Dr. Jeremy Weisz: 14:06
They need the whole automation piece.
Yoni Tserruya: 14:08
Yeah, they need everything. And that’s why we have the solution for sellers. And like we have the full suite and including the best data inside of it. But I think what’s really interesting recently in our industry is the trends that we are seeing that the, the, the sales industry is really shifting right now from a world that the sellers are doing a lot of manual work themselves. They’re choosing, you know, who to engage the campaigns and everything into a world that there is more and more automation.
The revenue operations takes all the data, doing all the enrichments, build the pipelines, even do the first outreach so that salespeople can focus just on selling, like reducing the manual work from salespeople and taking all the manual work to a back office automation work. And that trend is becoming more and more dominant in the market. That’s why we are investing a lot more in integrations, API and connectivity because we see that as the future trend.
Dr. Jeremy Weisz: 15:19
So let me see if I have this correct. Let’s say I’m a salesperson. Let’s say I use, you know, Pipedrive, right? I can go into Lusha, I can search. Okay, here’s my ideal customer of what I’m looking for. I get a bunch of, you know, whatever a thousand, 2000, 3000, 5000 names. I pipe them, I put them into Pipedrive. And then there’s an engage which automates personalized emails. Can I set up a campaign then of, okay, this is who I’m talking to here. And then how does they engage work. Do I pre I pre. Right. Let’s say follow up messages like once a week for like five weeks or something. I could put that person into that personalized email. Is that coming from. Does that get sent through Pipedrive or through Lusha. How does that work from the engage piece.
Yoni Tserruya: 16:07
So the engage is is through Lusha. I mean, we’re connecting to your email provider, and then we send the email and the you define the campaign in our platform. And, you know, once it’s replied, once you want to open it as an opportunity, you can push it to your CRM. That’s that’s this approach. I can say that this is like this is the current approach. When sellers are doing that, we see more and more use cases today that revenue operations teams want to take all the engagement to their hands and doing the campaigns from the Rev ops office.
Not so that the cells won’t do it themselves. And then the rev ops can take into account way more data. Data from the CRM, data from intelligence platform and just send better, better personalized messages. One of the things we allow today in Lusha, for example, you can take recent posts from social media or recent news and then their outreach or the email that you’re sending is really personalized. And it’s, you know, it has a much, much more warm approach for the prospect.
Dr. Jeremy Weisz: 17:22
Yeah. So basically, it’s not just, okay, you could write a personal sequence, an automated sequence, but it will pull in personalized things from that person’s social media. So each person is going to get a different message. Yeah.
Dr. Jeremy Weisz: 17:36
Yeah.
Dr. Jeremy Weisz: 17:36
Which is basically also Google anyone who sends cold email. I reached out to a couple people who sent a lot of cold email, and I was asking them, what should I ask Yoni? And they gave me some questions, but that’s really key. Just from a cold email perspective. If people are sending cold email, one of the ways people get slapped with cold email, if it’s the same message to everyone they Google knows. And so that actually really helps with deliverability and not getting, getting, putting the spam. Which if someone’s saying cold email gets one spam complaint, that could ruin that domain.
Yoni Tserruya: 18:15
Yeah. So first of all, I agree, I think, but there are few stages. Let’s call it that. The first stage is sending the same message to everyone that doesn’t work anymore. Like the customer. Identify that very quickly. Gmail can see it’s spam. That doesn’t work. So there is a second stage. When you send personalized email, like you take the recent post, you take recent news and you make a personalized approach. Dr. Jeremy Weisz. But that’s also, I think more and more customers feel that it’s generated automatically and it’s not that personal. So it works. It works today, but I’m not sure for a long time. I think the real breakthrough comes when there is a real relevance and intent and reason why you’re approaching.
And for that, I think you need a lot of intelligence that takes into account a lot of signals that increase the probability that now is the right time to reach out to this, this account. Like if you’re just reaching out randomly across the year, then you’re probably going to get ignored. But if you have, you know, reasons, for example, a C-level, just a change in that department or the integrated a new technology that complements to your technology, or they had the recent news that relevant to your service like you need better signal that makes this timing better time to connect. And I think the volume decreased, but the relevancy or the timing is way more accurate. That’s like the best approach today and less about volume, more about relevancy, and it’s more about data just aggregating a lot of data inside.
