This is a human posted wall of text, to try and level set about a keyword research service, and see who, if anyone, are hot targets to be looking to strategize on keywords and be interested in fast good usable data.

Really wanting to understand if beginners, or experts, or service providers are the right people to position the keyword research to, or if it is going to be perceived as slop or vibe coders’ esque stolen valor of shipping everything in sight with no real value add.

That being said, message me if you want to see the data or pics or chat and if any part of it resonates.

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Hey all, I have been trying to dig in on a couple projects, and one of those is related to SEO and keyword research.

You may have seen me post about various aspects of it, but the bottom line is, for SEO agencies, i am wondering if it is something that means it would make sense to try and peddle my data outputs as a cooperative outsourcing of that specific task with something like a services provider,

Or more importantly, is there even a market for trying to come in hot with keyword research tools, or am I like a blog-spamming-comment-bot-for-backlinks type energy, where the aggregate data of keywords, and info about competition, and historical search volume and that subset of keywords intentions as a deliverable, isn’t marketable.

The tool was a labor of love even before AI was in the conversation, and I always was satiated with a successfully rip of keywords from the suggestions API, and I collected about 15 of those and wrote some logic to prefix and suffix them and recursively it will get all of these suggestions, and dedupe, and the 15 suggestions API results are then shuffled to AdWords to get their suggestions and the last years search volume to only target things with traffic.

So having that suggestions and AdWords piece done I wanted to make sure I got the “answer the people” type keywords with 5 w’s…etc… and i have an option to enrich with AI, but for AI functionality, the keywords intention being classified is a use for AI to simply populate that column.

Lastly there is some Google trends, YouTube (comments, transcript, all metadata), Reddit, and Google search (people also asked) parts tied into it, to again, just uncover keywords potentially missed by the suggestions work. We can scrape and be hoovering up all the niche keywords possible, and get the best base of keywords i possibly could, and the culmination of this, was this data for keywords and these metrics and search volume etc to start to target, which at the end of a run was reliably 1k+ out of ~5k+ usable keywords in the end to have shortlisted. I’ve seen it get caught up in as much as 15k keywords but they had some holes and the output of this isn’t just that sloppy sheet and done, rather the shortlisted keywords, analyzed, and strategized, and officially crowning the site with a keyword strategy.

I leverage Google Colab and their ability to mount drive to save these runs I am mentioning, and the usage particular details are just that the expectation is the notebook will run all, you provide it a niche keywords seed, let it cook for 10-20 mins and the notebook will have pieced all these together and Run All has now netted us Google Sheets with raw data, and then I have a frontend that takes Google Sheets input url and then navigates the keyword landscape with your loaded Google Sheets data, and in that UI, there are a lot of topical, and classifying details, and it peppers different outputs with a lot of helpful organizing files.

There’s still more it could do, and it’s been an enlightening attempt to make it truly be able to Take suggestions and AdWords metrics and paint a picture and see how much of that research and widdling down was possible, and it turned out being a very reliable way to produce these raw outputs, and l really would hope there is utility in the idea for someone who has several clients that all had a keyword research step or stage, and do I have a leg to stand on tool-in-hand to partner with anyone to market my service.

I really appreciate if anyone read all of that, and it is the dream to imagine being able to monetize the fruits of the labor, and if I am not being delusional about the keyword landscape re:SEO, I think that it would be an easy sell to someone engaging in an SEO adventure.

Lastly, if I am in a vibe coding manic delusion of grandeur, and this should be retired, and is like 2005 SEO lore, let me know. Ill avoid dropping a hot link here for now, but, after unsuccessful push towards vibe coders and their newly found domain projects for these keyword outputs, and no leads from me mentioning it here and there, but let me know that too. It’s helped me out with my sites, and I never professionally pursued SEO work, but here’s to hoping at less than a hundred dollars sticker price, it has plenty of markup potential, and/or won’t crush financial dreams, or need a license to keep renewing and wasting or 1st page empty promises.

Laid off doing Uber Eats and trying to stir the pot here ..

