In the Room with Shira Simmonds

Welcome to In the Room CEO Decisions. This podcast is built around one idea: the decisions that shape companies rarely happen in public. They happen in rooms where the trade-offs are real and assumptions are tested. Each episode focuses on one decision that materially changes a company's trajectory. My guest today is Shira Simmons, CEO of SmartReach AI, a platform that helps sales teams to identify prospects, enrich them with intent signals, and personalize outreach at scale. But the decisions we're focusing on today actually happened earlier. Shira originally ran a lead generation agency delivering outbound campaigns for clients. The business worked. It generated revenue, clients, and data. The question she eventually faced was a familiar one for many operators. When do you keep selling the service and when do you stop and build the software instead? Turning an agency insight into a SaaS product sounds logical on paper, but in reality, it means shifting capital, attention, and risk away from a business that already works. So today we're going to unpack that decision. What the agency actually looked like behind the scenes, the operational friction that kept repeating across campaigns, the moment when building the product stopped being an idea and became a strategic bet. Shira, let's start with the agency.

Great. Thanks, Raphael. So nice to be here. I'm excited to share all these insights with you.

Thank you. It's great to have you on here as well. So the first thing I wanted to really ask is what did the agency originally look like? So what was, how did it work? What were the dynamics from a client perspective, revenue perspective? So how did it work for you?

Yeah, I mean, we, it's funny because I started off very small. This is my second company and I was like this, this time around, I'm going to keep it much smaller, but obviously, you know, man talks and God laughs. And I ended up growing the agency to over 100 people that I had across the globe. We had, you know, over 150 clients at one point. I think we were close to about $3 million in revenue. And our primary focus was booking calls on using email primarily. That was our main communication tool. And we were doing very, very, very well. We were leveraging a lot of outside tools, right? And so I was constantly having to keep on top of the different tool stacks, the different tools that were, you know, evolving and emerging in our space. This was definitely pre-AI, right? But in terms of building the database and in terms of doing the personalization, and I would say a big part of my team was also doing it very manual. So we would have what's called a whole manual list building team, which was insane now that I think about it, where we had like 20, 30 people that were actually going to every single website of every lead and prospect that they were, that we were building and checking to make sure that they met the criteria. And then we had another team that was also manually personalizing all of the emails. So they were looking for things on their LinkedIn and on their website and Googling them to personalize the emails manually. And so kind of that's where we were at as an agency. And what happened was in the industry is that AI kind of came Came out, first of all. But but before that, even before that, the the outreach industry really plummeted, I would say, and took a turn where a lot of the companies that were doing outreach started failing, primarily because Gmail changed their spam filters, and a lot of the mails that we were sending ended up going to spam. Not just us; I mean, every agency was dealing with it. It was an industry-wide issue, and. Google made it much harder for us to do our work where we used to book, you know, 10, 15 calls a week for clients. We were struggling to book 2 to 3. So there was a big shift in the industry that made me take a pause and reevaluate us as an agency and what needed to be done.

So it sounded like you had 2 or 3 big friction moments between the amount of, well, the number of people that you needed to do manual work, and then afterwards the Google sort of a restriction. And so presumably AI was a huge boom at that point when it came, because it afforded sort of a solution that could fix 2 of those 3 problems at least. And then—

Yes, definitely. Yeah. It wasn't really evolved to the point that it is now. And it was more around, you know, the automation. So my first decision was what I had was not scalable anymore because I had this huge manual team and we were booking less calls for our clients. The churn of the, of our clients really did increase and therefore our expenses really went up and our, you know, our profits went down. And I realized that, you know, this is not scalable to continue this long. Something had to change. And the first thing I did was I looked at the whole organization. And again, we had over 100 people. And at first I brought in an automation expert to kind of look at where are the areas that I can potentially automate. And that was a project in and of itself. Like, here are all the teams. This is how all the teams are working together, right? This is how they're communicating. It was actually interesting for me, like managing each of the team leaders that really didn't even know how they were doing things, right? In terms of were they the most efficient that they could be? Did it make sense to have so many people? But that kind of forced me to to really open the book a little bit and understand every single task from, you know, opening a browser to copying a LinkedIn profile. Every single step needed to be mapped out for each and every person in the company. So having over 100 people, that was a very big job.

