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Keyword research for parsing: how to pick words that work

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Why one broad word returns noise, how combinations narrow a search, and how to build a keyword list for a niche or a city.

Keyword research for parsing: how to pick words that work

Everything a parser returns is decided by the keywords you gave it. This is the step people skip, and then conclude that parsing produces junk — which it does, when the words are wrong.

Why a single broad word fails

One word matches everything containing it. "Marketing" returns agencies, job boards, motivational channels and courses in five languages. The list is large and mostly irrelevant, and cleaning it costs more than searching properly would have.

Combinations narrow honestly

Requiring two words to appear together cuts the noise dramatically: "marketing + b2b", "repair + appliances", "crypto + education". Each pair describes a real intersection rather than a broad topic.

A good rule: if a pair returns thousands of channels, it is still too broad. Add a third word or make one of them more specific.

Where to get the words

  • From your own customers. How they describe the problem, not how you describe the service. These rarely match.
  • From competitor channels. The vocabulary a niche actually uses — finding competitor channels.
  • From questions in chats. The phrasing people use when they are stuck is the phrasing that finds them.

Local searches are different

For a city, the city name is the weakest keyword you can use — it finds national news channels. Local communities are named after districts, developments, streets and stations, so the list becomes a list of place names combined with formats: "classifieds", "neighbours", "parents". See Telegram for local business.

Words for channels and words for chats

They are not the same list. A channel is named to be found; a chat is named by its members for themselves. Chats hide behind informal words and abbreviations that no channel would use as a title.

Once the list is built, the result still needs filtering — cleaning a database — and it is worth knowing what parsing can never return: what parsing can and cannot do.

How Neurogram does this

Everything above is manual work that runs into the number of hours in a day. Neurogram does it on your own accounts and without you: it collects channels and audiences, writes comments and replies with a language model, and keeps limits and quiet hours so the accounts survive. See pricing or look at your case.

Topic: Parsing

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