How a Long-Tail Keyword Became a Blog Post
A customer of ours — BrassTranscripts, a transcription service — noticed a search query appearing in their Bing Webmaster Tools data:
"how to quickly replace speaker 1 and speaker 2 with actual names in ms word transcript"
Fifteen words. Extremely specific. They brought it to Brass-SEO and asked: can we build a blog post around this?
What happened next is a good example of how Brass-SEO works in practice. The AI did not just say "yes, write a blog post." It cross-referenced BrassTranscripts' Google Search Console data, analyzed the search intent, designed a two-method content strategy, and produced a complete prompt the customer could paste directly into Claude or ChatGPT to generate the first draft.
Here is the full process — what the customer brought us, what Brass-SEO's AI did with it, and how a 15-word query became a published blog post.
Quick Navigation
- Why This Keyword Matters
- What Brass-SEO's AI Did First
- The Content Strategy It Designed
- The Prompt It Produced
- From Prompt to Published Post
- What This Looks Like at Scale
- Key Takeaways
- Frequently Asked Questions
Why This Keyword Matters
Most people think keyword research means finding a single word or two-word phrase with thousands of monthly searches. That is one approach, and it is the hardest one. You are competing against every major site in your industry for those terms.
Long-tail keywords — queries of four or more words — work differently. They have less competition, higher specificity, and stronger intent. Someone searching "transcription" could be looking for anything. Someone searching "how to quickly replace speaker 1 and speaker 2 with actual names in ms word transcript" has a transcript open in Word right now and needs help.
This is the kind of keyword that converts. The person is not browsing. They are doing.
What Brass-SEO's AI Did First
When BrassTranscripts brought this keyword to Brass-SEO, the AI did not just confirm it was a good keyword. It pulled up their Google Search Console data and cross-referenced it.
The first thing it found: BrassTranscripts was already ranking for related terms around speaker identification and transcript labeling. That is significant. It means Google already associates the site with this topic — so a new post targeting this specific how-to query would land in a neighborhood where the site had existing authority. That is the principle behind striking-distance keyword strategy, and the AI recognized it from the data.
Then it broke down the search intent — what this 15-word query reveals about the person typing it:
They have already transcribed something. This is not someone researching transcription services. They have a completed transcript. The work is done. They are in the cleanup phase.
They used an automated tool. The "Speaker 1" and "Speaker 2" labels are the default output of AI transcription services. Manual transcripts use real names. Automated ones use generic speaker labels.
They are working in Microsoft Word. They have the transcript as a Word document, which tells us they exported from a transcription tool or pasted the output into Word for editing.
They want speed. The word "quickly" is doing heavy lifting. They do not want a tutorial on audio editing or a recommendation to re-transcribe. They want the fastest path from "Speaker 1" to "John."
Based on this analysis, Brass-SEO's AI concluded: the post needs a fast solution first (the answer the searcher expects), then a smarter solution second (the one that leads to BrassTranscripts' AI prompt guide). That intent progression became the content strategy.
The Content Strategy It Designed
Brass-SEO's AI recommended a two-method post structure, with the order specifically chosen to match the search intent progression.
Method 1: MS Word Find and Replace (Lead With This)
The AI recommended leading with the direct answer the searcher expects. They opened Google (or Bing) looking for a keyboard shortcut — give it to them immediately. Ctrl + H opens Find and Replace. Type "Speaker 1:" in the find field, type the actual name in the replace field, click Replace All. Done in seconds.
Leading with the direct answer serves two purposes. It satisfies the search intent immediately — Google rewards pages that answer the query fast. And it builds trust with the reader, who now sees the site as helpful rather than salesy.
The AI also recommended a practical tip: always include the trailing colon in the find field (search for "Speaker 1:" not just "Speaker 1") to avoid accidentally replacing instances of "Speaker 1" that appear in the body text rather than as labels.
Method 2: AI Prompting (The Pivot)
Here is where Brass-SEO's AI identified the real value for BrassTranscripts. Find and Replace works for two speakers. What about five? What about a two-hour meeting with six participants where "Speaker 1" appears 200 times and you are not sure which speaker said what?
That is where AI prompts become the smarter tool. Instead of find-and-replace, you paste the transcript into an AI assistant and tell it: "Speaker 1 is John Doe, Speaker 2 is Jane Smith, Speaker 3 is Bob Wilson. Replace the labels and summarize the key decisions."
