Tag Archive | "Keyword"

Ranking the 6 Most Accurate Keyword Research Tools

Posted by Jeff_Baker

In January of 2018 Brafton began a massive organic keyword targeting campaign, amounting to over 90,000 words of blog content being published.

Did it work?

Well, yeah. We doubled the number of total keywords we rank for in less than six months. By using our advanced keyword research and topic writing process published earlier this year we also increased our organic traffic by 45% and the number of keywords ranking in the top ten results by 130%.

But we got a whole lot more than just traffic.

From planning to execution and performance tracking, we meticulously logged every aspect of the project. I’m talking blog word count, MarketMuse performance scores, on-page SEO scores, days indexed on Google. You name it, we recorded it.

As a byproduct of this nerdery, we were able to draw juicy correlations between our target keyword rankings and variables that can affect and predict those rankings. But specifically for this piece…

How well keyword research tools can predict where you will rank.

A little background

We created a list of keywords we wanted to target in blogs based on optimal combinations of search volume, organic keyword difficulty scores, SERP crowding, and searcher intent.

We then wrote a blog post targeting each individual keyword. We intended for each new piece of blog content to rank for the target keyword on its own.

With our keyword list in hand, my colleague and I manually created content briefs explaining how we would like each blog post written to maximize the likelihood of ranking for the target keyword. Here’s an example of a typical brief we would give to a writer:

This image links to an example of a content brief Brafton delivers to writers.

Between mid-January and late May, we ended up writing 55 blog posts each targeting 55 unique keywords. 50 of those blog posts ended up ranking in the top 100 of Google results.

We then paused and took a snapshot of each URL’s Google ranking position for its target keyword and its corresponding organic difficulty scores from Moz, SEMrush, Ahrefs, SpyFu, and KW Finder. We also took the PPC competition scores from the Keyword Planner Tool.

Our intention was to draw statistical correlations between between our keyword rankings and each tool’s organic difficulty score. With this data, we were able to report on how accurately each tool predicted where we would rank.

This study is uniquely scientific, in that each blog had one specific keyword target. We optimized the blog content specifically for that keyword. Therefore every post was created in a similar fashion.

Do keyword research tools actually work?

We use them every day, on faith. But has anyone ever actually asked, or better yet, measured how well keyword research tools report on the organic difficulty of a given keyword?

Today, we are doing just that. So let’s cut through the chit-chat and get to the results…

This image ranks each of the 6 keyword research tools, in order, Moz leads with 4.95 stars out of 5, followed by KW Finder, SEMrush, AHREFs, SpyFu, and lastly Keyword Planner Tool.

While Moz wins top-performing keyword research tool, note that any keyword research tool with organic difficulty functionality will give you an advantage over flipping a coin (or using Google Keyword Planner Tool).

As you will see in the following paragraphs, we have run each tool through a battery of statistical tests to ensure that we painted a fair and accurate representation of its performance. I’ll even provide the raw data for you to inspect for yourself.

Let’s dig in!

The Pearson Correlation Coefficient

Yes, statistics! For those of you currently feeling panicked and lobbing obscenities at your screen, don’t worry — we’re going to walk through this together.

In order to understand the relationship between two variables, our first step is to create a scatter plot chart.

Below is the scatter plot for our 50 keyword rankings compared to their corresponding Moz organic difficulty scores.

This image shows a scatter plot for Moz's keyword difficulty scores versus our keyword rankings. In general, the data clusters fairly tight around the regression line.

We start with a visual inspection of the data to determine if there is a linear relationship between the two variables. Ideally for each tool, you would expect to see the X variable (keyword ranking) increase proportionately with the Y variable (organic difficulty). Put simply, if the tool is working, the higher the keyword difficulty, the less likely you will rank in a top position, and vice-versa.

This chart is all fine and dandy, however, it’s not very scientific. This is where the Pearson Correlation Coefficient (PCC) comes into play.

The PCC measures the strength of a linear relationship between two variables. The output of the PCC is a score ranging from +1 to -1. A score greater than zero indicates a positive relationship; as one variable increases, the other increases as well. A score less than zero indicates a negative relationship; as one variable increases, the other decreases. Both scenarios would indicate a level of causal relationship between the two variables. The stronger the relationship between the two veriables, the closer to +1 or -1 the PCC will be. Scores near zero indicate a weak or no relatioship.

Phew. Still with me?

So each of these scatter plots will have a corresponding PCC score that will tell us how well each tool predicted where we would rank, based on its keyword difficulty score.

We will use the following table from statisticshowto.com to interpret the PCC score for each tool:

Coefficient Correlation R Score

Key

.70 or higher

Very strong positive relationship

.40 to +.69

Strong positive relationship

.30 to +.39

Moderate positive relationship

.20 to +.29

Weak positive relationship

.01 to +.19

No or negligible relationship

0

No relationship [zero correlation]

-.01 to -.19

No or negligible relationship

-.20 to -.29

Weak negative relationship

-.30 to -.39

Moderate negative relationship

-.40 to -.69

Strong negative relationship

-.70 or higher

Very strong negative relationship

In order to visually understand what some of these relationships would look like on a scatter plot, check out these sample charts from Laerd Statistics.

These scatter plots show three types of correlations: positive, negative, and no correlation. Positive correlations have data plots that move up and to the right. Negative correlations move down and to the right. No correlation has data that follows no linear pattern

And here are some examples of charts with their correlating PCC scores (r):

These scatter plots show what different PCC values look like visually. The tighter the grouping of data around the regression line, the higher the PCC value.

