Janis Zech: Hey, Udi. Hey, Philipp. How are you doing?

Philipp Stelzer: Yeah. I'm good. I'm good. How are you?

Janis Zech: Yeah. Pretty good. So what are we talking about with Udi today?

Philipp Stelzer: Yeah. Udi is the director of revenue operations at Lusha. And Lusha is a product led company, so that has some serious implications for how Udi and his team are tracking MQLs, PQLs, support different sales methodologies, create reports for leadership, and also how they do forecasting. And we dive into the specifics of all that. So it's a real operator episode, and we hope you enjoy listening to it.

Janis Zech: Udi, welcome.

Udi Cohen: Hey. What's up, guys?

Janis Zech: Yeah. Udi, could you maybe start with quickly introducing yourself, your background, how you ended up at Lusha? That would be great to hear.

Udi Cohen: Cool. So thank you for having me, first of all. Very excited. So I'm Udi. I'm working at Lusha as the director of revenue operations. I'm actually coming from a very technical background. I worked — Lusha is my fourth company. I worked in Yotpo and other companies here in Israel. And I worked as a Salesforce project manager, admin, you name it, but a very, very strong background, ten years of technical flows, Apex, everything I did there. And then in Lusha, I did the shift into revenue operations. In my last company, Yotpo, I was more in, like, trying to ask questions about the business needs and what the business — what I'm building for the business, and it became more interesting. And then I knew that in the new company, the new move will be a shift towards operations, and this is me. This is what I'm doing currently.

Janis Zech: And what is Lusha? I think some people probably have heard about it, but maybe you could summarize it in your own words.

Udi Cohen: Yeah. So Lusha is a sales intelligence platform. It can help salespeople, recruiters, or whoever is searching for B2B data to be able to prospect, to find relevant people. Lusha is very proud of the unique contacts they have and especially accurate phone numbers. It's a PLG company which users can start using for free. You have a few credits, and it's every month it's being renewed. So you can use it free and then decide if you want to have a bigger plan.

Janis Zech: Okay. Great. Yeah. And then also PLG. Right? That's sort of the topic that we have for this episode. And in our prep call, I remember distinctly, you described Lusha as a product led company, not as a company that has a product led go to market motion. I thought that was super interesting. And maybe you could just elaborate a little bit on that and why you think that differentiation is important.

Udi Cohen: I don't remember when I heard it, but someone said in some platform that it's very hard to be a company and start a product led growth motion because you already — like, it's changing the roots, changing the foundation of the company. So if you're starting as a PLG company, it means that it's not a motion. It's what you are. You're giving — you're building your product in a way that people can use it. People can get to a limit in a smart way after they are understanding the value of their product. If you look at Spotify, for example — Google is not using Spotify. You can use it, but then the ads are, like, nagging you and then you just say, okay, I will just buy — in Israel twenty dollars — I will just pay that, and that's it. I will listen to music, podcast, whatever. So this is the idea, and this is why I say PLG company because the whole foundation of your product is product led growth. And I think that this is very, like, implemented in me. So I mentioned it.

Janis Zech: Yeah. I can very much relate to that. I think if you look at the great product led companies, it is something that is steeped in the product. Right? How do you acquire users and then have an activation loop where they get value very quickly? And, you know, ideally, you have even virality. Right? Calendly is a great example. Right? You basically use it, you send it, you have virality. That's a fantastic motion. I think every SaaS entrepreneur always dreams of having that motion. But then one reality is also, like, what does it do to the RevOps motion. Right? Like — and maybe before we go into that, like, I'd love to hear a bit, like, what is your go to market approach at Lusha? Because I think it frames the discussion a bit, and then we can go really more into the deep dives of what does it mean for RevOps. Right?