Dr. Jeremy Weisz: 20:07
Yeah. And so I’m looking at you know, we’re in the connections with integrations was key. The automations there’s a bunch of different things here which is we talked about engage and there’s conversations records and analyses and automated prospecting and you know, building enrich and engage automatically. But what he’s talking about is really the signal and alert.
So which kind of crosses into the automations piece. And this is really interesting I think signals and alerts. Can you talk about like a use case? I don’t know, maybe there’s a use case for Lusha specifically, but I know if someone changes position. Right. Like there’s a new CMO. They’re going to be looking at different solutions. So there’s different signals and alerts. Talk about how people are using the signals and alerts.
Yoni Tserruya: 20:51
So I can give you an example of how we work. There are a few signals in alerts that increase the probability that the company can use Lusha. We’re using department headcount growth. So if we see a sales department that is growing like month over month this the headcount is growing. It’s a good indication that this company is, you know, growing their sales department. They need sales intelligence. And they have a good momentum. So that’s one thing that really serves us.
Another thing can be that just the traffic for the organization is growing. Like we know there is a sales organization, but the traffic for that organization is growing. Another indication can be, you know, they have a lot. They have a pretty big book of business, a pretty big revenue. Then we can understand that, okay. If they have a lot of customers, they also need signals and alerts. So we just try to understand whether this company has a sales organization. It’s growing. And then we can be complimentary service for their needs.
Dr. Jeremy Weisz: 22:03
Yeah I mean I think this is instructive for any company. I know a bunch of companies I’ve talked to. I don’t know if they would know what the signal is. Yeah, right. I’m curious what else have been good signals and alerts for other companies that use you like you mentioned for you obviously increased sales team increase in traffic. I’m curious about some other signals from other companies. And they’re like, this kind of falls into our sweet spot.
Yoni Tserruya: 22:32
I think, you know, the basics are job change alerts. Like someone, some executive changed the role. I think headcount growth is like it’s a big one as well. I think intent in general, if we got an indication that a specific company is searching for your industry or solution in your industry, that can also be an intent. And I think this this signals and alerts is growing.
Dr. Jeremy Weisz: 23:02
We’re about based on the searches from staff of that company. Like when you say they’re looking for the solution, is it pulling in data of what staff are looking for on a certain platform?
Yoni Tserruya: 23:14
Yeah. It’s not that we are aggregating this data, but we are getting that like there are providers that give that. It’s an indication that the company has an interest in specific industry. But I think I think the world of signals and alerts is growing a lot. We’re about to have like 20 different signals in the platform this quarter. And for me, if you ask me, that’s the future of Intelligence, because the more signals you have, then you get the beautiful. The beautiful thing about signals is that they have a time.
It’s time sensitive. And so that’s relevancy. And if you have enough signals, then you can start combining signals like for example, if you both have job change and you have growth together in the same department, that’s increasing the scoring way higher. And this like scoring mechanism based on signals, I think that’s going to be the future pipeline generation. It’s not even future. I think it’s already happened in the present. But you know, more and more companies are about to go to that direction because the spray and pray approach or the random approach is just not effective, not for you as a seller, and it’s not good for your customer to get those messages.
Dr. Jeremy Weisz: 24:35
Is that Yoni something Proprietary like those 20 signals or do you share like here are the here are the signals that we’re looking at.
Yoni Tserruya: 24:45
Some of them are pretty unique. But I think what’s really proprietary for Lusha is the ability to combine several signals and to create like a combined score. We have a pretty.
Dr. Jeremy Weisz: 24:59
I think I’ve seen. It’s like when I’ve looked at it, when someone’s inside the platform, there’s like a score that’s like 71 or high, right?
Yoni Tserruya: 25:07
Yeah. And yeah, we have a pretty, pretty advanced technology of recommendations. So we took into account a lot of data points. Some of them are not signals, but signals are big part of it. And then we learn the customer. And the more you use the platform the better the scoring becomes. And then that’s where AI really takes a lot of your headache from your data.