The closer the numbers cluster towards the regression line in either a positive or negative slope, the stronger the relationship.

That was the tough part – you still with me? Great, now let’s look at each tool’s results.

Test 1: The Pearson Correlation Coefficient

Now that we’ve all had our statistics refresher course, we will take a look at the results, in order of performance. We will evaluate each tool’s PCC score, the statistical significance of the data (P-val), the strength of the relationship, and the percentage of keywords the tool was able to find and report keyword difficulty values for.

In order of performance:

#1: Moz

This image shows a scatter plot for Moz's keyword difficulty scores versus our keyword rankings. In general, the data clusters fairly tight around the regression line.

Revisiting Moz’s scatter plot, we observe a tight grouping of results relative to the regression line with few moderate outliers.

Moz Organic Difficulty Predictability

PCC

0.412

P-val

.003 (P<0.05)

Relationship

Strong

% Keywords Matched

100.00%

Moz came in first with the highest PCC of .412. As an added bonus, Moz grabs data on keyword difficulty in real time, rather than from a fixed database. This means that you can get any keyword difficulty score for any keyword.

In other words, Moz was able to generate keyword difficulty scores for 100% of the 50 keywords studied.

#2: SpyFu

This image shows a scatter plot for SpyFu's keyword difficulty scores versus our keyword rankings. The plot is similar looking to Moz's, with a few larger outliers.

Visually, SpyFu shows a fairly tight clustering amongst low difficulty keywords, and a couple moderate outliers amongst the higher difficulty keywords.

SpyFu Organic Difficulty Predictability

PCC

0.405

P-val

.01 (P<0.05)

Relationship

Strong

% Keywords Matched

80.00%

SpyFu came in right under Moz with 1.7% weaker PCC (.405). However, the tool ran into the largest issue with keyword matching, with only 40 of 50 keywords producing keyword difficulty scores.

#3: SEMrush

This image shows a scatter plot for SEMrush's keyword difficulty scores versus our keyword rankings. The data has a significant amount of outliers relative to the regression line.

SEMrush would certainly benefit from a couple mulligans (a second chance to perform an action). The Correlation Coefficient is very sensitive to outliers, which pushed SEMrush’s score down to third (.364).

SEMrush Organic Difficulty Predictability

PCC

0.364

P-val

.01 (P<0.05)

Relationship

Moderate

% Keywords Matched

92.00%

Further complicating the research process, only 46 of 50 keywords had keyword difficulty scores associated with them, and many of those had to be found through SEMrush’s “phrase match” feature individually, rather than through the difficulty tool.

The process was more laborious to dig around for data.

#4: KW Finder

This image shows a scatter plot for KW Finder's keyword difficulty scores versus our keyword rankings. The data also has a significant amount of outliers relative to the regression line.

KW Finder definitely could have benefitted from more than a few mulligans with numerous strong outliers, coming in right behind SEMrush with a score of .360.

KW Finder Organic Difficulty Predictability

PCC

0.360

P-val

.01 (P<0.05)

Relationship

Moderate

% Keywords Matched

100.00%

Fortunately, the KW Finder tool had a 100% match rate without any trouble digging around for the data.

#5: Ahrefs

This image shows a scatter plot for AHREF's keyword difficulty scores versus our keyword rankings. The data shows tight clustering amongst low difficulty score keywords, and a wide distribution amongst higher difficulty scores.

Ahrefs comes in fifth by a large margin at .316, barely passing the “weak relationship” threshold.

Ahrefs Organic Difficulty Predictability

PCC

0.316

P-val

.03 (P<0.05)

Relationship

Moderate

% Keywords Matched

100%

On a positive note, the tool seems to be very reliable with low difficulty scores (notice the tight clustering for low difficulty scores), and matched all 50 keywords.

#6: Google Keyword Planner Tool

This image shows a scatter plot for Google Keyword Planner Tool's keyword difficulty scores versus our keyword rankings. The data shows randomly distributed plots with no linear relationship.

Before you ask, yes, SEO companies still use the paid competition figures from Google’s Keyword Planner Tool (and other tools) to assess organic ranking potential. As you can see from the scatter plot, there is in fact no linear relationship between the two variables.

Google Keyword Planner Tool Organic Difficulty Predictability

PCC

0.045

P-val

Statistically insignificant/no linear relationship

Relationship

Negligible/None

% Keywords Matched

88.00%

SEO agencies still using KPT for organic research (you know who you are!) — let this serve as a warning: You need to evolve.

Test 1 summary

For scoring, we will use a ten-point scale and score every tool relative to the highest-scoring competitor. For example, if the second highest score is 98% of the highest score, the tool will receive a 9.8. As a reminder, here are the results from the PCC test:

This bar chart shows the final PCC values for the first test, summarized.

And the resulting scores are as follows:

Tool

PCC Test

Moz

10

SpyFu

9.8

SEMrush

8.8

KW Finder

8.7

Ahrefs

7.7

KPT

1.1

Moz takes the top position for the first test, followed closely by SpyFu (with an 80% match rate caveat).

Test 2: Adjusted Pearson Correlation Coefficient

Let’s call this the “Mulligan Round.” In this round, assuming sometimes things just go haywire and a tool just flat-out misses, we will remove the three most egregious outliers to each tool’s score.

