One bot reads
the five and one stars.
Here is one of my most powerful automations. It reads the market before I build a thing. I give it a niche, and a reasoning model finds my competitors on places like Amazon and lands on the right categories. Then it reads only the polar reviews, the five star and the one star, because the neutral middle says nothing. The five stars tell me what buyers loved, so I include it at all costs. The one stars tell me what was missing, what broke, and which promises were not kept, so I add the gaps, avoid the faults, and use them in my copy to stand apart. A pricing algorithm suggests a fair price. In minutes I have a clear picture of the winning product, instead of a survey that costs money and delays my launch.
Stop guessing what to build. Let the market tell you.
Most people build a product on a hunch, then hope it sells. The careful ones run a survey, which costs money and pushes the launch back weeks. Both are slow, and both can be wrong. So I built a bot that reads the market instead. I give it a niche, it finds my competitors, and it reads only the five and one star reviews, the ones that carry real signal. It hands me what to include at all costs, the gaps rivals left open, the faults to avoid, and a fair price. Here is who it is for, what goes wrong without it, how it works, and what you get back.
Who it’s for
Anyone about to launch a product, a book, a course, or an app, and anyone upgrading one they already sell. If you are guessing what to build or dreading a slow survey, this is for you. It works even if you are new, because you give the bot a niche in plain words and it reads the market on your behalf.
What goes wrong
Without it, people add features they personally like, not the ones buyers actually want. So the product misses. You are not short on effort. You are missing the one thing every five star buyer loved, and the gap every one star buyer wished someone would fill.
How the bot works
You give it a niche. A reasoning model finds the rival products, reads only the five and one star reviews, and splits them into include and avoid. Then it prices it. You do not run a survey or read a thousand reviews yourself. The bot hands you the picture, sorted.
What you get back
A clear picture of the winning product, in minutes. A proper market survey costs a few hundred to a few thousand and takes weeks, so replacing it with a few minutes, then reusing the bot on every product and every upgrade, adds up fast.
I did not want to survey the market for weeks. I wanted the answer in minutes.
This is one of my most powerful automations, and it fixes the riskiest part of any launch, guessing what to build. The usual fix is to survey people to learn what they want and what they will pay. That takes time, costs money, and pushes your launch back. So I built a bot that skips the survey and reads the market instead, using the people who already voted with their wallets.
You give the bot a niche, and that is all. A reasoning model is smart enough to find your competitors on places like Amazon, land on the right categories, and pull up every rival product. If I am writing a book, it finds every book in that same category. It gathers the products first, then it goes to work on the proof that actually matters, the reviews left by real buyers.
Reviews come from people who bought and cared enough to speak, so that is my exact audience. The bot ignores the neutral three star reviews and reads only the extremes, the five star and the one star. The five stars tell me what buyers loved, so I include it at all costs. The one stars tell me what was missing, what broke, and which promises were not kept.
Then it does more than sort. It runs a pricing algorithm to suggest a fair price buyers are willing to pay, and it flags the odd feature that everyone quietly loved, the one I might have called secondary. Often that is the main thing to build around. It also shows the padding nobody uses, so I can ship a simpler, slicker product with fewer features that people genuinely want.
Here is how I make money from it. I build a winning product from the start, because the market has already shown me what to include and avoid, and that lifts conversion on the same traffic. I can run the same research for other companies as a premium service, since every business needs to know what its audience wants. And I teach the whole method inside my mastermind. Same bot, three income streams.
Proof point: the numbers here are kept deliberately modest, and I have documented how I run my business on autopilot on YouTube, in my income streams breakdown, so the conservative figures on this page are checkable. I count only the small lift a market-tested product gives to sales I would have made anyway, plus the survey money and weeks it saves. Small edges, compounding across many launches, turn into real money.
Three moves that turn competitor reviews into a winning product
What made this work was refusing to guess and refusing to survey. The market has already spoken about what it wants, out loud, in the reviews on your competitors’ products. The trick is to read the right ones. Most reviews are noise, but the five star and one star reviews are pure signal. First you read only those extremes. Then you split them into what to include and what to avoid. Then you price it and sharpen the copy around the gaps. Read the extremes, split the signal, price and aim. Get the first two right and the product almost designs itself.
Read only the extremes
The first move decides everything, and it is the one most people get wrong. They try to read every review, drown in the neutral middle, and give up. A three star review is a shrug, it tells you nothing. The signal lives at the poles. The five star reviews come from buyers who loved the product enough to praise it. The one star reviews come from buyers who were let down enough to warn others. Both groups are honest and specific. Read only those, and you cut a thousand reviews down to the handful of truths that decide whether your product sells.
