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Tag: Opportunities

Find Ranking Keywords, Uncover Opportunities, Check Rankings, & More: 5 Workflows for Easier Keyword Research
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Find Ranking Keywords, Uncover Opportunities, Check Rankings, & More: 5 Workflows for Easier Keyword Research

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Have you ever wished there were an easy way to see all the top keywords your site is ranking for? How about a competitor’s? What about those times when you’re stumped trying to come up with keywords related to your core topic, or want to know the questions people are asking around your keywords?

There’s plenty of keyword research workflow gold to be uncovered in Keyword Explorer. It’s a tool that can save you a ton of time when it comes to both general keyword research and the nitty-gritty details. And time and again, we hear from folks who are surprised that a tool they use all the time can do [insert cool and helpful thing here] — they had no idea! 

Well, let’s remedy that! Starting with today’s post, we’ll be publishing a series of quick videos put together by our own brilliant SEO scientist (and, according to Google, the smartest SEO in the world) Britney Muller. Each one will highlight one super useful workflow to solve a keyword research problem, and most are quick — just under a couple of minutes. Take a gander at the videos or skim the transcripts to find a workflow that catches your eye, and if you’re the type of person who likes to try it out in real time, head to the tool and give it a spin (if you have a Moz Community account like most Moz Blog readers, you already have free access):

Follow along in Keyword Explorer

1. How to do general keyword research

5:37 video

Find relevant keywords

You can do this a couple of ways. One is just to enter in a head keyword term that you want to explore — so maybe that’s “SEO” — and you can click Search. From here, you can go to Keyword Suggestions, where you can find all sorts of other keywords relevant to the keyword “SEO.”

We have a couple filters available to help you narrow down that search a little bit better. Here, without doing any filtering, you can see all of these keywords, and they’re ranked by relevancy and then search volume. So you do tend to see the higher search volume keywords at the top.

Save keyword suggestions in a list

But you can go through here and click the keywords that you want to save for your list. You can also do some filtering. We could group keywords by low lexical similarity. What this means is it’s basically just going to take somewhat similar keywords and batch them together for you to make it a bit easier.

Here you can see there are 141 group keywords under “SEO.” Fifty keywords have fallen under “SEO services” and so on. This gives you a higher level, topical awareness of what the keywords look like. If you were to select these groups, you could add a list for these.

When I say add list, I mean you can just save them in a keyword list that you can refer back to time and time again. These lists are amazing, one of my favorite features. What you would basically do is create a new list. I’m just going to call it Test. That adds all of your selected keywords to a list. You can continue adding keywords by different filters.

Filter by which keywords are questions

One of my other favorite things to filter by is “Are questions.” This will give you keywords that are actual questions, and it’s really neat to be able to try to bake these into your content marketing or an FAQ page. Really helpful. You can select all up here. Then I can just add that to that SEO Test list that we already created. I hope this gives you an idea of how to use some of these general filters.

Filter based on closely or broadly related topics and synonyms

You can also filter based on closely related topics, broadly related topics and synonyms. Keywords with similar result pages is very interesting. You can really play around with both of these filters. 

Filter by volume

You can also filter by volume. If you are trying to go after those high volume keywords, maybe you set a filter for here. Maybe you’re looking for long tail keywords, and then you’re going to look a little bit on the smaller search volume end here. These can all help in playing around and discovering more keywords.

Find the keywords a domain currently ranks for

Another thing that you can do to expand your keyword research is by entering in a domain. You can see that this changed to root domain when I entered moz.com. If you click Search, you’re going to get all of the keywords that that domain currently ranks for, which is really powerful. You could see all of the ranking keywords, add that to a list, and monitor how your website is performing.

Find competitors’ keywords

If you want to get really strategic, you can plug in some of your competitor sites and see what their keywords are. These are all things that you can do to expand your keyword research set. From there, you’re going to hopefully have one or a couple keyword lists that house all of this data for you to better strategically route your SEO strategy.

If we know that related questions are occurring most often, you can create strategic content around that. The opportunities here with these filters and sorts for keyword opportunities are endless.

2. How to discover ranking keywords for a particular domain or an exact page

1:37 video

See all the keywords a particular domain ranks for

This is super easy to do in Keyword Explorer. You just go to the main search bar. Let’s just throw in moz.com for example. I can see all the keywords that currently rank for moz.com.

We’re seeing over 114,000, and we get this really beautiful, high-level overview as to what that looks like. You can see the ranking distribution, and then you can even go into all of those ranking keywords in this tab here, which is really cool.

See all the keywords a specific page ranks for

You can do the same exact thing for a specific page. So let’s take the Beginner’s Guide. This will toggle to Exact Page, and you just click Search. Here we’re going to see that it ranks for 804 keywords. You get to know exactly what those are, what the difficulty is, the monthly search volume.

Keep track of those keywords in a list

You can add these things to a list to keep an eye on. It’s also great to do for competitive pages that appear to be doing very well or popular things occurring in your space. But this is just a quick and easy way to see what root domains or exact pages are currently ranking for.

3. How to quickly find keyword opportunities for a URL or a specific page

1:21 video

Find lower-ranking keywords that could be improved upon

I’m just going to paste in the URL to the Beginner’s Guide to SEO in Keyword Explorer. I’m going to look at all of the ranking keywords for this URL, and what I want to do is I want to sort by rank.

I want to see what’s ranking between 4 to 50 and see where or what keywords aren’t doing so well that we could improve upon. Right away we’re seeing this huge monthly search volume keyword, “SEO best practices,” and we’re ranking number 4.

It can definitely be improved upon. You can also go ahead and take a look at keywords that you rank for outside of page 1, meaning you rank 11 or beyond for these keywords. These could definitely also be improved upon. You can save these keywords to a list.

You can export them and strategically create content to improve those results. 

4. How to check rankings for a set of keywords

0:48 video

Use keyword lists to check rankings for a subset of keywords

This is pretty easy. So let’s say you have a keyword list for your target keywords. Here I’ve got an SEO Test keyword list. I want to see how Moz is ranking for these keywords.

This is where you would just add Check Rankings For and add your URL. I’m just going to put moz.com, check rankings, and I can immediately see how well we’re doing for these specific keywords.