But if I'm, I want to dig a little bit deeper into that because I've personally got experience of using automations in a previous life at EY. And there are things that you can do even pre-AI. There was RPA. There's things like, I've just had a blank, Zapier. There's a whole load of automation tools that are around long before AI, and those would have definitely helped with those kinds of manual automations that you're talking about. What I'd like to dig in further into is what was the nexus, if you will, the pivot moment where you realized that an agency wasn't the solution and you wanted to build a product? Because those are 2 different things. You could have continued down the agency route with the automations.

Yeah. So I'll be honest with you, really the light bulb moment for me went off when I started building The automations, and when I started building the automations, I realized that so many of these tools that I was you know outside tools, not our tools, right? That we were reliant on were a just so expensive, and I could probably build it, and I could build it better. And it was missing a lot, like because the tool were missing a lot of components that we needed in order to execute for our clients. We were ending up doing a lot of manual work that then I ended up automating, but it was an automation between their tools. and our processes, and I realized I can just have this all in-house. I don't need to build it this way. So that kind of was the pivotal moment. And I think the other pivotal moment was, again, the personalization aspect of cold email was a big component to our early success. I would say in 2000, well, later, because we launched much earlier, but I'm saying as the, as the cold email industry evolved, having personalization was key. And personalizing it the way that it needed to be done was only able to be done manually. And there was no tool that I could find that would enable me to personalize it the way I really wanted to. And that was kind of the second aha moment. I was like, okay, so I can connect the dots with these automations. I could build my own personalization engine and be able to scale because it just wasn't scalable otherwise. So that was kind of when the aha moment happened and I decided to build out my own. Initially though, I'll be honest, I was thinking of just building it for the agency. I wasn't thinking of allowing it to be for like a SaaS product, right? And I actually had a mentor, um, an ex-McKinsey exec who basically said to me, I really highly recommend that you, when you're building it out, build it out so that the technology can also be used as SaaS. And it sat, yeah, sat on me. I'll be honest with you for a while. I fought it. I fought it for a while. In for quite some time. And I was like, that's a whole different can of worms that I have never built. I guess my last platform also was kind of similar in my marketing company. Like we did have login and events, so very similar to what I built here. And yeah, so I thought a lot about it and then I just actually had a lot of interest from users that were writing and asking, can we use it? Can we use it? So I was like, okay, there's a demand for this. You know, I'm gonna build it out.

So it's really sort of the market and the demand really that drove that change. It's great validation for you. If I'm digging into a little bit sort of less the opportunistic slash, I wouldn't say opportunistic, but yeah, I mean opportunistic in that you're reacting to the market. But so from a strategic decision-making perspective, is there any thought or concern about, for example, sort of client churn or trying to improve client churn or increasing profitability? I mean, increasing profitability, obviously there's an aspect of that from the automation side, but were you thinking when you were changing over from agency to SaaS product, is this an opportunity to increase ROI, increase LTV and so on? Was that sort of a calculation or a thought process?

1,000%. I mean, that was probably one of the biggest Just, um, you know, there's an— in my decision here was looking at, okay, how can I scale this so that I can have hundreds of thousands of clients on this one platform and a much higher ROI and much lower my costs and lower my dependencies on these other tools that I was literally paying easily, like just on one tool alone, I think we were up to $20,000 a month.

Wow.

Just paying for one tool. Yeah. So, so that decision, when I realized, wait, if I build this rather than borrow it, right, or license it, the, it would reduce my expenses tremendously. I would be able to bring onto the platform thousands of clients. Yes, the SaaS model was not, you know, the agency fees. So they're much, it's a lower entry point, but I wanted to go after the larger enterprise, you know, companies that would eventually pay those fees as they added more seats on the platform. So absolutely the churn was, was crucial for us as well as the reduction of the expenses to increase our overall profit margins.