Dr. Jeremy Weisz: 25:36
I mean, another one would be funding announcements I imagine is probably a popular one.
Yoni Tserruya: 25:42
Yeah. Funding. Yeah, funding is great. Like opening a new site revenue. Revenue reach to you know, certain threshold. Those are kind of things that can work as well. Technology acquired like a new technology, you know, started to be used in a specific company.
Dr. Jeremy Weisz: 26:05
So you can see here, I mean, just poke around. Lusha, it’s really interesting. We’re looking at that’s related to discovery, which is more the Chrome extension buyer intent signal alerts. And then, you know, there’s lead streaming, the AI recommendations and prospect playlists and then the automations piece and then the connected systems piece. But I do want to talk about, you know, from the beginning what growing 15,000 customers in four years bootstrapped. What were some of the things that you were able to do to grow that quickly?
Yoni Tserruya: 26:42
I think the two main reasons were that we succeeded at the beginning was that we invested a lot in the data quality, like the data was good and people are very sensitive for that. They will pay you, but if data is not good, they will leave very quickly. And it’s like you waste their time if it’s not good. So the data was good and and the simplicity of the, the platform, like our plg and the freemium approach was pretty unique back then. So it really opened the market for us because the plg.
Dr. Jeremy Weisz: 27:19
It spread pretty quickly so people would go, this was great. You could try it out, go do it, and they don’t have to talk to anyone.
Yoni Tserruya: 27:26
Yeah, yeah. So that was like back then was pretty unique for salespeople. And you could do things pretty simply. Today we are building the same thing like we still plg. Still great data, but we are doing it for revops and for builders like people that basically used to have complex systems. We do it in a very simple way that they can take a lot of signals, combine them and build this scoring that we just spoke about in the platform and get like very clear, prioritized lists for their needs. And I think today, if they’re not doing it through our platform, they need to invest a lot of energy and combining a lot of external data sources. And if you’re losing using Lusha, you do it in a simple way in one platform that all your intelligence from multiple sources get connected. And it really helps for operational people that, you know, build the pipeline.Yoni Tserruya
Dr. Jeremy Weisz: 28:24
You know, at what point do you decide, okay, we need to put fuel on this. We need to raise money because you’re going to cut bootstrapping like we’re going to keep 100% of this company. We’re not going to like share it. But at what point do you go, okay, we need to we need to raise money because that’s another job in itself.
Yoni Tserruya: 28:41
You’re right. Well, I think at a certain point we understand that the opportunity is big and we want to we want to go all in and we want to fulfill, you know, bigger vision. And at a certain point, we understand that it’s going to be harder to do it without raising money. And because, you know, your competition is doing so. So it took us a while to do it. And I can say that at the point that we did that, we were it was one year after we understood we need to do it.
Like it took us a lot of time to get to the point that we were actually doing that. We were pretty much ready. But we understood that like it’s two different paths. If you’re raising or not, I think today maybe it’s a different story. Like if I would, you know, build Lusha today. I’m not sure that money is such a blocker. I think today you can do many more things without raising capital. But I think still, at a certain point, most of them, most of the companies are raising.
Dr. Jeremy Weisz: 29:53
So what was it like raising money? What were some of the challenges?
Yoni Tserruya: 30:01
You know, the main challenge for me, because just what you just mentioned, I mean, you can continue and run your business on your own and you can now bring in a partner and there is no way back. It’s one door choice can go, you know, you can you can, can, can reverse. So for me, the most important thing was to pick, you know, great partners, great people. Find the ones that I can I feel I can, can really get along with. And they also understand our industry pretty good. So we spent a lot of time finding the right people. And and I think we did I think.
Dr. Jeremy Weisz: 30:41
You have relationships or did you go out and reach out cold to some of these people?
Yoni Tserruya: 30:49
We I mean, we had a lot of meetings and, and, you know, the one that we really wanted to, to partner with was when we met them face to face. We went for dinners like, we did all this like we spent time. Spend time together. I think it was. It is important.
Dr. Jeremy Weisz: 31:03
Yeah. I do want to talk about, you know, we talk about product led growth, right. And I want to bring up just the again we’re looking at this, this this point in time when we’re looking at the pricing page. But why did you decide on the Free, Pro, Premium. Like as far as okay, here are the features that we’re going to include for free.