I can filter highest to lowest and vice versa.

5. How to track your keywords

2:08 video

Set up a Campaign

If you don’t already have a list of your keywords that you would like to track, I suggest watching the General Keyword Research video above to help discover some of those keywords. But if you already have the keywords you know that you want to track for a particular site, definitely set up an account with Moz Pro and set up a Campaign.

It walks you through all of the steps to set up a particular Campaign for a URL. If you already have your Campaign set up, for example this is my Moz Campaign and I want to add say a new list of keywords to track, what you can do is you can come into this dashboard view and then go to Rankings.

If you scroll down here, you can add keywords. So let’s say Moz is breaking into the conversion rate optimization space. I can paste in a list of my CRO keywords, and then I can add a label.

Use keyword labels to track progress on topics over time 

Now that’s going to append that tag so I can filter by just CRO keywords. Then I’m going to click Add Keywords. This is going to take a little while to start to kick into gear basically.

But once it starts tracking, once these keywords are added, you’ll get to see them historically over time and even you against your competitors. It’s a really great way to monitor how you’re doing with keywords, where you’re seeing big drops or gains, and how you can better pivot your strategy to target those things.

Discover anything new or especially useful? Let us know on Twitter or here in the comments, and keep an eye out for more quick and fun keyword research workflow videos in the coming weeks — we’ve got some good stuff coming your way, from finding organic CTR for a keyword to discovering SERP feature opportunities and more.

Try out some new tricks in Keyword Explorer





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New Opportunities for Image SEO: How to Leverage Machine Vision for Strategic Wins
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New Opportunities for Image SEO: How to Leverage Machine Vision for Strategic Wins

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Image search results used to give you the option to “view image” without having to navigate to the site the image was hosted on.

When it started in 2013, sites saw a 63% decline in organic traffic from image results.

Why?

Because there was no need to click through when the image could be viewed in full from within the search results.

And then everything changed

In February 2018, Google decided to remove the “view image” button. Now searchers must visit the site hosting that image directly, restoring image results to their former organic search driving power.

According to some recent studies, this change has increased organic image traffic a massive 37%.

Given image results’ return to value, marketers are asking themselves how they can make the most out of this search mechanism.

So what are some new ways we can leverage tools to better understand how to optimize images for ranking?

To explore this, I decided to see if Google’s Vision AI could assist in unearthing hidden information about what matters to image ranking. Specifically, I wondered what Google’s image topic modeling would reveal about the images that rank for individual keyword searches, as well as groups of thematically related keywords aggregated around a specific topic or niche.

Here’s what I did — and what I found.

A deep dive on “hunting gear”

I began by pulling out 10 to 15 top keywords in our niche. For this article, we chose “hunting gear” as a category and pulled high-intent, high-value, high-volume keywords. The keywords we selected were:

  • Bow hunting gear
  • Cheap hunting gear
  • Coyote hunting gear
  • Dans hunting gear
  • Deer hunting gear
  • Discount hunting gear
  • Duck hunting gear
  • Hunting gear
  • Hunting rain gear
  • Sitka hunting gear
  • Turkey hunting gear
  • Upland hunting gear
  • Womens hunting gear

I then pulled the image results for the Top 50 ranking images for each of these keywords, yielding roughly ~650 images to give to Google’s image analysis API. I made sure to make note of the ranking position of each image in our data (this is important for later).

Learning from labels

The first, and perhaps most actionable, analysis the API can be used for is in labeling images. It utilizes state-of-the-art image recognition models to parse each image and return labels for everything within that image it can identify. Most images had between 4 and 10 identifiable objects contained within them. For the “hunting gear” related keywords listed above, this was the distribution of labels:

[full interactive]

At a high level, this gives us plenty of information about Google’s understanding of what images that rank for these terms should depict. A few takeaways:

  • The top ranking images across all 13 of these top keywords have a pretty even distribution across labels.
  • Clothing, and specifically camouflage, are highly represented, with nearly 5% of all images containing camo-style clothing. Now, perhaps this seems obvious, but it’s instructive. Including images in your blog posts related to these hunting keywords with images containing camo gear likely gives you improved likelihood of having one of your images included in top ranking image results.
  • Outdoor labels are also overrepresented: wildlife, trees, plants, animals, etc. Images of hunters in camo, out in the wild, and with animals near them are disproportionately represented.

Looking closer at the distribution labels by keyword category can give use a deeper understanding of how the ranking images differ between similar keywords.

[full interactive]

Here we see:

  • For “turkey hunting gear” and “duck hunting gear,” having birds in your images seems very important, with the other keywords rarely including images with birds.
  • Easy comparisons are possible with the interactive Tableau dashboards, giving you an “at a glance” understanding of what image distributions look like for an individual keyword vs. any other or all others. Below I highlighted just “duck hunting gear,” and you can see similar distribution of the most prevalent labels as the other keywords at the top. However, hugely overrepresented are “water bird,” “duck,” “bird,” “waders,” “hunting dog,” “hunting decoy,” etc., providing ample ideas for great images to include in the body of your content.

[full interactive]

Ranking comparisons

Getting an intuition for the differences in top ranking (images ranking in the first 10 images for a keyword search) vs. bottom ranking (images ranking in the 41st to 50th positions) is also possible.

[full interactive]

Here we can see that some labels seem preferred for top rankings. For instance:

  • Clothing-related labels are much more common amongst the best ranking images.
  • Animal-related labels are less common amongst the best ranking images but more common amongst the lower ranking images.
  • Guns seem significantly more likely to appear in top ranking images.

By investigating trends in labels across your keywords, you can gain many interesting insights into the images most likely to rank for your particular niche. These insights will be different for any set of keywords, but a close examination of the results will yield more than a few actionable insights.

Not surprisingly, there are ways to go even deeper in your analysis with other artificial intelligence APIs. Let’s take a look at how we can further supplement our efforts.

An even deeper analysis for understanding

Deepai.org has an amazing suite of APIs that can be easily accessed to provide additional image labeling capabilities. One such API is “Image Captioning,” which is similar to Google’s image labeling, but instead of providing single labels, it provides descriptive labels, like “the man is holding a gun.”