Here are the adjusted results for the handicap round:

Adjusted Scores (3 Outliers removed)

PCC

Difference (+/-)

SpyFu

0.527

0.122

SEMrush

0.515

0.150

Moz

0.514

0.101

Ahrefs

0.478

0.162

KWFinder

0.470

0.110

Keyword Planner Tool

0.189

0.144

As noted in the original PCC test, some of these tools really took a big hit with major outliers. Specifically, Ahrefs and SEMrush benefitted the most from their outliers being removed, gaining .162 and .150 respectively to their scores, while Moz benefited the least from the adjustments.

For those of you crying out, “But this is real life, you don’t get mulligans with SEO!”, never fear, we will make adjustments for reliability at the end.

Here are the updated scores at the end of round two:

Tool

PCC Test

Adjusted PCC

Total

SpyFu

9.8

10

19.8

Moz

10

9.7

19.7

SEMrush

8.8

9.8

18.6

KW Finder

8.7

8.9

17.6

AHREFs

7.7

9.1

16.8

KPT

1.1

3.6

4.7

SpyFu takes the lead! Now let’s jump into the final round of statistical tests.

Test 3: Resampling

Being that there has never been a study performed on keyword research tools at this scale, we wanted to ensure that we explored multiple ways of looking at the data.

Big thanks to Russ Jones, who put together an entirely different model that answers the question: “What is the likelihood that the keyword difficulty of two randomly selected keywords will correctly predict the relative position of rankings?”

He randomly selected 2 keywords from the list and their associated difficulty scores.

Let’s assume one tool says that the difficulties are 30 and 60, respectively. What is the likelihood that the article written for a score of 30 ranks higher than the article written on 60? Then, he performed the same test 1,000 times.

He also threw out examples where the two randomly selected keywords shared the same rankings, or data points were missing. Here was the outcome:

Resampling

% Guessed correctly

Moz

62.2%

Ahrefs

61.2%

SEMrush

60.3%

Keyword Finder

58.9%

SpyFu

54.3%

KPT

45.9%

As you can see, this tool was particularly critical on each of the tools. As we are starting to see, no one tool is a silver bullet, so it is our job to see how much each tool helps make more educated decisions than guessing.

Most tools stayed pretty consistent with their levels of performance from the previous tests, except SpyFu, which struggled mightily with this test.

In order to score this test, we need to use 50% as the baseline (equivalent of a coin flip, or zero points), and scale each tool relative to how much better it performed over a coin flip, with the top scorer receiving ten points.

For example, Ahrefs scored 11.2% better than flipping a coin, which is 8.2% less than Moz which scored 12.2% better than flipping a coin, giving AHREFs a score of 9.2.

The updated scores are as follows:

Tool

PCC Test

Adjusted PCC

Resampling

Total

Moz

10

9.7

10

29.7

SEMrush

8.8

9.8

8.4

27

Ahrefs

7.7

9.1

9.2

26

KW Finder

8.7

8.9

7.3

24.9

SpyFu

9.8

10

3.5

23.3

KPT

1.1

3.6

-.4

.7

So after the last statistical accuracy test, we have Moz consistently performing alone in the top tier. SEMrush, Ahrefs, and KW Finder all turn in respectable scores in the second tier, followed by the unique case of SpyFu, which performed outstanding in the first two tests (albeit, only returning results on 80% of the tested keywords), then falling flat on the final test.

Finally, we need to make some usability adjustments.

Usability Adjustment 1: Keyword Matching

A keyword research tool doesn’t do you much good if it can’t provide results for the keywords you are researching. Plain and simple, we can’t treat two tools as equals if they don’t have the same level of practical functionality.

To explain in practical terms, if a tool doesn’t have data on a particular keyword, one of two things will happen:

  1. You have to use another tool to get the data, which devalues the entire point of using the original tool.
  2. You miss an opportunity to rank for a high-value keyword.

Neither scenario is good, therefore we developed a penalty system. For each 10% match rate under 100%, we deducted a single point from the final score, with a maximum deduction of 5 points. For example, if a tool matched 92% of the keywords, we would deduct .8 points from the final score.

One may argue that this penalty is actually too lenient considering the significance of the two unideal scenarios outlined above.

The penalties are as follows:

Tool

Match Rate

Penalty

KW Finder

100%

0

Ahrefs

100%

0

Moz

100%

0

SEMrush

92%

-.8

Keyword Planner Tool

88%

-1.2

SpyFu

80%

-2

Please note we gave SEMrush a lot of leniency, in that technically, many of the keywords evaluated were not found in its keyword difficulty tool, but rather through manually digging through the phrase match tool. We will give them a pass, but with a stern warning!

Usability Adjustment 2: Reliability

I told you we would come back to this! Revisiting the second test in which we threw away the three strongest outliers that negatively impacted each tool’s score, we will now make adjustments.

In real life, there are no mulligans. In real life, each of those three blog posts that were thrown out represented a significant monetary and time investment. Therefore, when a tool has a major blunder, the result can be a total waste of time and resources.

For that reason, we will impose a slight penalty on those tools that benefited the most from their handicap.