The AI specifically recommended linking to BrassTranscripts' AI prompt guide and calling out the Meeting Minutes Generator and Blog Post Generator prompts by name. These are ready-made prompts for exactly this kind of work. The transition from "tedious find-and-replace for 5+ speakers" to "just define the names once and let AI do it" is the content's natural pivot to BrassTranscripts' product.
The Comparison Table
The AI also designed a comparison table for the post:
| Factor | MS Word Find/Replace | AI Prompting |
|---|---|---|
| Speed (2 speakers) | Fastest | Comparable |
| Speed (5+ speakers) | Tedious | Fastest |
| Context awareness | None — literal text swap | Understands conversation flow |
| Formatting | No change to structure | Can reformat into minutes, summaries, posts |
| Accuracy | Exact match only | Can correct misattributions if given context |
This gives the reader a clear decision framework. For a quick two-speaker fix, use Word. For anything more complex, use an AI prompt — and here is the exact prompt to use.
The Prompt It Produced
This is the part that surprised BrassTranscripts. They came to Brass-SEO with a keyword. Brass-SEO's AI came back with a complete, ready-to-use prompt they could paste into Claude or ChatGPT to generate the first draft.
The prompt was not vague. It was a detailed content brief — roughly 300 words — that encoded everything the AI had learned from the intent analysis and the GSC data. Here is what it included:
Role assignment. It told the writing AI to act as an expert SEO content writer for BrassTranscripts specifically, matching the site's existing tone and audience.
Target keyword. It included the full 15-word keyword explicitly so the writing AI would incorporate it naturally into the title, introduction, and headers.
Post structure with rationale. It specified the two-method approach — lead with the MS Word shortcut, then pivot to AI prompting — and explained why that order matters for the search intent.
Specific tactical details. It included the Ctrl + H shortcut, the trailing-colon tip, the comparison table format, and named the specific prompts from BrassTranscripts' guide (Meeting Minutes Generator, Blog Post Generator) to reference.
Data-informed confidence. It noted that BrassTranscripts was already ranking for related terms around speaker identification, so this post would likely rank quickly by capturing adjacent how-to traffic. This is not a guess — it came from the GSC data.
Tone and formatting. It specified short paragraphs, H2 and H3 headers, and an authoritative but efficient tone. Blog posts for people in the middle of a task need to be scannable.
CTA. It included the call-to-action: encourage readers to explore the full prompt guide for more transcript workflows.
The customer pasted that prompt into their writing AI and had a first draft in about 30 seconds. The thinking that would normally take an hour — intent analysis, content structure, keyword placement strategy, competitive context — was done by Brass-SEO before the customer wrote a single word.
From Prompt to Published Post
An AI-generated draft is a first draft. The prompt got BrassTranscripts 80% of the way there, but the last 20% still requires a human. Here is what the review process looked like.
Fact-check the technical details. Does Ctrl + H actually open Find and Replace in current versions of Word? (Yes.) Does Replace All work as described? (Yes.) Are the prompt guide links correct and current? (Verified.)
Verify the keyword integration. Is the target keyword in the title, the first paragraph, and at least one H2? Does it read naturally or does it feel stuffed? The title tag was adjusted to be catchy while keeping the primary keyword intact.
Check the content length. The post needed to be long enough to be comprehensive but not so long that the reader searching for a quick fix bounces. For this topic, roughly 1,500 words was the target — enough to cover both methods thoroughly without padding. Here is our thinking on how long blog posts should be.
Add internal links. The draft included the external link to BrassTranscripts' prompt guide. Internal links to related posts about transcript formatting and speaker identification were added to strengthen the page's connection to the existing content cluster. Internal linking is one of the most reliable on-page SEO tactics, and new posts should always connect to existing content.
Submit to search engines. After publishing, the URL was submitted via IndexNow for faster discovery by Bing and Yandex — a step most publishers skip but which can shave days off the indexing timeline. We covered indexing mechanics in detail in why new blog posts take weeks to appear on Google.
The total time from "I found a keyword in Bing" to "published blog post" was under two hours. Most of that was the human review. The analysis, strategy, and prompt generation — the hard thinking — took Brass-SEO's AI about 30 seconds. You can read the finished post here: Replace Speaker 1 and Speaker 2 with Real Names in Your Transcript.