Split the loves and the gaps
The second move turns those truths into a build list. From the five stars you pull what buyers loved, and that goes on the include at all costs list, because it is proven to earn praise. From the one stars you pull two things, the gaps buyers wished were there, and the faults that broke the promise. The gaps become features you add so your product does what the rivals failed to do. The faults become a list of what to never repeat. Do this and you are no longer guessing, you are building the exact product the market already asked for.
Price it and aim the copy
The third move is the one that pays off twice. First, a pricing algorithm reads what buyers actually paid and complained about, and suggests a fair price they are willing to meet, so you do not leave money on the table or scare them off. Second, the faults you found in the one star reviews become your copy. You tell buyers, plainly, that your product does not have the problem the rivals have. That is how you differentiate without bragging. You simply promise the thing your competitors kept breaking, and you keep it.
Once the method is running, product research stops being a slow, expensive guess. You read only the extreme reviews, you split them into what to include and what to avoid, and you let the pricing and the copy fall out of the same data. Because the product is built on what buyers already said they wanted, it converts better on the same traffic and the same list. You ship a winner, you reuse the bot on every product and every upgrade, and every small lift on every sale quietly adds up. That is how a bot that reads reviews turns a risky launch into money you keep.
Before the system
- Building on a hunch and hoping the market agreed
- Paying for a slow survey that pushed the launch back
- Adding features I liked, not the ones buyers wanted
- Repeating the same faults my competitors were slated for
- Guessing at a price and leaving money on the table
After the system
- The market read in minutes, from real buyers
- What every five star buyer loved, built in
- The gaps every one star buyer wished were filled
- The faults to avoid, and the copy that says so
- A fair price buyers are already willing to pay
Prompt 1: find the competitor products in your niche
Before you read a single review, you need the right products to read. The biggest mistake is looking at the wrong shelf. Use this prompt to have a reasoning model find your true competitors and the exact categories they sit in.
The rival finder
Act as a market researcher with strong reasoning. I want to find the products that truly compete with what I plan to sell, and the categories they live in. About my niche: [describe in plain words what you plan to sell and the market it is for]. Find the rivals: reason your way to the best selling and most reviewed competing products on marketplaces like Amazon, name the exact categories and subcategories they sit in, and for each product note its rough price and how many reviews it has. Give me the shortlist worth reading, and why each one earns its place.
The output is the exact shelf to study. Get this right and every review you read after is from a real competitor, so the signal you pull is about your market, not a lookalike one.
Prompt 2: read the five star reviews for what to include
The five star reviews are where buyers tell you what they loved. The system works because it builds those loves in at all costs. Use this prompt to pull the include list from the top reviews of your rivals.
The include list builder
Act as a review analyst. I want to know what buyers loved most about my competitors, so I can build it into my own product. About the rivals: [paste the shortlist of competitor products from prompt one]. Read only the five star reviews: pull out what buyers praised again and again, the features and moments they loved, and the words they used. Rank them by how often they came up, flag any surprise feature that buyers loved but you would not have guessed, and give me a clear include at all costs list.
The output is a proven include list, drawn from buyers who were happy enough to speak. Build every one of these in and your product starts from what the market has already applauded.
The 3-minute overview of how this works
Before the build steps, watch this short overview. It’s the exact video from the Automations Made Easy page, and it walks through the mechanics behind machines like this one. 1,000+ students have used these mechanics to save two hours a day, with zero coding.
Want to learn the mechanics behind a bot that reads the whole market for you?
I teach the same mechanics that power this reviews analyzer inside Automations Made Easy. 1,000+ students have used these mechanics to save two hours a day and build little machines that quietly handle the boring work. No coding required.
Week one: your rivals found, the reviews read, your winning product mapped.
Most people put off product research because it feels enormous, so they either guess or pay for a slow survey. That is exactly why this matters. Research is meant to start with the reviews that already exist, not a survey you build from scratch. In week one you give the bot a niche, watch it find your rivals, and read only the five and one star reviews, so you trust the picture before you build a thing on it.
Week one looks like this. On Monday you give the bot a niche and let it find the competing products. Then you have it read only the five star reviews and hand you the include list. By midweek you point it at the one star reviews for the gaps and the faults. By the end of the week it has suggested a fair price and a differentiation angle, so you are holding a mapped, winning product instead of a hunch.
The point of the first week is not how many reviews you process. The point is to confirm the bot finds the right rivals, reads only the extremes, and hands you an include list and a gap list that ring true. Once that is locked, the price and the copy fall out of the same data, and you can map a winning product in minutes that would have cost you weeks and a survey budget.
