Janis Zech: Hello, and welcome to another episode of the RevOps Lab. We're here with Soham Maniar. I hope I pronounced this correctly. Welcome, Soham.

Soham Maniar: Hey. Thanks for having me.

Janis Zech: Yeah. We had a really good chat, I think, a few weeks ago about signal based outbound and a topic that's in my mind is actually something that has been around for a long time. At the same time, was really, really challenging to do ten years ago, five years ago. And probably only the most sophisticated outbound teams have done that. But now it's being democratized, and I think that was kind of the initial conversation. And you just basically really revamped your outbound strategy around this theme. So this is the topic for today, and let's maybe kick off with who are you, what do you do, and then we dive right into the topic. So, yeah, thanks for being with us.

Soham Maniar: Yeah. Thanks for having me. So my name is Soham. I've been kind of in the RevOps space for my entire career in some way, shape, or form. So I started out my career in Salesforce implementation at a company called Blue Wolf, and that kinda led me down the systems and tools route at Twitter. And from there, I spent some time at large and small companies kind of moving up the ranks in revenue operations where today I now lead revenue operations at Weaviate. And, yeah, I mean, I've been in the RevOps space for, like I said, my whole career, so I've seen it change quite a bit from being a very reactive type of org to now really not just a cost center, but a revenue generating center if you structure it right and you think about it right. And so it's been really great to see RevOps grow. As far as, yeah, what I own at Weaviate, it's kind of two distinct functions that overlap. One is typical kind of RevOps things. So making sure that we have the systems and tools for our sales teams to function correctly from a go to market strategy perspective. How are we forecasting, generating pipeline? What markets are we in? What are we not doing? All that kind of fun stuff. Process wise, deal desk, all those typical things that fall into the process bucket. And then I think the other distinct bucket that I own that's probably pretty unusual but has a lot to do with the signal based outbound is owning our sales development function. So our kinda junior sales reps who are responsible for booking meetings, reaching out to prospects, and doing all of that stuff. I hired our first one. Now our team has three, and they all report to me, which is fairly unusual, but pretty fun, and I've learned a lot. So, yeah, that's a little bit about me.

Janis Zech: I love this. So you combine the ops world with the having a back, you know, as we say, world. Right? So who better to talk to about this topic than you? And let's maybe kick off with, like, how would you define signal based outbound?

Soham Maniar: Yeah. It's a great question. I think you said something really important earlier, which is it's not anything new fundamentally. Right? From the beginning of prospecting and selling software, sellers have been keyed in on this whether they realize it or not, and some have just done it better than others. And really, at its core, all it is is finding people who are as high up on the awareness and intent curve as possible so that your sale is as easy as possible, and you don't have to warm these prospects up. That's really all it's ever been. Why it's different today and why it's kind of getting this new term or being coined slightly differently is because there are tools and platforms and ways in which you can ingest this signal that did not exist before. And I don't think it has to do with AI or anything that's kind of, like, in the last eighteen months, but I would say in the last three to four years, people have started to be a little bit smarter about defining their own awareness and intent curves as they overlap on their ICPs and kind of TAM, I guess, at large. And what that really allows them to do is focus intentionally on the right customers who are already aware of their product, their space, what they're selling, why it helps, so that when you do reach out, it's as easy as humanly possible. So signal based outbound today is really being able to understand what those trigger points are for you and your business that tell you someone is as close to ready to buy as possible, and then reaching out at that time as opposed to educating and building awareness.

Janis Zech: Yeah. That's beautifully put, I think, and I think something everybody looks for. Right? Like, how can we know who is in market and actually knows us, loves us, trusts us, and is just not booking that demo for some reason? And then we nudge them and they're like, oh, thank you so much that you reached out. This is a wonderful message. I've been actually waiting for you. And, yeah, I actually been thinking about buying your product a long time ago. And I think in between, very cold and I don't know you and there's some shape or form of message. And there's obviously a lot of way in between. So I think I'd love to spend some time on, like, kind of going through, like, how do you actually identify the right signals. Right? And I think you said something very important. Those signals are in context of your business and your go to market, so they probably vary a lot. But maybe we can use your company as an example and then abstract from there?

