Intentional internet use platform with DNS filtering for adults.

Ben Bozzay capitalized on the remote work boom during COVID-19, launching Tech Lockdown to offer DNS filtering services for adults. His YouTube content on avoiding compulsive internet habits went viral, drawing 50,000 website visitors a month and achieving a monthly recurring revenue of $7,500.

The founder began by creating a headless content management system using Strapi CMS to manage both free and paid content, integrated with a custom-gated content system and Stripe for payments. The static site and web app were developed using Nuxt.JS, with UI built quickly via TailwindCSS and TailwindUI, and initial payment flows handled through Stripe-hosted checkout pages to simplify compliance and tax. The first prototype offered basic functionality: users could link their home network to the DNS filtering service, with the integration built atop an enterprise DNS Filtering API; at this point, users couldn't set custom filtering rules or device-level controls. Testing and iteration involved close communication with early users and rapid feature updates, such as adding customization options and DNS logs. Building the first workable version took a few months of part-time work, with progress constrained by the founder’s full-time job. Early challenges included limited free time, customer feature requests that outpaced resources, and the need to maintain security and error monitoring, solved by using Sentry and staying lean with minimal infrastructure.

SEO The founder focused on publishing comprehensive, helpful content targeting specific problems and search terms around content blocking and digital wellbeing. This resulted in a steady increase in organic search traffic, now reaching 50,000 monthly visitors. Why it worked: High-quality, actionable content led to top rankings and captured users already seeking solutions, driving nearly all customer acquisition at near-zero cost.

Reddit Relevant guides and YouTube videos were regularly shared in targeted Reddit communities, where posts and comments referencing Tech Lockdown sparked significant referral traffic. Why it worked: Reddit’s engaged communities provided credibility and direct word-of-mouth exposure among self-motivated internet users.

YouTube Although not updated frequently, a small library of videos showcasing how to set up content filters ranked on YouTube and continued to drive signups and website visits over time. Why it worked: Demonstration videos matched the DIY needs of early adopters and funneled motivated users to the main product.

Email List Visitors were encouraged to join an email list, which was used to promote new content, features, and videos, maintaining engagement and driving purchases. Why it worked: Email allowed direct, recurring communication with high-intent prospects and supported growth without dependency on third-party platforms.

Subscription service for automating email and document data extraction.

Sylvestre Dupont, the co-founder of Parseur, came up with the idea for the data extraction tool during his sabbatical break year in 2013. While building a travel map website, he realized the tedious task of manually entering travel confirmation emails into the app and thought it would be great if the app could automatically extract the relevant information. This sparked the idea of building an email parsing tool, which eventually became Parseur.

The founders began by meeting in person in late 2015 to collaborate on market research, competing products, and feature design for their initial data extraction tool. They started with a test landing page ('Captain Parser') to validate market interest, using Google Ads and collecting emails instead of building the product right away. Once validated, they created mockups and iterations of the application interface and moved on to developing the MVP, focusing solely on email parsing for launch. Development took nearly a year—much longer than expected—because building a point-and-click data extraction engine required complex iterations and some full rewrites of core functionality. Technical challenges included making the extraction tool flexible yet simple for users, and getting payment processing (with Stripe) and VAT compliance (using Octobat) functioning, both of which added significant development time.

SEO Publishing detailed articles and use case content targeting specific queries around "email parsing," "PDF data extraction," and automation, they increased their organic traffic steadily. Over time, Google became their main source of new signups. Why it worked: Addressing high-intent, niche search terms drew in users actively searching for solutions, resulting in steady conversion to trials and paid plans.

Quora Answers The founders answered targeted questions about data extraction and email parsing on Quora, which quickly started bringing both site visitors and signups. Why it worked: Quora audiences were actively seeking solutions, and answers established expertise while linking directly to Parseur.

Zapier/Integration Directories Parseur invested in building integrations with workflow automation platforms like Zapier and ensuring listings in integration marketplaces. Over time, Zapier became a significant referral source, sending highly qualified users. Why it worked: Users found Parseur when searching for automation workflows, and integrations made onboarding straightforward for business customers.

