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SearchCap: Google Search Console beta live, PPC tips & SEO tasks

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Why Google AdWords’ Keyword Volume Numbers Are Wildly Unreliable – Whiteboard Friday

Posted by randfish

Many of us rely on the search volume numbers Google AdWords provides, but those numbers ought to be consumed with a hearty helping of skepticism. Broad and unusable volume ranges, misalignment with other Google tools, and conflating similar yet intrinsically distinct keywords — these are just a few of the serious issues that make relying on AdWords search volume data alone so dangerous. In this edition of Whiteboard Friday, we discuss those issues in depth and offer a few alternatives for more accurate volume data.

why it's insane to rely on Google adwords' keyword volume numbers

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Video Transcription

Howdy, Moz fans. Welcome to another edition of Whiteboard Friday. This week we’re going to chat about Google AdWords’ keyword data and why it is absolutely insane as an SEO or as a content marketer or a content creator to rely on this.

Look, as a paid search person, you don’t have a whole lot of choice, right? Google and Facebook combine to form the duopoly of advertising on the internet. But as an organic marketer, as a content marketer or as someone doing SEO, you need to do something fundamentally different than what paid search folks are doing. Paid search folks are basically trying to figure out when will Google show my ad for a keyword that might create the right kind of demand that will drive visitors to my site who will then convert?

But as an SEO, you’re often driving traffic so that you can do all sorts of other things. The same with content marketers. You’re driving traffic for multitudes of reasons that aren’t directly or necessarily directly connected to a conversion, at least certainly not right in that visit. So there are lots reasons why you might want to target different types of keywords and why AdWords data will steer you wrong.

1. AdWords’ “range” is so broad, it’s nearly useless

First up, AdWords shows you this volume range, and they show you this competition score. Many SEOs I know, even really smart folks just I think haven’t processed that AdWords could be misleading them in this facet.

So let’s talk about what happened here. I searched for types of lighting and lighting design, and Google AdWords came back with some suggestions. This is in the keyword planner section of the tool. So “types of lighting,” “lighting design”, and “lighting consultant,” we’ll stick with those three keywords for a little bit.

I can see here that, all right, average monthly searches, well, these volume ranges are really unhelpful. 10k to 100k, that’s just way too giant. Even 1k to 10k, way too big of a range. And competition, low, low, low. So this is only true for the quantity of advertisers. That’s really the only thing that you’re seeing here. If there are many, many people bidding on these keywords in AdWords, these will be high.

But as an example, for “types of light,” there’s virtually no one bidding, but for “lighting consultant,” there are quite a few people bidding. So I don’t understand why these are both low competition. There’s not enough granularity here, or Google is just not showing me accurate data. It’s very confusing.

By the way, “types of light,” though it has no PPC ads right now in Google’s results, this is incredibly difficult to rank for in the SEO results. I think I looked at the keyword difficulty score. It’s in the 60s, maybe even low 70s, because there’s a bunch of powerful sites. There’s a featured snippet up top. The domains that are ranking are doing really well. So it’s going to be very hard to rank for this, and yet competition low, it’s just not telling you the right thing. That’s not telling you the right story, and so you’re getting misled on both competition and monthly searches.

2. AdWords doesn’t line up to reality, or even Google Trends!

Worse, number two, AdWords doesn’t line up to reality with itself. I’ll show you what I mean.

So let’s go over to Google Trends. Great tool, by the way. I’m going to talk about that in a second. But I plugged in “lighting design,” “lighting consultant,” and “types of lighting.” I get the nice chart that shows me seasonality. But over on the left, it also shows average keyword volume compared to each other — 86 for “lighting design,” 2 for “lighting consultant,” and 12 for “types of lighting.” Now, you tell me how it is that this can be 43 times as big as this one and this can be 6 times as big as that one, and yet these are all correct.

The math only works in some very, very tiny amounts of circumstances, like, okay, maybe if this is 1,000 and this is 12,000, which technically puts it in the 10k, and this is 86,000 — well, no wait, that doesn’t quite work — 43,000, okay, now we made it work. But you change this to 2,000 or 3,000, the numbers don’t add up. Worse, it gets worse, of course it does. When AdWords gets more specific with the performance data, things just get so crazy weird that nothing lines up.

So what I did is I created ad groups, because in AdWords in order to get more granular monthly search data, you have to actually create ad groups and then go review those. This is in the review section of my ad group creation. I created ad groups with only a single keyword so that I could get the most accurate volume data I could, and then I maximized out my bid until I wasn’t getting any more impressions by bidding any higher.

Well, whether that truly accounts for all searches or not, hard to say. But here’s the impression count — 2,500 a day, 330 a day, 4 a day. So 4 a day times 30, gosh, that sounds like 120 to me. That doesn’t sound like it’s in the 1,000 to 10,000 range. I don’t think this could possibly be right. It just doesn’t make any sense.

