Having created multiple online ventures and reached tens of millions of users during the last 5-10 years, I am confused when realizing that many of my close friends and Finxter members believe they are “too late to the game” or they have “missed the train”.
This is for all the ambitious coders who have not yet given up on life: I’ve never seen an opportunity this big. 🚀📈
To make it simple (not easy!), let’s dive into this unique business playbook, a step-by-step approach to starting a software-as-a-service (SaaS) AI company that will work in many niches.
Read this article and get started immediately — this playbook works now and will likely work for half a decade or so.
Step 1. Identify the Unique Niche Problem
The first step in this playbook involves identifying a specific niche problem that your AI company will aim to solve. The more specific and under-served the niche, the better.
For example, you may be looking at the creation of an AI system, let’s call it foodvideos.ai, that could auto-generate YouTube videos within the food sector.
The aim is to fill a gap that few companies currently address, offering an unparalleled solution. How to find that gap? Be very specific in your niche selection and look at what other companies are already doing successfully – then niche down one level further.
Here are a few steps that can help you find a niche:
- Identify Your Interests and Passions: It’s generally more sustainable to operate a business that aligns with your interests or passions. If you care about what you do, you’ll be more committed and enthusiastic about your work, which can help you overcome challenges and persist when things get tough.
- Conduct Market Research: Analyze market trends and study your potential competitors. A deep understanding of the market will help you identify opportunities, anticipate challenges, and differentiate your business. Use tools like Google Trends, social media platforms, online forums, and other research tools to gather data and insights.
- Identify Problems to Solve: A successful business often stems from solving a problem or meeting a need that isn’t being adequately addressed by existing businesses. Try to identify problems that you can solve, needs that you can meet, or desires that you can fulfill with your product or service.
- Evaluate Profitability: A good niche should be profitable. This means that it should have enough potential customers who are willing and able to pay for your product or service. Consider the purchasing power of your potential customers, the price you can charge for your product or service, and the cost of delivering it.
- Test Your Idea: Once you’ve identified a potential niche, test your idea to verify its viability. You could do this by launching a minimal viable product (MVP), conducting surveys, or using other validation strategies. This will help you gauge interest in your product or service before you invest significant resources into your business.
- Refine Your Niche: Based on the feedback and data you collect from testing, refine your niche. This could involve narrowing it down, expanding it, or shifting focus. Remember, finding a niche is a dynamic process that involves iteration and adaptation.
You see that identifying a niche is not a one-time final step, so set aside a day or so and then just take whatever feels right in your guts! Move on with the next step and go from there.
Step 2. Capturing Unique Data
After zeroing in on the problem you want to solve, the next step involves capturing unique data that nobody else has.
In our case, it might be related to food trends, dietary preferences, visual aesthetics, or popular recipe structures. For example, you could crawl the 100 most popular YouTube food videos and extract the captions using speech-to-text Python code:
🎙️ Recommended: OpenAI’s Speech-to-Text API: A Comprehensive Guide
Your goal is to accumulate and analyze as much unique, relevant data as possible, creating a solid foundation for your AI models.
You can do web scraping to extract an initial data set from the web. Go the extra mile, make your hands dirty, ask insiders, and clean up your data set.
Create a first rough data set. It could be a folder with spreadsheets or a real database, doesn’t matter for now.
After a couple of days of aggressive aggregation of data, you’ll have gained a data set with specific useful data for a specific niche that few people in the work have.
And, more importantly, you’ll have gained a feeling for the niche and where the value is.
Step 3. Training a Superior AI Model
Armed with unique data, you then train a model that performs progressively better. The model could employ a meta-learning approach using multiple model outputs.
How does the model look? It may be something simple like a fine-tuned OpenAI API call. It may be a complex Python program that extracts value from your data using multiple steps.
In our case, it would be a pipeline to create a food video (e.g., with Python) based on a series of steps or prompts:
- Generate the text of the food video (e.g., prompting your fine-tuned GPT model)
- Generate the visuals of the food video (e.g., prompting Midjourney)
- Select some royalty music
- Put everything together in a Python project to create
.mp4video files based on user input.
For instance, it could utilize resources like the OpenAI API, harnessing the power of state-of-the-art AI algorithms to continuously improve and refine its results.
🚀 Download: Python OpenAI API Cheat Sheet (Free)
Step 4. Crafting a User-Friendly Interface
With a robust AI model in place, the next step in the playbook is to polish the user interface (UI) of your product.
The goal is to make the UI as simple and intuitive as possible, enabling users to interact with and benefit from the AI model with the least friction possible.
You can use Streamlit to set something up quickly:
🍎 Recommended: How I Created a Weekly Shopping List and Recipe App in Streamlit
A great UI can significantly enhance the overall user experience and is often a key differentiator in the market.
Step 5. Implementing a Subscription Business Model
Once you have a well-functioning AI model with a seamless UI, the next step is to implement a subscription-based business model.
You could start charging a reasonable monthly subscription fee. For our food video creator app, this could be a $99 monthly fee to create up to 99 videos (marketing message: $1 per food video!).
There are many SaaS payment providers you can choose from. With Finxter, we use Gumroad and FastSpring.
This not only creates a steady revenue stream but also ensures that you’re compensated for the continued service and updates you provide.
Step 6. Hustle to Acquire 10 Initial Customers
With a clear plan in place and a functional business model, the hustle begins to acquire your first customers.
Share your AI company URL on Reddit or Facebook groups, or run paid ads at a loss to get your first few customers.
The initial target could be as small as 1-10 customers. What’s important is to start somewhere and receive real-world feedback for your product.
Step 7. Iterate and Pivot until Reaching Product-Market Fit
Talk to your customers! Email is fine too.
Once you’ve acquired your first customers, the focus should be on constantly improving, tweaking, and pivoting your product until you achieve product-market fit. This is a pivotal moment in your journey where you realize that your product is satisfying the needs of your target market.
Step 8. Scaling Up
Having achieved product-market fit, the final step in the playbook is to scale up. There are plenty of options to do this, including online advertising, partnerships, or expanding into related niches. This is where the real growth of your AI startup begins.
In our example scenario with the $99 food video creation app, we would do the following SaaS math to scale things up:
- Churn: 5% of customers unsubscribe from our product per month
- Lifetime: 1/5% = 20 months is the average lifetime of a customer
- Lifetime Value (LTV): 20 months * $99/month = ~$2,000 is the sales generated by a customer over its lifetime.
Start buying ads to acquire leads to acquiring customers for less than your LTV. Say, your LTV is $2,000 per customer, and you pay $200 in ads to acquire a customer, you’ll 10x over 20 months. Keep scaling as long as your economies are in your favor. Improve efficiency as you go.
📈 Valuation: You can value your company at 5x annual profit, so if you have 1000 customers at $99/m, you’ll make $1.1 million in a year and your AI company could be worth $5 million, roughly speaking.
Feel free to watch my most recent video for the Discord mastermind group: 👇
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