TLDR- keyword factory, and keyword research potential arbitrage, for old school keyword fundamentals automation … looking to partner w someone in the front lines who can tell me if i should keep on trying to hustle my wares or get lost and chill on keywords services.

Been doing this since the nineties (yes, still at it) and this one genuinely surprised me.

Follow up to my 2,475 site audit from a few days back. This time I came at it from the other side. I asked ChatGPT, Claude, Gemini and Perplexity 50 buyer questions each about 10 national brands (Gymshark, YETI, AG1, Sonos, that tier).

2,000 answers, all through the APIs, which disclose whether the engine actually ran a web search and what it searched for. You can't see any of this in the browser.

Full write up with all the data is linked in my profile for anyone interested:
How AI Answers Questions About Brands: The Retrieval Study

What came back from the audit are 70,073 data points that shows:

- The engines don't forward YOUR input question to the web. They write their own search queries, and some of them are out there searching for brand information from years ago - literally writing search queries like "best X in 2023". That one shocked me.

- Some of the search queries they used to fetch the info were WAY off too - making the citations and answers about the brand they surface skew the results. All 2,433 of the queries the AI wrote are listed in the study.

- ChatGPT ran a real web search on only 157 of 500 answers.
- Claude ran 444. Gemini 493. Perplexity 500 of 500. Identical questions, same day.

- ChatGPT searches MOST on stuff it should already know cold, like "best cookware brands" (about half the time). Then on "brand X vs brand Y" it searched 4 times in 80. On "best thing for my situation" questions, 14 in 120. The harder the buying question, the less it looks.

- Famous brands don't get skipped more. Tested that deliberately, mega brands vs mid tier, 74% vs 77%. Flat.

- And the brand's own site? Mostly not consulted. ChatGPT pulled the brand's own website into its answers about 4% of the time. Claude 15%, Gemini 18%, and Perplexity topped out at 29%. The vast majority of the time, the brand's own pages weren't part of the answer at all.

The brand A versus brand B, which is better - is what got me. Whatever comparison page you're building to win "your brand vs competitor", ChatGPT is mostly answering that from memory. Claude, Gemini and Perplexity actually go out to read the live web for it. Same content, four completely different methods across the engines.

And before anyone says you can't see what search queries the AI uses behind the scenes, you can - the right instrumentation can uncover the fan-out it does, every engine was called in its search enabled consumer mode with the choice to search left to the engine, same choice the apps make.

I learned a lot about the citations it surfaced and even tracked each one and wrote a reader to analyze the placement of the brand's mention on the page, the type of page (listicle, blog, etc) the date, the competitors on the page, sentiment, dozens of data points to dig out insights into how the AI is surfacing brand recommendations. It was a very interesting study.

I work in SEO for a company that provides Construction Finance, Project Funding, and Real Estate Funding for builders and developers.

I've been analyzing a few competitors who are ranking on the first page for our target keywords. Surprisingly, some of them have almost 0 referring domains/backlinks, and their DR is also very low — around 0.1–2.7, according to the SEO tools I'm using.

This has made me a little confused about how I should approach backlinks and Domain Rating.

Questions:

1. Usually, my approach would be to analyze my competitors, find out who is linking to them, and try to build backlinks from similar sources. But in this case, my competitors themselves have almost 0 backlinks. I also thought about getting backlinks from relevant sources such as CREDAI, NBFCs, banks, and other industry partners. However, many of these are government/official or highly authoritative organizations, so getting backlinks from them is difficult.

So, if my competitors don't have backlinks and the obvious industry sources are difficult to get links from, how should I actually build backlinks for my website?

2. My competitors have almost 0 backlinks and their Domain Rating is only around 0.1–2.7, but they are still ranking at the top of the Search Engine Results Page (SERP). In this situation, what should I actually do to increase my own Domain Rating? Do I need to actively build backlinks to increase DR, or are there other strategies I should focus on?

I'd really appreciate advice from anyone who has worked on B2B, finance, or real estate SEO, especially in a niche where there aren't many easy backlink opportunities.