We ran all of the same images as the Google label detection through this API and got some great additional detail for each image.

Just as with the label analysis, I broke up the caption distributions and analyzed their distributions by keyword and by overall frequency for all of the selected keywords. Then I compared top and bottom ranking images.

A final interesting finding

Google sometimes ranks YouTube video thumbnails in image search results. Below is an example I found in the hunting gear image searches.

It seems likely that at least some of Google’s understanding of why this thumbnail should rank for hunting gear comes from its image label detection. Though other factors, like having “hunting gear” in the title and coming from the NRA (high topical authority) certainly help, the fact that this thumbnail depicts many of the same labels as other top-ranking images must also play a role.

The lesson here is that the right video thumbnail choice can help that thumbnail to rank for competitive terms, so apply your learnings from doing image search result label and caption analysis to your video SEO strategy!

In the case of either video thumbnails or standard images, don’t overlook the ranking potential of the elements featured — it could make a difference in your SERP positions.



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How to Target Featured Snippet Opportunities — Best of Whiteboard Friday
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How to Target Featured Snippet Opportunities — Best of Whiteboard Friday

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Once you’ve identified where the opportunity to nab a featured snippet lies, how do you go about targeting it? Part One of our “Featured Snippet Opportunities” series focused on how to discover places where you may be able to win a snippet, but today we’re focusing on how to actually make changes that’ll help you do that. 

Joining us at MozCon next week? This video is a great lead up to Britney’s talk: Featured Snippets: Essentials to Know & How to Target.

Give a warm, Mozzy welcome to Britney as she shares pro tips and examples of how we’ve been able to snag our own snippets using her methodology.

Target featured snippet opportunities

Click on the whiteboard image above to open a high-resolution version in a new tab!

Video Transcription

Today, we are going over targeting featured snippets, Part 2 of our featured snippets series. Super excited to dive into this.

What’s a featured snippet?

For those of you that need a little brush-up, what’s a featured snippet? Let’s say you do a search for something like, “Are pigs smarter than dogs?” You’re going to see an answer box that says, “Pigs outperform three-year old human children on cognitive tests and are smarter than any domestic animal. Animal experts consider them more trainable than cats or dogs.” How cool is that? But you’ll likely see these answer boxes for all sorts of things. So something to sort of keep an eye on. How do you become a part of that featured snippet box? How do you target those opportunities?

Last time, we talked about finding keywords that you rank on page one for that also have a featured snippet. There are a couple ways to do that. We talk about it in the first video. Something I do want to mention, in doing some of that the last couple weeks, is that Ahrefs can help you discover your featured snippet opportunities. I had no idea that was possible. Really cool, go check them out. If you don’t have Ahrefs and maybe you have Moz or SEMrush, don’t worry, you can do the same sort of thing with a Vlookup.

So I know this looks a little crazy for those of you that aren’t familiar. Super easy. It basically allows you to combine two sets of data to show you where some of those opportunities are. So happy to link to some of those resources down below or make a follow-up video on how to do just that.

1. Identify

All right. So step one is identifying these opportunities. You want to find the keywords that you’re on page one for that also have this answer box. You want to weigh the competitive search volume against qualified traffic. Initially, you might want to just go after search volume. I highly suggest you sort of reconsider and evaluate where might the qualified traffic come from and start to go after those.

2. Understand

From there, you really just want to understand the intent, more so even beyond this table that I have suggested for you. To be totally honest, I’m doing all of this with you. It’s been a struggle, and it’s been fun, but sometimes this isn’t very helpful. Sometimes it is. But a lot of times I’m not even looking at some of this stuff when I’m comparing the current featured snippet page and the page that we currently rank on page one for. I’ll tell you what I mean in a second.

3. Target

So we have an example of how I’ve been able to already steal one. Hopefully, it helps you. How do you target your keywords that have the featured snippet?

  • Simplifying and cleaning up your pages does wonders. Google wants to provide a very simple, cohesive, quick answer for searchers and for voice searches. So definitely try to mold the content in a way that’s easy to consume.
  • Summaries do well. Whether they’re at the top of the page or at the bottom, they tend to do very, very well.
  • Competitive markup, if you see a current featured snippet that is marked up in a particular way, you can do so to be a little bit more competitive.
  • Provide unique info
  • Dig deeper, go that extra mile, provide something else. Provide that value.

How To Target Featured Snippet Examples

What are some examples? So these are just some examples that I personally have been running into and I’ve been working on cleaning up.

  • Roman numerals. I am trying to target a list result, and the page we currently rank on number one for has Roman numerals. Maybe it’s a big deal, maybe it’s not. I just changed them to numbers to see what’s going to happen. I’ll keep you posted.
  • Fix broken links. But I’m also just going through our page and cleaning it. We have a lot of older content. I’m fixing broken links. I have the Check My Links tool. It’s a Chrome add-on plugin that I just click and it tells me what’s a 404 or what I might need to update.
  • Fixing spelling errors or any grammatical errors that may have slipped through editors’ eyes. I use Grammarly. I have the free version. It works really well, super easy. I’ve even found some super old posts that have the double or triple spacing after a period. It drives me crazy, but cleaning some of that stuff up.
  • Deleting extra markup. You might see some additional breaks, not necessarily like that ampersand. But you know what I mean in WordPress where it’s that weird little thing for that break in the space, you can clean those out. Some extra, empty header markup, feel free to delete those. You’re just cleaning and simplifying and improving your page.

One interesting thing that I’ve come across recently was for the keyword “MozRank.” Our page is beautifully written, perfectly optimized. It has all the things in place to be that featured snippet, but it’s not. That is when I fell back and I started to rely on some of this data. I saw that the current featured snippet page has all these links.

So I started to look into what are some easy backlinks I might be able to grab for that page. I came across Quora that had a question about MozRank, and I noticed that — this is a side tip — you can suggest edits to Quora now, which is amazing. So I suggested a link to our Moz page, and within the notes I said, “Hello, so and so. I found this great resource on MozRank. It completely confirms your wonderful answer. Thank you so much, Britney.”