Udi Cohen: So the go to market as a PLG company is to get as much revenue as possible, self-service. People, like, will use it, will see the value, will purchase. Zero CAC. That's it. No need for sales. No need for RevOps. No need for nothing. But, obviously, if you want to grow and if you want sustainable growth, you need enterprise. And we are working B2B and not B2C eventually. Users are people from companies. You can use Lusha with your Gmail or your Hotmail, for example. So our go to market is a sales led growth — let's say, like that — is use the PLG, what the product that was produced in terms of traffic, in terms of usage, aggregate it, and eventually sell enterprise deals for big companies. We have huge companies like Salesforce and HubSpot and Google that are using, and they have a plan, the enterprise plans. And this is my go to market and my mindset in RevOps, and this is what makes, I think, my role very interesting and with a lot of responsibilities because I have the power to do lead generation. Not a real lead generation from the street. It's from the store. Like, I'm fishing in the store, but there are a lot of people in the store. And you need to detect who is relevant and who is not. And beside the inbound that we are getting from the pricing page or the marketing forms, we also have the power to just use the users that we have — and think about it — talk to a person that already used your product is much different than, ah, did you hear about Lusha? I know that you heard about Lusha because you used it and used it pretty much because you meet our PQL criteria. So let's have a talk.

Janis Zech: Yeah. Yeah. So you mentioned PQL there. I know Lusha has, like, four plans. Right? Like, pro, premium, and enterprise or something like that. Like, you mentioned the credits in the beginning, that the free plan have a specific amount of credits. I think, you know, in our podcast, probably most people are familiar with that kind of model. The audience would be familiar. But what does it mean for kind of your PQL, MQL definition? Like, how do you define it? Do you even have MQLs or you just have PQLs? Do you have something like product qualified opportunities or company accounts? Right? Like, and what are the triggers — or the criteria you use to actually define those? I'm super curious how that's done.

Udi Cohen: Yeah. Good question, and the answer is wide, but I will try to give the mindset. MQL, of course — MQL for me, it's everything that we called inbound — is a person with intent, raises his hand, comes to us. This is MQL. Marketing brought it. Thank you, marketing. Go bring more. And when it comes to the PQL slash outbound, this is where it starts to get messy because it's about terminology. So you have the companies — for example, now you have Nike. Nike is not part of your database, but we all know that it's a good company. Let's say it's a perfect fit for Lusha, but they don't have users. Would it be harder to bring them to the table as opposed to another company? Let's say it's a five hundred employees company from the UK, which also have a good fit. So where will you spend your money or your effort? We found that it's much, much easier and works much better where it's already a company that you have in your database and that they're using, rather than just go and do a cold outbound. We tried cold outbound. We are always trying, but eventually we are coming back to the roots of, okay, we have people that know the product. Maybe we need to find additional logic, or maybe we should work with product on the plans or with the growth team on the plans that they're offering and the features that they're providing. Maybe we can set elegant limits where, okay, put this limit, and then I know that this person is a good fit for the new feature that we are promoting. Or we — for sure, if you use SFDC, which is part of the product, I know for sure that it's probably one of the operations team, and I know that they want to enrich their CRM. So this is a different use case. So to answer a short question with a short answer, we prefer to use the PLG and what the PLG produces and work with the logic on this population, as well as working with product and growth and R&D, which makes it even more interesting, of how we can together give the product that can support the PQL machine, the product qualified leads.

Janis Zech: I did mention what PQL is. So the way I would recap that, just for the audience, is you're trying cold outbound that isn't working as well as essentially fishing in the store of users you already have. Curious how you define kind of a free user. Is that an MQL, or is that already a PQL? When is an MQL a PQL? And do you — I mean, how do you do that? And I think it's hard. Right? And I assume it's evolving. It's not a constant. Like, you're learning constantly. But, like, when do you know that — and I know that there's also users that just basically swipe their credit card. Right? But you might know there's, like, ten users in a specific account that is really interesting, and you wanna actually really go out and work with them. So, like, how do you structure that free and then also the kind of self-onboarded paid customers?

