Your audience already
told you what to make.
Here is one of my favourite automations. To make sales, you have to make what people actually want, and guessing is hard. Most of us ask a chatbot and get a random answer, backed by nothing. So instead of guessing, I let my audience tell me. A bot watches the big creators in my space, reads every comment under each new video, and hunts for the gaps, the requests, and the content people quietly ask for. It runs the stats and hands me ranked video titles backed by real data. I approve the ones that fit my brand, and a second bot writes the script, clones my voice, builds the video, and posts it. I give people exactly what they asked for, so more of them buy.
Stop guessing what your audience wants. They said it in the comments.
To make a sale you have to put the right thing in front of the right person. The trouble is guessing what that thing is. Most people ask a chatbot for ideas and get a random list backed by no facts, then pour hours into content nobody asked for. So I built a bot that listens instead. It watches the big creators in my space, reads every comment under their new videos, and pulls out the gaps, the requests, and the suggestions people leave. It ranks the ideas by how often people ask, hands me titles backed by real data, and then a second bot turns the ones I approve into finished videos. Here is who it is for, what goes wrong without it, how it works, and what you get back.
Who it’s for
Any creator, marketer, or founder who sells to an audience and is tired of guessing what to post. If you have ever stared at a blank page wondering what video to make, this is for you. It works even if you have a small following, because it listens to the comments on the big accounts in your niche, not just your own.
What goes wrong
Without it, you guess. You ask a chatbot, you copy a trend, or you post what you feel like, and most of it lands flat. You are not short on effort. You are short on proof of what your audience actually wants, so half the content you make is a coin flip.
How the bot works
It watches the big creators in your space, reads every comment under each new video, and hunts for gaps, requests, and suggestions. It runs the stats and ranks the ideas. You do not read a single comment. The bot hands you titles ordered by how many people asked for them.
What you get back
Video ideas backed by real data, plus a second bot that turns the approved ones into finished, posted videos. A single audience survey from a freelancer runs a few hundred, and this hands you the same answers every week for almost nothing, on repeat.
I did not want to guess what to post. I wanted my audience to tell me directly.
This is one of the most efficient automations I run, and it lifted my conversion rates and my revenue. The premise is simple. To make sales you have to post what people want, and it is very hard to guess what that is. We usually ask a chatbot, which gives a random answer backed by no stats and no facts. So I decided the best way to know what people want was to ask them directly.
Here is what the bot does. It monitors a list of creators who are huge in my space, who make very useful content, and who have a large audience. It watches each new video and works out what it is about. Then it does the magic. It reads every single comment under the video, hunting for a few things: gaps, meaning things people hoped to find but did not, direct requests for a specific kind of video, and content suggestions for what to make next.
That is the signal I care about. The bot runs the stats on all of it, reasons over what people in my niche are actually asking for, and hands it to me as ready video titles I can go and create. This is not a hunch. It is what real people typed under real videos, counted and ranked, so the top title is the one the most people begged for.
Then I validate. I check which ideas fit my brand and make sense for me, because my brand, my audience, and my products are my own. Once I mark a topic as good to go, another bot writes the script for the video, the podcast, the email, whatever format I want. It compares the idea against my profile, my audience, my niche, my products, my values, and my copywriting style, then researches stats, case studies, and interesting facts to sprinkle in and make the piece sharper.
The wins stack up. I have real data, not guesswork, which raises my odds of a sale because I give people exactly what they want. I spent nothing on market research and not a second studying trends, because it comes straight from the source. I execute fast and produce a large amount of content on autopilot, and every piece carries a link to my paid programs, so it turns into revenue. I keep the numbers here deliberately modest, counting only the extra content I now ship and the small lift in conversion from making what people asked for.
Proof point: I have documented how I run my business on autopilot and the many income streams behind it on YouTube, in my 28 income streams breakdown and a real look at the daily work in a day in my life, so the conservative numbers on this page are checkable.
Three moves that turn other people’s comments into your next sale
What made this work was refusing to guess. Most people invent content ideas in their own head, then hope the audience agrees, and are surprised when half of it flops. This loop flips that. You listen to what people actually type under the biggest videos in your niche. You rank those signals by how often they come up, so the loudest need floats to the top. And you make the ones that fit your brand, on autopilot. Listen, rank, make, on repeat. That is how you post what people already asked for, instead of what you hope they want.