I don’t know if that’s going to work. I know it’s a nofollow. I hope it can send some qualified traffic. I’ll keep you posted on that. But kind of a fun tip to be aware of.

How we nabbed the “find backlinks” featured snippet

All right. How did I nab the featured snippet “find backlinks”? This surprised me, because I hardly changed much at all, and we were able to steal that featured snippet quite easily. We were currently in the fourth position, and this was the old post that was in the fourth position. These are the updates I made that are now in the featured snippet.

Clean up the title

So we go from the title “How to Find Your Competitor’s Backlinks Next Level” to “How to Find Backlinks.” I’m just simplifying, cleaning it up.

Clean up the H2s

The first H2, “How to Check the Backlinks of a Site.” Clean it up, “How to Find Backlinks?” That’s it. I don’t change step one. These are all in H3s. I leave them in the H3s. I’m just tweaking text a little bit here and there.

Simplify and clarify your explanations/remove redundancies

I changed “Enter your competitor’s domain URL” — it felt a little duplicate — to “Enter your competitor’s URL.” Let’s see. “Export results into CSV,” what kind of results? I changed that to “export backlink data into CSV.” “Compile CSV results from all competitors,” what kind of results? “Compile backlink CSV results from all competitors.”

So you can look through this. All I’m doing is simplifying and adding backlinks to clarify some of it, and we were able to nab that.

So hopefully that example helps. I’m going to continue to sort of drudge through a bunch of these with you. I look forward to any of your comments, any of your efforts down below in the comments. Definitely looking forward to Part 3 and to chatting with you all soon.

Thank you so much for joining me on this edition of Whiteboard Friday. I look forward to seeing you all soon. See you.

Video transcription by Speechpad.com



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SEO Channel Context: An Analysis of Growth Opportunities
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SEO Channel Context: An Analysis of Growth Opportunities

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Too often do you see SEO analyses and decisions being made without considering the context of the marketing channel mix. Equally as often do you see large budgets being poured into paid ads in ways that seem to forget there’s a whole lot to gain from catering to popular search demand.

Both instances can lead to leaky conversion funnels and missed opportunity for long term traffic flows. But this article will show you a case of an SEO context analysis we used to determine the importance and role of SEO.

This analysis was one of our deliverables for a marketing agency client who hired us to inform SEO decisions which we then turned into a report template for you to get inspired by and duplicate.

Case description

The included charts show real, live data. You can see the whole SEO channel context analysis in this Data Studio SEO report template.

The traffic analyzed is for of a monetizing blog, whose marketing team also happens to be one of most fun to work for. For the sake of this case study, we’re giving them a spectacular undercover name — “The Broze Fellaz.”

For context, this blog started off with content for the first two years before they launched their flagship product. Now, they sell a catalogue of products highly relevant to their content and, thanks to one of the most entertaining Shark Tank episodes ever aired, they have acquired investments and a highly engaged niche community.

As you’ll see below, organic search is their biggest channel in many ways. Facebook also runs both as organic and paid and the team spends many an hour inside the platform. Email has elaborate automated flows that strive to leverage subscribers that come from the stellar content on the website. We therefore chose the three — organic Search, Facebook, and email — as a combination that would yield a comprehensive analysis with insights we can easily act on.

Ingredients for the SEO analysis

This analysis is a result of a long-term retainer relationship with “The Broze Fellaz” as our ongoing analytics client. A great deal was required in order for data-driven action to happen, but we assure you, it’s all doable.

From the analysis best practice drawer, we used:

  • 2 cups of relevant channels for context and analysis via comparison.

  • 3 cups of different touch points to identify channel roles — bringing in traffic, generating opt-ins, closing sales, etc.

  • 5 heads of open-minded lettuce and readiness to change current status quo, for a team that can execute.

  • 457 oz of focus-on-finding what is going on with organic search, why it is going on, and what we can do about it (otherwise, we’d end up with another scorecard export).

  • Imperial units used in arbitrary numbers that are hard to imagine and thus feel very large.

  • 1 to 2 heads of your analyst brain, baked into the analysis. You’re not making an automated report — even a HubSpot intern can do that. You’re being a human and you’re analyzing. You’re making human analysis. This helps avoid having your job stolen by a robot.

  • Full tray of Data Studio visualizations that appeal to the eye.

  • Sprinkles of benchmarks, for highlighting significance of performance differences.

From the measurement setup and stack toolbox, we used:

  • Google Analytics with tailored channel definitions, enhanced e-commerce and Search Console integration.

  • Event tracking for opt-ins and adjusted bounce rate via MashMetrics GTM setup framework.

  • UTM routine for social and email traffic implemented via Google Sheets & UTM.io.

  • Google Data Studio. This is my favorite visualization tool. Despite its flaws and gaps (as it’s still in beta) I say it is better than its paid counterparts, and it keeps getting better. For data sources, we used the native connectors for Google Analytics and Google Sheets, then Facebook community connectors by Supermetrics.

  • Keyword Hero. Thanks to semantic algorithms and data aggregation, you are indeed able to see 95 percent of your organic search queries (check out Onpage Hero, too, you’ll be amazed).

Inspiration for my approach comes from Lea Pica, Avinash, the Google Data Studio newsletter, and Chris Penn, along with our dear clients and the questions they have us answer for them.

Ready? Let’s dive in.

Analysis of the client’s SEO on the context of their channel mix

1) Insight: Before the visit

What’s going on and why is it happening?

Organic search traffic volume blows the other channels out of the water. This is normal for sites with quality regular content; yet, the difference is stark considering the active effort that goes into Facebook and email campaigns.

The CTR of organic search is up to par with Facebook. That’s a lot to say when comparing an organic channel to a channel with high level of targeting control.

It looks like email flows are the clear winner in terms of CTR to the website, which has a highly engaged community of users who return fairly often and advocate passionately. It also has a product and content that’s incredibly relevant to their users, which few other companies appear to be good at.

There’s a high CTR on search engine results pages often indicates that organic search may support funnel stages beyond just the top.

As well, email flows are sent to a very warm audience — interested users who went through a double opt-in. It is to be expected for this CTR to be high.

What’s been done already?

There’s an active effort and budget allocation being put towards Facebook Ads and email automation. A content plan has been put in place and is being executed diligently.