We will use the level of PCC improvement to evaluate how much a tool benefitted from removing their outliers. In doing so, we will be rewarding the tools that were the most consistently reliable. As a reminder, the amounts each tool benefitted were as follows:

Tool

Difference (+/-)

Ahrefs

0.162

SEMrush

0.150

Keyword Planner Tool

0.144

SpyFu

0.122

KWFinder

0.110

Moz

0.101

In calculating the penalty, we scored each of the tools relative to the top performer, giving the top performer zero penalty and imposing penalties based on how much additional benefit the tools received over the most reliable tool, on a scale of 0–100%, with a maximum deduction of 5 points.

So if a tool received twice the benefit of the top performing tool, it would have had a 100% benefit, receiving the maximum deduction of 5 points. If another tool received a 20% benefit over of the most reliable tool, it would get a 1-point deduction. And so on.

Tool

% Benefit

Penalty

Ahrefs

60%

-3

SEMrush

48%

-2.4

Keyword Planner Tool

42%

-2.1

SpyFu

20%

-1

KW Finder

8%

-.4

Moz

-

0

Results

All told, our penalties were fairly mild, with a slight shuffling in the middle tier. The final scores are as follows:

Tool

Total Score

Stars (5 max)

Moz

29.7

4.95

KW Finder

24.5

4.08

SEMrush

23.8

3.97

Ahrefs

23.0

3.83

Spyfu

20.3

3.38

KPT

-2.6

0.00

Conclusion

Using any organic keyword difficulty tool will give you an advantage over not doing so. While none of the tools are a crystal ball, providing perfect predictability, they will certainly give you an edge. Further, if you record enough data on your own blogs’ performance, you will get a clearer picture of the keyword difficulty scores you should target in order to rank on the first page.

For example, we know the following about how we should target keywords with each tool:

Tool

Average KD ranking ≤10

Average KD ranking ≥ 11

Moz

33.3

37.0

SpyFu

47.7

50.6

SEMrush

60.3

64.5

KWFinder

43.3

46.5

Ahrefs

11.9

23.6

This is pretty powerful information! It’s either first page or bust, so we now know the threshold for each tool that we should set when selecting keywords.

Stay tuned, because we made a lot more correlations between word count, days live, total keywords ranking, and all kinds of other juicy stuff. Tune in again in early September for updates!

We hope you found this test useful, and feel free to reach out with any questions on our math!

Disclaimer: These results are estimates based on 50 ranking keywords from 50 blog posts and keyword research data pulled from a single moment in time. Search is a shifting landscape, and these results have certainly changed since the data was pulled. In other words, this is about as accurate as we can get from analyzing a moving target.

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Rewriting the Beginner’s Guide to SEO, Chapter 3: Keyword Research

Posted by BritneyMuller

Welcome to the draft of Chapter Three of the new and improved Beginner’s Guide to SEO! So far you’ve been generous and energizing with your feedback for our outline, Chapter One, and Chapter Two. We’re asking for a little more of your time as we debut the our third chapter on keyword research. Please let us know what you think in the comments!


Chapter 3: Keyword Research

Understand what your audience wants to find.

Now that you’ve learned how to show up in search results, let’s determine which strategic keywords to target in your website’s content, and how to craft that content to satisfy both users and search engines.

The power of keyword research lies in better understanding your target market and how they are searching for your content, services, or products.

Keyword research provides you with specific search data that can help you answer questions like:

  • What are people searching for?
  • How many people are searching for it?
  • In what format do they want that information?

In this chapter, you’ll get tools and strategies for uncovering that information, as well as learn tactics that’ll help you avoid keyword research foibles and build strong content. Once you uncover how your target audience is searching for your content, you begin to uncover a whole new world of strategic SEO!

What terms are people searching for?

You may know what you do, but how do people search for the product, service, or information you provide? Answering this question is a crucial first step in the keyword research process.

Discovering keywords

You likely have a few keywords in mind that you would like to rank for. These will be things like your products, services, or other topics your website addresses, and they are great seed keywords for your research, so start there! You can enter those keywords into a keyword research tool to discover average monthly search volume and similar keywords. We’ll get into search volume in greater depth in the next section, but during the discovery phase, it can help you determine which variations of your keywords are most popular amongst searchers.

Once you enter in your seed keywords into a keyword research tool, you will begin to discover other keywords, common questions, and topics for your content that you might have otherwise missed.

Let’s use the example of a florist that specializes in weddings.

Typing “wedding” and “florist” into a keyword research tool, you may discover highly relevant, highly searched for related terms such as:

  • Wedding bouquets
  • Bridal flowers
  • Wedding flower shop

In the process of discovering relevant keywords for your content, you will likely notice that the search volume of those keywords varies greatly. While you definitely want to target terms that your audience is searching for, in some cases, it may be more advantageous to target terms with lower search volume because they’re far less competitive.

Since both high- and low-competition keywords can be advantageous for your website, learning more about search volume can help you prioritize keywords and pick the ones that will give your website the biggest strategic advantage.

Pro tip: Diversify!

It’s important to note that entire websites don’t rank for keywords, pages do. With big brands, we often see the homepage ranking for many keywords, but for most websites, this isn’t usually the case. Many websites receive more organic traffic to pages other than the homepage, which is why it’s so important to diversify your website’s pages by optimizing each for uniquely valuable keywords.

How often are those terms searched?

