In 2020, Andy learned about a Google Sheets add-on called API Connector, which imports your data into a simple Google sheet.

Around the same time, Andy noticed the rise in popularity of Airtable.

Since Google Sheets and Airtable were close in compatibility, Andy decided to build a similar type of data integration tool for Airtable.

Andy’s 3-step method for coming up with ideas is helpful context for understanding how he came up with the idea: - Find a platform that is already growing massively. - Look at already successful tools for more mature platforms. - Build an equivalent tool for the new platform.

Prior to launching Data Fetcher, Andy taught himself to code in order to get a career in software.

He developed multiple software projects. The two notable projects were: - Verbly for learning Spanish conjugations, which landed on the front page of Hacker News - And Influence Grid, a directory of TikTok influencers.

Influence Grid was his first success – scaling to $3K MRR and sold for $55K

Grew to 190 paying customers and $6,500 in MRR in one year.

Around the time Andy had the idea, Airtable had opened their app marketplace to third-party developers. Airtable also used React.js, a programming technology he was familiar with.

Andy spent 1 month developing the first version, and then 3 months getting it through Airtable’s app marketplace review process.

While developing the app, Andy would tweet about it and collect emails from people who were interested.

When the app was live, he used this email list to create awareness and find his first few customers.

He went on to launch the Data Fetcher on Product Hunt, which drove even more customers.

Grew the initial awareness and potential customers by sharing the development process on Twitter. Once the app was live, he used Product Hunt to attract more customers.

At the time of his launch, 70-80% of customers found Data Fetcher organically via the Airtable app marketplace.

Now, he continues to grow through a no-code blog and YouTube channel which teaches people how to use Data Fetcher in various instances.

After 2 failed startups, the founders set their sights on working on something people want and are ready to pay for. Their priority even before they had decided on the idea for the product was to find an audience, a group of people who faced a problem, and who currently pay for a software tool to solve their problem. App marketplaces were a way to mitigate some of this risk.

They had some prior experience with building a Shopify store, and also had a friend who built a $20k/mo Shopify app without any employees.

To find problems worth solving, they browsed the entire Shopify app store, which at the time had 3,000+ apps. Going through every single app, jotting down interesting ones, especially ones that had poor reviews indicating that they could do a better job at solving the same problem, and picked 5 out of the 100s of those ideas they identified, based on their goals and constraints:

• An existing problem that people were already paying for
• Existing apps weren’t doing the best possible job at solving customer’s needs
• The app had the potential to grow to at least $3k in MRR, which after costs would allow the founders to live comfortably in Bengaluru

They spent 2 full weeks to build and submit and MVP to the Shopify app store.

It took them 30 days to hit $400 MRR.

Since they were building an alternative to existing apps on the Shopify app store, they did not have to start with a blank canvas. The purpose of the MVP was to validate whether they should continue pursuing this idea, or if they need to try something else. So they only included the absolute minimum set of features with which they could launch a free app and hopefully gain traction. But they also made sure that early users could;

• Achieve their primary objective when installing such an app (aka add a WhatsApp chat button to their store)
• Customize the bare minimum necessary to make the chat widget their own (the text inside the chat button)

Additionally, they learned from reading 100s of reviews on other apps that Shopify merchants greatly valued ease-of-use. If they could click one button to achieve their objective, that’s the best solution. And so they focused on designing an app where merchants only had to enter their phone number and click on a button labeled “Enable”.

Their goal was to acquire users organically, so they made sure the app store optimization was right. That included a clear and specific name that matched the user’s search terms; and a crisp listing page with catchy screenshots and description text

The MVP of the app was titled “WhatsApp Chat Button” because that’s precisely what users wanted to add to their store. Hence the URL of the app ends with /WhatsApp-chat-button.

In 40 days, they had 2,000+ users, got featured on the Shopify app store, and launched the first paid plans. In the following 30 days, they crossed $400 in MRR, and validation was complete. They knew they were on to something.

To this day, they haven’t explored other channels of growth or customer acquisition. No ads, SEO, or partnerships yet. Their takeaway when it comes to user acquisition is to build one major channel of customer acquisition that works brilliantly for you (for them, the Shopify app store), that’s better than having 5 channels that are somewhat working.

Adrian Tobey realized there was a significant gap in the WordPress ecosystem for an integrated CRM and marketing automation tool while working at his parents' digital marketing agency. He frequently encountered frustrations with existing solutions, particularly Infusionsoft, which had clunky and outdated web forms. This pain point inspired him to initially create a simple solution for better forms, which evolved into a broader vision.

