What is the scariest part of building a product? It is not having no ideas. It is having too many ideas, with every one of them looking like tomorrow’s unicorn, until you actually build it and discover it was only fireworks inside your own head. This route is much more practical: use Semrush to set the direction, Reddit to validate the demand, RPA to automate pain-point collection, and AI to work backward toward products and content.

This is not the magical “find the trend, chase the hit, make money in three days” spell.

The usage context is clear: a master’s degree, a non-technical background, starting from zero code to build an AI product for a daughter, and publicly documenting experiments in Reddit marketing and AI growth. This method is not designed for a large company that already has a ten-person data team. It is for solo builders, small teams, and content operators who want to feel the pulse of demand from market signals.

Clawd inner monologue:
This method feels more like walking across a beach with a metal detector: a beep does not prove there is treasure underneath, but it is still more scientific than digging with your eyes closed. (￣▽￣)⁠／

Why Reddit: not a traffic pool, but a place where problems surface

Platform choice starts with the data layer. DataReportal’s social media report is used to support one judgment: Reddit’s user base has passed a certain threshold, and in some countries its “addressable users for discussion” are close to, or even above, short-video platforms. But that threshold is only written as X, without a concrete number, so we should not fill in a shiny number here.

The real point is not just that Reddit has many users. Its mechanism is unusual. In this method, Reddit works as an overseas “database of real user needs.” Not because Reddit has stronger traffic magic, but because it naturally encourages people to say their problems out loud.

On many content platforms, users scroll, like, save, and share. Those signals are useful, but they often answer only one question: did this content catch attention? Reddit is different. Many threads start with a concrete problem: something is hard to use, a choice is confusing, a scenario keeps getting stuck, or an alternative product may or may not be worth buying.

The reasons are important:

  • Visible demand: users actively describe the problems they meet, instead of only consuming content passively.
  • Deep discussion: comment chains are long, and people add, challenge, and correct each other’s views.
  • Less persona packaging: discussion does not depend on big influencer branding, so the information is closer to real usage contexts.
  • Clear topic structure: each Subreddit is already a segmented market of “people × scenario.”
  • Global and English-language context: useful for overseas demand research and validation.

So in this method, Reddit is not merely “a place to post and get traffic.” Its job is to find problems that really exist, appear repeatedly, and may be worth paying to solve; with that goal, Reddit becomes a cost-effective demand research field.

Clawd chimes in:
Reddit’s value is not “everyone is there.” It is “people explain their annoying problems there in painful detail.” For demand research, that difference is huge. Surveys sometimes produce polite answers. Complaint posts are often closer to the truth. A like is a passerby nodding. A long Reddit comment is a customer sitting down for thirty minutes and casually roasting the previous product until there is nothing left.

Step one: use Semrush to narrow the demand direction first

Then comes the question of “what to sell.” Semrush first narrows the direction of small but real demand. This step is not about finding the product immediately. It is about building a pool of candidate needs.

Two hard filters cut away the noise:

  • Low KD: choose 0-14%. KD is keyword difficulty in SEO. The lower the number, the less crowded the keyword is.
  • CPC above 0: this means advertisers are already willing to pay for the term. The actual filter in this workflow is > 0.01.

Put together, the meaning is clear: look for places that are “not unwanted, but not yet flattened by an army.” CPC > 0 is used as a commercial signal, meaning advertisers are already willing to pay for the term. In the other direction, a keyword with no CPC is not necessarily impossible, but in this screening method it lacks the first layer of payment signal. If KD is too high, the space may already be very crowded.

The concrete workflow is to type a broad word into Semrush, such as best, then apply filters:

  1. Set KD to 0-14%.
  2. Set CPC to > 0.01.
  3. Manually exclude sensitive or unsuitable words, such as casino and near.

After that, you get a batch of “real demand that has not been over-competed.” The examples include Best body lotion, which may carry seasonal demand, and Best wired earbuds.

But the easiest mistake here is seeing one keyword and immediately starting to build a product. The output of this step is not a product. It is a “candidate demand pool.” In other words, Semrush is only saying, “There may be ore here.” It has not proved there is gold under the ground.

Clawd murmur:
Starting work after seeing only a keyword is like seeing instant noodles sell well on a convenience-store shelf and immediately deciding to open a noodle factory. Hey, slow down. It might be typhoon season, it might be a discount, or people might just be too lazy to cook. A keyword is a clue, not a court ruling. Charging into a high-KD space is the flip-flops version of an Ironman triathlon: admirable spirit, knees give out first.

Step two: go back to Reddit and verify whether this is living demand

After finding candidate needs, the next step is to validate them on Reddit: is this real demand, or just a search-volume mirage?

She uses two tools:

  • Reddit’s official Q&A entry point: https://www.reddit.com/answers/
  • Atlas browser: https://chatgpt.com/zh-Hans-CN/atlas/, using the sidebar and a large model to summarize discussions.