Uncovering search volume

The higher the search volume for a given keyword or keyword phrase, the more work is typically required to achieve higher rankings. This is often referred to as keyword difficulty and occasionally incorporates SERP features; for example, if many SERP features (like featured snippets, knowledge graph, carousels, etc) are clogging up a keyword’s result page, difficulty will increase. Big brands often take up the top 10 results for high-volume keywords, so if you’re just starting out on the web and going after the same keywords, the uphill battle for ranking can take years of effort.

Typically, the higher the search volume, the greater the competition and effort required to achieve organic ranking success. Go too low, though, and you risk not drawing any searchers to your site. In many cases, it may be most advantageous to target highly specific, lower competition search terms. In SEO, we call those long-tail keywords.

Understanding the long tail

It would be great to rank #1 for the keyword “shoes”… or would it?

It’s wonderful to deal with keywords that have 50,000 searches a month, or even 5,000 searches a month, but in reality, these popular search terms only make up a fraction of all searches performed on the web. In fact, keywords with very high search volumes may even indicate ambiguous intent, which, if you target these terms, it could put you at risk for drawing visitors to your site whose goals don’t match the content your page provides.

Does the searcher want to know the nutritional value of pizza? Order a pizza? Find a restaurant to take their family? Google doesn’t know, so they offer these features to help you refine. Targeting “pizza” means that you’re likely casting too wide a net.

The remaining 75% lie in the “chunky middle” and “long tail” of search.

Don’t underestimate these less popular keywords. Long tail keywords with lower search volume often convert better, because searchers are more specific and intentional in their searches. For example, a person searching for “shoes” is probably just browsing. Whereas, someone searching for “best price red womens size 7 running shoe,” practically has their wallet out!

Pro tip: Questions are SEO gold!

Discovering what questions people are asking in your space, and adding those questions and their answers to an FAQ page, can yield incredible organic traffic for your website.

Getting strategic with search volume

Now that you’ve discovered relevant search terms for your site and their corresponding search volumes, you can get even more strategic by looking at your competitors and figuring out how searches might differ by season or location.

Keywords by competitor

You’ll likely compile a lot of keywords. How do you know which to tackle first? It could be a good idea to prioritize high-volume keywords that your competitors are not currently ranking for. On the flip side, you could also see which keywords from your list your competitors are already ranking for and prioritize those. The former is great when you want to take advantage of your competitors’ missed opportunities, while the latter is an aggressive strategy that sets you up to compete for keywords your competitors are already performing well for.

Keywords by season

Knowing about seasonal trends can be advantageous in setting a content strategy. For example, if you know that “christmas box” starts to spike in October through December in the United Kingdom, you can prepare content months in advance and give it a big push around those months.

Keywords by region

You can more strategically target a specific location by narrowing down your keyword research to specific towns, counties, or states in the Google Keyword Planner, or evaluate “interest by subregion” in Google Trends. Geo-specific research can help make your content more relevant to your target audience. For example, you might find out that in Texas, the preferred term for a large truck is “big rig,” while in New York, “tractor trailer” is the preferred terminology.

Which format best suits the searcher’s intent?

In Chapter 2, we learned about SERP features. That background is going to help us understand how searchers want to consume information for a particular keyword. The format in which Google chooses to display search results depends on intent, and every query has a unique one. While there are thousands of of possible search types, there are five major categories to be aware of:

1. Informational queries: The searcher needs information, such as the name of a band or the height of the Empire State Building.

2. Navigational queries: The searcher wants to go to a particular place on the Internet, such as Facebook or the homepage of the NFL.

3. Transactional queries: The searcher wants to do something, such as buy a plane ticket or listen to a song.

4. Commercial investigation: The searcher wants to compare products and find the best one for their specific needs.

5. Local queries: The searcher wants to find something locally, such as a nearby coffee shop, doctor, or music venue.

An important step in the keyword research process is surveying the SERP landscape for the keyword you want to target in order to get a better gauge of searcher intent. If you want to know what type of content your target audience wants, look to the SERPs!

Google has closely evaluated the behavior of trillions of searches in an attempt to provide the most desired content for each specific keyword search.

Take the search “dresses,” for example:

By the shopping carousel, you can infer that Google has determined many people who search for “dresses” want to shop for dresses online.

There is also a Local Pack feature for this keyword, indicating Google’s desire to help searchers who may be looking for local dress retailers.

If the query is ambiguous, Google will also sometimes include the “refine by” feature to help searchers specify what they’re looking for further. By doing so, the search engine can provide results that better help the searcher accomplish their task.

Google has a wide array of result types it can serve up depending on the query, so if you’re going to target a keyword, look to the SERP to understand what type of content you need to create.

Tools for determining the value of a keyword

How much value would a keyword add to your website? These tools can help you answer that question, so they’d make great additions to your keyword research arsenal:

  • Moz Keyword Explorer – Our own Moz Keyword Explorer tool extracts accurate search volume data, keyword difficulty, and keyword opportunity metrics by using live clickstream data. To learn more about how we’re producing our keyword data, check out Announcing Keyword Explorer.
  • Google Keyword Planner – Google’s AdWords Keyword Planner has historically been the most common starting point for SEO keyword research. However, Keyword Planner does restrict search volume data by lumping keywords together into large search volume range buckets. To learn more, check out Google Keyword Planner’s Dirty Secrets.
  • Google Trends – Google’s keyword trend tool is great for finding seasonal keyword fluctuations. For example, “funny halloween costume ideas” will peak in the weeks before Halloween.
  • AnswerThePublic – This free tool populates commonly searched for questions around a specific keyword. Bonus! You can use this tool in tandem with another free tool, Keywords Everywhere, to prioritize ATP’s suggestions by search volume.
  • SpyFu Keyword Research Tool – Provides some really neat competitive keyword data.