To validate his idea, Adrian engaged with the WordPress community and his network of agency clients, identifying recurring issues and gauging interest in a comprehensive solution. He built the initial version of Groundhogg himself and released it to gather user feedback. The positive response and constructive criticism helped him refine the product, making it more robust and user-friendly.

Challenges like customer skepticism and the complexity of educating users about the new self-hosted CRM model were significant. However, Adrian relied on organic growth strategies like podcast appearances and engaging in industry-specific groups, which also offered crucial user feedback. The key lesson was the importance of directly addressing identified customer needs and continuously iterating based on real-user experiences.

Adrian Tobey, the founder of Groundhogg, developed the minimum viable product (MVP) over the course of three intense months from August to November 2018. Utilizing his deep familiarity with WordPress and his skills from previous projects like FormLift, he built the self-hosted CRM and marketing automation tool directly as a WordPress plugin. The MVP included essential features such as a CRM, an email builder, a user journey map, and reporting functionalities.

The initial development phase was arduous, filled with numerous coding challenges and debugging sessions to get the product to a stable and usable state. Adrian had to quickly iterate on feedback and constantly improve the software’s user experience and interface. His initial prototype was janky and had a subpar user experience, but it worked for its intended purpose. This rapid development and iterative process helped him launch the first version of Groundhogg to early users, who provided crucial feedback for subsequent improvements. By focusing on solving real pain points and leveraging his knowledge of the WordPress ecosystem, Adrian efficiently built a product that quickly attracted hundreds of customers.

Podcasts

Adrian reached out to many podcasters and requested interviews. These podcast appearances became an excellent organic way to drive traffic to the Groundhogg website. It didn't cost money, just time, and Adrian did as many as possible. This strategy brought significant attention from the WordPress community and supplemented their initial marketing efforts effectively.

Why it worked: Podcasts offer a direct way to appeal to specific industry communities. By participating in WordPress-related podcasts, Adrian tapped into an already interested audience. His presence on these platforms built credibility and trust, driving traffic and sales from highly relevant listeners.

Industry Facebook Groups

Adrian actively contributed to key industry Facebook Groups. Some group owners even asked for a "group deal" for his product, which he provided at the beginning. This proved to be a winning low-cost strategy to introduce Groundhogg to potential customers in a trusted environment.

Why it worked: Industry-specific Facebook groups gather people with a common interest, making it easier to reach a targeted audience. Offering group deals encouraged communities to support and try the product collectively, leveraging the influence and trust within these groups.

Groundhogg Academy and Ongoing Training

Adrian created the Groundhogg™ Academy on LifterLMS, populated it with Quick Start courses, and made it free to all users. He also conducted Live Weekly Office Hours every Tuesday, providing ongoing training and support.

Why it worked: Offering free, high-quality training materials and live support significantly increased customer success and satisfaction. It made it easier for new users to get started, reduced churn, and fostered a community of informed and engaged users.

Certified Partner Program

Groundhogg developed a Certified Partner Program, including digital marketing agencies who implement Groundhogg for their clients. This program offered partners training and a recurring commission of up to 30%.

Why it worked: This approach leveraged the existing customer base and market reach of digital marketing agencies. By providing a strong incentive through a 30% commission, Groundhogg motivated these partners to promote and implement their software widely, driving significant growth and sales.

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.

I came up with the idea when I was working on a project for deploying applications for a company and found it incredibly time consuming. I did some research on solutions and found there was space for a cheaper solution that focused on simplicity and ease of use. The other major competitor required a sever to host the application on so I focused on building the product as web app. My background is in IT administration, focused on End User Compute. Our idea was validated by releasing the product for free and announcing it via a carefully curated post on Reddit (made by co-founder Dale).

First was mapping out the design for an MVP, working out how to build the front-end application and backend workflows with relatively low coding experience. We decided on using BubbleIO to build the front end, while the backend workflows were built with on Azure and Github Actions. We also use many SaaS solutions like SendGrid, Gleap (chatbot), Monday, GPT Team and many others. The starting costs were extremely low thanks to free tier SaaS solutions. This allows us to slowly scale up and validate the MVP before going all in. The business received a small advancement from Dale and then we were able to cover costs with income as we expanded. It took roughly a year to build the MVP to a point I was happy with it, it proved to be much more difficult than I thought to build the solution. There were many late and stressful evenings trying to get things to work as I wanted but there were also many exciting moments like landing our first customers and positive feedback as well as our first pay check. Devlopment really sped up with the advancement of AI which assisted in a lot of the coding for new features.