Soham Maniar: Good question. So I'll frame it two different ways. I think there's generally speaking for any software company, there's some universal signals that just kinda matter. And to me, there's two forms of those. One is your website. Every software company ever in history has had a website. Now tracking has gotten kind of logistically and compliance wise a little bit more challenging, but you're still able to do it and say which companies are viewing certain pages on my website, and then you can work backwards to say certain pages have more of a tendency to tell me that someone is aware and ready to buy. That's pretty standard universal. Anybody can do it even if you started your company tomorrow. The other is product usage, and that one obviously varies based on kind of your company and your product and what it does. But at the end of the day, if you are selling a software product, you should be able to understand the motions in which people are in the pathways in which they enter your product, and what a successful kind of entry point looks like, and what a neutral entry point, and what a bad entry point looks like. And I can talk more about that later when we dive into kind of product usage metrics that matter. But to me, product usage and website is if you were to have a one day old company or a one week old company, you should be able to start somewhere because it's something anybody can do. So that's kind of the signals that could work for anybody. The other signals are very kind of channel and business maturity dependent. So, you know, anybody that's listening to this, take it with a grain of salt and really apply the logic to your business. But some context on Weaviate. Right? So it's an AI native vector database. Since twenty nineteen, it's been open source, and it still continues to be open source today. So for me, the learning curve was there are so many different channels of this business, and each of them comes with its own set of signals, and we can even talk about stacking signals later. But the more channels, the better because the more channels, the more signals. And so for us, we have a few different ones. We have open source. We have kind of a PLG free to pay motion, but the free motion is kind of its own thing. So people can sign up for a sandbox. It lives for fourteen days. You can play around with it. You can extend it three times, and then at the end of that, you kinda lose access to your data and you gotta make a choice. There's serverless, which is almost like our pay as you go monthly, and you pay as little as twenty five dollars a month to use some of our basic functionality, and you can use that forever. And it scales up and down with the amount of data volume that you store. And then the last is kind of enterprise. So we made enterprise cloud as probably our newest product, it's been this for, you know, less than two years, and it's really when we started to consider ourselves a proper enterprise business. So across those four channels, you know, I think some businesses are lucky if they have one or two channels, and we have four. A fifth if you actually just count marketing kind of has its own channel in terms of the collateral that exists. You could argue it's a layer on top of all of those because it feeds into each of those, but for the sake of signal, you could almost say marketing collateral, the website, all of that is its own set of signals as well. So what makes Weaviate a really interesting business from a signal perspective is exactly that, which is I have all the options. So I spent the first — I've been here about nine months. I spent the first three to four months before we really brought in any BDRs to go action this, just understanding what signals we have at our disposal. So to kind of quickly answer your question and dive into some of the specifics, open source is a really interesting one. So there's plenty of tools. You can even do it kind of your own way depending on the technical resources that you have at your disposal. But we have a tool called Scarf where there's a pixel that sits on top of our open source packages. And, really, all it does is it de-anonymizes the companies that are using us open source. And so then we're able to go dive in and figure out which companies are using us open source, at what level, at what scale. That in and of itself, even if you weren't to stack that with anything else, is a really interesting channel for us. So we can go figure out, you know, which of those companies are using us heavily and start to unpack why and what they're building. So that's kind of open source just as one channel. Sandbox and serverless all bucket together, and, really, that's just pure product usage. Right? So how many people are signing up from certain companies? What are they doing in their first day? What are they doing in their first thirty days? Candidly, this is where we're, like, the least mature, but I would argue is, like, one of the most important places to really double down and understand. Because when you think about that awareness curve again, who are the people that are the most mature? The ones that are already using your product. And then one layer above that, the ones that are using your product extremely well. Those are the ones where your level of effort and energy that you have to put in to convert them is the least. So, you know, that's kind of like the product usage section. Then there's sort of the enterprise side of things. And, really, enterprise is the best example of stacking signals across everything. Because any enterprise seller can tell you that you just don't have one signal from one person unless it's like an inbound form submission that says, please, I'm ready to pay, which, you know, sometimes happens. But any enterprise seller will tell you it took them a long history of unpacking all the different things that happened. And that's where signal based selling becomes really, really interesting. So a fun one that I can kinda mention that's interesting for us, and then I'll pause, is GitHub. So we have, you know, through a tool that we use called Common Room — there's plenty of other tools out there that kind of do this sort of thing — but you can basically plug in your own GitHub repo if you're an open source platform and then see which users are starring, forking, commenting, building on your repo, which is a huge signal for an open source company to be able to say, what are the developers doing within my repo? So, you know, that's a great signal for us. It turns up quite a lot in and of itself. And then when you stack it with open source usage, website visits, right, I view that signal based selling as it really becomes putting a puzzle together, which is for this type of company, what is the order of operations that tells me someone is ready to buy? Is it open source usage for x number of weeks, and then they come to our technical documentation and view a certain blog, and then they do this and that and the other thing, and finally land at product usage, and we can see that journey through and through, which makes it super interesting to kind of learn from.

