store. The goal here is bring common room AI to your business systems wherever it's needed. MCPs are really popular. They're kinda par for the course. Every new feature we build will have representation in our MCP server. So just think of it as another way to access all the insights and data that powers signals in common. room. Amazing. Three huge initiatives coming forward, from Comroom, and that is not all. And we will be we are obviously gonna be talking about this over the next months, quarters. And so stay tuned, everyone, for what, for what the future brings here at Common Room. I do wanna move on to a few questions that we've had submitted from the audience. One of them, Viroj, is, quick thing about packaging. So, you know, Buyer County, Data Agent, are those separate SKUs, or are they bundled within kind of the the broader common room experience? Yeah. That's a great question. Data agent is a separate add on. It's available for free while it's on beta, so we'd love for you to try it out, give us feedback. But we do plan to make it a continuously running agent that's scanning systems for data inconsistencies and providing you with that, like, automatic and continuous data hygiene. Full Enrich is an add on, but Buyercaddy and org three sixty are just out of the box. Obviously, for org three sixty, you need to connect to CRM, Salesforce today, HubSpot soon. And but, yeah, the rest of it is just platform capabilities. Fantastic. With, another question from the audience is, know, is there any plans on making some type of manager module or creating a new role? The further context behind this question is my managers need to have admin rights to see reporting that matters to them. In addition, it's hard to view segments and other lists in a team view. We'd love to have some some kind of manager team mapping. What are your thoughts on that, Piraj? Yeah. That's a great request. It's something we've heard. And, this quarter, we actually have a, manager reporting, beta planned. So, Eric, we yeah. My email is veraj@commonroom.io. I'd love to have you and your team get some early access to this and, provide information, or, like, feedback on how we should replicate this. You know, part of my thought here is there is a whole world where we can replicate manager hierarchies from your HRIS, etcetera. But, also, I know that there are matrix organizations where, you know, manage what typically an HRIS would have around manager hierarchy is not how you want to see reporting data. So that's the path that's the part we're trying to figure out. Is this something we should allow customization in common room or just automate out of the box? But that request makes a lot of sense. It is something we're planning to do. Yeah. And then and then, you know, I think part of your question also is around, like, whether a seat is required in common room or not. So I would love to get your feedback there as well because today, you're right. You have to have a seat in common room as an admin in order to see some of the reporting. Yeah. Fantastic. Another question is related to the Buyer Caddy tech stack. Is that available only in Prospect, or or can you use it in, regular segment building? And I I can It's available it across. Right? Yeah. yeah. It's available anywhere. Everywhere, you can filter on stuff. You can use it for scoring. You can use it for play building. You can use it for prospecting. It's part of our system data. Yeah. And, another follow-up question to that as well, Viroj, is, like, how often are signals refreshed, within the common room platform? This is broader question from the audience. The general answer is continuously. So for out of the box signal, things like job changes, all of our, you know, person three sixty, all three sixty, tech stack information, You don't need, like, jobs, news, everywhere from daily, weekly, to continuous. There are some things that we just go and eagerly fetch all the time. So from a customer perspective, obviously, I can break down each one if needed. But our sorta contract with the customers is, hey. This is the most current and accurate information available, and we keep it fresh without you needing to do anything. And then for second and third party signals, obviously, it depends. Right? There's data from things like GitHub or Slack that are really real time and get pushed. Where that's not available, we fetch every fifteen minutes or so. But in aggregate, we try and keep things kinda continuously fresh across the board. Fantastic. Wonderful. Well, Viroj, I think that's all the questions that we have from the audience. So thank you so much to everyone who submitted questions. They're fantastic questions and, you know, obviously, piques some curiosity on our end. We're always looking for feedback from our customers, always looking to understand, like, how you're using Common Room, what you're experiencing, what you wish Common Room would do. That's a very long, list of list of things, I'm sure. But this is why we have Barag on on a webinar like this so he can, you know, solicit feedback directly. And that's the nice thing about being at a company of our size. We're moving fast. We're constantly evaluating what's next for us, and we're really excited about what what the rest of 2026 brings for us. So with that being said, everyone, thank you so much for joining us today. Stay tuned for the next quarter as we continue to roll out more improvements for Color Room. We'll be back again in the next quarter with Raj to kind of, you know, summarize what we roll out over the next few months. Once again, we have, this recording will be available about twenty four hours after. You can find it on our website. For any information, go to commonroom.io or commonroom.ai, and, you can get in touch with us. So wonderful. Thanks so much. You all have a wonderful rest of your day, and we'll talk to you soon. Thanks, everyone.