What we recommend next

  1. Approach SEO in a way as systematic as what you do for Facebook and email flows.

  2. Optimize meta titles and descriptions via testing tools such as Sanity Check. The organic search CTR may become consistently higher than that of Facebook ads.

  3. Assuming you’ve worked on improving CTR for Facebook ads, have the same person work on the meta text and titles. Most likely, there’ll be patterns you can replicate from social to SEO.

  4. Run a technical audit and optimize accordingly. Knowing that you haven’t done that in a long time, and seeing how much traffic you get anyway, there’ll be quick, big wins to enjoy.

Results we expect

You can easily increase the organic CTR by at least 5 percent. You could also clean up the technical state of your site in the eyes of crawlers -— you’ll then see faster indexing by search engines when you publish new content, increased impressions for existing content. As a result, you may enjoy a major spike within a month.

2) Insight: Engagement and options during the visit

With over 70 percent of traffic coming to this website from organic search, the metrics in this analysis will be heavily skewed towards organic search. So, comparing the rate for organic search to site-wide is sometimes conclusive, other times not conclusive.

Adjusted bounce rate — via GTM events in the measurement framework used, we do not count a visit as a bounce if the visit lasts 45 seconds or longer. We prefer this approach because such an adjusted bounce rate is much more actionable for content sites. Users who find what they were searching for often read the page they land on for several minutes without clicking to another page. However, this is still a memorable visit for the user. Further, staying on the landing page for a while, or keeping the page open in a browser tab, are both good indicators for distinguishing quality, interested traffic, from all traffic.

We included all Facebook traffic here, not just paid. We know from the client’s data that the majority is from paid content, they have a solid UTM routine in place. But due to boosted posts, we’ve experienced big inaccuracies when splitting paid and organic Facebook for the purposes of channel attribution.

What’s going on and why is it happening?

It looks like organic search has a bounce rate worse than the email flows — that’s to be expected and not actionable, considering that the emails are only sent to recent visitors who have gone through a double opt-in. What is meaningful, however, is that organic has a better bounce rate than Facebook. It is safe to say that organic search visitors will be more likely to remember the website than the Facebook visitors.

Opt-in rates for Facebook are right above site average, and those for organic search are right below, while organic is bringing in a majority of email opt-ins despite its lower opt-in rate.

Google’s algorithms and the draw of the content on this website are doing better at winning users’ attention than the detailed targeting applied on Facebook. The organic traffic will have a higher likelihood of remembering the website and coming back. Across all of our clients, we find that organic search can be a great retargeting channel, particularly if you consider that the site will come up higher in search results for its recent visitors.

What’s been done already?

The Facebook ad campaigns of “The Broze Fellaz” have been built and optimized for driving content opt-ins. Site content that ranks in organic search is less intentional than that.

Opt-in placements have been tested on some of the biggest organic traffic magnets.

Thorough, creative and consistent content calendars have been in place as a foundation for all channels.

What we recommend next

  1. It’s great to keep using organic search as a way to introduce new users to the site. Now, you can try to be more intentional about using it for driving opt-ins. It’s already serving both of the stages of the funnel.

  2. Test and optimize opt-in placements on more traffic magnets.

  3. Test and optimize opt-in copy for top 10 traffic magnets.

  4. Once your opt-in rates have improved, focus on growing the channel. Add to the content work with a 3-month sprint of an extensive SEO project

  5. Assign Google Analytics goal values to non-e-commerce actions on your site. The current opt-ins have different roles and levels of importance and there’s also a handful of other actions people can take that lead to marketing results down the road. Analyzing goal values will help you create better flows toward pre-purchase actions.

  6. Facebook campaigns seem to be at a point where you can pour more budget into them and expect proportionate increase in opt-in count.

Results we expect

Growth in your opt-ins from Facebook should be proportionate to increase in budget, with a near-immediate effect. At the same time, it’s fairly realistic to bring the opt-in rate of organic search closer to site average.

3) Insight: Closing the deal

For channel attribution with money involved, you want to make sure that your Google Analytics channel definitions, view filters, and UTM’s are in top shape.

What’s going on and why is it happening?

Transaction rate, as well as per session value, is higher for organic search than it is for Facebook (paid and organic combined).

Organic search contributes to far more last-click revenue than Facebook and email combined. For its relatively low volume of traffic, email flows are outstanding in the volume of revenue they bring in.

Thanks to the integration of Keyword Hero with Google Analytics for this client, we can see that about 30 percent of organic search visits are from branded keywords, which tends to drive the transaction rate up.

So, why is this happening? Most of the product on the site is highly relevant to the information people search for on Google.

Multi-channel reports in Google Analytics also show that people often discover the site in organic search, then come back by typing in the URL or clicking a bookmark. That makes organic a source of conversions where, very often, no other channels are even needed.

We can conclude that Facebook posts and campaigns of this client are built to drive content opt-ins, not e-commerce transactions. Email flows are built specifically to close sales.

What’s been done already?

There is dedicated staff for Facebook campaigns and posts, as well a thorough system dedicated to automated email flows.

A consistent content routine is in place, with experienced staff at the helm. A piece has been published every week for the last few years, with the content calendar filled with ready-to-publish content for the next few months. The community is highly engaged, reading times are high, comment count soaring, and usefulness of content outstanding. This, along with partnerships with influencers, helps “The Broze Fellaz” take up a half of the first page on the SERP for several lucrative topics. They’ve been achieving this even without a comprehensive SEO project. Content seems to be king indeed.

Google Shopping has been tried. The campaign looked promising but didn’t yield incremental sales. There’s much more search demand for informational queries than there is for product.

What we recommend next

  1. Organic traffic is ready to grow. If there is no budget left, resource allocation should be considered. In paid search, you can often simply increase budgets. Here, with stellar content already performing well, a comprehensive SEO project is begging for your attention. Focus can be put into structure and technical aspects, as well as content that better caters to search demand. Think optimizing the site’s information architecture, interlinking content for cornerstone structure, log analysis, and technical cleanup, meta text testing for CTR gains that would also lead to ranking gains, strategic ranking of long tail topics, intentional growing of the backlink profile.