Fantastic. Makes complete sense. And once you did start making that change, were there any surprises along the way, things that broke that you were caught unawares by, or that you planned for, but didn't quite work out the same way that you expected that either turned out to be lessons learned or things that you discounted or maybe even benefits?

So many. So the first I would say is that I actually was introduced by this mentor that I had to a company that was at that point, I mean, what year was this? Maybe 2023. That was an expert in AI and there weren't many at that time and they were very expensive. I remember I paid $15,000 for this consult. for this consultation, you know, and he was supposed to build the first kind of MVP prototype for me. And I got taken. Okay. And yeah, it was pretty bad. And I have a degree in management information systems. And this, as I said, is my second company that I understand how to build the architecture of a platform. So I know how to put all the pieces together and how to make it work. And then I hire programmers to actually do the actual coding. So it was very upsetting to me that I let myself have that happen, right? It was somebody that came through a recommendation of someone that I trusted, so I didn't expect that to happen. That was a big setback. And then I think the biggest setback happened when AI really exploded, right? Because here I was writing all these hyper-personalized emails, and actually what happened with AI, and the big surprise was that it started hurting the technology that I just invested years building. Because everybody was starting to personalize their emails using AI. Gmail and all the other platforms started getting smart at detecting AI-written emails. And so this whole platform and, and everybody started sending more cold emails because it was so easy to write them. Right? So it actually caused major harm to the whole platform that I built. And so that was really a huge setback.

How did you overcome that?

So we actually, and also I'll tell you another setback was that with AI, everybody has their own tone. Everybody has their own way of writing. And you can train the AI definitely, but it takes time. And when users would log in and have it run, they were like, I don't sound like that. So we would say, okay, edit the message, teach it how you, you know, your tone, your style, tell it to remove these words. So I created Um, the next version, which allowed you to edit it and have a learning engine built into it so that it learned your tone and your style. And then in addition, I added another feature that allowed you to write the message yourself. Okay. So it wasn't coming from AI, but just hyper-personalize and do deep research in specific areas. Okay. So for example, you could say, Raphael, loved what you just posted and then put in brackets, insert Raphael's latest post on LinkedIn. Right? So the rest of the email would be written by you, but it would do deep research. Or I see that you guys are focused on this ICP and these are your last 2 clients that you had a press release about, right? And those would be deep researched inside the email. So that was a pivotal change that I made in the, and I had to develop more and, you know, code more and, and build that out. And that made a huge impact because that was basically a tool now that users could use that was not reliant on the AI's tone, right? You can have your voice, right? And you could insert all this deep and use AI just for the research component so that it really looks like you hyper-personalized it manually, but you didn't. So yeah, that, that's definitely, you know, one area that I had to make a quick pivot and, you know, add additional development to.

And digging into that a little bit deeper, because obviously AI is continually improving and upgrading and at an accelerated rate, is that Affecting your business as well? Are you continually having to keep ahead of the curve and adapt the tool to be doing things that you can't do as an individual?

Um, the answer to that is that I have to continue being on top of all the different, um, AI models because Claude just came out with one and they're able to do this and this. So like you have to really be on top of that to know how to incorporate it into your technology. So you always have the latest and greatest so that, that For sure, but I also made a strategic decision to pivot towards the data, which I think was the right decision for us because I'm just getting an alert. Hold on one second.

I am as well. Hello.

Did you just get one?

No, I just got an email alert. I thought it was a similar alert as well.

Okay. No, it looks like it's not coming here. Okay. So I made a decision as well to focus because one of the areas that I realized most companies would not be able to compete on is the data. And that's actually one of our biggest value points is because we've been, we had been doing this for 14 years, have tremendous amounts of data on every single prospect that we've ever emailed for or messaged on LinkedIn for any of our clients. And if we had this data that AI can only run on data, right? And we have the data. So I also made a decision to really try to focus on becoming a bigger data company with intent and behavioral signals. And that's where Then the combination of the two, the personalized messaging with those intent and behavioral signals of data that we can bring into our platform and own was, was a good decision. I think, you know, was, was a necessary decision for us to basically be able to stand on our own and not have to worry about AI taking everything over.