Affiliate Program They launched an affiliate program offering 20% lifetime commissions, enabling partners and agencies to promote Parseur in relevant verticals—sometimes even running their own ads. Why it worked: It incentivized third parties to drive qualified leads without upfront costs, expanding reach efficiently.

PDF-to-CSV tool for bank statement data extraction.

The idea for Bank Statement Converter was born out of a personal need and frustration. The founder wanted to analyze his own finances but was stuck with PDF bank statements that were difficult to work with. This led him to write a script to extract transaction data, and he realized that if he had this problem, others might too.

He decided to turn this script into a web app and collaborated with a friend to handle the front end while he focused on the back end. Inspired by the principles of launching a Minimal Viable Product (MVP), they initially created a simple tool for uploading PDFs and converting them to CSV downloads. Through this process, they faced various challenges, such as refining their API to handle real-world use cases like multiple file uploads and password-protected PDFs.

Early user interaction helped them validate the need for their product, as people started using it immediately. There was also a lesson they learned along the way: avoid building features based on assumptions rather than actual user demand. This realization saved them time and resources, allowing them to focus on what's truly needed by their users.

When building Bank Statement Converter, Angus Cheng began by writing Kotlin code to extract transaction data from PDF bank statements—a process that initially took over 10 hours. Recognizing potential wider utility, Angus partnered with a friend to transform this script into a web app. They had a single-page application ready quickly, focusing initially on functionality with an API stack that included three endpoints to handle PDF uploads, password setting, and conversion requests. The backend was powered by a tech stack of PDFBox for reading PDFs, AWS Lightsail for hosting, Ansible for deployment, and Kotlin with Ktor for the HTTP server. Within a week, they had a working version live online, though initial challenges included missing vital features like registration or a payment system, and limitations in handling diverse bank statement formats. Despite the simplicity at launch, it was a testament to agile development and user-driven iterations that relied heavily on feedback and ongoing adjustments.

Word of Mouth

Bank Statement Converter experienced steady growth primarily through word of mouth. As users found the service effective for converting bank statements, they likely recommended it to peers, fostering organic growth.

Why it worked: People tend to trust and act on recommendations from those they know. Since the product effectively solved a common problem, users shared their positive experiences, leading to new customer acquisitions without the need for aggressive marketing.

Google Search Ads

In the initial six months, Bank Statement Converter invested about $1,000 USD monthly in Google Search Ads to boost visibility and attract customers.

Why it worked: Initially, Google Ads brought awareness and some customer inflow. However, the cost exceeded returns, prompting them to cease this expense. While it didn't generate immediate profits, it validated interest in the product, guiding future marketing strategies.

Supporting More Banks

The strategy involved enhancing the software to support more bank statement formats. They engaged in customizing configurations for specific banks to ensure higher conversion accuracy.

Why it worked: By continuously improving the system to support a wide range of bank statements, Bank Statement Converter increased the likelihood of successful conversions for potential users. This adaptability led to higher subscriptions as users received reliable outcomes, encouraging repeat usage and subscriptions.

Customer Retention through Quality Service

Their approach to retaining customers focused on maintaining software reliability. Customers with ongoing needs, such as accountants, continued their subscriptions as long as the service remained effective.

Why it worked: High retention rates were achieved by ensuring the software consistently met user expectations. For recurring needs, reliability was key, prompting ongoing subscriptions without any additional marketing efforts.

AI tool turning text instructions into Excel formulas.

David Bressler, the founder of Excelformulabot.com, came up with the idea while on paternity leave. After discovering the power of AI and its potential in Excel formulas, he realized there was a need for an AI-based Excel formula generator. With 1 billion Excel users worldwide, Bressler saw a big enough market and quickly built a barebone application that went viral and gained traction through Reddit, TikTok, Instagram, and Twitter. Since the launch in September 2022, the website has generated over $14K in monthly recurring revenue.

Excelformulabot was developed quickly to capitalize on the growing AI industry, with a minimalistic MVP built using the no-code platform Bubble.io. The initial version had basic functionality: an input field for user instructions, a button for generating formulas, an output field displaying the results, and a copy button. This barebone MVP took just a few weeks to build, reflecting David's urgency to harness the first mover's advantage in the AI space. He faced challenges related to unexpected high API costs due to viral exposure and immediately had to create a business model to manage costs efficiently. Feedback from the Excel subreddit was crucial for iterating on the initial version, which transitioned into a subscription-based platform with paywalls and logins over several months, demonstrating the effectiveness of user feedback in refining product offerings.