  2. Three- or six-month intensive sprint of comprehensive SEO work would be appropriate.

Results we expect

Increasing last click revenue from organic search and direct by 25 percent would lead to a gain as high as all of the current revenue from automated email flows. Considering how large the growth has been already, this gain is more than achievable in 3–6 months.

Wrapping it up

Organic search presence of “The Broze Fellaz” should continue to be the number-one role for bringing new people to the site and bringing people back to the site. Doing so supports sales that happen with the contribution of other channels, e.g. email flows. The analysis points out is that organic search is also effective at playing the role of the last-click channel for transactions, often times without the help of other channels.

We’ve worked with this client for a few years, and, based on our knowledge of their marketing focus, this analysis points us to a confident conclusion that a dedicated, comprehensive SEO project will lead to high incremental growth.

Your turn

In drawing analytical conclusions and acting on them, there’s always more than one way to shoe a horse. Let us know what conclusions you would’ve drawn instead. Copy the layout of our SEO Channel Context Comparison analysis template and show us what it helped you do for your SEO efforts — create a similar analysis for a paid or owned channel in your mix. Whether it’s comments below, tweeting our way, or sending a smoke signal, we’ll be all ears. And eyes.



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Build a Search Intent Dashboard to Unlock Better Opportunities
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Build a Search Intent Dashboard to Unlock Better Opportunities

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We’ve been talking a lot about search intent this week, and if you’ve been following along, you’re likely already aware of how “search intent” is essential for a robust SEO strategy. If, however, you’ve ever laboured for hours classifying keywords by topic and search intent, only to end up with a ton of data you don’t really know what to do with, then this post is for you.

I’m going to share how to take all that sweet keyword data you’ve categorized, put it into a Power BI dashboard, and start slicing and dicing to uncover a ton insights — faster than you ever could before.

Building your keyword list

Every great search analysis starts with keyword research and this one is no different. I’m not going to go into excruciating detail about how to build your keyword list. However, I will mention a few of my favorite tools that I’m sure most of you are using already:

Please note that these tools are a great way to scale your keyword collecting but each will come with the need to comb through and clean your data to ensure all keywords are at least somewhat relevant to your business and audience.

Once I have an initial keyword list built, I’ll upload it to STAT and let it run for a couple days to get an initial data pull. This allows me to pull the ‘People Also Ask’ and ‘Related Searches’ reports in STAT to further build out my keyword list. All in all, I’m aiming to get to at least 5,000 keywords, but the more the merrier.

For the purposes of this blog post I have about 19,000 keywords I collected for a client in the window treatments space.

Categorizing your keywords by topic

Bucketing keywords into categories is an age-old challenge for most digital marketers but it’s a critical step in understanding the distribution of your data. One of the best ways to segment your keywords is by shared words. If you’re short on AI and machine learning capabilities, look no further than a trusty Ngram analyzer. I love to use this Ngram Tool from guidetodatamining.com — it ain’t much to look at, but it’s fast and trustworthy.

After dropping my 19,000 keywords into the tool and analyzing by unigram (or 1-word phrases), I manually select categories that fit with my client’s business and audience. I also make sure the unigram accounts for a decent amount of keywords (e.g. I wouldn’t pick a unigram that has a count of only 2 keywords).

Using this data, I then create a Category Mapping table and map a unigram, or “trigger word”, to a Category like the following:

You’ll notice that for “curtain” and “drapes” I mapped both to the Curtains category. For my client’s business, they treat these as the same product, and doing this allows me to account for variations in keywords but ultimately group them how I want for this analysis.

Using this method, I create a Trigger Word-Category mapping based on my entire dataset. It’s possible that not every keyword will fall into a category and that’s okay — it likely means that keyword is not relevant or significant enough to be accounted for.

Creating a keyword intent map

Similar to identifying common topics by which to group your keywords, I’m going to follow a similar process but with the goal of grouping keywords by intent modifier.

Search intent is the end goal of a person using a search engine. Digital marketers can leverage these terms and modifiers to infer what types of results or actions a consumer is aiming for.

For example, if a person searches for “white blinds near me”, it is safe to infer that this person is looking to buy white blinds as they are looking for a physical location that sells them. In this case I would classify “near me” as a “Transactional” modifier. If, however, the person searched “living room blinds ideas” I would infer their intent is to see images or read blog posts on the topic of living room blinds. I might classify this search term as being at the “Inspirational” stage, where a person is still deciding what products they might be interested and, therefore, isn’t quite ready to buy yet.

There is a lot of research on some generally accepted intent modifiers in search and I don’t intent to reinvent the wheel. This handy guide (originally published in STAT) provides a good review of intent modifiers you can start with.

I followed the same process as building out categories to build out my intent mapping and the result is a table of intent triggers and their corresponding Intent stage.

Intro to Power BI

There are tons of resources on how to get started with the free tool Power BI, one of which is from own founder Will Reynold’s video series on using Power BI for Digital Marketing. This is a great place to start if you’re new to the tool and its capabilities.

Note: it’s not about the tool necessarily (although Power BI is a super powerful one). It’s more about being able to look at all of this data in one place and pull insights from it at speeds which Excel just won’t give you. If you’re still skeptical of trying a new tool like Power BI at the end of this post, I urge you to get the free download from Microsoft and give it a try.

Setting up your data in Power BI

Power BI’s power comes from linking multiple datasets together based on common “keys.” Think back to your Microsoft Access days and this should all start to sound familiar.

Step 1: Upload your data sources

First, open Power BI and you’ll see a button called “Get Data” in the top ribbon. Click that and then select the data format you want to upload. All of my data for this analysis is in CSV format so I will select the Text/CSV option for all of my data sources. You have to follow these steps for each data source. Click “Load” for each data source.

Step 2: Clean your data

In the Power BI ribbon menu, click the button called “Edit Queries.” This will open the Query Editor where we will make all of our data transformations.


The main things you’ll
want to do in the Query Editor are the following:

  • Make sure all data formats make sense (e.g. keywords are formatted as text, numbers are formatted as decimals or whole numbers).

  • Rename columns as needed.

  • Create a domain column in your Top 20 report based on the URL column.