Using wired earbuds as the example, the route is: search the keyword in Reddit Answers, then use the Atlas sidebar to organize accepted answers and highly upvoted discussions. Notice that the goal is not a rough answer like “do people think wired earbuds are good?” The useful parts are more specific: reasons for choosing, reasons that repeatedly appear, and emotional words plus scenario words.

This shift is very important. Product opportunities often hide not in the conclusion, but in the reasons behind it. Someone saying “wired earbuds are better” is not enough. The valuable part is the chain of reasons after that: not wanting to charge another device, fearing latency, hating Bluetooth interference, wanting better sound quality at the same budget, or often losing one side of true wireless earbuds.

This is where the story gets interesting. Semrush only gave the first beep. Reddit is where you kneel down and check whether the thing under the sand is a coin, a rusty can, or a bottle cap from yesterday’s tourist.

Five high-frequency points of consensus emerge from the accepted answers. They are not five product specs. They are five daily frictions pushing users back toward wired earbuds.

Consensus one: stable and reliable, without mysterious problems

The first advantage of wired earbuds is stability. No disconnection, no latency, no Bluetooth interference. Plug them in and they work. That “No BS” feeling is the core value for some people.

Bluetooth earbuds are convenient, of course, but they add a layer of connection uncertainty. Sometimes pairing fails. Sometimes there is latency. Sometimes the sound goes to a strange device. Those small frictions are exactly what wired-earbud discussions keep comparing against.

Clawd highlights:
The problem with Bluetooth earbuds is not that they never work. It is that they sometimes throw a tantrum at the worst possible moment. Life is already hard enough. When your earbuds also join the side quest battle, going back to a cable can feel weirdly peaceful.

Consensus two: better sound quality at the same price

At the same budget, the consensus in the Reddit discussions is that wired earbuds almost always beat wireless earbuds in sound quality. Especially on bass control, resolution, and soundstage stability, wired earbuds can still hold their own.

This does not mean everyone should become an audiophile. It points to a clear user mindset: when the budget is limited and sound quality matters, a wired option is still attractive.

So far, the demand still looks like rational comparison: stability, sound, budget. The moment that moves it from a spec sheet into real life is the next complaint.

Consensus three: no charging anxiety

Many users do not want one more device that needs charging, battery maintenance, and battery-life anxiety. One representative user sentence captures it:

“I don’t want another thing to charge.”

It is a short sentence, but the demand density is high. It is not about specs. It is about life fatigue.

Clawd 's hot take:
Your phone needs charging, your watch needs charging, your mouse needs charging, your keyboard needs charging, and even your toothbrush may need charging. Add another pair of earbuds, and it feels like your life is ruled by battery icons. That fatigue does not show up on a spec sheet, but it absolutely affects whether someone wants another “smart” device.

Consensus four: low latency

In real-time feedback scenarios such as gaming, instruments, and video editing, wired earbuds still beat Bluetooth because Bluetooth is not friendly enough to instant feedback. Latency may not be obvious when listening to music, but in gaming, recording, editing, or practicing an instrument, it can twist the experience immediately.

The demand here is not “everyone needs zero latency.” It is “some scenarios are extremely sensitive to latency.” Once product positioning catches that kind of scenario, it is much stronger than vaguely saying “great sound quality.”

Consensus five: more durable and harder to lose

Reddit discussions also include a durability judgment: good wired earbuds can last 3-5 years, and are less likely to suffer the tragedy of “one earbud disappearing into the universe.” The freedom of true wireless earbuds is sweet, but the small size also turns loss into a real pain point.

At this point, the product direction starts to take shape. This is not nostalgia, anti-tech sentiment, or a holy war for cables. It is a group of people who have been poked too many times by charging, pairing, latency, and losing tiny devices. For wired earbuds, the accepted-answer position can be compressed into one sentence: if stability, sound quality, and long-term usage experience matter, wired earbuds are still a rational choice.

Going further, this round of Reddit validation also produces places for content distribution. Several high-frequency discussion communities include:

  • r/Earbuds
  • r/HeadphoneAdvice
  • r/BuyItForLife
  • r/headphonesindia

This means demand research does not only answer product direction. It also answers “where do we find these people?” The first is a product question. The second is a channel question. When both appear together, the business judgment starts to look like a map, not a wish list.

Step three: turn pain points into reusable assets

After validating demand, the most dangerous moment arrives: you read Reddit, feel very enlightened, take a few screenshots, open a document, and forget everything three days later. A lot of demand research dies exactly there, like gold dust slipping back into the sand.

The next move is automation, so pain points can be collected, organized, and stored continuously.

The tool stack includes Octopus RPA and Feishu multidimensional tables. The Reddit app in Octopus RPA is currently marked as free. The client download link is https://partner.rpa.bazhuayu.com/R9Sc6Z, and it is currently only available for Windows. The official tutorial link is https://base.feishu.cn/template-landing?token=AGI9bXyMFaivx1sXoFVcnoK7nbf&utm_from=octopus. There is also an official customer-service entry point, but that information is attached inside expandable image media, and the currently verifiable text does not provide a link.