Udi Cohen: So the MQL — I think what you might be referring to is the attribution for marketing of what we are producing eventually, because they can say — they can claim, hey, we brought these registrations. You use the simple logic. It's MQL. So my terminology — I'm not sure it's aligned with the industry terminology. It's Lusha terminology. Let's call it that way. MQL is everyone who raised their hand. That's it. It's easier to understand that. Everything else that we're running logic over the database, for me, it's PQL. And then we know — I don't care about the attribution too much because I care about bringing revenue and securing the revenue, of course. And for example, just to give you, like, a logic, a very simple one — and this one, we also use Lusha, like our own product. When we see a new registration coming into Salesforce, every registered user is getting into Salesforce as a contact under its account. It's being enriched by Lusha. So we know the company size, we know the country, we know all the company data, and we know about him. We know the telephone number, we know the role. So for example, if we see a manager, a VP of sales, head of operations, or like a manager title or relevant manager title, this is for me a PQL. Why? Because, as I said, it's not something — it's not someone who raises their hand, but they see that it's a person that, hey, why would a VP of sales or a director of sales register to Lusha? This is not their use case. It's for BDRs, for salespeople. They probably want to evaluate it. So let's go and check them. And by the way, this PQL came after we recruited the first director of sales in the US. And she said, I logged in, and I was very disappointed that no one reached out to me. So she said, hey, you know what? Maybe we have something here. And we have the obvious PQLs of people reaching limits. You have the free account. You used your x amount of credits. Boom. Let's call you. Let's see what it's all about. Of course, putting there some filters if it's a good company, if it's a good country, because it's different between the countries. And the good thing about it is — if we are talking about emails and deliverability and calling people — it's more of a white action. It's called, like, in the deliverability world, like, you have the gray actions and you have the white actions. It's a user. He accepted the terms and conditions, you can probably call him. And they might expect to get a call. If I'm using — now I download the tool and I'm using it — it makes sense for a person to try to sell it to me. I will get it. So this is two PQLs I gave you, and now we are working more on models with the BI team to get, like, more — take a lot of considerations, use AI to teach the system what's working and what's not. But eventually, what is always working, at least in my experience in Lusha, you need a compelling event. You need a reason. The BDR or the AE needs to understand what is the reason why I'm calling you and why I'm calling you right now. Okay, you just registered and you are a manager, so I can start the conversation. You reached the limit. Or it's a very psychological approach as I see it. And many times, I'm talking to the BDR teams, and I'm asking them, guys, like, what is the reaction of the person that you're talking to? Is this surprised, or is the conversation in a good environment? Like, it's a good conversation. It's not — they are mad, they are not. And it gives me, like, the things that you don't see in the numbers.

Janis Zech: Yeah. Nice. Yeah. I think that's great. Yeah. I think RevOps talking to the internal stakeholders, I think, is so important.

Udi Cohen: This is the best.

Janis Zech: Actually — and on that point, there was one thing I wanted to ask you also is, like — so you mentioned, right, like, all the users, the new users, the free users, end up in Salesforce. I'm assuming — do you take Salesforce sort of as your system of truth? And if so, right, like, how do you feed all the product data in? Like, do you have, like, specific events that are then, like, I don't know, pushed to some field in Salesforce, or is this handled in a separate system? How have you solved that at Lusha?

Udi Cohen: Great question because we are getting technical. And by the way, we, in my team, we kept the technicals. So we are doing both the operational stuff, but we are very, very, very strong in technical, like integrations and Salesforce. I never used partners. I like to know what we are doing and to be able to provide scalable solutions that can support the future. So this question is something that we are really around — how we get the data, which data we want to get. We don't want every single data point that we have. So my answer is, first of all, yes, we are getting all the users. It's being created as a record in Salesforce — accounts, contacts, the domains themselves. It's like a mimic of the database of Lusha. And also the important fields — the account status, how many credits they have, what the plans. So this kind of data points we are getting. We got too many fields. Like, we really reached the five hundred field limit in Salesforce, which is very hard, but it's because of that. And then we thought, what should we do? And we understood that we need to work more with the BI and not get all the fields, but get signs from BI or insights from BI for interesting logic. So this is the tactic that we are currently starting to do. So we have both. First of all, the important fields, because if a CSM is now working on an account or a BDR works on an account, we do want them to be able in one system to see the relevant data. But once it gets to all the features and when they use it, less time and what the exact amount of credits they consume in each product — it's just too much. And this is why we are using both Salesforce with the data that we have there, which is always easier and faster. But also a logic that from the BI team — we are using Vocato to do the integrations, works perfect.