From there the maths is simple and conservative. A proper market survey costs a few hundred to a few thousand and takes weeks. I count only the small lift a market-tested product gives to sales I would have made anyway, plus that survey money saved on every launch. That lift is modest on one product, but the product keeps selling for years, and I reuse the bot on every new one and every upgrade. Over three to five years, those small edges stack across many launches and quietly compound into real money.
All of this runs while you work, sleep, or plan the next product. You give the bot a niche, and it finds the rivals, reads the extreme reviews, splits the loves from the gaps, and prices it. No more guessing what buyers want, no more paying for a slow survey, no more repeating the faults your competitors are slated for. You get a clear picture of the winning product, mapped and priced, set to sell.
Prompt 3: read the one star reviews for gaps and faults
The one star reviews are the goldmine most people are too squeamish to read. They hold the gaps and the broken promises. Use this prompt to pull the two lists that matter, what to add and what to never repeat.
The gap and fault finder
Act as a review analyst. I want to know what let buyers down about my competitors, so I can fill the gaps and avoid the faults. About the rivals: [paste the shortlist of competitor products from prompt one]. Read only the one star reviews: split the findings into two lists. First, the gaps, what buyers wished was there and expected but did not get. Second, the faults, what broke and which promises were not kept. For each fault, write one line I could use in my copy to promise I do not have that problem.
The output is your gaps to add and your faults to avoid, plus ready copy lines that set you apart. This is how you build the thing the rivals failed to, and say so, without bragging.
Prompt 4: set a fair price and your differentiation
The product is only a winner if it is priced right and positioned clearly. The last move turns the review data into a price and a angle. Use this prompt to suggest a fair price and to sharpen how you stand apart.
The price and position setter
Act as a pricing and positioning strategist. I have my include list, my gaps, and my faults from the competitor reviews, and I want a fair price and a clear angle. About the market: [paste the rival prices, the include list, the gaps, and the faults you found]. Set the price and the angle: based on what buyers paid and what they complained about on price, suggest a fair price they are willing to meet and explain the range. Then write my one line differentiation, the single promise that answers the biggest fault my competitors kept making.
The output is a fair price and a sharp angle, both drawn from what buyers already said. Now you know what to build, what to charge, and what to promise, all from reviews you read in minutes.
The exact build, step by step
You give the bot a niche
Start with one line, not a research brief. You tell the bot the niche you want to sell in, and that is the whole input. There is no survey to write, no audience to recruit, no weeks to wait. This single change is what removes the cost and the delay, because the hard step is now just naming your market honestly. When that is all it takes to begin, you stop putting off the research and start reading the market the same day.
It finds your competitors’ products
Here is where the reasoning earns its place. From your niche the bot is smart enough to find the relevant products and categories on places like Amazon, and navigate to the exact shelf where your rivals live. If you are writing a book, it finds every book in that same category. It does not scrape blindly, it reasons its way to the true competitors, so the reviews it reads next are from products that really compete with yours, not lookalikes.
It reads only the five and one star reviews
Now the bot ignores most of the reviews on purpose. A three star review is neutral, a shrug that tells you nothing, so it is skipped. The bot reads only the extremes, the five star and the one star reviews. These come from real buyers who cared enough to speak, the people whose opinion is worth having. This is the step most people cannot bring themselves to do, because they try to read everything. The polarity is the whole trick, and it cuts the noise away.
The five star reviews become your include list
From the five star reviews the bot pulls what buyers loved, and files it under add at all costs. This is the proven part of your product, the features and moments that earned praise from people who paid. It often surfaces a surprise, one feature you thought was secondary that turns out to be the main thing everyone loved. That single insight can reshape what you build around. You do not guess at what matters, you build in what the market has already applauded.
The one star reviews show the gaps and faults
This is the goldmine. From the one star reviews the bot pulls two lists. First, the gaps, what buyers expected and wished was there but did not get, so you add those and do what the rivals failed to do. Second, the faults, what broke and which promises were not kept, so you avoid them and, better still, use them in your copy. You tell buyers plainly that you do not have the problem your competitors keep repeating. That is honest differentiation, drawn straight from their own reviews.
You get a fair price and the whole picture
This is the moment it all pays off. The bot runs a pricing algorithm on what buyers paid and complained about, and suggests a fair price they are willing to meet. Then it hands you the whole picture in minutes, the loves to build in, the gaps to fill, the faults to avoid, and the angles for your copy. It even tells you where you can strip padding nobody uses, so you ship a simpler, slicker product. Something that used to cost a survey and weeks is done before lunch.
Give a niche
You give the bot the market you want to sell in, one line, no survey needed.
Read the extremes
It finds your rivals and reads only the five and one star reviews, the ones with signal.
Split loves and gaps
It sorts them into what to include at all costs and what to add or avoid.