Viral Marketing on Social Media

Excelformulabot experienced significant growth through viral marketing, particularly on TikTok, Twitter, Instagram, and Reddit. The platform gained traction when users began sharing it as a "website that feels illegal to know." The ripple effect from influencers and micro-influencers posting about Excelformulabot amplified the brand's reach substantially. The virality continued across different social platforms, leading to widespread recognition and traffic.

Why it worked: Viral marketing tapped into the power of social proof. When influencers shared their experiences, their followers were intrigued and inclined to check out the service themselves. The portrayal of the site as a secretive hack added a compelling element that spurred curiosity and shareability.

Influencer Collaborations

Direct engagement with influencers has been a crucial part of Excelformulabot’s marketing strategy. David Bressler reached out to influencers whose audiences aligned with the product's use case in areas like finance, data, and accounting. Collaborations were either based on free promotions or paid partnerships, typically ranging from $200 to $3K per engagement.

Why it worked: Engaging influencers allowed Excelformulabot to tap into established communities that trusted their recommendations. This strategy effectively positioned the product in front of targeted users who found immediate value in the tool, especially amidst audiences who frequently use Excel.

Organic SEO and Branding

Excelformulabot benefitted from organic search traffic, largely driven by people searching for terms like "Excel formula bot." The brand's presence as both the category creator and the main solution provider resulted in high exposure on search engines. The site also garnered backlinks from reputable sites, enhancing its organic search appeal.

Why it worked: The brand's dominance in its niche and the creation of targeted content helped capture users actively searching for AI solutions for Excel. Having a name that directly matched user intent searches significantly enhanced discoverability and credibility.

Email Marketing and User Engagement

For customer retention and reengagement, Excelformulabot deployed email marketing strategies. Personalized messaging was developed based on user interactions, such as the type of formulas searched and user engagement levels. These tailored emails helped retain paying customers as well as encourage trial users to convert.

Why it worked: Personalized email campaigns aligned closely with user behavior, increasing the relevance and impact of each communication. This approach fostered a sense of connection and ensured users saw continued value in maintaining their subscriptions.

Stripo's founder, Dmytro Kudrenko, a seasoned programmer-turned-entrepreneur, identified a major gap in the email marketing industry when he realized HTML email design required coding skills that marketers usually lack. Launching in 2017, Stripo rapidly grew to one million users worldwide, generating approximately $400,000 in monthly recurring revenue by offering an intuitive, coding-free email template builder with seamless one-click exports to over 80 platforms.

The initial build of Stripo was handled by a small, resource-constrained team, consisting of at least three developers, a QA, a BA, a CEO, and a designer. For the frontend, they used the Angular framework, while the backend was based on a Java microservices architecture, both deployed on Amazon AWS, leveraging the team’s extensive experience with the Java tech stack. The team focused on building an email editor that separated design from data, enabling marketers to easily create and manage professional emails without coding. Early development involved collaborating closely through healthy debates to make user-focused decisions. Reaching a working product took several months of iterative prototyping and testing; after about nine months, the product was stable enough to introduce paid plans. A core challenge was differentiating their editor from existing email service providers by providing unique solutions like modules and seamless integrations with email marketing tools—efforts enabled by prioritizing integration capabilities and direct export functionality.

SEO & Organic Content They produced comprehensive blog articles, eBooks, and educational webinars addressing key email marketing topics and new technologies, which became the main driver of organic traffic and customer acquisition. Their blog served as a resource hub, sharing use cases, expert interviews, and in-depth industry insights. Why it worked: High-value content positioned Stripo as a trusted authority, attracting both individual users and agencies searching for reliable information and tools.

Partnerships & Integrations Stripo invested heavily in direct integrations with over 80 major ESPs and email platforms, making it easier for users to export emails directly to their preferred tools. They also offered a plugin version to embed the editor into other platforms like CRMs. Why it worked: Seamless integrations removed technical barriers, expanded their reach, and made Stripo attractive for large teams and agency workflows.