Close and apply your
changes by hitting the “Edit Queries” button, as seen above.

Step 3: Create relationships between data sources

On the left side of Power BI is a vertical bar with icons for different views. Click the third one to see your relationships view.

In this view, we are going to connect all data sources to our ‘Keywords Bridge’ table by clicking and dragging a line from the field ‘Keyword’ in each table and to ‘Keyword’ in the ‘Keywords Bridge’ table (note that for the PPC Data, I have connected ‘Search Term’ as this is the PPC equivalent of a keyword, as we’re using here).

The last thing we need to do for our relationships is double-click on each line to ensure the following options are selected for each so that our dashboard works properly:

  • The cardinality is Many to 1
  • The relationship is “active”
  • The cross filter direction is set to “both”

We are now ready to start building our Intent Dashboard and analyzing our data.

Building the search intent dashboard

In this section I’ll walk you through each visual in the Search Intent Dashboard (as seen below):

Top domains by count of keywords

Visual type: Stacked Bar Chart visual

Axis: I’ve nested URL under Domain so I can drill down to see this same breakdown by URL for a specific Domain

Value: Distinct count of keywords

Legend: Result Types

Filter: Top 10 filter on Domains by count of distinct keywords

Keyword breakdown by result type

Visual type: Donut chart

Legend: Result Types

Value: Count of distinct keywords, shown as Percent of grand total

Metric Cards

Sum of Distinct MSV

Because the Top 20 report shows each keyword 20 times, we need to create a calculated measure in Power BI to only sum MSV for the unique list of keywords. Use this formula for that calculated measure: 

Sum Distinct MSV = SUMX(DISTINCT('Table'[Keywords]), FIRSTNONBLANK('Table'[MSV], 0))

Keywords

This is just a distinct count of keywords

Slicer: PPC Conversions

Visual type: Slicer

Drop your PPC Conversions field into a slicer and set the format to “Between” to get this nifty slider visual.

Tables

Visual type: Table or Matrix (a matrix allows for drilling down similar to a pivot table in Excel)

Values: Here I have Category or Intent Stage and then the distinct count of keywords.

Pulling insights from your search intent dashboard

This dashboard is now a Swiss Army knife of data that allows you to slice and dice to your heart’s content. Below are a couple examples of how I use this dashboard to pull out opportunities and insights for my clients.

Where are competitors winning?

With this data we can quickly see who the top competing domains are, but what’s more valuable is seeing who the competitors are for a particular intent stage and category.

I start by filtering to the “Informational” stage, since it represents the most keywords in our dataset. I also filter to the top category for this intent stage which is “Blinds”. Looking at my Keyword Count card, I can now see that I’m looking at a subset of 641 keywords.

Note: To filter multiple visuals in Power BI, you need to press and hold the “Ctrl” button each time you click a new visual to maintain all the filters you clicked previously.

The top competing subdomain here is videos.blinds.com with visibility in the top 20 for over 250 keywords, most of which are for video results. I hit ctrl+click on the Video results portion of videos.blinds.com to update the keywords table to only keywords where videos.blinds.com is ranking in the top 20 with a video result.

From all this I can now say that videos.blinds.com is ranking in the top 20 positions for about 30 percent of keywords that fall into the “Blinds” category and the “Informational” intent stage. I can also see that most of the keywords here start with “how to”, which tells me that most likely people searching for blinds in an informational stage are looking for how to instructions and that video may be a desired content format.

Where should I focus my time?

Whether you’re in-house or at an agency, time is always a hit commodity. You can use this dashboard to quickly identify opportunities that you should be prioritizing first — opportunities that can guarantee you’ll deliver bottom-line results.

To find these bottom-line results, we’re going to filter our data using the PPC conversions slicer so that our data only includes keywords that have converted at least once in our PPC campaigns.

Once I do that, I can see I’m working with a pretty limited set of keywords that have been bucketed into intent stages, but I can continue by drilling into the “Transactional” intent stage because I want to target queries that are linked to a possible purchase.

Note: Not every keyword will fall into an intent stage if it doesn’t meet the criteria we set. These keywords will still appear in the data, but this is the reason why your total keyword count might not always match the total keyword count in the intent stages or category tables.

From there I want to focus on those “Transactional” keywords that are triggering answer boxes to make sure I have good visibility, since they are converting for me on PPC. To do that, I filter to only show keywords triggering answer boxes. Based on these filters I can look at my keyword table and see most (if not all) of the keywords are “installation” keywords and I don’t see my client’s domain in the top list of competitors. This is now an area of focus for me to start driving organic conversions.

Wrap up

I’ve only just scratched the surface — there’s tons that can can be done with this data inside a tool like Power BI. Having a solid data set of keywords and visuals that I can revisit repeatedly for a client and continuously pull out opportunities to help fuel our strategy is, for me, invaluable. I can work efficiently without having to go back to keyword tools whenever I need an idea. Hopefully you find this makes building an intent-based strategy more efficient and sound for your business or clients.



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Uncovering SEO Opportunities via Log Files
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Uncovering SEO Opportunities via Log Files

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I use web crawlers on a daily basis. While they are very useful, they only imitate search engine crawlers’ behavior, which means you aren’t always getting the full picture.

The only tool that can give you a real overview of how search engines crawl your site are log files. Despite this, many people are still obsessed with crawl budget — the number of URLs Googlebot can and wants to crawl.

Log file analysis may discover URLs on your site that you had no idea about but that search engines are crawling anyway — a major waste of Google server resources (Google Webmaster Blog):

“Wasting server resources on pages like these will drain crawl activity from pages that do actually have value, which may cause a significant delay in discovering great content on a site.”

While it’s a fascinating topic, the fact is that most sites don’t need to worry that much about crawl budget —an observation shared by John Mueller (Webmaster Trends Analyst at Google) quite a few times already.

There’s still a huge value in analyzing logs produced from those crawls, though. It will show what pages Google is crawling and if anything needs to be fixed.

When you know exactly what your log files are telling you, you’ll gain valuable insights about how Google crawls and views your site, which means you can optimize for this data to increase traffic. And the bigger the site, the greater the impact fixing these issues will have.