Price and picture
It suggests a fair price and hands you the whole winning product, in minutes.
Build this reviews analyzer inside the same playbook 1,000+ students use
Automations Made Easy teaches the mechanics behind machines like this one. Step by step, no code, plain English. Save two hours a day and own a bot that reads the market for you, so you spend your time building winners instead of guessing what buyers want.
The six months after I switched it on
Here is the shape of the first six months after I launched a product this bot mapped. The line tracks the extra monthly revenue from a market-tested product, the small lift it gives to sales I would have made anyway, which is exactly how better research pays off in practice.
Monthly lift from a market-tested product
Three things matter on this chart. The lift climbs steadily as the product keeps converting, not in a spike. The gains come from building what buyers already said they wanted, lifting the same traffic, not from spending more. And every one of those months runs off research the bot did in minutes and I reuse on every new product.
What other students built
I teach the simple skills behind machines like this in Automations Made Easy. Students who built their own version sent back what changed in their first month.
“I was about to spend a month and a real budget on a survey. I gave this a niche instead and had the whole picture the same afternoon. I built the product the reviews asked for, and it converted from day one.”
“The one star reviews were the goldmine I was too scared to open. The bot pulled the gaps my competitors left wide open, and I filled every one. My copy now promises exactly the thing they kept getting wrong.”
“It found a feature buyers loved that I had written off as minor. I rebuilt the whole product around it. Turns out that was the thing everyone actually wanted, and I would have shipped without it.”
“I now run this research for a couple of companies as a paid service. They pay a premium because it answers the one question that decides their launch. Same bot I use on my own products, another income stream.”
What’s inside Automations Made Easy
AME isn’t a library of pre-built automations. Every business is slightly different. What’s reusable across all of them is the underlying mechanics: how to set up little machines that listen, write, and follow up while you sleep, and how to wire the pieces together without writing code.
The program walks you through six modules: The Right Tools (the cost-effective, no-code stack I actually use), Task Selection Mastery (which automations are worth building first), Design Secrets (mapping an automation before you build it), Zero to Hero (complete beginner to confident automator), Real-World Application (we build a full automation together, end to end), and Monetization Mastery (turn the skill into a side-business).
It also includes done-for-you templates you import in two clicks, over-the-shoulder training videos, and the same playbook 1,000+ students have used to save two hours a day. No coding required. If you can copy and paste, you can build this.
The reviews analyzer: common questions
Pulled from what readers and Automations Made Easy students ask most.
Why read only the five and one star reviews?
Because the middle is noise. A three star review is a shrug that tells you nothing useful. The five star reviews come from buyers who loved the product enough to praise it, and the one star reviews come from buyers let down enough to warn others. Both are honest and specific. Reading only the extremes cuts a thousand reviews down to the handful of truths that decide whether your product sells. Automations Made Easy teaches the same focus.
Do I need to be technical or a researcher to use this?
No. You give the bot a niche in plain words, and it does the finding and the reading. A reasoning model locates your true competitors on places like Amazon, reads the polar reviews, and sorts them for you. The skill you need is knowing what you want to sell, which is exactly what the method teaches. The heavy reading and the sorting are handled the same careful way every time.
How can it find the right competitors from just a niche?
Because a reasoning model can navigate the way a person would, only faster. From your niche it works out the relevant categories and subcategories, lands on the shelf where your rivals sit, and pulls up the best selling, most reviewed products there. If you are writing a book, it finds every book in that category. You can review the shortlist before it reads a single review, so nothing is a black box.
What exactly do I get at the end?
A clear picture of the winning product, in minutes. An include at all costs list from the five star reviews, a gaps list and a faults list from the one star reviews, ready copy lines that set you apart, and a fair price a pricing algorithm suggests. It even flags padding nobody uses, so you can ship something simpler. You get a full product map, not a pile of raw reviews.
How does this actually make me money?
In a few ways. A market-tested product converts better on the same traffic, so you earn more from work you were already doing. You can run the same research for other companies as a premium service, since every business needs to know what its audience wants. And you can teach the method inside a mastermind. Small lifts on many sales, across many launches and clients, compound into real money over time.
More Money Makers like this one
Built from the same handful of mechanics. Each one captures, converts, or earns money that would have walked out the door.
Build this reviews analyzer yourself, or learn the mechanics inside Automations Made Easy.
If you want to learn the mechanics behind a bot that reads the whole market and set up your own at home, Automations Made Easy is the playbook. Step by step, no code, plain English. If you want to talk through how to point it at your niche, read the right reviews, and price the product it maps, I take a small number of consulting clients each month.
€497 one-time · Lifetime access · 1,000+ students
