Most people who try to create a digital product start with the wrong question:
“What should I make?”
A better question may be:
“What are people already paying for — and what do they keep complaining is missing?”
That small change can completely alter the way you create products.
Instead of sitting at your computer trying to invent the next great ebook, course, template, prompt pack, spreadsheet, calculator, checklist, or software tool, you can study products that already have customers.
Their reviews contain something extremely valuable: customers telling you what they wanted, what disappointed them, what confused them, and what they wish someone would create.
Artificial intelligence can help turn those scattered comments into product ideas.
The basic method uses three AI prompts:
- Mine competitor reviews.
- Find a recurring “pain gap.”
- Create a small product that closes that gap.
The original version of this idea sounds almost too easy: someone claims Claude created a digital product in about an hour, and the product generated enough money to cover that month's rent.
That outcome should not be treated as guaranteed. The useful idea is the process behind it.
You are using existing customer demand to decide what to build instead of building first and hoping people care later.
Here is a practical version of the method from beginning to end.
Step 1: Pick a Market Where People Already Spend Money
Do not start by asking AI for random digital product ideas.
Start with a market.
Good markets contain people actively trying to accomplish something, avoid something, save time, make money, reduce frustration, learn a skill, organize something, or produce a measurable result.
Examples might include personal budgeting, Etsy sellers, teachers, real-estate agents, job seekers, parents of young children, fitness coaches, content creators, wedding planners, Airbnb hosts, freelancers, homeschool parents, photographers, small-business owners, travelers, or college students.
You are looking for an area where people already buy tools and information.
Search places such as Amazon, Etsy, Gumroad, Udemy, app stores, Reddit discussions, Facebook groups, YouTube comments, software review sites, online marketplaces, and niche communities.
Look for products with substantial numbers of reviews.
Five competitors with hundreds of reviews can teach you far more than fifty products nobody has purchased.
Step 2: Build a Competitor List
Create a simple document containing roughly five to ten products serving the same customer.
Try to keep the products close enough that their customers face similar problems.
For example, suppose you want to make something for people selling digital downloads on Etsy.
Your competitor list could contain an Etsy SEO course, keyword research spreadsheet, listing optimization checklist, product research tool, seller planner, and listing-description prompt pack.
Do not worry if the products are different formats.
You are studying the customer problem more than the product format.
Record the product name, price, promise, target customer, key features, source page, positive reviews, negative reviews, and questions people ask before purchasing.
One particularly useful group is three-star reviews.
One-star reviews often come from angry customers or unusual circumstances. Five-star reviews tell you what buyers love. Three-star reviews frequently reveal something more interesting:
“This is good, but…”
Everything after the word “but” can be valuable.
Step 3: Use the Review-Mining Prompt
Now bring the review information into ChatGPT, Claude, Gemini, or another capable AI model.
If the AI has web access, you can ask it to research public reviews and provide the source pages it used. If it does not have reliable web access, copy actual reviews into the conversation yourself.
Never assume an AI-generated quotation from a customer is real unless you can verify it. AI systems can produce convincing text that was never written by an actual reviewer.
Here is a stronger version of the first prompt:
I am researching the market for [TYPE OF PRODUCT].
Analyze customer reviews for these competing products:
[COMPETITOR LIST]
Identify recurring patterns across the products.
Group findings into:
customer goals, common complaints, missing features, confusing parts, time-consuming tasks, reasons for refunds or dissatisfaction, desired outcomes, features customers repeatedly request, and things customers say they currently have to do manually.
Ignore isolated complaints unless there is evidence they represent a broader pattern.
Rank recurring problems by frequency, severity, urgency, and willingness to pay for a solution.
Do not invent customer quotations or review statistics. Clearly separate verified information from inference.
Finish with the 10 strongest unresolved customer problems you found.
The goal is not merely to collect complaints.
You want patterns.
If one person complains that an ebook uses a font they dislike, that probably means little.
If dozens of buyers across several products say, “This tells me what to do but doesn't show me exactly how to do it,” you may have discovered something valuable.
Step 4: Search for the Pain Gap
A pain gap is the distance between what customers want and what existing products consistently give them.
Suppose six Etsy courses teach keyword research.
Customers keep saying:
“I learned how keywords work, but I still don't know which keywords to use for my own listing.”
The market may not need another 100-page Etsy SEO guide.
It may need something much smaller:
An Etsy Keyword Decision Worksheet that takes a seller from product idea to final keyword selection in fifteen minutes.
That is the shift.
You are not asking:
“How can I make a better Etsy SEO course?”
You are asking:
“What problem remains after people buy the Etsy SEO course?”
That question can reveal far less competitive opportunities.
Step 5: Run the Pain Gap Prompt
Use a second AI prompt focused on finding the most commercially interesting unresolved problem.
Try this:
Using the competitor review research above, identify the strongest pain gap in this market.
A pain gap is a recurring problem, frustration, missing outcome, or unmet expectation that appears across multiple competing products and is still poorly solved.
Ignore unusual or isolated complaints.
Give extra weight to problems where customers:
repeatedly complain about the same issue,
lose significant time,
feel confused after purchasing,
need to buy several products to accomplish one task,
create their own workaround,
ask repeatedly for a missing feature,
or would receive an obvious financial, emotional, or time-saving benefit from fixing it.Give me the five strongest pain gaps.