Download our free keyword research template!

Keyword research can yield a ton of data. Stay organized by downloading our free keyword research template. Customize the template to fit your unique needs. Happy keyword researching!

Now that you know how to uncover what your target audience is searching for and how often, it’s time to move onto the next step: crafting pages in a way that users will love and search engines can understand.

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Measuring the quality of popular keyword research tools

Contributor JR Oakes measures the quality of popular keyword research tools against data found in Google search results and performing page data from Google Search Console.



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SearchCap: Google AMP ads, political ad laws & keyword cannibalization

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

The post SearchCap: Google AMP ads, political ad laws & keyword cannibalization appeared first on Search Engine Land.



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How to Do a Keyword-Driven Content Audit (with Keyword Explorer)

Posted by Dr-Pete

As content marketers, we frequently suffer from What Have You Done For Me Lately Syndrome (WHYDFMLS). As soon as we’re done with one piece of content, we’re on to the next one, barely stopping to check analytics for a couple of days. Analytics themselves are to blame, in part. Our default window into traffic-based analytics is somewhere in the realm of 30 days, leading us to neglect older content that’s still performing well but may not be competing day-to-day with the latest and greatest.

I’m a big believer in digging back into your hidden gems and looking for content that’s still performing but may be due for an update, rewrite, or even just testing a better title/headline. How do we find this content, which is often buried in our this-week-focused analytics?

Let’s think like SEOs. One approach is to find older content that’s still ranking for a solid number of keywords, but may be out of date or under-performing. This is content that’s still driving traffic, but we may be overlooking. We don’t have to fight an uphill battle to get it ranking – we just have to better tap the potential this content is already demonstrating.

Step 0 – The “Exact Page” filter

Before we begin, I’m going to jump to the end. You may know that we recently launched Keywords By Site in Keyword Explorer, which allows you to peer into a keyword “universe” of millions of searches to see how a given domain is ranking. What you may not know is that you can also look up a specific page with the “Exact Page” filter. Go to the Keyword Explorer home page, and it’s the last entry in the pull-down:

Here’s a zoom-in. I’ve entered a popular post from my personal website:

Click the search (magnifying glass) button and you’ll get back something like this:

Even for my small blog, I’ve got a healthy list of keywords here, and some ranking in the top 50 that have solid volume. I also know that this post still gets decent traffic, even though it was written in 2009. If I were still active in the usability space, this would be a prime candidate for a rewrite, and I’d know exactly what keywords to target.

This is all well and good when you have an exact page in mind, but how do you audit an entire site or blog when you don’t know what’s performing for you? I’m going to outline a 6-step process below.

Step 1 – Get all rankings

Let’s say I want to find some buried content treasure right here on the Moz Blog. In the Keyword Explorer menu, I’ll select “root domain” and enter our root domain, “moz.com”:

I’ll get a similar report as in Step 0. Under “Top Ranking Keywords”, I’m going to select “See all ranking keywords”. In this case, I get back a table of more than 53,000 keywords that moz.com currently ranks

for. Not too shabby. These are not just keywords I actively track, but all of the keywords moz.com ranks for in Keyword Explorer’s “universe” of roughly 40 million keywords.

Step 2 – Export keywords

So, how does a keyword list help us to better understand our content? Above the keyword table, you’ll see two options, “Export CSV” and “Add to…”:

I’m going to choose the export – we’re going to want the whole, beautiful mess for this job. What I’ll get back is a file with every keyword and the following columns:

  • Keyword
  • Minimum Volume
  • Maximum Volume
  • Keyword Difficulty
  • Top Rank
  • Top Ranking URL

That last column is the important one. The export contains the top ranking URL for moz.com for each of the keywords (note: your maximum export size does vary with your Moz Pro membership level). This is where we can start forging the content connection.

Step 3 – Filter pages

I ended up with 30K keyword/URL pairings in the CSV. So that the viewers at home can follow along, I’m going to do the next few steps in Google Sheets. The first thing I want to do is filter out just what I’m interested in. In the “Data” menu, select “Filter”. You’ll see green arrows appear next to each column header. Click on the one next to “Top Ranking URL” (the last column). I’m going to use “Filter by condition” with “Text contains” and isolate all ranking URLs with “/blog/” in them:

This leaves me with 13,266 keyword/URL pairings. Personally, I like to copy and paste the filtered data to a new worksheet, just because working with filtered data tends to be a bit unpredictable. So, now I’ve got a separate worksheet (named “Filtered”) with just the keywords where the Moz blog ranks.

Step 4 – Pivot pages

If you haven’t used pivot tables, I’d strongly encourage you to check them out. Annie Cushing has a great Excel tutorial on pivot tables, and I’ll walk you through a couple of basics in Google Sheets. Generally, you use pivot tables when you want to group data and calculate statistics on those groups very quickly. In this case, what I want to do is group all of the matching URLs in my data set and get the counts. In other words, how many keywords is each unique blog post ranking on?