Here’s the features that we’re going to include in the Pro because I’m sure a lot of time and thought went into this particular, you know, it costs real money, even the 40 credits per month, like even right where we’re looking at with the free version costs you money. So talk about the what’s included in the free, why that’s free. And then what you decided why you decided these features in the pro version.
Yoni Tserruya: 31:54
In general. I think, you know, the free is like it’s mainly for individual seller that starts to use the platform in a very in a small scale that you can taste the data, you can see if it works, can, you know, touch the features, and if it works, you know, or need a bit scale or advanced features, then they need to to buy and purchase. I believe that, you know, I believe that anything that you can give for free at the beginning is good approach in SaaS and like And users want to try before thereby. And if you allow it to them, then the ones that buy can stay longer. And that’s the general approach that we have in mind. And I think it stays up until today.
Dr. Jeremy Weisz: 32:48
Yeah I’m just curious. So like if you’re looking at the some of these obviously you know, the pro if you want more seats you need to get pro right. If you want more credits you want to get pro. But there’s still a lot included in the in the free but also in the Pro version. There’s definitely a different technology and intent alerts which you’re not going to get in the free version. You know, and so on. I’m curious, you know, why 40 credits. Why not 100? Why not 500? Why not ten? Like why? Why 40? It seems kind of random.
Yoni Tserruya: 33:27
There is an industry standard for pricing. Like we have competitions. So we’re pretty much, you know, see what the bench. But I can say that in general we are more and more become usage based, oriented, that the volume you are consuming. That’s the number one criteria. And every feature that you use can consume credits. So you basically buy credits. And by using the platform it consume from that credit balance. I believe that that’s where the industry, that’s where technology is going into usage. And even, you know, more than that. So that’s the current approach.
Dr. Jeremy Weisz: 34:08
Yeah. Building the company. Right. So you start off you have a co-founder, I believe he was buying data from you for some for something right.
Yoni Tserruya: 34:22
At the beginning. I mean, he wanted but then, you know, then we partnered.
Dr. Jeremy Weisz: 34:25
Yeah. Talk about the team, the evolution of the team.
Yoni Tserruya: 34:30
Wow. That’s big. You know, I think at the beginning, I have an interesting journey here to talk about. At the beginning, you know, the company is have very few people. Everyone. Everyone are builders. Everyone knows how to do hands on work, and even everyone are multidisciplinary. Like they can do several things. For example, the marketeer can both build campaigns and build the messaging and build the website. They can do a lot of stuff and also me. If I think about my job, like every three months, I basically switch my role or did something different from from developer to, to team leader to to product to designer to analyst to whatever it is. Because we were bootstrapped. You don’t hire those people like, you know, before. You need the need. You have the need you start building.
And only when it scale, you hire the person. It’s pretty much the opposite way around. And then I think, you know, we grew the company and we only brought people when there was a clear need. And, you know, if we if you if we didn’t generate revenue, we couldn’t hire people. So it was very I call it the law of physics works when you when you know you don’t have capital raise you just income, you know, income and expenses. And that’s what you that’s what you work on. And then we raised money and I think it’s changed a bit because you want to grow faster. You want to accelerate stuff and you are hiring or you are expanding. You have higher expenses than than revenues. And that’s where I think, actually, things didn’t work very efficient as they were in the beginning.
We scaled, but it created a lot of, you know, noise as well in the company of how many things you can do simultaneously, because the truth is that you cannot do a lot of things simultaneously pretty well, but that I only understand that after a while. And now I think what happened, you know, today the world is, is, has changed because now companies that have less resources, more revenue are the ones that everyone are looking at. And AI allows you to do much more with less resources. So in a way, now we’re kind of doing the backward approach. We are not trying to increase headcount, but we are trying to have better outcome with less resources. And it’s kind of going back to the basics for me, in a way. That’s why I think, you know, bootstrapping today is, is more closer to the real reality than it was in the past, I think.
Dr. Jeremy Weisz: 37:16
So has that changed the hires that you’ve made? And how?