PR & Industry Thought Leadership Stripo's team engaged in industry interviews, case studies (e.g., FC Chelsea, Forbes), and participated as panelists at relevant events. They shared product improvements and innovations openly within the community. Why it worked: Thought leadership and association with high-profile clients bolstered trust, credibility, and word-of-mouth growth among email marketers.

Product-led Innovations They were early adopters of technologies like AMP for Email and offered interactive content generators, establishing a reputation as an innovator. Key product advancements were communicated through content and community involvement. Why it worked: Introducing new features ahead of competitors attracted forward-thinking customers and kept retention high by continuously providing value.

Before starting AutoMemes.ai, I was freelancing on Fiverr, creating custom video memes for brands and creators. While the work was fun, it was also repetitive and time-consuming—every meme meant searching for content, writing clever captions, and manually editing everything in CapCut. Around early 2025, AI tools were exploding in popularity. I saw people using AI to write articles, code apps, and even compose music. That’s when it hit me: "If AI can do all that, why not memes too?" That question turned into an obsession—and eventually, a product.

At first, I quietly automated part of the process and kept selling memes on Fiverr. Clients loved the results and kept coming back. That gave me the confidence to go all in.

I didn’t know how to code, so I used ChatGPT to learn and build the first version. The early users were actually my old Fiverr clients—and they’re still using the product today. That’s how I knew this wasn’t just a fun idea, it was a real business.

Unlike other projects I had started, this one solved a real pain I had personally experienced. That made all the difference.

Fiverr Order Confirmation

Max Ibarra created the first version of AutoMemes.ai without prior coding experience by learning as he went, using ChatGPT as his primary guide and support. He built the product as a web app and leveraged no-code/low-code tools and AI APIs, likely with platforms such as Vercel for hosting and Next.js or a similar modern JavaScript framework for development (as is common among indie developers in 2025, though exact tech stack details were not specified in the sources). Early on, he partially automated the meme-making process while still delivering orders manually on Fiverr—iterating on the workflow based on direct client feedback. The first prototype focused on automating the slowest parts of meme creation: sourcing video clips, generating captions, and editing them together into viral meme formats. Max reached a working version within weeks, thanks to rapid prototyping and testing real-world output with his existing Fiverr clients. The main challenges included learning to code from scratch, troubleshooting integration issues with various APIs, and refining the AI’s ability to create genuinely funny and engaging video memes.

Growing AutoMemes.ai has been all about experimentation. Besides building in public on Twitter, I’ve tried multiple strategies across content, SEO, and creator partnerships.

Every day, I publish new meme templates on TikTok, YouTube Shorts, and on my website, both to attract organic traffic and showcase what the tool can do. I also run niche TikTok meme accounts where every meme includes a visible watermark from AutoMemes.ai—this drives curiosity and clicks from people who want to know how the memes were made.

I offer all green screen templates for free as a lead magnet. These are especially useful for content creators looking for easy hooks. I also engage in Reddit communities where creators share meme ideas and resources. Giving value in those spaces has helped build trust.

100+ free green screen meme templates

I experimented with cold outreach on WhatsApp to indie hackers and creators from groups I’m part of—but I learned the hard way that this can backfire. I even got kicked out of a group for coming off too spammy. My advice: don’t cold DM strangers on WhatsApp. Instead, focus on giving value and building relationships.

I also run a newsletter where I share strategies and real-life case studies on how different businesses are growing on social media using meme marketing. It's another way to give value, stay connected with my audience, and keep learning together. It’s early, but the results are promising.

TikTok Growth Analysis @inflow

Right now, I’m testing sponsorships with green screen creators to drive traffic directly from viral content.

In the end, what’s worked best is creating useful, shareable content consistently—and making sure people know where it came from.

Kubernetes made easy - save time, money, and resources using the Syself platform

The idea for Syself came from firsthand experience with the challenges of managing Kubernetes at scale. Before starting Syself, I worked extensively in cloud infrastructure and DevOps, helping companies deploy and maintain Kubernetes clusters. I repeatedly saw teams struggling with complexity, high costs, and the steep learning curve of Kubernetes. Many businesses wanted the power of Kubernetes but lacked the expertise or resources to operate it efficiently. That’s when I realized there was an opportunity: What if Kubernetes could manage itself?