Janis Zech: Yeah. I mean, you know, please keep talking. I think, like, you just doing a monologue here is like working perfectly fine for this podcast episode. It's perfectly fine, but, you know, still, like, I'll to fulfill my duty as a host ask you a question. But no, like, I think the — I mean, what you said right in the beginning, I think, like, a big piece and I think this is probably one big challenge that many companies face is this first step is the de-anonymization and then to do it in a way that it doesn't feel like too artificial or like a blocker, like you create this artificial gateway that then the customer has to jump through. Like, I think, like, the most basic example here is probably, like, gated content. You know, like, download our cheat sheet, but please enter your email address first. Right? So this is one of those, you know, which is really annoying. And then, like, once you've done this, like, for example, the pixel, right, I think this is, like, super elegant and, like, really good way of doing it. And I think also just looking at the product stats and so on. Then to figure out, okay, you know, what actually then is a good signal? So now you are able to, like, collect the data and then actually look at all the different potential signals and then to figure out, okay, which of these signals is real or, basically, how to put it, like, is worth, like, you know, doubling down on because it generates the highest conversion rate. And that part, that's something I'm curious about and I would like to dig a little bit deeper into because I feel like this is actually not so easy. So let's say you de-anonymize and then there's lots of stuff going on suddenly in the product, like hundreds of companies starting to use the repository and so on, building their own stuff — like, where do you start? Like, how do you actually figure this out?

Soham Maniar: Yeah. It's a great question. I mean, not that we figured it out in some perfect way, but I think it's — like with many things, there's a gray area, and it all depends on kinda what you're looking to optimize for. So what I mean by that is, you know, certain signals — my opinion is standalone signals are only helpful if you're looking to see what they convert to immediately after. So as an example, you shouldn't look at people who just hit the pricing page as a standalone signal to try to pattern recognize anything, unless you're looking to say, by that channel of that signal, how many people turn into a stage one opportunity? Right? If you wanna see exactly what happened on the other side of that kind of hill, then it's a helpful exercise to say, okay. Well, we had five hundred people hit the pricing page and five of them turned into stage one opportunities just from that pricing page visit. Then the signal in and of itself is something you can key off of and double down on, or cut if it's not helping. When you kinda take a step back, again, it's just my opinion based on what I'm seeing, at least for our business — you're never gonna see an enterprise deal get to a closed won state off of just one or two signals. It tends to be multiple signals across multiple people over a very long period of time. So that's where you have to kind of be — it's more art than science, but it's both — to really understand what are all the different ways in which people can engage with your company and then kind of tier them. So I almost imagine a pyramid where the tier one kind of signals are things that, you know, correlate directly to them building in the product or engaging in buying activity. So if they download a pricing guide, that's a gated piece of content, and there's a product sign up. Right? So these are all and statements, not or. Within each tier, there's and statements among the tiers, then you can try to figure out the or statements if that makes sense. So there's those tier one things for your business that you know when somebody does it, they're pretty much ready to buy, and there shouldn't be very many of them. And then there's kind of the tier two things, which tell you they're very aware of your business, your space. Maybe they're working with a competitor, all that kind of stuff. So you know that there's no need to really validate, but it's more just convince. And then there's the validate tier, which is, you know, they might just be hitting your website, and just starring your GitHub repo, and liking a few social posts. Those are all surface level things. It's not nothing, but it's helpful to know where they sit on that awareness curve. So back to your point. Right? Figuring out what converts to closed won, it becomes much more than just a signal game because at some point, your sales reps step in, and there's multiple people involved in the process, and it becomes much more than just what signal brought them in the door. So to me, it's always about exactly that, which is what signals brought them in the door willing to have a conversation. Signals are just that. They're just the handle to the door. Right? That's all they are. They're not gonna help close the deal because that — I think that is much more than a signal at that point.

