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- Revamp: Re-inventing Marketing Messages with AI
Revamp: Re-inventing Marketing Messages with AI
Founded in 2023, Revamp helps businesses understand customers and increase retention by using AI to send better-targeted emails and ads.


Co-founders: 3 (Stephen Campbell, Amin Akhtar, Xinchi Qi)
Employees: 4
Amount Raised: $500K USD
Core Technology: AI-Powered Customer Segmentation for eCommerce; helping brands and agencies understand customer behavior by creating smarter segments for targeted email and paid acquisition campaigns.
Table of Contents
What's Your Story?
I grew up around a lot of entrepreneurial environments, so from a young age, I had a sense that I wanted to build something of my own. That really solidified when I started doing internships and working at big tech companies—like Ericsson, and I even had offers from Apple.
Those experiences made it clear that the traditional path wasn’t for me. It wasn’t just about being an employee—it was the structured, sheltered environments where everything is planned and things move slowly. That just didn’t suit me.
Revamp AI is actually my third startup. The first was in agri-tech focused on IoT sensors, and the second was Dreamwell, an AI-powered influencer marketing SaaS platform. Across those experiences, I probably made every early-stage mistake a founder could make. At Dreamwell, I had two co-founders and it was a valuable experience, but we struggled to find strong market validation early on. The traction just wasn’t there.
Over time, I personally discovered a more promising niche within marketing—one that had significantly more potential. At the same time, the vision between me and the team started to diverge. So I decided to exit and join a new venture—Revamp AI—focused on that clearer opportunity.
Biggest Struggle?
The biggest challenge for any early-stage startup is finding product-market fit. It’s easy to get distracted by customer noise—people suggesting features they think they want, but that often don’t lead anywhere.
Unless there's real commitment—ideally monetary—those requests can be misleading. At Dreamwell, we didn’t manage that well and got pulled in too many directions. It’s something we’ve significantly improved at Revamp AI, where we now stay laser-focused on solving validated problems.
What keeps you going?
What keeps me going is the belief that I can do this. But more importantly, you have to know what you're signing up for. Building a startup means going through a lot of pain—“eating shit,” as the saying goes—until one day you hit product-market fit and things start to change. If you don’t understand that upfront, it’s easy to burn out. You need to bet on yourself and truly believe in what you're building.
Early mistakes?
One of the biggest early mistakes is not clearly defining what kind of startup you’re building. You need to understand what product you’re creating, who it’s for, and how you plan to reach and sell to those users. That clarity should shape your entire strategy. Don’t stay stuck in your head, assuming what users want—talk to them, iterate quickly, and use that feedback to drive toward product-market fit.
If you're technical, that’s a huge advantage—but you also need to understand the mechanics of tech-driven product-market fit. There are great frameworks and books out there, but the key is applying them fast and early. That’s where everything starts.
The Problem: Poor, Impersonal Marketing Emails and Messages
Email marketers and paid media buyers often face major hurdles when trying to understand customer behavior:
eCommerce data is scattered across multiple platforms
Most brands and agencies lack the technical expertise to unify and make sense of that data
Even when they manage to consolidate it, turning the data into insights and action remains difficult
As a result, marketers rely on broad, generic segments for emails, while media buyers settle for basic targeting in acquisition campaigns—leading to millions of impersonal emails and wasted ad dollars on poorly defined audiences.
The Solution: Personalised Marketing Messages using AI
Revamp continuously tests message variations in real time and automatically delivers the top-performing content to each customer, maximising engagement without any manual effort. It enables true 1:1 behavioral targeting through dynamic wait-time optimisation, real-time message generation, and precise brand voice control—all fully automated. As customers interact with your messages, Revamp’s AI learns from their behavior and campaign results to refine and improve your copy over time, ensuring your messaging gets smarter and more effective with every send.


How did you come up with and validate the idea?
Revamp has pivoted a bunch of times. I actually joined in early 2024—around January. My co-founder found me through the Gen AI Collective, this community he started. We got to chatting about different problems we wanted to solve, and he was like, “Hey, you just moved to the Bay Area—why don’t you join us?” So I did.
When I came in, I looked at what Revamp had tried so far—things like an email segmentation tool, campaign builder, stuff like that. But it wasn’t really sticking. So I said, “Alright, let’s look at the users we already have, especially the ones not paying—what’s the one thing they actually want, and what’s something that would clearly show our value?” That led us to flow automations using AI. We started pitching that to users, and it just stuck. That was the first moment where it really felt like we had something.