What’s happening? Oh, actually, this is “types of lighting.” Google clearly knows that there are way more searches for this. There’s a ton more searches for this. Why is the impression so low? The impressions are so low because Google will rarely ever show an ad for that keyword, which is why when we were talking, above here, about competition, I didn’t see an ad for that keyword. So again, extremely misleading.

If you’re taking data from AdWords and you’re trying to apply it to your SEO campaigns, your organic campaigns, your content marketing campaigns, you are being misled and led astray. If you see numbers like this that are coming straight from AdWords, “Oh, we looked at the AdWords impression,” know that these can be dead f’ing wrong, totally misleading, and throw your campaigns off.

You might choose not to invest in content around types of lighting, when in fact that could be an incredibly wonderful lead source. It could be the exact right keyword for you. It is getting way more search volume. We can see it right here. We can see it in Google Trends, which is showing us some real data, and we can back that up with our own clickstream data that we get here at Moz.

3. AdWords conflates and combines keywords that don’t share search intent or volume

Number three, another problem, Google conflates keywords. So when I do searches and I start adding keywords to a list, unless I’m very careful and I type them in manually and I’m only using the exact ones, Google will take all three of these, “types of lights,” “types of light” (singular light), and “types of lighting” and conflate them all, which is insane. It is maddening.

Why is it maddening? Because “types of light,” in my opinion, is a physics-related search. You can see many of the results, they’ll be from Energy.gov or whatever, and they’ll show you the different types of wavelengths and light ranges on the visible spectrum. “Types of lights” will show you what? It will show you types of lights that you could put in your home or office. “Types of lighting” will show you lighting design stuff, the things that a lighting consultant might be interested in. So three different, very different, types of results with three different search intents all conflated in AdWords, killing me.

4. AdWords will hide relevant keyword suggestions if they don’t believe there’s a strong commercial intent

Number four, not only this, a lot of times when you do searches inside AdWords, they will hide the suggestions that you want the most. So when I performed my searches for “lighting design,” Google never showed me — I couldn’t find it anywhere in the search results, even with the export of a thousand keywords — “types of lights” or “types of lighting.”

Why? I think it’s the same reason down here, because Google doesn’t believe that those are commercial intent search queries. Well, AdWords doesn’t believe they’re commercial intent search queries. So they don’t want to show them to AdWords customers because then they might bid on them, and Google will (a) rarely show those, and (b) they’ll get a poor return on that spend. What happens to advertisers? They don’t blame themselves for choosing faulty keywords. They blame Google for giving them bad traffic, and so Google knocks these out.

So if you are doing SEO or you’re doing content marketing and you’re trying to find these targets, AdWords is a terrible suggestion engine as well. As a result, my advice is going to be rely on different tools.

Instead:

There are a few that I’ve got here. I’m obviously a big fan of Moz’s Keyword Explorer, having been one of the designers of that product. Ahrefs came out with a near clone product that’s actually very, very good. SEMrush is also a quality product. I like their suggestions a little bit more, although they do use AdWords keyword data. So the volume data might be misleading again there. I’d be cautious about using that.

Google Trends, I actually really like Google Trends. I’m not sure why Google is choosing to give out such accurate data here, but from what we’ve seen, it looks really comparatively good. Challenge being if you do these searches in Google Trends, make sure you select the right type, the search term, not the list or the topic. Topics and lists inside Google Trends will aggregate, just like this will, a bunch of different keywords into one thing.

Then if you want to get truly, truly accurate, you can go ahead and run a sample AdWords campaign, the challenge with that being if Google chooses not to show your ad, you won’t know how many impressions you potentially missed out on, and that can be frustrating too.

So AdWords today, using PPC as an SEO tool, a content marketing tool is a little bit of a black box. I would really recommend against it. As long as you know what you’re doing and you want to find some inspiration there, fine. But otherwise, I’d rely on some of these other tools. Some of them are free, some of them are paid. All of them are better than AdWords.

All right, everyone. Look forward to your comments and we’ll see you again next week for another edition of Whiteboard Friday. Take care.

Video transcription by Speechpad.com

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SearchCap: Google AdWords app, SEO success & managing redesigns

Below is what happened in search today, as reported on Search Engine Land and from other places across the web.

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SearchCap: Google Speed Update, schema reviews & PPC artificial intelligence

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Martin Luther King Jr. Day 2018 Google doodle honors Dr. King & his dream for a better world

The image was designed by guest artist Cannaday Chapman and created in collaboration with the Black Googlers Network.

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Zhou Youguang Google doodle honors Chinese linguist known as the ‘Father of Pinyin’

Youguang’s work helped bridge multiple Chinese dialects into a written language.