For each one, provide:
Pain Gap Name
Customer Problem
Evidence Pattern
Current Workaround
Why Existing Products Fail
Desired Outcome
Likely Willingness to Pay
Simplest Product That Could Solve ItScore each opportunity from 1–10 for urgency, frequency, ease of creation, competition, and monetization potential.
Then recommend the single strongest opportunity.
This step stops you from chasing every complaint.
You want one painful, repeated problem.
Step 6: Look for the “Workaround Signal”
One of the strongest signals in product research is a customer saying something similar to:
“I ended up making my own spreadsheet.”
“I have to copy everything into Google Sheets.”
“I use three different apps to do this.”
“I created my own checklist.”
“I keep a separate notebook.”
“I wish there were a template for this.”
“I have to calculate this manually.”
Those statements can point directly to product opportunities.
A workaround proves the customer cares enough about the problem to spend time solving it personally.
Your job may simply be to turn that homemade workaround into a polished product.
Step 7: Do Not Build Yet — Validate the Gap
This is the step missing from many versions of the three-prompt strategy.
AI finding a pain gap does not mean customers will pay you.
Before spending days creating something, search the exact problem.
Look at Google searches, Reddit posts, YouTube comments, marketplace searches, Facebook discussions, forums, TikTok comments, Quora questions, and product reviews.
Ask yourself whether people describe this frustration naturally without someone leading them to it.
A strong signal looks like this:
“I wish somebody would make…”
A weaker signal looks like this:
“Yes, I suppose I might use that.”
Search demand can matter, but direct expressions of frustration may matter more for narrow digital products.
You can take validation one step further by creating a simple landing page describing the product before creating the full version.
If people join a waiting list, request access, or purchase a preorder, you have stronger evidence.
Step 8: Ask AI to Create the Smallest Gap-Closing Product
Now use the third prompt.
Do not tell the AI:
“Create an ebook about Etsy.”
That is far too broad.
Give it the exact pain gap.
For example:
We discovered this customer pain gap:
[PAIN GAP]
Target customer:
[CUSTOMER]
Desired outcome:
[OUTCOME]
Current alternatives:
[ALTERNATIVES]
Their main weaknesses:
[WEAKNESSES]
Design the smallest useful digital product that solves this problem completely.
The product should help the customer reach the desired outcome with the least possible friction.
Suggest the best format first: checklist, spreadsheet, calculator, template, swipe file, prompt pack, mini-course, workbook, database, decision tree, guide, or simple software tool.
Do not add content simply to make the product appear larger.
Create:
product concept,
product name,
core promise,
contents,
instructions,
templates,
examples,
user workflow,
common mistakes,
quick-start section,
FAQ,
and final deliverable structure.Then create the first complete version.
This is where AI can dramatically shorten production time.
A 70-page ebook might not be needed.
The best solution could be a two-page checklist.
Or a 15-column spreadsheet.
Or 25 carefully structured prompts.
Or a Notion template.
Or a calculator.
Or a small web application.
Sell the result, not the number of pages.
Step 9: Make the Product Better Than the AI Draft
Do not immediately sell the first AI output.
Use it yourself.
Try to complete the task from beginning to end exactly as a customer would.
You will quickly spot problems.
Maybe the instructions assume knowledge beginners do not possess. Perhaps the spreadsheet needs examples. Maybe the prompts produce inconsistent results. A worksheet could require clearer explanations.
Ask several people from the target market to test it.
Watch where they stop.
Watch what they ask.
Those moments reveal where the product needs work.
Your goal is not to create more content.
Your goal is to remove friction between the customer and the promised result.
Step 10: Turn the Pain Gap Into Your Marketing
Here is where this method becomes especially interesting.
The research that created the product can create the sales page too.
Suppose customers repeatedly complained:
“I bought three meal planners, but none of them create a grocery list automatically.”
Your headline practically writes itself:
“Plan Your Meals and Generate Your Grocery List in 10 Minutes.”
The pain gap becomes the marketing angle.
You can ask AI to transform review patterns into a landing page, email sequence, social posts, FAQ, product description, video script, Pinterest posts, or short-form video hooks.
Do not copy competitors' reviews or pretend their customers are your customers.
Use the themes you discovered.
Step 11: Start With a Small Price and Learn
Your first objective does not need to be making thousands of dollars.
Your first objective can be getting ten strangers to buy.
Those ten sales can teach you what no AI prompt can tell you.
What made them purchase?
What nearly stopped them?
What feature did they value most?
What was still missing?
What would they pay more for?
A $9 product can become a $29 toolkit.
A $29 toolkit can reveal demand for a $79 package.
A template can reveal demand for software.
A checklist can lead to a course.
Your small gap-closing product can act as market research for the next product.
The Bigger Opportunity: Build Products Backward
Traditional product creation often works like this:
Idea → Product → Marketing → Find Customers.
The pain-gap approach reverses much of that process:
Customers → Complaints → Unmet Need → Product → Marketing.
That distinction matters.
You are listening before creating.
AI makes the research much faster, but AI itself is not the business strategy.
The strategy is identifying repeated customer frustration that competitors have failed to remove.
The three prompts — review mining, pain-gap discovery, and gap-closing product creation — are simply tools for doing that faster.
The real opportunity lies inside sentences customers are already writing:
“I wish this included…”
“I still can't figure out…”
“I hate having to…”
“This would be perfect if…”
“I had to make my own…”
Those complaints may look negative to the company receiving the review.
To an entrepreneur, they can look very different.
They can be product specifications.
And sometimes the next profitable digital product is hiding inside the complaint everyone else ignored.
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