Listen: read every comment, not just yours
The first move is where the honesty comes from. You do not sit and brainstorm in a vacuum. You point the bot at the big creators in your space, the ones with large, engaged audiences, and it reads every comment under each new video they publish. It is hunting for three things: gaps, where people wanted something the video did not give them, requests, where they ask straight out for a certain video, and suggestions, where they tell the creator what to make next. Those comments are the most honest market research you will ever get, because people wrote them for free, unprompted, about a topic they care about. You are just the one who bothered to read them all.
Rank: let the stats pick the winners
The second move is what turns a pile of comments into a decision. A hundred scattered requests are noise until you count them. The bot runs the stats across everything it read, groups the same need said in different words, and ranks the ideas by how many people asked. What comes back is not a hunch, it is a list of video titles ordered by real demand, with the thing the most people begged for sitting at the top. This is the difference between asking a chatbot for ideas and knowing which idea your audience will actually watch. One is a guess dressed up as an answer. The other is a count of what real people said they want.
Make: build only what fits your brand
The third move is where it turns into money, and where you stay in control. You do not make every ranked idea. You approve only the titles that fit your brand, your audience, and your products, and you skip the rest. Then a second bot takes over. It writes the script matched to your profile and your style, digs up stats and case studies to make it sharper, clones your voice, picks an avatar, builds the video, adds the B-roll and effects, and posts it. Because it is modular, the same idea can go out as an email, a newsletter, or a podcast instead. You gave people exactly what they asked for, so more of them stay, trust you, and buy.
Once the loop is running, content stops being a guess. You listen to what people type under the biggest videos in your niche, you rank those needs by how often they come up, and you make only the ones that fit your brand. Every piece answers something real people asked for, so it converts better, and a second bot builds it while you approve the next one. You spend nothing on market research and produce more than the creators who are still guessing. That is how other people’s comments quietly become your next sale.
Before the system
- Guessing what to post and hoping it lands
- Asking a chatbot for ideas backed by nothing
- Paying for surveys or hours spent studying trends
- Making content half your audience never wanted
- Writing, filming, and posting every piece by hand
After the system
- Video titles ranked by what people actually asked for
- Real data from real comments, counted and sorted
- Zero spend on market research, straight from the source
- Every piece answers a need people typed out loud
- A second bot writes, voices, and posts it for me
Prompt 1: pick the creators worth listening to
The bot is only as good as the accounts it watches. The biggest mistake is listening to the wrong crowd and mining comments from people who will never buy from you. Use this prompt to build a watch list of creators whose audience is also your audience.
Watch list builder
Act as an audience researcher. I want a short list of big creators in my space whose comments will tell me what my own audience wants. About my niche: [describe your niche, who you sell to, and what you sell]. Give me the kinds of creators to watch: who has the right audience, how to tell their followers overlap with my buyers, which signs mean their comment sections are active and honest, and which accounts to avoid because their crowd will never buy. For each point, one line on why it matters.
The output is a watch list built on overlap, not follower count. Get this right and every comment the bot reads comes from someone who could actually become your customer.
Prompt 2: teach the bot what a gap and a request look like
Not every comment is a signal. Most are praise, jokes, or noise. The system works because it knows the difference. Use this prompt to define exactly what counts as a gap, a request, or a suggestion, so the bot pulls the right things out.
Signal spotter
Act as a comment analyst. I am reading every comment under videos in my niche and I want to pull out only the comments that tell me what to make next. About my content: [describe the type of content you make and the audience you serve]. Define the signals: what a gap sounds like when someone wanted more than the video gave, what a direct request for a video sounds like, what a content suggestion sounds like, and which comments to ignore as noise. For each one, give two short example comments so it is easy to spot.
The output is a clear rule for what counts as a real signal. Feed it in and the bot stops surfacing praise and jokes and starts surfacing the things people genuinely want made.
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 your market for you?
I teach the same mechanics that power this comments 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 watch list set, your first ranked ideas in hand.
Most people keep guessing what to post because building a listening system sounds like a huge project, so they never start and stay stuck brainstorming in the dark. That is exactly why this matters. A comments analyzer is meant to start small, with a handful of accounts, and grow as you trust it. In week one you set your watch list, let the bot read the comments, and get your first ranked list of ideas, so you can see the demand before you make a thing.
Week one looks like this. On Monday you list five or six big creators whose audience overlaps with yours. Then you point the bot at their newest videos and let it read every comment, pulling out the gaps, requests, and suggestions. By midweek you have a ranked list of titles ordered by how many people asked. By the end of the week you approve two or three that fit your brand and watch the second bot turn the first one into a finished video, built from a demand you can point to.