The "aha" moment came when I was helping a company migrate from a managed Kubernetes service to a self-hosted setup on a more cost-effective cloud provider. The migration was technically possible but incredibly tedious—provisioning nodes, configuring networking, ensuring updates wouldn’t break anything. It became clear that automation and simplicity were missing from Kubernetes management, especially for companies that wanted to optimize costs and avoid vendor lock-in.

My image

How We Built the First Version of Syself: Identifying the Core Problem & Market Need: Before writing a single line of code, I spent months talking to DevOps engineers, CTOs, and Kubernetes users to understand their biggest challenges. The common pain points were clear—Kubernetes was too complex, managed services like AWS EKS and GKE were expensive, and self-hosting Kubernetes required too much manual effort. Companies wanted automation, flexibility, and cost savings without vendor lock-in.

That’s when the idea for Syself Autopilot took shape. Our goal was simple: one command to create a production-ready Kubernetes cluster without the hassle of manual setup and management. Instead of competing with managed cloud services, we wanted to provide an open, cost-efficient alternative that worked on any infrastructure—especially on affordable providers like Hetzner.

Building an MVP (Minimum Viable Product): To move quickly, we focused on a single core feature: automated Kubernetes provisioning on Hetzner Cloud. We used Cluster API, an open-source Kubernetes lifecycle management tool, and built a custom controller to handle node provisioning and scaling. Instead of overwhelming users with too many options, we created a simple CLI tool that allowed them to deploy clusters with just one command.

Once we had the prototype, we tested it with real users—DevOps teams, startup founders, and Kubernetes enthusiasts. We collected feedback on usability, performance, and security, and then refined the product with bi-weekly updates. The key was iterating fast—we kept improving the tool based on real-world use cases and fixing pain points that surfaced during testing.

Developer Communities & Forums Syself shared its automation-focused Kubernetes solution in forums like Reddit, relevant Slack groups, and developer communities. These discussions targeted DevOps engineers and startups experiencing similar infrastructure challenges. Why it worked: Direct engagement allowed Syself to build credibility quickly and reach early adopters already interested in cloud automation.

Open-Source Contributions The team contributed improvements to projects like Cluster API and openly shared their own tools, which drew interest from the Kubernetes ecosystem. This approach fostered trust and demonstrated technical capability to the target audience. Why it worked: Open-source participation established Syself as a knowledgeable resource and generated organic word-of-mouth within the infrastructure community.

Technical Content & Case Studies Syself published technical blog posts and case studies that highlighted specific cost savings and simplified operations using their tool, appealing to decision-makers and technical leads. Why it worked: Detailed, educational content helped articulate Syself’s value proposition and provided tangible proof to technical buyers evaluating Kubernetes solutions.

Free Trials & Direct Outreach They offered free trials to DevOps teams and engaged in one-on-one conversations, guiding prospects through evaluating the platform. Why it worked: Personalized support and a hands-on experience addressed concerns directly and converted engaged users into the first paying customers.

I actually did not start with MrScraper at first. I bought it from an Indiehacker named Kai. It happened in 2024 when I had plenty of cash sitting around from my profit from running my technical writing agency, penateam.com, and realized that scaling an agency is a pain in the butt.

I was googling on the internet and got hooked on the idea of flipping businesses instead of starting from scratch. Then, after interviewing many sellers from acquire.com. I decided to acquire MrScraper because it serves a big chunk of the market compared to other businesses I talked to and it was listed only for five figures back then, so I had nothing to lose.

After I acquired it, I realized that it had so much SEO traffic and people signed up, so I knew that people wanted this but could not figure out how to use it. So that is an "aha" moment that demand is there. I just need to make a better product.

Since I already have the first version of the product and an existing customer base, I already have some users to perform A/B test. I used a profit that I got from my agency, penateam.com, to hire a bunch of engineers from Asia to improve the product even more by looking at data from customers daily.