My image

My image

While we initially grew Pckgr using a reddit post. We have since expanded into working with Microsoft MVPs who run YouTube channels or blog posts and have been able to show demos of the product to their subscribers. Since working with these professionals, we have seen a massive growth in our customer base. We also run a private Facebook group with over 1k members where we share new features and updates we are working on. We also have a budget for running ad campaigns but its been hard to track the metrics of how much this is leading to paid subscriptions.

My recommendation to entrepreneurs is to find a niche in the market of something you are good at. Build a working MVP and then share your work on Reddit, offering the service for free. Be prepared for harsh and sometimes downright mean feedback but it's the best way to get your product out there for free.

Leandro, a former freelance software developer from Buenos Aires, pivoted from freelancing to building Sync2Sheets, a tool syncing Notion databases with Google Sheets. Launched rapidly in just two weeks, the product now boasts $9k MRR and over 400 paying customers, including Canva and Wix.

The first version of Sync2Sheets was built by repurposing code from a previous project that synced data from Mercado Libre to Google Sheets, adapting it to work with the new Notion API shortly after its release. The core technology stack included Firebase for hosting, cloud functions, and Firestore to power the backend and API, which fit naturally with Google Workspace Add-ons. For the user experience, a significant effort went into mapping Notion database properties to Google Sheets, using features like conditional formatting and data validation to mimic Notion's display and interactivity within Sheets, while ensuring edits or column reordering by users would not disrupt syncing. Development of the MVP took just two weeks from start to store submission, but a major last-minute bug was discovered in production where the last row would be overwritten—this required a quick fix just before launch. The final steps involved OAuth review and marketplace submission, which the founder noted as an involved process.

Reddit and Facebook Groups The founder actively posted tutorials and product videos in Notion-related Facebook groups and the r/Notion subreddit, as well as replied to relevant questions using alerts from F5Bot to mention Sync2Sheets when appropriate. This channel generated early visibility and around 15 installs per day in the initial stage. Why it worked: Leveraging engaged communities let Sync2Sheets target users who had a clear need for Notion-Sheets integration, driving qualified initial traffic and installs.

YouTube SEO After observing that the search results for "Notion Google Sheets" were mostly video, the founder produced a targeted YouTube tutorial. This video was specifically designed for people searching for those keywords and led to noticeable referral traffic. Why it worked: Video search demand was high for this use case, so directly addressing keyword intent with a demo video captured ready-to-convert users.

Removing the Free Plan A year after launch, Sync2Sheets removed its free plan and switched to a paid-only product with a trial period. This change resulted in sign-ups rising from 15 to over 40 paying customers a month and reduced churn because users were less likely to cancel without a free fallback. Why it worked: By requiring payment for ongoing use, only genuinely interested customers converted, improving both revenue and retention.

Max Sinclair met his co-founder at a founder speed dating program in Toronto. Seeing the potential of Stable Diffusion's AI for e-commerce, they launched Ecomtent, which now boasts a 25% MoM growth rate and $100K ARR.

The first version of Ecomtent focused on generating AI-powered lifestyle product images. The CTO built the initial MVP using the then-new Stable Diffusion model, training custom AI models for each individual product. This process required customers to provide 5–10 images per product, with significant manual effort from the team to train each model—making scaling difficult. Early prototypes suffered from typical generative AI issues: about 85% of the images included unusable distortions and hallucinations. After launching this version, the founders quickly iterated based on customer feedback, building a second MVP by late April that solved the scalability issue, reduced model hallucinations, and eliminated the need for many input images. The product’s foundation now centers on more automated, less labor-intensive generation and uses proprietary improvements on top of Stable Diffusion.

Founder Sales / Direct Outreach Initial customers were acquired directly via the founder’s industry network and through personalized outreach. The founder created a list of top targets and secured warm introductions using LinkedIn and existing contacts. Why it worked: Leveraging personal relationships and industry credibility led to faster trust-building and higher conversion rates early on, even before significant brand awareness existed.

Word of Mouth Word of mouth grew organically as customers had positive experiences and referred others. This was visible as an increasing source of new customers after the initial network outreach. Why it worked: Happy customers in a niche B2B space, especially decision-makers like Heads of Ecommerce, shared the tool with peers, creating credibility and lowering acquisition costs.