Janis Zech: So, I mean, I think, obviously, you wanna make sure that the CSMs, SDRs, BDRs have the right information, as you mentioned, at the point of their workflow when they're actually executing, right, the calls or the emails or whatever the outreach is. Like, what signals have you seen work really well? Like, are there specific examples you could give?

Udi Cohen: So maybe a step before. For me, adoption is the most important part while you are implementing the system or a new process. So the mindset that we implemented in Lusha — each role should have one — like, as few objects as possible. So if you're an AE, you will work with opportunity. That's it. You will have reports of accounts, domain, whatever, but you work with opportunity. This is your tool, your main object. Yes. We have additional enablement systems which are used for other stuff, for example, call recording or forecasting or whatever. But if you're in Salesforce, you are now having a deal, you work with the opportunity. If you're a BDR, you work with a different object. It's not a lead. It's a custom object that knows how to work with leads and contacts, but this is what you're working with. So once you give them a path and you back it with a one-object or a button-click one-button process, it works good and the adoption is very high. And then we can also measure, and then I can answer your question.

Janis Zech: Yeah. I mean, maybe let me jump in there. I really love this. I mean, the reason we started Weflow is to simplify essentially workflows for AEs, CSMs, SEs initially, right, before we went into full pipeline management forecasting. And I think the reality is that most implementations of Salesforce struggle to have strong adoption. Right? I think we see this all the time. It is something that is, I think, also deeply ingrained in the actual experience for the end user. Right? Like, how do you create a simplified, focused, and efficient experience that really is focused on focusing the folks on the right things, because they have so much stuff to do. There's so much context switching, and the reality is that most people don't really do this. So I just wanna, you know, point this out here because I think — I love this point so much. And thanks for not answering my question and diving into this topic because, you know, it speaks to my heart.

Udi Cohen: No. But I'm really proud of how we implemented it because of the ease of use. You know, I mean — it's — you need to ask the BDRs and AEs at Lusha, but for me, the fact that they have this object — think about the reporting also. You don't need — like, you can build the dashboard from one object. You can do everything there and put all the filters because you don't need to have, like, multiple objects, and then you can't use filters. Never mind. This is too technical.

Janis Zech: No. No. It's fine. It's fine. I think the audience appreciates it. We can't go technically enough. So yeah.

Udi Cohen: I can talk about it for hours. But yesterday, the CEO just texted me, Udi, this dashboard is amazing. And to hear that from the CEO, for a dashboard in Salesforce, it means that the system works good. Why? Because we built it in a way that most of the data are being collected from the processes. It's not like a manual thing for the people to do. It's happening automatically. And we have a great dashboard. They are very, very important on our dashboards and they are being used by all the C-levels. And this is because of what we just spoke — like, ease of processes, ease of use, and not trusting people.

Janis Zech: Trust the process.

Udi Cohen: Trust the process. Yeah. Make mandatory fields.

Janis Zech: Yeah. Actually, let me jump on that one because — and that would have been my next question. Because if you have a product led company and you have this whole motion with the free users and so on, do you even work with, like, classical sales methodologies, like, I don't know, like, SDR, BDR working well with BANT, AEs working more with MEDDIC, for example, just to stick with popular approaches? Or are you actually not looking so much at the stages, but really you more look at, I don't know, like, retention data or, like, product led metrics?

