Why better data will make you more money.

When I first started as a junior data scientist, I had a bit of a crisis.

I couldn’t see the value.

It wasn't clear to me how what I was doing brought actual "money" to the organization. Why the organization invested all that money to solve that problem? How does this model for predicting next year's marketing budget actually help the company earn more money? Why people are talking about data all the time?

As I worked more closely with people from different parts of the business, I began to see the bigger picture. This improved my work because I learned how to provide valuable solutions that actually solved people's problems. Instead of just playing with data, applying fancy methods, and showing "cool stuff.”

I realized that better data saves more time, expensive time. So, better data equals more money.

But not just any data—actionable, meaningful data.

Back then, "better data" meant hiring expensive data analysts or scientists to provide business insights. They would analyze information to help companies make smarter decisions and grow. For many, this has worked fine.

But today, AI has flipped the script. ChatGPT can analyze your data and give unlimited, powerful business insights 24/7 at 20$ per month. It's like having a team of data experts in your pocket, ready to help you make smarter decisions anytime you need them.

If you’re an entrepreneur, solopreneur, or just someone who wants to know how to turn AI into a powerful data analysis team, keep reading.

The Problem

Let me tell you about my friend Alex.

He’s a sharp entrepreneur who launched a tech company a few years ago. One day, over coffee, he let out a deep sigh, saying, “I feel like I’m driving blindfolded. We keep having meetings, but nothing’s moving forward. It’s frustrating—and it’s costing us a fortune.”

Alex’s frustration is familiar to many. Endless meetings, but no progress. No clear direction. It’s like steering a ship without a compass—you’re burning fuel (or money) without making any real headway.

The problem isn’t effort. It’s data.

The right data.

You might think, “I’ll just ask for more data!” But here’s the twist: more data doesn’t mean better results. Raw, unprocessed data is like dumping a puzzle on the table without the picture on the box. You’re still lost—just with more pieces to sort through.

This is where businesses bleed money. Unproductive meetings. Missed opportunities. Projects launched without a clear need. It all adds up. Fast.

What you need is meaningful data—data that guides decisions. It’s like switching on a GPS for your business. Suddenly, you know where you are, where you need to go, and how to get there.

Remember Alex? Once he got the right data in his hands, his company’s productivity took off. Later, he told me, “It’s like someone finally turned the lights on.”

So, if you feel like you’re wasting time and resources, ask yourself: do you have the data to guide you? Because in business, flying blind isn’t just frustrating—it’s expensive.

How AI Can Help

This is where AI comes in.

Think of AI as your personal data detective. It doesn’t just collect data—it finds what you didn’t even know you were missing.

AI can help you gather useful information about your competitors, your industry, and what customers want. This information can help your business make better decisions. Tools like scraper GPTs (which you can grab for free in the GPT store) can do this in minutes.

But AI isn’t just about gathering information—it can also analyze it and build predictive models for you. Feed it raw data—text documents, spreadsheets, web pages—and it spits out clear, actionable insights. Need to refine your pricing strategy? Figure out what features to add to your product? AI can guide you.

And it’s simple. You can literally drag and drop your data and ask AI questions like you’re chatting with a colleague: “What are the key trends in my sales data?” or “How do I make my course offer more competitive?”

Here’s how AI can help you tackle your data problems:

1. Data Retriever: Use AI to crawl the web, gather structured data on competitors, trends, and customer insights. Use a scraper from the GPT store.

2. Data Analyst: Ask AI to extract actionable insights from raw sources like text, documents, and web pages. Explain your problem, drag and drop data, ask your questions.

3. Data Scientist: Drag and drop data and ask AI to build a predictive model for you. It's that simple.

An example

Let’s say you run a small online business—a one-person operation selling digital courses.

Your goal? Boost sales and grow your audience.

Your problem? You have lots of content, but you’re not sure what’s actually driving engagement and revenue.

Here’s how AI can change the game for you:

Step 1: Data Retrieval from Social Media

First, you need to get your hands on your social media data—Instagram, X, LinkedIn, wherever your audience hangs out.

You want to see what’s working and what’s flopping.

How do you do this?

Go to your profile settings and click “download my data.” Now, you’ve got the raw material.

Step 2: Upload Your Data to ChatGPT

Next, drag and drop that data into ChatGPT. Now, the fun part—ask it to pull out insights that actually move the needle.

Example Prompts you can try:

• "Identify my 3 top performing posts in terms of engagement rate over the past 30 days. What common themes and format do they share?"

• “Which content—promotional or educational—gained the most traction?”

"Based on my post impression data, what are the optimal days for me to post content for maximum reach?

• “What patterns show up in my top-performing posts, and how do they tie to sales?”

• “Which topics seemed to cause spikes in traffic or course sign-ups?”

"Examine my post engagement data (likes, comments, shares) for the past 30 days. Are there any patterns in terms of topics, that consistently generate higher engagement?"

You can even combine this with other data to see how your sales posts stack up against regular content.

Step 3: Analyze Your Sales Funnel Data

Now, you need to break down your sales funnel.

Take your customer data—open rates, click-throughs, course sign-ups—and drop it into ChatGPT. Add feedback or reviews to get a full picture.

Example Prompts for ChatGPT:

• “Which emails or social posts led to the most sales?”

• “What’s the common thread between customers who bought vs. those who didn’t?”

• “Which courses or products had the highest conversion, and what marketing tactics were linked to them?”

Step 4: Get Actionable Insights

After feeding your data into ChatGPT, it will spit out actionable insights you can use to level up your strategy.

Example Outputs:

• Keyword Optimization: “Your posts on "productivity" had 40% more engagement.”
• Content Strategy: "Teaching people 'How to make money while sleeping' got 30% more likes and shares than posts trying to sell stuff."
• Sales Conversion: "Emails sent on Monday mornings with 'quick learning' in the subject line got the most opens and sales."
• Course Focus: “Your course on ‘Advanced Marketing Strategies’ had a 20% higher conversion rate than others. Consider turning it into a series or offering a premium version. Creator X and Y are proposing a similar product at 459$.”

Step 5: Implement and Optimize

Now it’s go-time. Take what you’ve learned and put it to work. Build GPTs for your most frequent types of analysis to save time. Don’t follow the outputs blindly. Use them as a strategic advantage. Whenever you hit a “what’s next?” moment, call on your Data Analytics Agents to give you that extra edge.

AI is the secret weapon for solopreneurs and small businesses. It’s the same kind of power that used to cost $5k a month, and now it’s in your pocket for $20 (and a fraction of your time).

So, try it out. Experiment. If you hit a wall, DM me.

— Charafeddine