After selecting all of the data on that new “Filtered” tab, click the “Data” menu again, and then “Pivot tables…” at the bottom. This opens up a new sheet with a blank table. On the right are some slightly cryptic options. Under “Rows”, I’m going to add “Top Ranking URL”. This tells Google Sheets that each row in the pivot table should be a unique (grouped) URL from the top ranking URLs. Next, I’ll select the “Values”::

The COUNTA() function just tells Google Sheets to return the total count for each URL (for some reason, COUNT() only works on numeric values). As a bonus, I’ve also selected the SUM() of Max Volume. This will total up the volume for all of the ranking keywords in our data set for each URL.

Pivot table results can be a bit hard to work with (in both Excel and Google Sheets), so I’m going to copy and paste the data (as values only) into a new sheet called “Audit”.

Step 5 – Find candidates

Let’s get to the good stuff. When I group the URLs, I’m left with 1,604 unique blog posts in this particular data set. I can easily sort by posts ranking for the most keywords or posts with the most potential search volume (under “Data” / “Sort range”). I’m going to stick to raw keyword count. Here’s just a sample:

Obviously, there’s a ton here to dig into, but right away I noticed that two of the posts in the top 10 seemed to have some connection to graphics and/or image search. This stood out, because it’s not a topic we write about a lot. Turns out the first one is a video from May 2017, so not a great candidate for an update. The second, however (highlighted), is a tools post from early 2013. This post was surprisingly popular, and given how many new tools have come out in the past 4-1/2 years, is a perfect candidate to rewrite.

Here’s a link to the full Google Sheet. Feel free to make a copy and play around.

Step 6 – Back to Step 0

Remember that “Exact URL” option I talked about at the beginning of this post? Well, now I’ve got a URL to plug back into that feature and learn more about. Our data dump showed 170 ranking keywords, but when I target that exact URL, I’m likely to get even more data. Here’s just a sample:

Sure enough, I get almost double that count (348) with an exact URL search, and now I have an entire treasure trove to sort through. I sorted by volume (descending) here, just to get a sense of some of the more interesting keywords. I can, of course, repeat Step 6 with any of the URLs from Step 5 until I narrow down my best prospects.

Next steps (for the adventurous)

If I were going to rewrite the post I found, I’d want to make sure that I’m targeting two sets of keywords: (1) the important keywords I currently rank highly on (don’t want to lose that traffic) and (2) higher volume keywords I have the potential to rank on if I target them better. I might target, for example, a few choice keywords where I currently rank in the top 20 results and have a Page Authority that’s better than (or, at least, not too far from) the listed Keyword Difficulty.

Of course, you can also feed any of these keywords back into Keyword Explorer for more suggestions. Ideally, you’re looking for a handful of solid keyword concepts to target. The goal isn’t to stuff every variation into your rewritten post. The goal is to create a better, newer, more useful post that also happens to intelligently incorporate highly relevant keywords.

Bonus: Walk-through video

If you’d like to learn more about the Keyword Explorer features discussed in this post, I’ve created a short (roughly 2 minute) walk-through video:

Give it a try and let me know what you find. While I’ve chosen to focus on Keyword Explorer in this post (hey, we have to pay the bills), this same process should work with a handful of other popular keyword research tools, as well.

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SearchCap: Local ranking factors, keyword bidding & more

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

The post SearchCap: Local ranking factors, keyword bidding & more appeared first on Search Engine Land.



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How to Use the "Keywords by Site" Data in Tools (Moz, SEMrush, Ahrefs, etc.) to Improve Your Keyword Research and Targeting – Whiteboard Friday

Posted by randfish

One of the most helpful functions of modern-day SEO software is the idea of a “keyword universe,” a database of tens of millions of keywords that you can tap into and discover what your site is ranking for. Rankings data like this can be powerful, and having that kind of power at your fingertips can be intimidating. In today’s Whiteboard Friday, Rand explains the concept of the “keyword universe” and shares his most useful tips to take advantage of this data in the most popular SEO tools.

How to use keywords by site

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

Video Transcription

Howdy, Moz fans, and welcome to another edition of Whiteboard Friday. This week we’re going to chat about the Keywords by Site feature that exists now in Moz’s toolset — we just launched it this week — and SEMrush and Ahrefs, who have had it for a little while, and there are some other tools out there that also do it, so places like KeyCompete and SpyFu and others.

In SEO software, there are two types of rankings data:

A) Keywords you’ve specifically chosen to track over time

Basically, the way you can think of this is, in SEO software, there are two kinds of keyword rankings data. There are keywords that you have specifically selected or your marketing manager or your SEO has specifically selected to track over time. So I’ve said I want to track X, Y and Z. I want to see how they rank in Google’s results, maybe in a particular location or a particular country. I want to see the position, and I want to see the change over time. Great, that’s your set that you’ve constructed and built and chosen.

B) A keyword “universe” that gives wide coverage of tens of millions of keywords

But then there’s what’s called a keyword universe, an entire universe of keywords that’s maintained by a tool provider. So SEMrush has their particular database, their universe of keywords for a bunch of different languages, and Ahrefs has their keyword universe of keywords that each of those two companies have selected. Moz now has its keyword universe, a universe of, I think in our case, about 40 million keywords in English in the US that we track every two weeks, so we’ll basically get rankings updates. SEMrush tracks their keywords monthly. I think Ahrefs also does monthly.

Depending on the degree of change, you might care or not care about the various updates. Usually, for keywords you’ve specifically chosen, it’s every week. But in these cases, because it’s tens of millions or hundreds of millions of keywords, they’re usually tracking them weekly or monthly.