SEO The team published in-depth, helpful content on their blog, resulting in a viral post that spiked daily homepage visits from about 50 to 2,700 and improved their Google ranking from #17 to #7. Why it worked: Targeting fresh, people-first content addressed highly relevant search intent, significantly boosting organic reach and credibility with a broader audience.

Simon, the founder, started his eCommerce business with a 5K EUR investment inherited from his grandmother. After successfully creating several brands and generating over 150M+ EUR in revenue, he identified the need for a SaaS solution for SMS marketing and cart abandonment recovery in the competitive EU eCommerce market. This led to the birth of CartFox.io, which aims to become their flagship product within a year or two.

The founders began building CartFox.io by meeting with their in-house development and engineering team to explore technical possibilities. They used plain PHP—without any frameworks—to write a high-performance backend, focusing on features needed for their own eCommerce brands. The first MVP was developed and designed over several months, directly integrating with their shops for early real-world testing. Since their team already had experience with various eCommerce platforms, they were able to implement essential functions quickly and iterate based on feedback from actual store usage. One notable challenge was ensuring the product integrated smoothly with platforms like WooCommerce, Shopify, PrestaShop, and Magento, all of which they supported from early on for wider usability.

Cold Outreach via LinkedIn & Social Media They directly contacted local and regional eCommerce store owners through LinkedIn and other social media channels, allowing for personalized demos and relationship building. Why it worked: This channel created immediate, trust-based conversations with potential users in their target demographic, converting initial interest into active customers, especially in regions where the team had strong networks.

Industry Conferences & Networking CartFox attended regional events such as the Balkans eCommerce Summit in Sofia and regularly sought out in-person meetings across Europe to connect with eCommerce business owners. Why it worked: Face-to-face interactions at industry-focused gatherings helped establish credibility and trust, putting the product in front of decision-makers within the target market.

Product-Led Onboarding (Demo Trials) They offered live demos and hands-on onboarding, encouraging prospective customers to test the platform before making a decision. Why it worked: Letting prospects see the product function in real environments reduced uncertainty and made the value proposition clear, pushing hesitant leads over the line.

Paid Ads (Abandoned) They experimented with Google Ads and Meta Ads but found these channels ineffective for CartFox and soon discontinued them. Why it worked/failed: The offering was too niche for broad ad targeting, making direct outreach and industry engagement more effective in reaching relevant customers.

He used Shopify Facebook Groups and communities to read people’s problems and questions, add comments, and start conversations. It’s a long job that only a few people want to do, but it works.

At some point, Matt found 3 people who wanted the same thing but it didn’t exist in the Shopify App Store. They wanted features from a bundled app that didn’t exist. And if 3 people want it, maybe there are more.

Built the first working version in 14 days. Once it was launched, reached $3K in MRR. And by December they already hit $10K.

The widget was coded using HTML, CSS, and Javascript. He used Shopify API with the “script tag” endpoint so that the widget could be loaded into Shopify stores. It wasn’t that complicated, learned how to do it in 2017 and Shopify became better at creating documentation.

Started with the widget and not the dashboard because it was not important initially. It allowed him to show people he was working on something. They didn’t care about the dashboard. They cared about how it will appear on their Shopify Store.

Then he finished the dashboard, and in 14 days, a first version was ready and working.

The first users were the ones from the Facebook Group, and then he kept contacting people who commented and posted in the communities. They slowly grew that way, and after a couple of months, they started to have real traction when they launched the business with influencers and the Shopify App Store.

By offering 30% for every user referred, they had influencers posting on Instagram, sending emails, creating YouTube videos, etc. about the app.

JR and Leng came up with the idea for Beam Analytics when they saw that Google Analytics was deemed not GDPR compliant. They wanted to create an affordable alternative that prioritized GDPR compliance and user privacy while offering valuable web analytics. After doing extensive research and drafting a product requirement, they launched Beam in January 2023 and have been steadily attracting and retaining customers through social media, blog posts, and partnerships.

The development of Beam Analytics involved a well-planned engineering and design process that aimed to create a polished product suitable for GDPR compliance and enhanced analytics functionalities. The team utilized a robust tech stack starting with ClickHouse for data processing, leveraging TinyBird for a managed service to avoid infrastructure maintenance. They employed Vercel and Supabase to facilitate the front-end and back-end processes, respectively, and chose Hertzner servers to ensure their data stays within EU borders. The product design was informed by a professional designer to enhance its visual appeal, with the name and logo brainstorming leading to Beam, symbolizing the illumination through data. The build phase incorporated designing funnels and cohort retention for advanced analytics, with legal research ensuring GDPR compliance. Despite the groundwork laid by their previous experiences with Flurly and GraphJSON, the process was challenging in managing costs and legal nuances, taking approximately three months from initial concept to product launch.

