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You Ask, I Answer: Finding Industry-Specific Content Marketing Opportunities

Patricia asks, “I know the cannabis and CBD space is growing exponentially. What kinds or types of content should I be producing?”

This is an interesting question that will rely heavily on SEO data. The method I recommend for finding industry-specific content marketing opportunities is a three step process: intent-based permutation, validation, followed by predictive analytics. Watch the video for a brief walkthrough of the methodology and results – and how you can apply it to any industry.

The SEO software used in the video is by AHREFs. Disclosure: AHREFs is a sponsor of my podcast, Marketing Over Coffee, and I receive indirect financial benefit from the sponsorship.

You Ask, I Answer: Finding Industry-Specific Content Marketing Opportunities

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Machine-Generated Transcript

What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for watching the video.

In today’s episode, Patricia asks,

I know the cannabis and CBD CBD space is growing exponentially what kinds

of types of content should I be producing?

I know very little, actually nothing about the cannabis space, but we can use proven methods for data analysis in content marketing, to identify, extract and then plan, what works, what anyone should be doing in any kind of industry. So the method we’re going to use, we’re going to use two different methods three, technically, we don’t have time for the third right now is intent based permutation validation, and then predictive analytics. Briefly, what you need to do is take if you’re trying to understand any space, take as long as you have domain experience and you know, the basics of the space like I do know that cannabis, CBD oil and marijuana probably the more common industry terms in the legalized marijuana space that you would someone would be searching for. So the first thing we need to talk about our intent based keywords, intent based keywords or keywords that people would type that indicate that they have an interest in learning about something about doing something about possibly buying something.

And we also know that based on what Patricia is asking for our content recommendations, what stuff should she be making. So think about what we have here, we have really three or four groups of keywords, we have the beginning intent ones, like best or top or compare, which indicates somebody has strong interest. We have the topic itself, CBD and cannabis and stuff. And then we have content types. There are also other

intent keywords like near me, or reviews or things like that, that we would want to include as well. So using a method called permutation, not combination, but permutation we preserve the order, but basically mix and match every possible combination. every possible permutation of these keywords, you create, let’s flip over here, you would create a keyword list that looks something like this, where you would have the blog and the content and stuff. And you can see, this goes on for thousands of rows as is every possible logical permutation of those three keyword buckets. You have your intent base words, you have your content words, your topic words, and you have your content forms and types. And then you have additional intent words, and we get every possible reasonable permutation without duplicates here. That was the thousands of you. So that’s step one is to create massive keyword list. Step two, is to do validation. And for this, I use the RFID keyword explorer tool because it allows you to dump in 10,000 keywords at a time.

When you do this, it will then score them and tell you here’s how much volume each keyword gets. Now, they’re the generic topics and I find it interesting by the way that you have marijuana, Cannabis, but CBD oil itself is the top term which cool.

But we start going down. There are a couple of irrelevant ones. This one here for example, Christian book distributors, we know that’s probably one we don’t want to to include in our our ethics. So let’s exclude for the purposes of this keyword search. Let’s exclude that stuff. And stay on topic.

Now, cannabis videos CBD oil reviews,

CBD reviews, CBD oil review,

cannabis events.

So we’re starting to see

cannabis blogs cannabis conference. Okay, so now we’ve got a good sense right off the bat of the type of content that

Patricia should be creating

the videos about reviews

would be a logical thing to do or videos about or at cannabis industry events would be a logical thing to do.

Scroll down a bit more here. We also see things like forums. Now granted, these are much smaller searches than the you know the 10s of thousands now 13,000 monthly searches for cannabis videos. That is, that is a market opportunity right there. It is something that people are searching for something that they are interested in. Let’s go ahead and click the on that to get a sense of what are some of the terms growing.

Interesting, some comedy videos educational video, so there is

some very, very

good information here about things you could do. Now, there are some also notes in here.

For example, the Why is YouTube cracking down on cannabis videos that that in itself is a useful piece of information to know that you might need more than one video hosting platform, depending on the content of your videos, and whether the algorithm thinks that they are objectionable content. Note that of all of the other types of content we put in like blogs and websites and podcasts, those are not coming up in search nearly as much as that big, big, big big list cameras video. So this is a video

at least from what the audience is searching for. This is very much a video first ecosystem. So the short answer to Patricia’s specific question is what types of content should she be producing? The answer is video. But for all of us, this is the methodology to use to understand the space to be able to gather information about it. And then the next step would be using predictive analytics software using machine learning software to take these trends and forecast them forward to look ahead at when should you be making these different types of content. If we look here, we see cannabis videos and events. Going down here, let’s actually switch this over to scaled views. We know we know that CBD oil are the best CBD oil as a review term is going to be the the growth term followed by CBD reviews,

and CBD oil reviews. So those are

clearly the things that we should be focusing on. But let’s exclude let’s just focus in on this one cannabis videos.

apply a filter

videos and events. Let’s see when in the next year, should we be paying attention to things?

Interesting as April of next year, we’ve also got some spikes coming up in August in September, in December. So in terms of times when you’d want to create extra content, a lot of content, you’d want to focus on those times when audience interest is going to be highest going forward. So this is how you apply this three step process that we’re talking about here. That is intent based permutation, validation, and then predictive analytics to identify any, any space any industry, as long as people search for it. And let’s be honest, people are looking for it, you can find out what is likely to happen. And where you should be focusing your efforts, your time, your energy and your budget.

If shameless plug if you’d like help doing this for your industry, let trust insights know it’s my company, go to trust insights.ai and be happy to help you build these forecasts for your own company. But this methodology works really really well for things that have search volume, where you want to specifically understand a content strategy, what types of content should you be producing? And when should you produce them? So great question Patricia. Fun question to dig into and be able to look at all the different analytics for this. As always, if you have comments, please leave them in the comments box. Otherwise, please subscribe to the YouTube channel and the newsletter, and I’ll talk to you soon. want help solving your company’s data analytics and digital marketing problems.

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