The point of the first week is not how many videos you ship. The point is to prove that the ideas coming out are real, that they trace back to comments people actually typed, and that the top one is genuinely the most asked for. Once you trust the ranking, you stop guessing forever, and every piece you make from then on answers something your audience already asked you for.
From there the maths is simple and conservative. A single audience survey from a freelancer runs a few hundred, and this hands you the same answers every week for almost nothing. Count only one extra on-target video a week and a small lift in conversion from making what people asked for. That edge is modest in one week, but it repeats, and the content keeps working for years. Over three to five years, those small gains stack across many pieces and quietly compound into real money, all from comments you did not have to write.
All of this runs while you work, sleep, or plan your next launch. The bot watches the big accounts, reads every new comment, ranks the ideas, and waits for your yes. Then the second bot writes, voices, builds, and posts the video, or sends it as an email, a newsletter, or a podcast instead. No more guessing, no more paying for research, no more content nobody asked for. You just approve the ideas your audience already handed you.
Prompt 3: rank the ideas by real demand
A pile of requests is noise until you count it. The move that turns comments into a decision is ranking. Use this prompt to group the same need said in different ways and order the ideas by how many people asked.
Demand ranker
Act as a data analyst. I have a batch of comments that ask for things, request videos, or point out gaps, and I want them turned into a ranked list of video ideas. About the batch: [paste or describe the comments you collected and the topics they touch]. Rank them: group comments that ask for the same thing in different words, count how many people asked for each, order the ideas from most wanted to least, and turn each one into a plain video title. For the top ideas, one line on the exact need it answers.
The output is a ranked list of titles backed by a real count, not a hunch. Run this and you always know which idea to make first, because the demand for it is measured, not guessed.
Prompt 4: check an idea against your brand before you make it
A popular idea is not always your idea. The last move keeps you in control, so you make only what fits. Use this prompt to weigh a ranked title against your brand, your audience, and your products before a single video gets built.
Brand fit checker
Act as a brand strategist. I have a ranked list of video ideas my audience asked for, and I want to keep only the ones that fit me. About my brand: [describe your audience, your products, your values, and what you do and do not talk about]. Check each idea: does it fit my brand and audience, does it lead toward something I sell, could it hurt my positioning, and how might I angle it to sound like me. For each idea, a clear keep or skip and one line on why.
The output is a filtered list of ideas that are both wanted and on brand. Approve these and every video you make answers a real need while still pulling people toward what you sell.
The exact build, step by step
Pick the creators worth listening to
Start with the right ears. You list the creators who are huge in your space, the ones who make useful content and hold a large, active audience whose followers overlap with your buyers. The bot watches every new video they publish, the moment it lands. This is the quiet secret to the whole thing. You are not limited to the comments on your own small account, you borrow the honest, unfiltered feedback sitting under the biggest videos in your niche. The better your watch list, the better every idea that comes out the other end.
The bot watches the video and gets the topic
Before it reads a single comment, the bot watches the whole video and works out exactly what it is about. This matters more than it sounds. A comment only means something in context, and knowing the topic lets the bot tell a real content request apart from an off-hand remark. It is not skimming a title, it is understanding the subject the way a person would after watching. That grounding is what makes the next step sharp, because when it reads the comments it already knows what people are reacting to and what a gap in this particular video would look like.
It reads every comment and pulls the signal
Now the real work. The bot reads every single comment under the video, hunting for three things. Gaps, where someone wanted a piece the video never gave them. Requests, where someone asks straight out for a certain video to be made. Suggestions, where someone tells the creator exactly what to cover next. These are the comments that tell you what people want, and they are buried among the praise and the jokes that mean nothing for your content. A human would never read them all. The bot reads every one and keeps only the lines that carry a real, usable need.
It runs the stats and ranks the titles
A pile of requests is noise until you count it. The bot runs the stats across everything it pulled, groups the same need said in different words, and reasons over what people in your niche are actually asking for. What comes back is a ranked list of video titles, ordered by real demand, with the thing the most people begged for sitting at the top. This is the moment guesswork dies. You are no longer asking a chatbot for random ideas, you are reading a measured count of what your audience said they want, turned into titles you can go and make.