It took about 3 weeks to rebuild and launch our first improved product, and it was more painful than I thought. I need to step away a lot more from my agency and focus more building MrScraper.

At this moment, I realized that building SaaS is harder than building an agency. With an agency, you get guaranteed revenue every time you deliver a service. For SaaS, there is a high chance that no one would use your product even if you put in 100+ hours into it! And you also need to spend a lot of $$ for server, hiring a good team, convincing them to join and stay working with you, and many other headaches. It's completely different than the agency business model, where you can just simply run a business by yourself and stay profitable for as long as you want.

My image

We tried almost every channel possible, including SEO, X, Reddit, Facebook, etc. I even posted a desperate post on Reddit that went viral but was embarrassing, lol. I truly wanted to give up back then due to the high cost of employees and almost minimal revenue. This post made me an additional $500/month.

Then I checked all the data again, and the main revenue drivers were actually SEO and outbound to our ICPs; I understood that I could not serve all customers, so I doubled down on that and neglected all channels.

Andd thenn suddenly an enterprise client submitted an inbound ticket inquiring about a SEVEN FIGURES contract, and my MRR goes BRRRR!

This is also why I wrote this post: to get a high-quality backlink while sharing my journey. Thanks to Pat for this!

We're still pretty small compared to other players, though, and I am still trying to figure out the best and scalable strategy to grow the business, but so far, SEO and outbound are the best revenue drivers for MrScraper.

Component library streamlining web developers' landing page creation.

Manu, the founder of Aceternity UI, transformed a hobby of crafting beautiful web components into a booming business after noticing that people preferred ready-to-use code over explanatory blogs. With rapid launches and feedback-driven improvements, his Aceternity UI Pro reached $80k in revenue just two months post-launch, heavily leveraging platforms like Twitter and Product Hunt to build momentum.

The founder created the first version of Aceternity UI by leveraging tools and frameworks he was already familiar with: Next.js for the web app, Tailwind CSS for styling, framer motion for animations, and Vercel for hosting. The initial build focused on a simple website that allowed rapid addition of reusable, visually appealing components, and prioritized offering real, useful examples for free to eliminate friction for developers. Development began with components the founder had previously created for personal and blog projects, which accelerated the prototyping process. The first full working version took just a weekend to build. The most notable challenge was resisting the urge to over-optimize or perfect the code before launch, recognizing that quick iteration with user feedback would be more valuable than internal standards at this stage.

Twitter / X The founder directly promoted Aceternity UI on Twitter, sharing component demos, development updates, and learnings. His authentic and consistent posting quickly grew his Twitter following to 20,000 in four months. Why it worked: Engaging directly with the developer community on Twitter led to personal, viral sharing and built word-of-mouth buzz.

Product Hunt A launch on Product Hunt brought the initial user base and drove early traffic to the site. This exposure helped Aceternity UI quickly find its first customers and sparked valuable product feedback. Why it worked: Product Hunt’s audience is primed for new developer tools and early adopters, providing an immediate credibility boost.

Word of Mouth & Referrals Satisfied customers shared Aceternity UI with colleagues and within tech networks, which led to organic growth and high-trust referrals. Some high-profile mentions included coverage by YouTubers like Fireship. Why it worked: Developers trust peer recommendations for tools they depend on, leading to strong conversion and loyalty.

Kyle Bigley started TxtCart after realizing the untapped potential in SMS marketing during his dropshipping days in college. He launched the AI-powered SMS marketing company in 2019, generating $1M ARR while still bootstrapped, and is on track for $3M ARR by 2026.

The founders started building TxtCart by first assembling a technical team: the non-technical founder connected with a CTO and then a third developer via personal networking. They focused on building an MVP for SMS cart recovery, completing it in approximately four months, including development and Shopify app submission (which itself took 4–6 weeks). Development was lean and budget-conscious, with some creative and UI/UX work handled by freelancers found on platforms like Fiverr (for which they spent around $1,260). The very first version was functional, focusing solely on the core task (SMS cart recovery) and prioritizing working software over polished design. A key challenge was balancing speed of delivery and minimal resources, but being “good enough” proved sufficient for the early stage; the app grew significantly before any major UI update.