Yeah. Yeah. It's interesting. I think that also lends to a, to an opportunity if you can Sort of look at the history of when sort of what worked and what didn't work with people and what sort of look for flags like that. You can probably also further refine and attune the messaging approach if you're not already doing that.

No, that was originally what I built from the beginning.

But with the database, I mean, with the database, you can do some really interesting analysis around that probably.

And I love that because I'm a data nerd.

That makes two of us.

Anyone targeting Marketing executives in the UK with a SaaS product, what are they mostly responding to? What's the tone? What's the messaging? What's the call to action? What's the subject line? So we have a tremendous amount of data that we're sitting on and how many of them are opening, how many of them are replying, how many are booking a call. The learning engine that I built is based on that so that it automatically will optimize the messaging based on, yeah, based on that data. So The, the big decision for me when AI came out was let's not fully be reliant on AI. Let's use the assets that we have, which is the data and continuously build that data.

Yeah. And looking at the numbers today, are there any particular KPIs, outcomes that you think really validate that pivot from agency to SaaS?

So it's interesting. We definitely are seeing higher conversion rates on booked calls, which is the outcome.

Right.

The main goal of the— and the purpose of the software is to be able to book more calls for our clients. So first of all, we also see a very big difference. We're able to compare as part of our data comparison, the different communication channels of email and LinkedIn, as well as cold call, right? So we're able to see all 3. And so first of all, what we've been able to conclude is that LinkedIn over time, because of all the spam issues, has really taken over. That's number one. And we've been able to, you know, improve some of our conversion rates on email were like 0.05% that we were able to book calls for. And it's over 1% for most of our clients on LinkedIn. So the results speak for themselves, right? Definitely in terms of like how many we used to have to send hundreds of thousands of emails and now we can send a few hundred of LinkedIn messages. So that, that's the big difference right now.

That's really powerful. And in terms of outcomes that are more on the financial side, how are you, are you seeing a massive difference between being an agency-style business versus a SaaS business? We talked earlier about the difference between the pricing between the two models.

I think we're still early on with that. We definitely are seeing growth every month. I have yet to really invest in the marketing that needs to be done on the SaaS side, but I'm First perfecting a little bit more of the software and adding some more components, but definitely we're having growth month over month so that I can say it's good. I mean, we definitely have a ways to go, but we're definitely seeing progress.

But you're looking to take over the world?

Just help people grow their businesses. That's our goal.

Fantastic. Great. Um, and if you were to share sort of an insight, a thought about your journey and the lessons that you've learned along your journey through that transition to other CEOs that might be listening to this, what would you say is the The biggest lesson learned that you, you had, you'd like to share?

I mean, I don't know if my team would agree with this or not, because I am known for, you know, constantly coming up with ideas and running with them. And so I would say like, if I didn't make that pivot when I saw the signs and I was stuck and focused on this vision that unfortunately had a lot of challenges around it, I would have been in big trouble. So I think it's about Listening to your gut and understanding we need to make, and not being afraid of making change, right? And going for it because I had a lot of team members that would say, no, no, no, no, we have to stay focused. We have to stay focused on email. And I was like, no, I really want to try all of our data and knowledge on LinkedIn right now and test and learn and test and learn because especially in our industry, it's ever-changing. There's always, always going to be more challenges coming and so many So much competition in the martech space, so much competition, and there's so much noise that for me, it wasn't about the noise as much as it was the results. Like I just constantly wanted to test and test and test and learn until I knew that I can bring on clients and I can bring them calls and I can grow their business through the different technology components that I built and leveraging the AI, but also leveraging our data. And so I would just say, keep testing and learning and don't be afraid. To take some risks.

That's a great way to end the call. Thank you very much, Vera, for sharing that.

My pleasure.

Yeah, it was a really, really interesting, interesting call. So thank you very much. And I look forward to the next opportunity to speaking together.

Me too. Thanks, Raphael. Take care.

You too. Best.

Bye. Bye.