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SearchCap: New PageSpeed Insights, Google AdWords reviews & the Search Engine Land Awards

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SearchCap: Alexa & Google Assistant, AMP URLs & link building

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Google to roll out new Search Console features in coming weeks

After comprehensive beta user testing, Google begins release of the new Google Search Console reports to all verified users.

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SEO Ranking Factors & Correlation: What Does It Mean When a Metric Is Correlated with Google Rankings? – Whiteboard Friday

Posted by randfish

In an industry where knowing exactly how to get ranked on Google is murky at best, SEO ranking factors studies can be incredibly alluring. But there’s danger in believing every correlation you read, and wisdom in looking at it with a critical eye. In this Whiteboard Friday, Rand covers the myths and realities of correlations, then shares a few smart ways to use and understand the data at hand.

SEO Ranking Factors and Correlation

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Video Transcription

Howdy, Moz fans, and welcome to another edition of Whiteboard Friday. This week we are chatting about SEO ranking factors and the challenge around understanding correlation, what correlation means when it comes to SEO factors.

So you have likely seen, over the course of your career in the SEO world, lots of studies like this. They’re usually called something like ranking factors or ranking elements study or the 2017 ranking factors, and a number of companies put them out. Years ago, Moz started to do this work with correlation stuff, and now many, many companies put these out. So people from Searchmetrics and I think Ahrefs puts something out, and SEMrush puts one out, and of course Moz has one.

These usually follow a pretty similar format, which is they take a large number of search results from Google, from a specific country or sometimes from multiple countries, and they’ll say, “We analyzed 100,000 or 50,000 Google search results, and in our set of results, we looked at the following ranking factors to see how well correlated they were with higher rankings.” That is to say how much they predicted that, on average, a page with this factor would outrank a page without the factor, or a page with more of this factor would outrank a page with less of this factor.

Correlation in SEO studies like these usually mean:

So, basically, in an SEO study, they usually mean something like this. They do like a scatter plot. They don’t have to specifically do a scatter plot, but visualization of the results. Then they’ll say, “Okay, linking root domains had better correlation or correlation with higher organic rankings than the 10 blue link-style results to the degree of 0.39.” They’ll usually use either Spearman or Pearson correlation. We won’t get into that here. It doesn’t matter too much.

Across this many searches, the metric predicted higher or lower rankings with this level of consistency. 1.0, by the way, would be perfect correlation. So, for example, if you were looking at days that end in Y and days that follow each other, well, there’s a perfect correlation because every day’s name ends in Y, at least in English.

So search visits, let’s walk down this path just a little bit. So search visits, saying that that 0.47 correlated with higher rankings, if that sounds misleading to you, it sounds misleading to me too. The problem here is that’s not necessarily a ranking factor. At least I don’t think it is. I don’t think that the more visits you get from search from Google, the higher Google ranks you. I think it’s probably that the correlation runs the other way around — the higher you rank in search results, the more visits on average you get from Google search.

So these ranking factors, I’ll run through a bunch of these myths, but these ranking factors may not be factors at all. They’re just metrics or elements where the study has looked at the correlation and is trying to show you the relationship on average. But you have to understand and intuit this information properly, otherwise you can be very misled.

Myths and realities of correlation in SEO

So let’s walk through a few of these.

1. Correlation doesn’t tell us which way the connection runs.

So it does not say whether factor X influences the rankings or whether higher rankings influences factor X. Let’s take another example — number of Facebook shares. Could it be the case that search results that rank higher in Google oftentimes get people sharing them more on Facebook because they’ve been seen by more people who searched for them? I think that’s totally possible. I don’t know whether it’s the case. We can’t prove it right here and now, but we can certainly say, “You know what? This number does not necessarily mean that Facebook shares influence Google results.” It could be the case that Google results influence Facebook searches. It could be the case that there’s a third factor that’s causing both of them. Or it could be the case that there’s, in fact, no relationship and this is merely a coincidental result, probably unlikely given that there is some relationship there, but possible.

2. Correlation does not imply causation.

This is a famous quote, but let’s continue with the famous quote. But it sure is a hint. It sure is a hint. That’s exactly what we like to use correlation for is as a hint of things we might investigate further. We’ll talk about that in a second.

3. In an algorithm like Google’s, with thousands of potential ranking inputs, if you see any single metric at 0.1 or higher, I tend to think that, in general, that is an interesting result.

Not prove something, not means that there’s a direct correlation, just it is interesting. It’s worthy of further exploration. It’s worthy of understanding. It’s worthy of forming hypotheses and then trying to prove those wrong. It is interesting.

4. Correlation does tell us what more successful pages and sites do that less successful sites and pages don’t do.

Sometimes, in my opinion, that is just as interesting as what is actually causing rankings in Google. So you might say, “Oh, this doesn’t prove anything.” What it proves to me is pages that are getting more Facebook shares tend to do a good bit better than pages that are not getting as many Facebook shares.