Janis Zech: Yeah. Yeah. No. I get it. I mean, like, one of those things is like, how often did someone open an email. Right? Sure. Like, that's, you know, that's maybe one of the weakest signals here.

Soham Maniar: Yeah. Think so. So some value there, but, I mean, don't freak out over it if someone opened the email thirty times, like, that could mean a lot of different things. You have to operate with a very healthy level of skepticism when it comes to signals. Right? I think companies that are overly optimistic about the signals they see and the results they see from signals, you're probably missing something very obvious when it comes to the other side of it, so I think there's a healthy level of skepticism that should be there when you're dealing with any of these signals. Because think about how — I always put myself in the end user's perspective. Just think about your typical day. You work in tech. You're coming across ten to twelve websites in a day. You're clicking things. You're downloading things. You're liking posts. I don't even realize I do it half the time. Right? And I'm just kinda doing things because I'm down a pathway. But subconsciously, there's probably two to three vendors I'm considering for something right now, whether it's a forecasting tool or pipeline management tool, whatever what have you. Subconsciously, I am doing things in and around that sphere, and I may not even realize that I'm hitting the same pricing page three times in a week. Those are the signals you wanna pay attention to essentially. So if you're ever stuck — whoever's listening to this, if you ever stop trying to figure out what signals matter, take a step back and put yourself in the shoes of what do you do day to day and how are you interacting with these things, then you might see some reality around your interaction with what you would consider to be signals and what's real and what's not.

Janis Zech: So I think what you described earlier is actually a beautiful description of the awareness funnel — it's very fuzzy. And I think that's the reality for anyone who's been in marketing. Right? Like, knowing that you need X touch points and they will come from many different areas. But then, like, I think what you're basically describing — because I think the website combined with product usage data is very down the funnel already, right? Where, I mean, yes, some companies have the luxury of that data. I mean, website data for sure, but like product usage data, not so much if you're not product led or open source. Right? This is very specific to your example. But let's say you're sales led and you sell to the enterprise. Right? Like, how do you even do it? Right? And I think how I understand you is like you stack multiple signals together to basically say, okay, look, I mean, they looked at our pricing page. They did an interactive product tour on our website. We see density across the account. We see recurring users. And then maybe my question then is, like, do you look at signals in context of, like, contacts or accounts or both, and how do you orchestrate those?

Soham Maniar: Good question. I mean, I think where we are right now, we see so much potential in front of us that it's more on the account level. And so I think what we're, like, circling around a little bit here in this conversation is this concept of, like, scoring and prioritization. Right? Because when you stack signals, inevitably, what you come up with is kind of a tiered breakdown of — if you have a hundred thousand accounts in your database that you could sell to and you start to score them all across the same criteria, you'll start to see that ten percent are excellent and twenty five percent or whatever, and then the rest are all terrible. Right? So then it's giving you some sort of area to focus your prioritization on based on behavior and not just fit. Right? And I think that's a super important point too just to kinda segue, which is typically how people have tackled the space prior to signals and behavior and AI and kinda some of the things that allow you to tap into behavior now is just firmographic fit. And we've all understood ICP, and people go through that whole ICP definition exercise multiple times through the journey of their company to say, how many engineers do they have and how many x y z do they have and, like, all that kind of stuff and how much funding. And those are all surface level firmographic data that I see as old world. Now it's not not valuable, but I think it needs to be blended with behavior. So back to your question around stacking signals and what does that really mean in reality, it's just a prioritization framework, right, at the end of the day, which is which companies am I seeing a ton of noise from? And I actually really like your phrasing there, which is density. Right? I think that's actually the best way to describe it, the best adjective for what we're talking about, which is the accounts with the most density and noise are the ones where you should be focusing your attention because your reps will spend the least amount of time selling to them and the most amount of time guiding them along a journey that they're already on. Right? That's really, I think, what it comes down to at the end of the day. And so how we use that in real life at Weaviate is kind of the accounts that we have our sales reps focus on are all signal based and scoring based. Now hand raisers come in and random accounts pop up on our LinkedIns and seem like they could be a good fit, you always wanna keep some space for that. But we're not doing the typical — add heads as we wanna enter new territories and then just hope that we sell enough into that territory. Right? I think we're trying to approach it a slightly different way, and it all stems from this concept of signal and noise, and we'll see how it works.