I’d say at that time, our main KPI was just straight-up revenue, to be honest. So it wasn’t like we had a fixed number of users we planned to talk to or a super formal validation process. It was more like—what’s the idea that actually sticks and drives real growth and traction? That was the truth we were chasing. When I joined Revamp, there wasn’t much revenue, if any. So my number one goal was just to get the company alive—get something working that people would actually pay for. That’s what guided the decision.
What was your process for building the MVP?
That’s a pretty high-level question, so I’ll break it down into two parts.
First, on the product side, you need to really understand what the customer needs and what their current pain point is. Are they already using a solution? And if so, what gaps exist in that solution that stop them from getting the outcome they want? In our case, we found a clear gap, and once we saw that, we had a pretty strong idea of what the product could be—whether it would sit on top of another platform or act as a full end-to-end solution.
Then on the engineering side, we mapped out the technical requirements. Things like: What kind of data are we processing? What’s the volume? In our case, it was messaging—so we asked, “With our first 10 brands, are we sending maybe half a million emails a month? What does that look like in terms of API calls, email infrastructure, latency, scaling?” All that backend stuff.
Once we had both the product and engineering requirements lined up, we cut the meetings and just started building. I was the main IC at the time—even though I wasn’t the only technical founder—so I built out most of the MVP myself. We got it done in about two weeks and launched.
For out first launch, it was a closed beta. We launched it to the existing customers we were already talking to and focused on proving value—basically showing, “Hey, we’re actually helping you make money.” Once we did that, we started charging them.
Looking back, I don’t think there’s anything major we’d change. Sure, nothing is ever perfect, and there’s always room for improvement. It’s easy in hindsight to say we could’ve done this or that better, but given the data we had and where we were at the time, I think we made the right calls.
How do you approach product development and track product-market fit?
At the early stage, your biggest bottleneck is bandwidth—especially engineering time. So every feature we build has to be super focused and aligned with one core KPI: revenue.
We run regular team meetings where engineering and product sync with sales and customer success. Together, we identify product gaps, figure out what customers are asking for, and prioritise the features that are most likely to drive revenue. Once we agree on the top priorities, we just iterate fast—build, test, improve. It’s all about tight feedback loops and making sure everything we ship moves the needle.
For me, the biggest metric to track is churn. Do customers actually like your product—and more importantly, do they stick? So far, we’ve had zero churn, which is super rare and a really strong signal. If you’re seeing high churn, it usually means you have an attractive enough product to bring users in, but not enough value to keep them. That’s a red flag—either your product isn’t delivering, or it’s not solving a real problem.
After churn, the next thing we focus on is identifying our value drivers—which features or product lines are bringing in the most revenue and delivering the most value. Once we find that, we double down. It’s a total Pareto Principle thing: figure out what 20% of your product is driving 80% of your results, and make sure that 20% is rock solid.
How did your decide on your business model and pricing?
Our business model is super simple: we make our customers more money than they pay us. That’s it.
The way we’ve designed the product makes it really easy for customers to see the difference in revenue they’re making with us versus without us. Once we prove that value, it becomes a no-brainer for them to stick with us. It’s a very clear, very simple model—and that’s what makes it work. As for pricing, since we're essentially a B2B2C SaaS marketing tool, we have a custom pricing arrangement with each of our customers.
Your most successful marketing strategies?
Our first paying customers were actually users already in our pipeline—people who had tried the product before but weren’t paying. We went back to them and said, “Hey, we’ve got something new—want to try it out?” Since they’d used us before and had nothing to lose, they said yes. We ran the trial, ended up making them a ton of money, and they were happy. That’s how we landed our first paying customers.
Our most successful strategy so far has been social proof—especially case studies. Closing that first big customer in a specific segment, like fashion, was tough. But once we landed one, we used them as a case study, put their logo on our site, and that gave us instant credibility with others in the space.
Platforms like LinkedIn and Twitter have also worked well for us. But really, it comes down to understanding where your customers are. For us, it's been e-commerce brands and agencies, and they live in three places: Twitter, LinkedIn, and in-person events—like Shopify meetups.
That said, everything we’ve done so far has been 100% online, and it’s worked great. Honestly, we have more inbound interest than we can even handle at the moment. But once we launch our self-serve product, we’ll definitely expand our channels and start showing up at more in-person events.