I don’t really care, to be honest, whether that is a direct Google ranking factor or whether that’s just something that’s happening. If it’s happening in my space, if it’s happening in the world of SERPs that I care about, that is useful information for me to know and information that I should be applying, because it suggests that my competitors are doing this and that if I don’t do it, I probably won’t be as successful, or I may not be as successful as the ones who are. Certainly, I want to understand how they’re doing it and why they’re doing it.

5. None of these studies that I have ever seen so far have looked specifically at SERP features.

So one of the things that you have to remember, when you’re looking at these, is think organic, 10 blue link-style results. We’re not talking about AdWords, the paid results. We’re not talking about Knowledge Graph or featured snippets or image results or video results or any of these other, the news boxes, the Twitter results, anything else that goes in there. So this is kind of old-school, classic organic SEO.

6. Correlation is not a best practice.

So it does not mean that because this list descends and goes down in this order that those are the things you should do in that particular order. Don’t use this as a roadmap.

7. Low correlation does not mean that a metric or a tactic doesn’t work

Example, a high percent of sites using a page or a tactic will result in a very low correlation. So, for example, when we first did this study in I think it was 2005 that Moz ran its first one of these, maybe it was ’07, we saw that keyword use in the title element was strongly correlated. I think it was probably around 0.2, 0.15, something like that. Then over time, it’s gone way, way down. Now, it’s something like 0.03, extremely small, infinitesimally small.

What does that mean? Well, it could mean one of two things. It could mean Google is using it less as a ranking factor. It could mean that it was never connected, and it’s just total speculation, total coincidence. Or three, it could mean that a lot more people who rank in the top 20 or 30 results, which is what these studies usually look at, top 10 to top 50 sometimes, a lot more of them are putting the keyword in the title, and therefore, there’s just no difference between result number 31 and result number 1, because they both have them in the title. So you’re seeing a much lower correlation between pages that don’t have them and do have them and higher rankings. So be careful about how you intuit that.

Oh, one final note. I did put -0.02 here. A negative correlation means that as you see less of this thing, you tend to see higher rankings. Again, unless there is a strong negative correlation, I tend to watch out for these, or I tend to not pay too much attention. For example, the keyword in the meta description, it could just be that, well, it turns out pretty much everyone has the keyword in the meta description now, so this is just not a big differentiating factor.

What is correlation good for?

All right. What’s correlation actually good for? We talked about a bunch of myths, ways not to use it.

A. IDing the elements that more successful pages tend to have

So if I look across a correlation and I see that lots of pages are twice as likely to have X and rank highly as the ones that don’t rank highly, well, that is a good piece of data for me.

B. Watching elements over time to see if they rise or lower in correlation.

For example, we watch links very closely over time to see if they rise or lower so that we can say: “Gosh, does it look like links are getting more or less influential in Google’s rankings? Are they more or less correlated than they were last year or two years ago?” And if we see that drop dramatically, we might intuit, “Hey, we should test the power of links again. Time for another experiment to see if links still move the needle, or if they’re becoming less powerful, or if it’s merely that the correlation is dropping.”

C. Comparing sets of search results against one another we can identify unique attributes that might be true

So, for example, in a vertical like news, we might see that domain authority is much more important than it is in fitness, where smaller sites potentially have much more opportunity or dominate. Or we might see that something like https is not a great way to stand out in news, because everybody has it, but in fitness, it is a way to stand out and, in fact, the folks who do have it tend to do much better. Maybe they’ve invested more in their sites.

D. Judging metrics as a predictive ranking ability

Essentially, when I’m looking at a metric like domain authority, how good is that at telling me on average how much better one domain will rank in Google versus another? I can see that this number is a good indication of that. If that number goes down, domain authority is less predictive, less sort of useful for me. If it goes up, it’s more useful. I did this a couple years ago with Alexa Rank and SimilarWeb, looking at traffic metrics and which ones are best correlated with actual traffic, and found Alexa Rank is awful and SimilarWeb is quite excellent. So there you go.

E. Finding elements to test

So if I see that large images embedded on a page that’s already ranking on page 1 of search results has a 0.61 correlation with the image from that page ranking in the image results in the first few, wow, that’s really interesting. You know what? I’m going to go test that and take big images and embed them on my pages that are ranking and see if I can get the image results that I care about. That’s great information for testing.

This is all stuff that correlation is useful for. Correlation in SEO, especially when it comes to ranking factors or ranking elements, can be very misleading. I hope that this will help you to better understand how to use and not use that data.

Thanks. We’ll see you again next week for another edition of Whiteboard Friday.

Video transcription by Speechpad.com

The image used to promote this post was adapted with gratitude from the hilarious webcomic, xkcd.

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