When I was 17, I learned about paid ads; I just turned 27, so that's almost 10 years ago. At that time, managing pay-per-click advertising campaigns was a niche skill that not many people knew, yet it completely captivated me. What particularly stood out to me was the ability to test the market with a low budget, gauging the reception of a product or service. This approach was a game-changer for me, offering unprecedented access to data-driven decision-making for entrepreneurs.
This interest led me down a path of data-driven decision-making over the past 10 years. At 19, I started my own agency (ewmnow.com), where I gained critical insights and analytics from my clients. This experience allowed me to form equity partnerships with several top-performing Direct-to-Consumer (DTC) brands.
As I gained greater insight into the broader market, I became interested in expanding my agency's services into software, aspiring to launch my own product.
After working with numerous software clients, I felt ready to develop my own software, but the crucial question remained: What software should I create?
- Hire a few market analysts to identify the top 20 software ideas.
- For each idea, have my agency develop:
UI/UX and prototype flows.
Animated video advertisements.
Landing pages selling the SaaS.
- Deploy fixed-budget, omni-channel paid advertising campaigns.
- Analyze the results with the analysts to determine the most viable idea based on market receptiveness, CPA/LTV ratio, and TAM/SAM/SOM.
- Develop and bring the most viable product to market.
Looking back, this was an excellent plan. However, I ended up building ViableView instead.
Instead of choosing the most logical approach to immediately maximize my return on investment, I opted for an innovative idea: creating a market data aggregator and AI model. This model would scan the entire market, run profitability simulations, and determine the TAM, SAM, and SOM, all without needing any prototype development or advertising tests.
After conceiving this idea, I searched the web for existing solutions, only to find, to my surprise, that none existed. Most market analysis tools were highly segmented, focusing on single markets, and many didn't calculate SAM or offer a way to target SOM. Moreover, they didn't offer profitability simulations with CPA/AOV market data and often required expensive yearly contracts.
Current offerings are inadequate and not ideal for smaller entrepreneurs. I recognized an obvious problem waiting to be solved, and I was determined to be the one to solve it.
I embarked on a quest to build the ultimate AI-Powered, Data-Driven Market and Product Analysis tool.
This journey was challenging. Knowing my limitations, I hired a team of experts. After a rigorous selection process, I built a formidable data team comprising Data Scientists, Engineers, and ML practitioners.
Initially, I wanted to analyze the SaaS market, but I soon expanded my vision to include every market.
But before finalizing our initial focus, I took one more look at the market to identify a sector lacking in data and analysis tools for entrepreneurs, ensuring our first step was in the right direction.
This led me to Digital Downloadable Products.
Over the past six months, I've had the privilege of leading our data and development team, guiding us towards creating what we have today.
ViableView has since become a pioneer in the digital product market. We are the first and only platform offering comprehensive data aggregation modelling simulation, and market analysis in this rapidly growing billion-dollar sector. Our approach provides entrepreneurs with unparalleled insights into downloadable digital products, setting a new standard for data-driven success.
Over the next two months, we plan to expand into physical products, then SaaS, and finally real estate and commodities before the end of 2024. Bringing my vision full circle to build the ultimate AI-Powered, Data-Driven Market and Product Analysis tool, not just in one market, but across all sectors.
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