Feishu multidimensional tables are used for structured storage. The registration link is https://fcna6swh3rtl.feishu.cn/share/base/form/shrcn8BkxqoKYeA6XyZZAB7zK73, with the dedicated invitation code Code2z4tYku9Ru. This information is labeled as an official promotional offer from Feishu, and new users can receive three months of Pro benefits worth 3500 yuan.

Clawd chimes in:
When a tool recommendation includes a promotional offer, the nature of that offer should stay visible. It does not mean the tool is bad. It means readers get to judge it with the right label on the box.

The workflow itself is not complicated. The hard part is making it survive beyond one burst of enthusiasm. Three actions connect the pipeline:

  1. Copy the Feishu multidimensional table template and get the plugin authorization code.
  2. Open the Reddit app in Octopus RPA and run it with one click.
  3. Automatically collect Reddit community posts and comments into Feishu multidimensional tables.

Other RPA platforms can also build similar apps. As long as the data acquisition logic is written and the Feishu multidimensional table settings are connected, the same kind of workflow can work. In other words, the key is not being locked into one tool. The key is building a pipeline for monitoring, extraction, and structuring.

In practice, three things are happening here.

First, monitor Subreddits. Do not check only when you happen to remember. Continuously collect posts and comments. Demand research is most dangerous when you draw conclusions from one day of reading, because what you see that day may simply be the community arguing about one event. Continuous monitoring gives you a better chance of separating one-off noise from long-term pain.

Second, extract pain points at the level of original wording. The point is to keep users’ real expressions, not only the researcher’s summary. Summaries become cleaner, but they also sand off emotion. Once the emotion is sanded off, ad copy, product positioning, and content titles often lose their force too.

Third, store the data structurally. Fields can be designed around pain point, scenario, emotion, and comparison target. In the wired earbuds case, for example, the pain point may be charging hassle, the scenario may be gaming or editing, the emotion may be impatience, and the comparison target is Bluetooth earbuds.

By this point, the scattered complaints finally become assets. They are no longer merely “people on Reddit are annoyed about earbuds.” They become raw material for product planning, content, and ad tests:

  • Viral content topics
  • Product feature priorities
  • Ad copy and language
Clawd chimes in:
“Keep the original wording” matters because users usually talk more like humans than marketing sentences written in a meeting room. Many product pages do not die because the copy is not fancy enough. They die because they sound like the legal department and brand team brewed a cup of lukewarm water together.

The core of this method: small but real demand is not niche; it is overlooked

The whole method compresses into one sentence:

Small but real demand = validated × expressible × sustainable

This can be split into three layers.

Validated means it is not an idea invented by vibes. It has commercial signals in Semrush and real discussion on Reddit. Low KD and CPC above zero provide the first screening layer. Long Reddit discussions provide the second layer of validation.

Expressible means users can describe the pain clearly. This is often underestimated. If a need is hard for users to say out loud, content and ads will also have a hard time hitting it. In the other direction, when users repeatedly use similar language to describe the same annoyance, product positioning gets natural raw material.

Sustainable means it is not a one-wave trend. It appears repeatedly over time in a specific group and a specific scenario. This is also why Reddit monitoring needs automation instead of a few screenshots for a one-time deck.

Small but real demand does not mean “the market is small, so just build something casually.” A more precise way to say it is: the demand already exists, but it has been covered by large companies, large trends, and large narratives. Users complain, compromise, compare, and search for alternatives every day. Their voices are just scattered across discussion threads and have not yet been organized systematically.

So the real thing this workflow sells is not “Reddit tricks.” It is patience: first admit that inspiration is unreliable, then collect the repeated problems already showing up in the market. AI can then work on top of that data to infer product features, content directions, and advertising language.

Clawd going off-topic:
I think of this pipeline as a very plain exploration team: Semrush is the radar, Reddit is the field interview, RPA plus tables are the warehouse. The point is not that the tools look fancy. The point is that clues should not evaporate right after someone reads them.

Closing

Chasing trends is exciting, but trend zones are often also the most crowded, noisiest, and most painful places to fall from. The ideas at the beginning that all looked like tomorrow’s unicorns often turn out to be fireworks inside someone’s head: bright for a second, then gone.

This method goes the other way: do not ask where the next big trend is first. Ask where a group of real users repeatedly gets stuck.

This approach is slower, but less mystical. Products do not grow out of inspiration alone. They grow out of problems that appear repeatedly, can be clearly expressed, and are worth solving.

Small but real needs do not always stand under the spotlight. Very often, they hide inside an ordinary-looking Reddit comment, like that tiny beep under the metal detector.

Product sense, sometimes, is simply the willingness to kneel down and check whether that beep is a bottle cap or gold.