What are server logs?

A log file is a recording of everything that goes in and out of a server. Think of it as a ledger of requests made by crawlers and real users. You can see exactly what resources Google is crawling on your site.

You can also see what errors need your attention. For instance, one of the issues we uncovered with our analysis was that our CMS created two URLs for each page and Google discovered both. This led to duplicate content issues because two URLs with the same content was competing against each other.

Analyzing logs is not rocket science — the logic is the same as when working with tables in Excel or Google Sheets. The hardest part is getting access to them — exporting and filtering that data.

Looking at a log file for the first time may also feel somewhat daunting because when you open one, you see something like this:

Calm down and take a closer look at a single line:

66.249.65.107 - - [08/Dec/2017:04:54:20 -0400] "GET /contact/ HTTP/1.1" 200 11179 "-" "Mozilla/5.0 (compatible; Googlebot/2.1; +http://www.google.com/bot.html)"

You’ll quickly recognize that:

  • 66.249.65.107 is the IP address (who)

  • [08/Dec/2017:04:54:20 -0400] is the Timestamp (when)

  • GET is the Method

  • /contact/ is the Requested URL (what)

  • 200 is the Status Code (result)

  • 11179 is the Bytes Transferred (size)

  • “-” is the Referrer URL (source) — it’s empty because this request was made by a crawler

  • Mozilla/5.0 (compatible; Googlebot/2.1; +http://www.google.com/bot.html) is the User Agent (signature) — this is user agent of Googlebot (Desktop)

Once you know what each line is composed of, it’s not so scary. It’s just a lot of information. But that’s where the next step comes in handy.

Tools you can use

There are many tools you can choose from that will help you analyze your log files. I won’t give you a full run-down of available ones, but it’s important to know the difference between static and real-time tools.

  • Static — This only analyzes a static file. You can’t extend the time frame. Want to analyze another period? You need to request a new log file. My favourite tool for analyzing static log files is Power BI.

  • Real-time — Gives you direct access to logs. I really like open source ELK Stack (Elasticsearch, Logstash, and Kibana). It takes a moderate effort to implement it but once the stack is ready, it allows me changing the time frame based on my needs without needing to contact our developers.

Start analyzing

Don’t just dive into logs with a hope to find something — start asking questions. If you don’t formulate your questions at the beginning, you will end up in a rabbit hole with no direction and no real insights.

Here are a few samples of questions I use at the start of my analysis:

  • Which search engines crawl my website?

  • Which URLs are crawled most often?

  • Which content types are crawled most often?

  • Which status codes are returned?

If you see that Google is crawling non-existing pages (404), you can start asking which of those requested URLs return 404 status code.

Order the list by the number of requests, evaluate the ones with the highest number to find the pages with the highest priority (the more requests, the higher priority), and consider whether to redirect that URL or do any other action.

If you use a CDN or cache server, you need to get that data as well to get the full picture.

Segment your data

Grouping data into segments provides aggregate numbers that give you the big picture. This makes it easier to spot trends you might have missed by looking only at individual URLs. You can locate problematic sections and drill down if needed.

There are various ways to group URLs:

  • Group by content type (single product pages vs. category pages)

  • Group by language (English pages vs. French pages)

  • Group by storefront (Canadian store vs. US store)

  • Group by file format (JS vs. images vs. CSS)

Don’t forget to slice your data by user-agent. Looking at Google Desktop, Google Smartphone, and Bing all together won’t surface any useful insights.

Monitor behavior changes over time

Your site changes over time, which means so will crawlers’ behavior. Googlebot often decreases or increases the crawl rate based on factors such as a page’s speed, internal link structure, and the existence of crawl traps.

It’s a good idea to check in with your log files throughout the year or when executing website changes. I look at logs almost on a weekly basis when releasing significant changes for large websites.

By analyzing server logs twice a year, at the very least, you’ll surface changes in crawler’s behavior.

Watch for spoofing

Spambots and scrapers don’t like being blocked, so they may fake their identity — they leverage Googlebot’s user agent to avoid spam filters.

To verify if a web crawler accessing your server really is Googlebot, you can run a reverse DNS lookup and then a forward DNS lookup. More on this topic can be found in Google Webmaster Help Center.

Merge logs with other data sources

While it’s no necessary to connect to other data sources, doing so will unlock another level of insight and context that regular log analysis might not be able to give you. An ability to easily connect multiple datasets and extract insights from them is the main reason why Power BI is my tool of choice, but you can use any tool that you’re familiar with (e.g. Tableau).

Blend server logs with multiple other sources such as Google Analytics data, keyword ranking, sitemaps, crawl data, and start asking questions like:

  • What pages are not included in the sitemap.xml but are crawled extensively?

  • What pages are included in the Sitemap.xml file but are not crawled?

  • Are revenue-driving pages crawled often?

  • Is the majority of crawled pages indexable?

You may be surprised by the insights you’ll uncover that can help strengthen your SEO strategy. For instance, discovering that almost 70 percent of Googlebot requests are for pages that are not indexable is an insight you can act on.

You can see more examples of blending log files with other data sources in my post about advanced log analysis.

Use logs to debug Google Analytics

Don’t think of server logs as just another SEO tool. Logs are also an invaluable source of information that can help pinpoint technical errors before they become a larger problem.

Last year, Google Analytics reported a drop in organic traffic for our branded search queries. But our keyword tracking tool, STAT Search Analytics, and other tools showed no movement that would have warranted the drop. So, what was going on?

Server logs helped us understand the situation: There was no real drop in traffic. It was our newly deployed WAF (Web Application Firewall) that was overriding the referrer, which caused some organic traffic to be incorrectly classified as direct traffic in Google Analytics.

Using log files in conjunction with keyword tracking in STAT helped us uncover the whole story and diagnose this issue quickly.

Putting it all together

Log analysis is a must-do, especially once you start working with large websites.

My advice is to start with segmenting data and monitoring changes over time. Once you feel ready, explore the possibilities of blending logs with your crawl data or Google Analytics. That’s where great insights are hidden.

Want more?

Ready to learn how to get cracking and tracking some more? Reach out and request a demo get your very own tailored walkthrough of STAT.





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