Facebook (Meta) Ads TxtCart initially relied on Facebook (Meta) Ads to reach Shopify merchants and ecommerce entrepreneurs, targeting SMBs and dropshippers. This generated awareness and drove installs, leveraging Meta’s targeting and retargeting capabilities. Why it worked: Meta's broad reach and granular targeting enabled cost-effective acquisition of early users, especially newer ecommerce operators.

Shopify App Store Ads They capitalized on the then-new Shopify App Store Ads soon after launch, bidding on high-intent keywords like “SMS.” Early adoption before the channel became crowded made ads very effective, with early clicks costing under $10 (now as high as $75 per click). Why it worked: Being early let them attract users actively seeking SMS solutions, leading to high app listing visibility and strong installs at sustainable costs.

Influencer Marketing & YouTube As ad costs rose, TxtCart increasingly invested in influencer marketing and YouTube sponsorships to reach ecommerce operators through trusted content creators. This shift supplemented direct paid ads and enhanced word of mouth. Why it worked: Social proof and community endorsements carried extra weight for their SMB audience, fueling credibility and organic reach.

PLG, Word of Mouth & Affiliates TxtCart benefited from product-led growth, strong word of mouth within the Shopify ecosystem, and affiliate partnerships. Satisfied clients—especially those seeing measurable ROI—shared results and referred others, while affiliate commissions incentivized promotion. Why it worked: Refer-a-friend and affiliate strategies scale with happy users, compounding growth without proportional marketing spend.

AI-powered platform for professional headshots from selfies.

After a varied career including a failed coffee bar, a marketing agency stint, and multiple small ventures, Ricardo Ghekiere's lightbulb moment came post a night out in Spain. Teaming up with Miguel Rasero, who had found success with Minecraft servers and AI projects, they transformed BetterPic.io, growing it from $1,500 to $20,000 in monthly revenues by July 2024.

Building BetterPic's product was a complex yet innovative process primarily focused on utilizing AI technology for creating professional headshots from selfies. Initially, Miguel Rasero worked alone, developing the AI model using open-source tools like Stable Diffusion, building with his proficiency in Python and JavaScript. Early development involved rigorous testing and iterations on text-to-image models, image processing, pipeline optimization, and advanced training methods, resulting in gradual improvement of the AI's ability to produce quality headshots. The first prototype faced challenges, especially in achieving realistic facial resemblance and texture details, which took three months to reach acceptable quality. The tech stack included Vue 3 (Nuxt) for the frontend, Supabase for authentication, PostgreSQL for the database, Vercel for deployment, and Node.js for the backend. Despite launching incomplete before a vacation, the experience taught valuable lessons in rapid problem-solving under pressure, highlighting the chaotic but rewarding journey of a solo founder deploying a cutting-edge product.

SEO

BetterPic focused on search engine optimization (SEO) from the start, producing content and building links to improve visibility in search results. They targeted specific keywords like 'studio AI headshots,' improving their Google rankings over time. Despite some setbacks, such as temporarily losing their ranking for 'AI headshot generator,' they persevered and regained positions. This strategy gradually increased their monthly organic revenue.

Why it worked: Customers were actively searching for AI-generated headshots and related services. By optimizing their website for popular search terms and consistently improving their content strategy, BetterPic captured organic traffic, which was crucial for their low average order value business model.

Pinterest

BetterPic leveraged Pinterest as an unconventional yet effective marketing channel. By posting over 100 headshot images on their Pinterest page, they amassed 750,000+ impressions. This approach drove significant traffic to their site without incurring direct costs.

Why it worked: Pinterest is a visual platform, ideal for showcasing headshots. It attracted users interested in visual content, leading to increased brand visibility and website visits. The approach was creative and leveraged an untapped marketing avenue for BetterPic's type of service.

Pricing Strategy

To increase the average order value, BetterPic adjusted their pricing strategy. They raised the price of their basic package from $25 to $29, making the $35 package appear more attractive. This change resulted in a 400% sales increase of the $35 package.

Why it worked: By strategically altering their pricing tiers, BetterPic nudged customers toward a higher value package without making significant changes to the offerings themselves. This psychological pricing tactic effectively increased revenue per customer.