Udi Cohen: This is a very, very good question. I know that I'm saying it about every question, but — so in Lusha, we really evolved, like, from being PLG when I just started, and the sales used to sell, like, a thirty-nine dollar monthly plan as a conversion where the PLG couldn't convert. Then we did, like, a huge change where we started to do, like, more SLG, which I — as I expand with the PLG and then turn it into enterprise sales. And then we just, like, wanted to go upmarket, to do, like, more structured playbooks and sales methodology. So right now, we are using MEDDPICC for the mid market, and we are trying. We're really trying — the stages will not be, like, things that you must go through because this is how we set it up. It needs to make sense. If you are now doing a business discovery, then what we are expecting you to fill while you're doing the business discovery — we want to make sure that you are doing a value setting and you are not just showing features. So this is the MEDDIC stuff that we're capturing with the persona, what is the use case, and stuff like that. And so this is how we're using the stages. Because in each stage, you must enter something that relates to the methodology. And of course, if you are sending that contract or if we can do stuff automatically, we will do it. And the stage will eventually reflect exactly where the deal is currently at. You can use it for forecasting, and we have a very, very strong forecast for land. Usually, we have, like, sixty days — or the thirty days is very accurate, and sixty days is also pretty good.

Janis Zech: Yeah. Yeah. Actually, okay. Great. You're kinda like answering my questions. But for example, just to — for the SMB, it was too much. So it's more of a straightforward kind of sale. Like, more like — sales cycle is much shorter, so they just asked to remove the methodology. So it needs to make sense. But once you do, like, sixty, seventy — at least for us, sixty, ninety day sales cycle — then you need more structure. You need, like, to really sell it properly.

Udi Cohen: Yeah. I mean, that makes total sense. Right? You have, like — the bigger the deal, like, the bigger the company, the more stakeholders, the more you need to multithread.

Janis Zech: And expectation in.

Udi Cohen: Expectation of the customer. If you are a big customer, you expect to do a certain process and not like someone selling you credits via the phone.

Janis Zech: Yeah. Yeah. Yeah. For sure. Yeah. Yeah. Of course. Yeah. People are used to, like, a specific process, and they want to have that process. Yeah. But you mentioned forecasting, and this actually is something I also thought is — you know, like, I think if you have a very strong product-led motion, you can always assume — okay, you kinda, like, have this huge amount of historic data that can convert a certain amount of people who come in, and that, of course, makes your forecast probably a lot more accurate than if you're, like, a company that is relying on a few big enterprise deals each quarter. So yeah. I mean, kinda went into that direction already, but, yeah, curious how forecasting works at Lusha at the moment, and if you could elaborate a bit on that.

Udi Cohen: Yeah. Definitely. So as you said, we have a long tail of data history, which helps us to understand, like, pacing wise, if we are getting what we need to feed the funnel. It starts from registration. It comes down to the inbounds, the MQLs that we are getting, and also the PQLs. So number wise, we have the formula, and the formula has to work. And usually, with big numbers, it's working. If your conversion rate is twenty percent, then it might be nineteen or twenty-one, or in a big month or good month, it will be twenty-five — I'm just throwing numbers, but something like that. It's very, very predictable. So you rely on the volume and say, okay, if I will get this volume and the mix will stay the same — it usually stays the same in terms of company size and the countries that we are getting it — then you can predict how many, for example, meetings and demos you will have. So this is the funnel. But when we are talking about revenue, eventually you have opportunities. You have the AEs themselves that know where it stands and what exactly they expect. So of course, we can read what they are putting in the opportunity. But we also — we use Clari for forecasting. They also need, once a week, to put what they project to finish the month with. That is not really — it's related, but they're like — it's a free text for them. Okay, I have this pipeline and the coverage of the pipeline. I have a target of one hundred, for example, and I have a four hundred pipeline. My pipeline coverage is four x. So they can project and put the numbers that they think, and this is where we are becoming really, really accurate — where a person puts his insights rather than just reading it from the data, which a lot of the time is correlated.