You approve the ideas that fit your brand
Here is where you stay in charge. You look at the ranked titles and approve only the ones that fit your brand, your audience, and your products. Your brand is your own, so a popular idea that pulls the wrong way gets skipped without a second thought. This step is fast, because the hard part, finding out what people want, is already done. You are simply choosing which of the proven ideas are worth your name on them. Everything you approve carries a link toward what you sell, so the content you make does more than get watched, it moves people toward a sale.
A second bot writes, voices, and posts it
Once you say yes, another bot builds the whole thing. It writes the script matched to your profile, your audience, your values, and your copywriting style, then researches stats, case studies, and interesting facts to sprinkle in and make it sharper. It clones your voice, picks one of your avatars, generates the video, and adds the B-roll, cuts, and effects a videographer would. Then it posts across your channels on its own. Because it is modular, the same idea can go out as an email to your list, a newsletter article, or a podcast episode instead. You gave people what they asked for, and it turns into content and revenue without you touching it.
Watch the creators
The bot watches every new video from the big accounts whose audience overlaps with yours.
Read the comments
It reads every comment, pulling out the gaps, requests, and suggestions people leave.
Rank the titles
It runs the stats and hands you video titles ordered by how many people asked.
Make and post
You approve the on-brand ones and a second bot writes, voices, and posts the video.
Build this comments 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 your market for you, so you spend your time making what people asked for instead of guessing what to post.
The six months after I switched it on
Here is the shape of the first six months after I turned the comments analyzer on. The line tracks the extra value from the on-target content I now ship, the small lift in conversion from making what people asked for, plus the research spend I no longer pay, which is exactly how this bot pays off in practice.
Monthly value from making what people asked for
Three things matter on this chart. The value climbs steadily as more on-target content builds trust and pulls people toward what I sell, not in a spike. The gains come from making what my audience asked for, plus the research spend I never pay. And every one of those months happens while the bot reads the comments and ranks the ideas for me.
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 used to spend Sunday nights guessing what to film. Now I open a ranked list of things my audience literally asked for and just pick. My last three videos were my best because people had asked me for them in the comments.”
“The part that sold me was reading gaps from the big accounts, not my own. My following is small, so mining their comments gave me a mountain of ideas I never would have found on my own page.”
“I stopped paying for audience surveys. This hands me the same answers every week for nothing, and the second bot builds the video too. I make more content and I make the right content.”
“Knowing week one was just picking five accounts and reading the ranked list kept it simple. By month two I was posting only ideas people had asked for, and my opt-ins climbed because the content finally matched what they wanted.”
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 comments analyzer: common questions
Pulled from what readers and Automations Made Easy students ask most.
Do I need a big audience for this to work?
No, and that is the point. The bot reads the comments under the big creators in your space, not just your own. So even with a small following you get a mountain of honest requests from the exact people you want as customers. You are borrowing the feedback sitting under the biggest videos in your niche and turning it into your own content plan.
How is this different from asking a chatbot for video ideas?
A chatbot gives you a random list backed by nothing. This gives you a ranked list backed by real comments people typed under real videos. One is a guess dressed up as an answer, the other is a count of what your audience actually asked for. That difference is the whole reason it lifts conversions, because you make what people already said they wanted.
What exactly is the bot looking for in the comments?
Three things. Gaps, where someone wanted more than the video gave them. Requests, where someone asks straight out for a certain video. And suggestions, where someone tells the creator what to make next. It ignores the praise and the jokes and keeps only the lines that carry a real, usable need, then counts how often each one comes up.
Do I still control what gets made?
Always. The bot hands you ranked ideas, but nothing is made until you approve it. You keep only the titles that fit your brand, your audience, and your products, and you skip the rest. A popular idea that pulls the wrong way gets passed by. The second bot only builds the ones you say yes to, so your brand stays yours.
Does it only make videos?
No, it is modular. Once you approve an idea, the second bot can turn it into a video and post it across your channels, or send it as an email to your list, a newsletter article, or a podcast episode instead. The same proven idea can go out in whichever format suits you, so one piece of demand becomes content in several places.
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 comments analyzer yourself, or learn the mechanics inside Automations Made Easy.
If you want to learn the mechanics behind a bot that reads your market and tells you exactly what to make, Automations Made Easy is the playbook. Step by step, no code, plain English. If you want to talk through how to pick your creators, tune the signals, and wire the second bot that writes and posts for you, I take a small number of consulting clients each month.
€497 one-time · Lifetime access · 1,000+ students