What This Looks Like at Scale
This was one keyword and one blog post, but every site with traffic has hundreds of similar opportunities sitting in its search data. Your Google Search Console account contains queries where your site appeared but did not rank well. Some of those queries are long-tail how-to questions just like this one, where a single targeted post could capture traffic that currently goes nowhere. See our GSC guide for how to find them.
What Brass-SEO did for BrassTranscripts is what it does for every customer who connects their data:
- You find a keyword — in GSC, Bing Webmaster Tools, or by asking Brass-SEO to surface opportunities
- Brass-SEO analyzes the intent — who is searching, what they need, what stage they are in
- It cross-references your data — checks if you already rank for related terms, identifies the competitive landscape
- It designs the content structure — what to lead with, where to pivot, what CTA to include
- It produces a ready-to-use prompt — a content brief you can paste into any writing AI to generate the first draft
- You review, fact-check, and publish
Steps 2 through 5 are the ones that normally take the most time. They are also the ones where most people either skip the research (and write generic content) or spend hours doing it manually. Brass-SEO compresses that into a single conversation.
You bring the keyword and the expertise about your business. Brass-SEO does the analysis and gives you a plan. The result is content that matches the search intent because it was built from the data, not from guesswork. That is how you choose the right keywords to target and turn them into posts that rank.
Key Takeaways
Long-tail keywords convert. A 15-word query with low monthly searches can be more valuable than a 2-word query with 10,000, because the person searching knows exactly what they need.
The data shapes the strategy. Brass-SEO did not guess at the content structure. It analyzed the search intent and cross-referenced the GSC data to design a strategy that matches what the searcher needs and what the site is already positioned to rank for.
The hard part is the thinking, not the writing. Without the intent analysis and data context, a writing AI produces generic content. With it, the same AI produces a targeted first draft in seconds. Brass-SEO does the thinking so you can skip to the writing.
Your search data has these keywords right now. Every site with traffic has long-tail queries in its GSC data that nobody has written content for. Finding and acting on them is one of the highest-return activities in SEO.
Frequently Asked Questions
How do you find long-tail keywords in your search data?
In Google Search Console, go to the Performance report and sort by impressions. Look for queries with high impressions but few clicks, or queries longer than 5 words. These are often specific how-to questions that a single targeted blog post could rank for. Bing Webmaster Tools has a similar report. Brass-SEO surfaces these automatically when you connect your data.
Is it worth writing a blog post for a keyword with very low search volume?
Often yes. A keyword with 20 monthly searches and perfect commercial intent — someone ready to buy, sign up, or take action — can be worth more than a keyword with 5,000 searches from people casually browsing. The post also builds topical authority for your site, which helps all your other pages rank better.
How long does it take a new blog post to start ranking?
Typically 2 to 8 weeks for Google to crawl, index, and assign a stable position. Long-tail keywords with low competition tend to rank faster because fewer pages compete for those exact queries. Submitting via IndexNow can speed up Bing indexing. See why new blog posts take weeks to appear on Google for the full timeline.
Can I use this process for my own business?
Yes. The workflow is the same regardless of industry. Find a specific query in your search data, analyze what the searcher needs, design content that delivers it, and use an AI assistant to draft it quickly. The only requirement is access to your search data — either through Google Search Console directly or through a tool like Brass-SEO that reads it for you.
What AI tools work for writing blog post drafts from a prompt?
Any major AI assistant — Claude, ChatGPT, Gemini — can generate a solid first draft from a well-structured prompt. The quality of the output depends almost entirely on the quality of the prompt. A prompt that includes the target keyword, content structure, specific details, tone guidance, and CTA will produce a much better draft than "write a blog post about [topic]."
Try It With Your Own Data
The keyword that started this case study was hiding in search data that had been sitting there for weeks. It took noticing it, understanding the intent behind it, and building content around it.
Your search data has similar opportunities right now — specific questions your audience is asking that nobody has written a good answer for.
Brass-SEO connects to your Google Search Console and GA4 data and helps you find them. Ask it "what keywords am I close to ranking for?" or "what questions are people searching that I don't have content for?" and it surfaces the long-tail opportunities hiding in your data — the same kind of opportunity that turned a 15-word Bing query into a targeted blog post.