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Fastest Way To Find The Best Keywords For SEO or SEM
Often times, I’ve heard from people who run AdWords campaigns or write blog post that they do very little keyword research. They just use the keywords provided in AdWords Keyword Planner or simply come up with keywords themselves. Yes, this may work, but why put it to chance.
Thorough keyword research is necessary for SEO or SEM success, but it can take a long time. If you are a startup company or have limited marketing budgets, you just don’t have any to spare.
How To Do Keyword Research Faster With A.I.
Twinword Ideas is a keyword tool that speeds up the keyword research process. Instead of skimming through thousands of keywords, our A.I. can help you filter the list down to only a hundred or so that you can then manually select from.
Below is a step-by-step guide on ways to use our A.I. smart filters.
Step 1) What are you selling?
I sell…
Type your product or service (not your brand name) into the Suggest tab search box and click search or press enter.
Estimated Keyword Count: 2,305
Step 2) Where do you sell?
I sell…
Offline only.
If you sell in local (physical) locations, you can use the “Local” user intent smart filter to narrow your keyword list down.
Online only.
Move on to Step 3.
Both online and offline.
Move on to Step 3.
Estimated Keyword Count: 119 (Local)
Step 3) Why are you looking for keywords?
I need keywords for…
Web page titles, meta descriptions, tags, and content (SEO)
Move the minimum “Search Volume” slider up to get keywords with volume.
Move the maximum “Organic Competition” slider down to get less competitive keywords.
AdWords, Bing, or other paid campaigns (SEM / PPC)
Move the maximum “Paid Competition” slider down to see cheaper keywords.
Move the minimum “Relevance Score” slider up to see more relevant keywords.
Use the Pattern “Include” / “Exclude” filters to only include keywords that have certain patterns and remove patterns you don’t.
Estimated Keyword Count: 754
Step 4) What kind of users are you hoping to get?
Get keywords searched by users who are…
Just starting their buying journey and looking for general info.
For keywords searched by top of the funnel users, select the “Know” user intent smart filter.
Know what they want and are comparison shopping.
For keywords searched by bottom of the funnel users, select the “Do” and “Buy” user intent smart filters.
Estimated Keyword Count: 136
Step 5) Are you ONLY interested in long-tail keywords?
Long-tail keywords are highly specific keywords that have higher conversion rates, but lower volume. The user intent of these keywords are generally really clear.
Yes, only long-tails please.
Move the minimum “Word Count” slider up to see longer keywords.
No, I want everything.
Move on.
I don’t know.
Move on.
Estimated Keyword Count: 52 (Long-tails only)
Step 6) Skim through the remaining keywords and select.
After AI-powered filtering, the number of remaining 50-150 keywords versus the initial 2,305 keywords is a no-brainer. All you have to do now is to go over the remaining keywords and select the ones you want, move them to a new group and export your list.
You can export / download the your keywords in various formats including Excel (XLSX and XLS) and Comma-Separated Values (CSV).
More Smart Filters
The above is only a guide. There are many ways to slice this cake with this AI-powered knife. You can always mix and match to see which settings give you the best results. The goal is to filter keyword lists down to a manageable size so you can then go through the list in a reasonable time.
Go give this keyword research tool a try and do keyword research faster. There’s no more excuse not to do your research!
4 Comments
Great advice Joseph 🙂
Thanks, Noel! Good luck researching and hopefully we’ll keep saving you time as we further tweak the tool!
Hi Joseph,
In your FAQ I read :
“Advanced features that only have English support
Organic competition data
Relevance score
User intent detection
LSI graph”
But if I type a french keyword like for exemple “voiture”, there are results in both organic and relevant column ??
So can we trust them ?
Hi Laurent,
You are correct that those features you’ve listed only support English. However, as you’ve noticed, you still were able to get some numbers under the organic competition and relevance columns.
First, let me explain how each works. The Relevance Score is calculated by understanding how closely each keyword suggestion is related to the original search term. Note that I used the term “related” and not “matches”. Our technology can understand English words and can know that two completely different words can have related meanings. The Organic Competition Score estimation includes looking at the SERP results for your topic and seeing how often those suggestions appear.
With that said, that doesn’t mean we only use the semantic meanings of the word. We of course also use exact matches too. This also means that when semantic understanding fails, we can fallback to exact match too.
In your case of French keywords, I would think that if any number shows up, it means the relevance found matching words (without actual semantic/meaning understanding). This is also the case in Organic Competition.
However, in the end, I always still recommend to take these sort of numbers “with a grain of salt” (or a sack of salt). They are mainly guidelines. This is also true for search volume as historical values cannot really predict the future. What you want to do instead is use these keywords to guide your writing, but also future-proof your content. You do this by putting your readers first and make high quality content that can satisfy a need.
I hope that answers your question. Thanks for your interest and feel free to reply if you have further questions.
Good luck,
Joseph
Twinword, Inc.