What's your sales process like?
Our sales process is pretty straightforward.
We start with discovery questions to understand the brand—what they do, what their goals are—then we show them social proof, like the results we've achieved for similar companies. After that, we give them a quick product demo, and if they’re interested, we move them into a free trial. From there, it’s all about showing value.
If I had to give advice to other founders: provide real value upfront. That’s what works for us. In our case, it’s easy—we can literally show a number on the screen that proves we’re making customers more money. But every founder needs to figure out what their core value prop is and how to clearly communicate it. As for trials, we do offer free trials. We’re confident in the product, and it helps us close deals once people see the results firsthand.
What was your approach to fundraising and pitching investors?
For Revamp, we raised a small friends and family round after YC, along with the $500K YC investment. But beyond that, we haven’t raised any other formal rounds.
Right now, we’re actually cashflow positive, so we don’t need to raise. If we do open a round, it’ll be to scale faster—like hiring more engineers—which wouldn’t be a bad idea. But we’re in a great position where it’s optional, not necessary. That said, from my past experience—especially at Dreamwell—I’d say fundraising is a completely different skill set. It’s not the same as sales or execution. It’s its own game, and it’s all about storytelling. The story you're telling isn't about today—it's about the future you’re building.
The way I see it, when an investor meets you, they come in with a bank of doubts and skepticism. Your job in the pitch is to systematically remove those doubts. That means painting a clear vision, showing how you're going to achieve it, and backing it up with strong social proof—logos, traction, anything that shows you're already making progress.
When it comes to using those funds, I think it really comes down to what KPI you’re optimising for. That varies from company to company, but for us, it’s always been growth—which ties back to revenue, product milestones, and user traction. The key is to identify your biggest bottleneck to growth, and then pour resources into that. It’s pretty straightforward: figure out what’s holding you back, and focus your funding there. Everything else follows from that.
Can you walk us through how you assembled your team and how you lead them today?
When I first joined Revamp, I wasn’t a co-founder—I came on as a founding engineer. That gave both sides a chance to test the waters and see if this was really the team we wanted to build something big with. The co-founder relationship is a very special one, so that period was important. Over time, as we built trust and alignment, it became clear to both of us that I was already operating like a co-founder—so I formally stepped into that role.
Right now, we’re a small team of four, plus a few contractors. It’s me and my co-founder, a founding go-to-market lead, and a full-time intern helping with sales. We also have a VA based in the Philippines. Even with such a lean team, we’re cashflow positive—and we’re currently doubling our revenue every two months. It’s not common, but we’ve been super focused and intentional with how we operate and grow.
We have a pretty flat structure—nothing too hierarchical. It’s really just two main functional areas. I lead the product and engineering side, handling all the technical development. Our CEO focuses more on customer success and fundraising. And our go-to-market lead manages client relationships and handles some of the marketing. So essentially, we’re split into two key functions: go-to-market and product/engineering. It’s lean and simple, and it works well for us at this stage.
What's your daily/weekly workflow like?
We start each day with a morning stand-up—just a quick sync to make sure everyone knows what the others are working on. Everyone’s tasks are pretty different. For me, when I’m focused on product and engineering, the work is more deep and focused—heads-down coding or building. On the sales side, the work is more interactive and involves a lot of talking and creativity.
We do our best to stay in our zones, but we also rely on each other a lot. So it’s really about timing things well—knowing when to sync up, when to ask for input, and when to stay focused.
Any specific tips for building an AI-centric startup?
I think it really depends on what kind of AI startup you’re building.
If you're working on a frontier or deep tech AI startup, where the focus is on pushing the boundaries of the technology itself, then your core effort should be on the tech—on building something defensible and out-executing your competitors. In that space, it's less about user-facing features and more about your underlying innovation. Startups like that can sometimes raise a lot of money pre-revenue, but it’s a different game from what we're doing at Revamp.
On the other hand, if you're more of a PLG (product-led growth) AI company, like we are, then I’d say: don’t stress too much about the exact tech stack. Yes, use the latest tools when possible—but prioritise what you’re already good at. If you're great with Python, don’t slow yourself down just to learn TypeScript for one cool tool. Use what helps you build fast and stay productive.
For someone like me, I onboard quickly—I can pick up new tools in a week or two—but that's very individual. The main thing is: stay fast, stay focused, and build with what you know.