Yoni Tserruya: 37:21
I think in general you need more again, hands on people that knows how to build stuff. We are in a we now need to build a lot of stuff, and we need to also run a lot of AI and agents for us. So you need builders, people. You don’t. You don’t need.The ones that you know are big managers, tells everyone what to do. But very far from the execution, you need the builders, you know, the ones that can do things on their own and get to the details when it’s necessary. And, and I think we are in an era that you need, you know, very strong ICS that can do a lot of stuff or can, you know, run a lot of automation beneath them, rather than big managers that can manage a lot of people. I think the equation between how many people I manage or how many people there is in the company versus am I successful is broken.
It’s like it’s changing. So today you want to have less people but more outcome. And it basically means you want a single individual contributor that can do a lot of stuff and less managers in the company. And I think it’s really hard for people to understand that, you know, there are still a lot of people that believe that the amount of people I manage means I’m successful. But if I ask me as who I’m looking for to hire in the company, I’m looking for the ones that are very strong IQs, not necessarily look to manage or to grow very fast in the managerial path. They really want to be professional, you know, understand technology, how they can, you know, build stuff, automate stuff like how they can have higher impact. But know without managing people. So I think it’s really changed. I think it’s changing pretty fast.
Dr. Jeremy Weisz: 39:20
I want to talk about a couple of use cases. Obviously this is a BDR And account executive use case. And there’s a rev ops use case starting with the account executive maybe talk about elastic. How do they use Lusha?
Yoni Tserruya: 39:37
Yeah. So I think that’s the main use case. Most of our customers are using that use case you know. So if you are BDR you typically have, you know, a region or a specific named account that you try to sell to. And then you need to get, you know, what the main and the best contact people in the company that I need to connect with and then try to connect them and, you know, take this lead and turn it into an opportunity, like something that it’s really in, in a sales process. That’s the BDR work. And they consume a lot of data and they mainly try to generate opportunities for salespeople, the salespeople, they account executives themselves. They might have an existing opportunity, but they also they also need to use an intelligence platform because they are not necessarily work. Just talk to the right person.
They might need to bring additional people to the loop, and they need to access to connect them as well. Or they just need to get additional information about the company, about, you know, revenue technologies, signals what happened in this company. How do I penetrate? So they need more intelligence, which is not necessarily contact details. So that’s let’s say in general the use cases of sellers both bdrs and and account executive, they need they need to nail a deal and they need intelligence to to close it. I think the revops is different story. They’re not they don’t talk to customers directly. They build pipelines and they work on, you know, they work on the CRM, on integrating data sources, on cleaning up data and make the data accurate, validate and something that people can trust them. So they’re basically building workflows of data enrichment, scoring mechanisms, sorting.
And they want to build a pipeline that their salespeople can work on after they did all the, you know, data optimization behind the scenes. So they need data at scale. They use it through API, they use it through workflows and automations, and and they build the scoring and the and the sorting mechanism on their side. But the same need exists for both of them. They need accurate data. If it’s not accurate, we’re wasting their time. And the number one thing that today slows sales organization is, you know, when the data is just inaccurate, data decaying is something that you cannot trust on. So it’s the same intelligence and different way to consume it with, you know, more automation and AI around DevOps use cases.
Dr. Jeremy Weisz: 42:26
And so, you know, I’m curious from a technology resources, you know, perspective, you know, I’m wondering what are some of your favorites, you know, from your tech stack. And obviously Lusha is part of your tech stack. What else do you use internally?
Yoni Tserruya: 42:44
So we use like extensively. Now we’re using N8N if you’re familiar with them.
Dr. Jeremy Weisz: 42:50
Sure. It’s like Make or Zapier. Yeah.
Yoni Tserruya: 42:53
We’re building workflows. Like we basically try to identify a task that currently people are doing it manually. And we ask, can we automate that? And if we can automate that, a lot of times we just use Natan to automate that, using our data behind the scene and using the data we have in the systems. Try to automate this stuff.
Dr. Jeremy Weisz: 43:16
What’s an example that maybe you were you maybe didn’t think it was able to be automated or someone was like, you know, I don’t think that can be automated, that you actually automate it.