Janis Zech: Yeah. Yeah. And, I mean, how do you — right. So I think some of the listeners will now basically ask themselves, okay. There are even specific tools you can use to get signals right, in the open source example or GitHub. How do you orchestrate that? Like, how do you layer it today? Right? And then how do you — I mean, because I think in my mind, right, it's a prioritization for time spent of SDRs or XDRs. Right? And then the question is what channels do the XDRs use that actually work? But let's maybe table that for now and first go into the orchestration layer. Right? Because I think a lot of people now listening to this are like, okay, well, that's great. I have all these different signals in all different places. Like, how do I actually bring it together so that then people can act on it right in their engagement tools or whatever they're using?

Soham Maniar: Sure. Yeah. I mean, when I hear the word orchestration, I think of a couple different things, which is kind of enrichment, which is kind of like an always on topic forever and ever. Short answer here is, you know, every tool does enrichment now, so I just pick one. Right? Like, I'm not really on the boat of there's this best — you know, you gotta do waterfall and you gotta do it through Clay. Like, they're all good. Figure out your budget and figure out what works. If you have the budget for a ZoomInfo, go do a ZoomInfo. If you have the budget for only a Clay monthly plan, then do a Clay monthly plan. But enrichment is, frankly, it's not my favorite thing to work on because it's always kind of just like a cost cutting exercise and a what can we do, what's the most we can do with very little exercise, but it's unfortunately part of the game, and there's nothing you can do about it. So I like to just have people who really are smarter about it than I am work on it, because I'm probably not the best person, but it's a necessary evil. But it points to the bigger thing around orchestration, which is kind of how do you activate these signals through channels, I guess, is how I think of the word orchestration. At the end of the day, it's part experiment and part collaborating with marketing and your leadership to understand your tone of voice of your company that you wanna have and the brand that you wanna portray. And what I mean by that is, you know, if you're okay having a brand of high volume, high noise, but we're always there and we're always in front of you when you're ready to make the decision, go email. Right? And go deep down the automating your email with custom variables and Clay and AI agents or whatever you wanna do. If it's very targeted to people who are already kind of out in public, but it's a professional place, then you can go with LinkedIn. If it's less professional and more casual, you go with X or Twitter. Right? So I think it really is — there's no one answer, and ultimately, you have to do all the channels. What I will say is, you know, calling is making a comeback for sure. And there's great tools out there in terms of phone calls. But across — I think any successful go to market org today needs to have a prospecting first mentality and not just for XDRs, but for everybody. To the — you know, I think hot take is, like, to the point of I communicate at large to the whole company. If you see anything on LinkedIn, whether you're an engineer or CEO or anybody, if you see anything on LinkedIn, if you know anybody that's talking about RAG or semantic search or anything like that, call it out in our GTM channel, and we'll find the right salesperson to connect you to. Because you just never know where these things come from today, and there's no one right channel. So that's kind of the high level on the channel. I can give, like, a specific example. Right? I think one that a lot of people have talked about — there's Brendan Short who is pretty big in this space. He now runs his own kind of agency where he does a lot of this stuff in terms of orchestration. So shout out to him if you guys need help. He's probably always busy, but he's really, really helpful. But something he's done that works really well, and it's kind of like an autopilot signal, is the website visitor one. So when somebody from within your ICP hits the website, specifically the pricing page, there's no reason for anybody to kind of sit there and manually think about the message that goes out. Right? And, again, this all comes within the what brand tone of voice you wanna have, but a really easy win is setting up an automated website visitor play and say, hey. If this company has stacked signals across other stuff, you can filter it down as narrow as you want. But, you know, if this company is within our ICP with x amount of revenue and x employees, but also has a product sign up in the last ninety days, and then they hit our pricing page, send them this canned message. Right? So you wanna work backwards from the message you wanna send and what you're looking to accomplish, and then you can just figure out which signal pathways to filter it down through. You can do that with virtually any signal. You can do it at GitHub repo star, people who have done that with viewed our technical documentation in the last ninety days and send them down exactly the pathway in terms of what they should be learning about our product next because you know what that persona looks like. Right? So you can get very creative with it. But the way to orchestrate it is just start. Start with something. Right? I kinda had that same moment for myself where I didn't really know where to start. And then I talked to Brendan, and he was like, just get the website visitor ones out the door. Right? And we have some level of consistent meetings that come through that every quarter where nobody's really doing any work. It just comes out automatically when someone hits the pricing page.

