In one sentence: Natural language processing, usually shortened to NLP, is the branch of computing that lets software handle ordinary human language, so a typed or spoken sentence can be acted on for what it means rather than matched word for word.
Somebody types: who can fix a garage door spring on a sunday near me. No capital letters, no punctuation, one run-on thought. NLP is the work that pulls it apart into the object (a garage door spring), the job (repair rather than installation), the constraint (weekend hours), and the place (wherever the phone is standing).
It also absorbs the mess. Misspellings, plurals, the customer word against the trade word, the same question asked five ways. That is why "cost to replace a water heater" and "how much for a new hot water tank" land in the same neighborhood of results even though the two phrases share almost no words.
None of this is exotic or new. NLP sits behind the spam filter on your inbox and the phone menu that asks you to say why you are calling. What changed is how good it got, and how much of search now leans on it instead of on exact text matching.
Understanding is not the same as agreement. Two systems can read one sentence and reach different conclusions about what the person wanted, which is part of why your position for a phrase can differ from one engine to the next without a word on your site having changed.
The practical effect is that repeating a phrase does not do what it did fifteen years ago. Software that already understands burst pipe and 3 a.m. and emergency belong together does not need you to type "emergency plumber Orlando" nine times down the page. It needs you to answer the question.
Two habits do most of the work. Use the words your customers use, not only the words on your invoice: a homeowner says the pipe under the sink is leaking, your estimate says supply line failure, and your page should carry both. Then attach the qualifier to the answer itself. Say what it costs, how fast you can be there, and which towns you cover in the sentence, not in a table three screens down.
It changes how many pages you need, too. Back when software could only match text, one page stuffed with every variation of a phrase was a defensible tactic. Now that questions arrive whole, with the qualifiers attached, the page that tends to win is the one built for that exact question. That is the reason our learning library runs to 361 in-depth guides rather than a dozen pages trying to cover everything at once.
NLP reads the parts of a page that are not prose, too. Headings, question-and-answer blocks, and page titles carry weight because they are already shaped like something a person asked out loud. How that shapes the way pages get planned and written is covered on the SEO hub.
Semantic search is what you get when this understanding is applied to matching: results chosen by meaning rather than by shared words. Search intent is the label for what the person is actually trying to accomplish. Conversational search is the same machinery holding a thread across several questions, so the second one can just say how much does that run and still make sense. A long-tail keyword is what one of those spoken-length questions looks like once it turns up in a keyword tool.
NLP is one branch of it. Artificial intelligence is the wide umbrella, and natural language processing is the part concerned specifically with human language. A chatbot uses NLP. So does the search box on a site that has no chatbot anywhere near it.
The phrases still matter as evidence of what a page covers, and they still tell you what people are actually asking. What stopped mattering is repetition. Say the thing once, clearly, in a sentence a customer would recognize, then move on to the next thing they need to know.
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