Yoni Tserruya: 43:28
So we did a few things in sales process. First, we did lead qualification. We got a lead and then we just take this lead. We do a lot of enrichment behind the scene to qualify if it’s qualified, lead or not, and only if it’s qualified then we might we we forward it to a human and and that didn’t happen before. Before that we we had to use, you know, SDRs to qualify that. Another thing that we are doing today, which is pretty nice, we are we take all the conversation intelligence of our sales reps. We just downloaded all of it. And then we took like the top six sellers of of all the companies in all the company. And then we told the AI, take all those conversations of these six people, this is how you sell it passed, and now we basically have an AI culture that know how to sell Lusha.
You know how to teach it, how to handle objections and answer pricing questions. And so now we’re using it for two purposes. One, when there is a new rep joining the company, he can just chat with this culture and ask questions. And also after every conversation that happens in the system, we took the transcript. We send it to the culture, and the culture gives you feedback on what can you do better next time. And then we just automate that and send it to the rep. So basically we have enabling sales enablement enablement culture automatically for every conversation. And all of those things. You know we couldn’t do it like two years ago without technology of today. So that those two examples.
Dr. Jeremy Weisz: 45:16
But part of that is because they’re using Lusha conversations though, right? So it’s being recorded and analyzed inside of Lusha. So it’s not like you have to set up a separate system. It’s all inside Lusha. Is that right?
Yoni Tserruya: 45:29
Yeah, exactly.
Dr. Jeremy Weisz: 45:30
And is that also powering? Because if you go to Lusha.com, there’s actually you can say, hey, are you struggling to scale your outbound efforts? And there’s a question you could talk to. Lucy answers the AI power. Does that get fed into there? So that I mean, eventually I could just ask the questions. And that’s your sales rep. Does that get fed into the the the chatbot inside of Lusha to.
Yoni Tserruya: 45:57
You’re talking about the conversation intelligence.
Dr. Jeremy Weisz: 45:59
Yeah. Yeah. Like if I look at Lusha right here right I can I can talk to Lucy. Answers AI powered right here. Right. And can I ask those same questions? And basically it functions as a sales person or one of your top salespeople.
Yoni Tserruya: 46:19
Yeah. So that’s that. This is intercom and that’s also AI that gives you support. And yeah part of it we trained it to answer support tickets. And we also trained it to to answer simple sales needs. So if you need like you have certain sales questions this you know AI can answer you and give you the answer without even talk to to a sales rep for sure.
Dr. Jeremy Weisz: 46:43
Yeah. How to use lush’s intense solutions. So yeah. But it’s really interesting. All this is integrated into to Lusha. You know, Yoni, first of all thanks for sharing the journey. It’s pretty remarkable what you’ve accomplished. My last question is more just on your favorite resources. It could be favorite books. It could be favorite technology apps, software. What are some of your favorite resources that that you know could be app on your phone that you use regularly?
Yoni Tserruya: 47:16
Actually today, I mean, it’s not anything special. I mean, I read a lot of books, but to me, what happened today is, you know, in the past, I used to learn from companies that are bigger than Lusha, and they’re like few years ahead of Lusha. But today, I learned from companies that are newer and younger, and they, you know, they born for the AI age. I learned from AI first companies and and so I don’t know their names. And the way I discovered this content is basically based on LinkedIn and X.
I’m just, you know, I’m consuming a lot of content from companies or from entrepreneurs that are just building their first companies because they think the way they think about building that is AI first approach, and that’s the main thing I consume. And besides that, I’m just having tons of conversations with Gemini or ChatGPT about everything that crossed my mind, and I just learned from them a lot. that any any almost any, you know, anything that I don’t know. I first start by learning there and then and I become more knowledgeable. And, you know, the more the time advanced. I’m just using it more and more and more. It’s, I guess, like it’s not new, but it just it’s the way I’m consuming today.
Dr. Jeremy Weisz: 48:41
Yeah. Some of those AI tools like Gemini ChatGPT and you’re kind of integrating N8N to create some solutions for yourself. You know, first of all, thank you everyone. Check out Lusha.com to learn more. And we’ll see you next time. Yoni thanks so much.
Yoni Tserruya: 48:56
Thank you very much.