Janis Zech: Yeah. No. I think that's super smart, makes a lot of sense, and, yeah, I think it's just what you should do with these automations. As many automations as possible because, like, I think it's also about speed. Right? So somebody goes to a pricing page, it's currently top of mind, so it's important to react quickly. You hear this all the time with sales and, I mean, I think it's just so true. Automations are the way to guarantee that even if it's one AM somewhere.

Soham Maniar: Yeah. It's controlled, right? You take human error out of it, I think, is the main benefit.

Janis Zech: Yeah, for sure. For sure. You know, before we close, just curious, like, what are some of, like, the top mistakes that you maybe made, like, on your journey, like, things you can, you know, share with our listeners that you would say, like, hey, like, definitely avoid these one, two, three things that I totally failed at, if you wanna share.

Soham Maniar: Yeah. I mean, I think number one mistake — this may sound obvious, but — not setting up the metrics that you wanna measure yourself against before you go start building. It's very hard in an operational capacity when you get dropped in the middle of a huddle of sales reps asking you to create fields, and a CEO asking for strategy and vision on x y z, and marketing is asking for your help on attribution. And that's just the nature of the role at RevOps. You just get dropped in the middle of those conversations on day one, especially as you have a little bit more tenure. The most beneficial thing you can do when you're in a RevOps role and especially with everything we just talked about is pick some metrics. Just start somewhere and measure yourself against them, but just put it on paper because the worst thing you can do is spend three months — and I did it here, and I've done it at all other jobs and it never seemed to learn, but I'll preach anyways — which is the worst thing you can do is just go attack problems because it's very easy to just go tackle the low hanging fruit, but set yourself up for success, set up boundaries, set up a framework in which you wanna operate and be successful, and you're gonna be much happier at the six, eight month mark when you have something to compare against because you can always tweak. So that's the number one thing that comes to mind. The other that comes to mind is kind of vendor bloat and head on a swivel. Like, there's way too many tools out there, and the worst thing you can do is spend your time all day talking to new vendors. Your time is extremely valuable when you're a RevOps person, especially at a startup, and all the different things you have to be doing. You need focus time to go build and test and iterate. If you're talking to two to three AI companies every week about their new way of doing x y z, you're gonna burn all your time, and that company may not be around six months from now, or they may pivot, and then you're just like, what did I do all this for? So understand your problems really, really well because I guarantee you can solve eighty percent of them with tools that have existed forever. Right? It's not like the problems are new because the tools are new. The problems are always the same problems. The tools just may give you a five percent better way of solving it or save you ten percent of the time, but really be staunch in understanding your problems and what the right solution looks like. And the tools likely don't matter much at the end of the day. They all kinda do the same things.

Janis Zech: I mean, that's obviously right? Like, there's an exception here — obviously Weflow, the revenue side. Weflow is the only difference. But, like, I fully agree on the two of those and consolidating the space for sure. Absolutely. Yeah. Awesome. I mean, we unfortunately have a hard stop today, and I joined late. I honestly think Philipp was alluding to this earlier. Super, super valuable episode, and I think we could have gone a lot deeper also.

Soham Maniar: Yeah. Let's do a second one.

Janis Zech: Yeah. Let's do a second one. Let's do it. I really enjoyed it. I think it's such an important topic. And, yeah, thank you so much for joining and sharing this. But, you know, last question. Any book you would recommend or any blog or any industry report, anything people can learn from?

Soham Maniar: Yeah. I mean, I mentioned this at the top of the call. I'm not a huge book reader, so you can forgive me for that one. But in terms of blogs, like, there's a lot of great ones out there. I tend to focus my attention away from the tactical kind of, like, RevOps blogs. Although, Janis, I will give you a shout out. Your content is amazing, and I'm not just saying that because I'm on here. It's the reason that I reached out to you. I think anything in that sphere where people give real advice and talk about how to solve real problems is ultra helpful. That being said, RevOps is a stressful role, and something that I find really helpful — it's a blog called Ultra Successful by Dr. Julie Gur