Twitter

Beam Analytics effectively utilized Twitter as an initial launch platform. They crafted a Tweet thread to announce their product, which helped them gain early traction. With only 4k followers, the Tweet achieved just under 30k views, demonstrating the power of engaged followers and word-of-mouth marketing.

Why it worked: Twitter allowed them to reach both direct followers and a broader audience through retweets and engagements. The personal approach of engaging directly with users searching for Google Analytics alternatives also helped in creating genuine interactions and gathering feedback.

Content Marketing and SEO

Before their launch, Beam Analytics prepared several blog posts focusing on their GDPR compliance and unique features like funnel analysis. They aimed to boost their search engine visibility and provide detailed answers to potential questions from users.

Why it worked: Consistent content helped establish their authority in the market, especially concerning GDPR compliance. This approach also built a foundation for SEO, targeting users who might be searching for GDPR-compliant analytics tools.

Community Engagement

Beam Analytics also engaged users on platforms like Hacker News. They solicited feedback, which increased traffic to their site, although with mixed results in conversion rates.

Why it worked: Community engagement provides invaluable feedback and exposure to tech-savvy audiences actively seeking new tools. Although conversion was initially low, such engagement helps in refining product positioning and gaining lasting users interested in their developments.

Affiliate Marketing

The company started experimenting with affiliate marketing through platforms like Rewardful and later switched to Reflio due to cost considerations. This effort is aimed at leveraging user networks to broaden Beam Analytics' reach.

Why it worked: Affiliate marketing taps into the power of networks where existing users recommend Beam to others. This form of marketing can result in authentic endorsements and expand user base incrementally as it benefits both referee and referrer.

Saurav Pathak, the Chief Product Officer of Bagisto, came up with the idea for the open-source e-commerce platform after realizing there was a huge gap between demand and supply for platform-driven e-commerce solutions. With the goal of making it simple for developers to create their own online stores, Bagisto has generated over $1 million in revenue and has a user base of 200,000.

The founders built Bagisto as an open-source e-commerce platform, choosing Laravel as the framework for its active global community and ease of adoption. The initial development centered on building a minimal viable product (MVP) with only basic e-commerce features to keep things as simple as possible for end users. Early development was iterative: they faced challenges in convincing merchants to trust a new open-source project from India, and had to address technical and credibility concerns as they updated the code and fixed issues reported via community feedback. All development utilized the Laravel PHP framework for backend, and standard open-source tooling (such as GitHub for version control and issue tracking). The team released their MVP on October 31, 2018—so the timeline from project ideation to the first working version was several months. Continuous engagement with the community for bug fixes, updates, and live support played a key role in maturing the product quickly after the initial release.

Developer Community & Open Source Platforms The team listed Bagisto on open-source directories and developer-centric sites like Product Hunt, Betapage, and GitHub, helping them reach an audience already interested in software tools. User feedback and contributions via GitHub rapidly improved the product and generated early adoptions, leading to over 5,000 GitHub stars, 70,000+ downloads, and a contributor base of over 150. Why it worked: Reaching out directly to the developer ecosystem ensured early adopters could easily discover, try, and improve the product, creating foundational word-of-mouth and grassroots traction.

Content Marketing & Tutorials Bagisto created video tutorials demonstrating how to use and customize the platform, which helped users get started and solve problems independently. These were distributed via their website and social channels. Why it worked: High-quality, educational content lowered the barrier for new users, enabled self-service adoption, and strengthened trust with developers.

Tech Media Coverage (Laravel News Feature) A strategic turning point was the feature on Laravel News, a high-visibility platform in the Laravel and PHP community. After this exposure, daily website users jumped from about 100 to 300 within a year and spiked organic growth. Why it worked: Third-party validation from an authoritative Laravel community source instantly exposed Bagisto to high-intent audiences, catalyzing adoption and credibility.

Search Engine Optimization (SEO) From early on, Bagisto focused on content publication and optimizing their site for search, which helped improve rankings and discoverability on SERPs for relevant queries. Why it worked: Capturing organic search intent brought in a steady flow of traffic from people researching e-commerce solutions and Laravel-based platforms.