Janis Zech: Yeah. I really love this. I mean, you know, I think the first motion you explained is very much an SMB motion. Right? Like, high velocity, high volume, almost like consumer forecasting, which is more focused on conversion rates. And I think the second motion is the typical bottom-up forecasting motion. Right? I mean, we are, you know, we are in the same space as Clari and the other folks, so that's something which was obviously also very interesting. I think bringing that together is something that is very interesting, right, because you wanna capture the whole picture and not just the SMB. And it sounds like you have even over the years structured SMB, mid market, and then enterprise. So obviously, all these have different sales cycle lengths, ASPs, and also forecasting motions in that sense, which is really great to hear. We are a big believer that, you know, like, every AE should have their own number and have their own accountability and really drive the forecast submission. And then you have the overrides and the rollups and the adjustments. Right? And the bigger the deals, the more you do that on a deal by deal basis. But, yeah, I think that all essentially gives you more data points, right, to combine your maybe weighted forecast with the forecast submissions, right, and machine learning algorithm that actually runs a prediction and then gives you — right? Like, because I think it's really about combining different aspects to then run, like, a more accurate revenue machine.

Udi Cohen: And usually, it's aligned, and this is where it's like, okay, I can trust the data. Nice. And by the way, we are talking here about RevOps, and this is my world — like, my team's work — to tell the story behind the numbers. Numbers, everyone can see. Eventually, you need to — we do have the ability to create good reports and insightful reports, but the most interesting part is to know the story behind the numbers. Why did this conversion rate drop this month? I know why it dropped. To tell the story. And I think this is the main value, beside all the building of processes. This is the main value that we have as the people that see everything and don't have — like, you know, I don't have motivation — I'm not getting more money if the company is successful or not. I'm not commission-based, me specifically. So I always say the truth because I have no other option because —

Janis Zech: You have no interest. Right? You're unbiased.

Udi Cohen: Have any interest. Yeah.

Janis Zech: This is one. I mean — and I think it's, like, unbiased. I think, you know, it's a big theme. But what I really love about this story you just told us the last thirty minutes is — you pretty much described, like, making sure that you actually have the data capture capabilities, bring that into the workflows, and then actually use that for both forecasting, but also understanding why things drop off in the revenue funnel. Right? Why is stuff leaking? And I think that's exactly it — it's like from a very, you know, nitty gritty technical infrastructure layer down to providing really, like, deep insights and understanding the business end to end and the go to market motions and where there are opportunities to improve or where there are risks. Right? And I think that's essentially what, like, great RevOps looks like. So, yeah, I really appreciate you sharing this.

Udi Cohen: And it makes you more proactive than reactive because you understand. You're steps ahead, and I think this is also part of where you become more impactful — where you come into the business and say, I see this trend. Like, this looks not very promising, or this looks really good. Let's double click. And they are very appreciative, and you become a partner. And this is eventually how you can really affect revenue. Satisfying.

Janis Zech: Yeah. That's great. And that's also a big discussion. Right? How to make RevOps less reactive, more proactive. And I think the framework that you outlined there, I think, is a great angle and perspective on that. Udi, thanks so much for joining. I think it's been an extremely insightful episode. We always ask this one closing question. You know, looking back at your career, what advice would you give your younger self or someone who's just starting out in their career?

Udi Cohen: Yeah. So another good question. I thought about it a lot, and it's hard to tell it in one sentence. But eventually, I'm coming from a very, very technical world or background where I used to get the request and just deliver. I would, like, do the best scalable solution, but it was — I gave a technical solution. I didn't understand the business. I didn't ask about, okay, but why are you doing it? What is the impact on the business? And once I started to ask, what is the impact on the business? — this is where I started to understand and be interested in the business, and this is where I started to be more proactive and not reactive. And I think it's related to the last part. So my advice is — once you get a request, start thinking about the business and the business impact, the business needs and the business impacts, and not how I solve it with the systems.

Janis Zech: Great. Fantastic. Yeah. Thank you so much, Udi.

Udi Cohen: Thank you for having me.

Janis Zech: Yeah. Again, great episode. Loved it. Thank you so much for sharing this.

Udi Cohen: Thank you. Thank you. Bye bye.