SaaS Interviews with CEOs, Startups, Founders
His SaaS Will Be Huge Because of $1m+ Agency With Ready To Go Customers
21 Jan 2022
Chapter 1: What are the key features of Pulse and how does it predict content performance?
At the moment, we're pre-rev, but as soon as we hit revenue generation, we know that we have a hundred and so agencies that are going to be taking the platform on from day one. You are listening to Conversations with Nathan Latka, where I sit down and interview the top SaaS founders, like Eric Wan from Zoom. If you'd like to subscribe, go to getlatka.com.
We've published thousands of these interviews, and if you want to sort through them quickly by revenue or churn, CAC, valuation, or other metrics, the easiest way to do that is to go to getlatka.com and use our filtering tool. It's like a big Excel sheet for all of these podcast interviews. Check it out right now at getlatka.com. Hey, folks. My guest today is Joe Call.
He's a 25-year-old marketing expert owning a marketing agency and an emerging technology in the machine learning AI space called Pulse. Pulse predicts the outcome of creative content before it's published, maximizing return on ad spend for brands and marketing agencies alike.
Chapter 2: How accurate is Pulse in predicting emotional responses to content?
Joe, you ready to take us to the top? For sure. All right. So I have 10 ad creatives. Who are you publishing them to before I actually launch them on Facebook to see if they're going to give me a good return?
So what we're doing is we're taking creatives, uploading them through our ML platform, identifying a number of different key factors through the machine learning in terms of hue, saturation, luminance, object identification, and a number of other key factors in terms of the natural language that's used in the written context of text formatting to identify based on petabytes of historical data, how people have reacted previously, cross correlate that against how they're likely to react to that piece of content in the future.
The machine learning is now complete. We're at 97% accuracy on the prediction model. 97% accuracy on what? What are you trying to predict?
Chapter 3: What pricing models do agencies use for the Pulse platform?
On predicting the outcome of emotional responses to creative content. So when someone is publishing a piece of content, are they going to feel angry about it? Are they going to feel sad about it? Confused? Unhappy? How many people are going to engage with it? What type of engagement is that likely to be? We can predict that with 97% accuracy now. How do you know, though?
I mean, I scroll a lot of Facebook ads in the course of a day that I never interact with, and maybe one makes me angry, but I give no signal to Facebook that I'm angry.
Chapter 4: How does the guest fund the development of Pulse?
I just keep scrolling. How are you able to capture that? Yeah, sure. So that's based on a number of other engagement statistics in terms of watch time, in terms of frequency of watch, in terms of frequency of communication around the piece. But fundamentally, we leverage available public data to identify trends of how people have reacted to similar pieces of content.
So while you might not react, other people will react in a similar way and possibly more forthcoming with that information. That subsequently gives us the data set to identify how people are likely to react. Similar process and identification process to natural language processing, but it's kind of NLP on steroids.
And so I understand why brands or agencies want to pay you for this, but give me a sense of how you price.
Chapter 5: What type of agencies are likely to adopt Pulse?
What are they paying on average per month to use this tech? Yeah, it varies. So it depends on how many campaigns they're running simultaneously, but it varies from Ā£500 a month in British pounds all the way up to however much they want to be paying. But the range for SaaS subscriptions is Ā£500 to Ā£5,500 a month. What's like your sweet spot though?
I know it's sort of weird to force you an average, but it was Ā£600, Ā£700 a month, a good average? Yep. Around about 5,500 is probably going to be the average for the majority of significant sized agencies. If they're smaller sized agencies, they're going to be going for the 500 pound a month package. Well, I know, but the real question I'm asking is what kind of agencies are using you, right?
Chapter 6: How does the guest balance running an agency and a SaaS product?
So I'm asking what the mix is effectively by asking what the average is. Sure. At the moment, we're pre-rev, but as soon as we hit revenue generation, we know that we have 100 and so agencies that are going to be taking the platform on from day one. And of those, they're sort of roughly falling into the 2,000, 2,500 bracket. And so how are you learning that?
Are you sending them a PDF with like made up prices to see how people respond and you've had a good response to a $5,000 price point for large agencies? So it's based on a number of things. We've not priced it based on what they would want. We priced it based on what we know we can achieve and based on what we know our direct competitors are using.
And we're building a technology that's subsequently substantially better than our direct competitors.
Chapter 7: What challenges does the guest face in scaling Pulse?
So we know quite confidently that the agencies that are going to be deploying this sort of solution are going to be quite satisfied on the price point side of things. Majority of entry point for similar products like Talkwalker, for example, people are paying six grand a year for a similar product. When did you launch the business? What year? Middle of last year, June of 2020.
We've been burning through cash quite fast since then. How much are you burning? We've done 1.48 million pounds so far. Okay. And why is it so expensive to build this?
Chapter 8: What insights does the guest share about future plans for Pulse?
Lots of machine learning, lots of computer vision, predominantly the bulk of the spend has gone into that. The tech stack that we have behind this has meant that we've had to deploy some quantum computation elements as well, and a variety of other facets to the product in the back end to handle these vast quantities of data that we have.
Where'd you get 1.7 million, 1.8 million bucks to burn through? So $150,000 has come from private investors. The rest has come from me and the money that I've accrued over the past however long by running my marketing agency. Oh, very cool. So you've had significant success then in the marketing agency to be able to put $1 million, $2 million of your own money into the business. Been okay.
Been okay. Yeah, no, this is great. Okay, cool. I love a story like this. So how do you decide? Do you have partners in the agency? No. Okay, got it. So it's your own agency. I see. I see. And how do you make money at the agency? Is it people pay to spend 100 grand a month for them and you take 10%? Basically that, yeah. It depends on what model we're working on.
So you've got the paid ad model, but then it's a full service agency. So we do video production, animation, photography, creative design, branding, the whole suite in one place. And why let other people take equity and put in 150K? Why not just put in another 150K yourself and keep 100% control? I'm strategic.
So I'm not going to say who the investors are, but there are a couple of private investors that we've taken on board who are fundamentally going to help us long-term with our long-term vision and plan for what the product can do. But fair to say you still own more than 95% of the business? Yes, at present. Close, close. Oh, okay. You said at present. Are you raising now?
Are you about to announce around? Uh, we may be announcing around at the start of next year. Um, you know, additional capital is always useful, particularly when you're deploying a product like this, it's very complex, requires a lot of funding behind it.
Um, yes, we may be launching another round, but over and above that we have, you know, option pools and a variety of other facets that, um, are going to decrease my, uh, my equity holding. Doesn't your ability to avoid dilution drastically decrease the second you go from $0 in revenue to one? And if so, wouldn't you want to do that before going out and raising another round? Yeah, absolutely.
So that's absolutely the case. So by the time this podcast goes live, I'm assuming it's going to be January 22 anyway. So, you know, from the point at which we launched the product early next year, you know, we're definitely going to have a few months of live phase before we actually implement a new round.
I bet you can't guess what SaaS founders waste the most time on after they pass 15 employees. Think about it. Think about it when you onboard a new team member. How much time as a founder do you take to set up their email account, get them added to the Trello board? If it's a sales hire, you've got to onboard them to Salesforce or Slack. This is a terrible use of your time as a founder.
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