So in this universe of keywords, you might only rank for some of them. It’s not ones you’ve specifically selected. It’s ones the tool provider has said, “Hey, this is a broad representation of all the keywords that we could find that have some real search volume that people might be interested in who’s ranking in Google, and we’re going track this giant database.” So you might see some of these your site ranks for. In this case, seven of these keywords your site ranks for, four of them your competitors rank for, and two of them both you and your competitors rank for.

Remarkable data can be extracted from a “keyword universe”

There’s a bunch of cool data, very, very cool data that can be extracted from a keyword universe. Most of these tools that I mentioned do this.

Number of ranking keywords over time

So they’ll show you how many keywords a given site ranks for over time. So you can see, oh, Moz.com is growing its presence in the keyword universe, or it’s shrinking. Maybe it’s ranking for fewer keywords this month than it was last month, which might be a telltale sign of something going wrong or poorly.

Degree of rankings overlap

You can see the degree of overlap between several websites’ keyword rankings. So, for example, I can see here that Moz and Search Engine Land overlap here with all these keywords. In fact, in the Keywords by Site tool inside Moz and in SEMrush, you can see what those numbers look like. I think Moz actually visualizes it with a Venn diagram. Here’s Distilled.net. They’re a smaller website. They have less content. So it’s no surprise that they overlap with both. There’s some overlap with all three. I could see keywords that all three of them rank for, and I could see ones that only Distilled.net ranks for.

Estimated traffic from organic search

You can also grab estimated traffic. So you would be able to extract out — Moz does not offer this, but SEMrush does — you could see, given a keyword list and ranking positions and an estimated volume and estimated click-through rate, you could say we’re going to guess, we’re going to estimate that this site gets this much traffic from search. You can see lots of folks doing this and showing, “Hey, it looks this site is growing its visits from search and this site is not.” SISTRIX does this in Europe really nicely, and they have some great blog posts about it.

Most prominent sites for a given set of keywords

You can also extract out the most prominent sites given a set of keywords. So if you say, “Hey, here are a thousand keywords. Tell me who shows up most in this thousand-keyword set around the world of vegetarian recipes.” The tool could extract out, “Okay, here’s the small segment. Here’s the galaxy of vegetarian recipe keywords in our giant keyword universe, and this is the set of sites that are most prominent in that particular vertical, in that little galaxy.”

Recommended applications for SEOs and marketers

So some recommended applications, things that I think every SEO should probably be doing with this data. There are many, many more. I’m sure we can talk about them in the comments.

1. Identify important keywords by seeing what you rank for in the keyword universe

First and foremost, identify keywords that you probably should be tracking, that should be part of your reporting. It will make you look good, and it will also help you keep tabs on important keywords where if you lost rankings for them, you might cost yourself a lot of traffic.

Monthly granularity might not be good enough. You might want to say, “Hey, no, I want to track these keywords every week. I want to get reporting on them. I want to see which page is ranking. I want to see how I rank by geo. So I’m going to include them in my specific rank tracking features.” You can do that in the Moz Keywords by Site, you’d go to Keyword Explorer, you’d select the root domain instead of the keyword, and you’d plug in your website, which maybe is Indie Hackers, a site that I’ve been reading a lot of lately and I like a lot.

You could see, “Oh, cool. I’m not tracking stock trading bot or ark servers, but those actually get some nice traffic. In this case, I’m ranking number 12. That’s real close to page one. If I put in a little more effort on my ark servers page, maybe I could be on page one and I could be getting some of that sweet traffic, 4,000 to 6,000 searches a month. That’s really significant.” So great way to find additional keywords you should be adding to your tracking.

2. Discover potential keywords targets that your competitors rank for (but you don’t)

Second, you can discover some new potential keyword targets when you’re doing keyword research based on the queries your competition ranks for that you don’t. So, in this case, I might plug in “First Round.” First Round Capital has a great content play that they’ve been doing for many years. Indie Hackers might say, “Gosh, there’s a lot of stuff that startups and tech founders are interested in that First Round writes about. Let me see what keywords they’re ranking for that I’m not ranking for.”

So you plug in those two to Moz’s tool or other tools. You could see, “Aha, I’m right. Look at that. They’re ranking for about 4,500 more keywords than I am.” Then I could go get that full list, and I could sort it by volume and by difficulty. Then I could choose, okay, these keywords all look good, check, check, check. Add them to my list in Keyword Explorer or Excel or Google Docs if you’re using those and go to work.

3. Explore keywords sets from large, content-focused media sites with similar audiences

Then the third one is you can explore keyword sets. I’m going to urge you to. I don’t think this is something that many people do, but I think that it really should be, which is to look outside of your little galaxy of yourself and your competitors, direct competitors, to large content players that serve your audience.

So in this case, I might say, “Gosh, I’m Indie Hackers. I’m really competing maybe more directly with First Round. But you know what? HBR, Harvard Business Review, writes about a lot of stuff that my audience reads. I see people on Twitter that are in my audience share it a lot. I see people in our forums discussing it and linking out to their articles. Let me go see what they are doing in the content world.”

In fact, when you look at the Venn diagram, which I just did in the Keywords by Site tool, I can see, “Oh my god, look there’s almost no overlap, and there’s this huge opportunity.” So I might take HBR and I might click to see all their keywords and then start looking through and sort, again, probably by volume and maybe with a difficulty filter and say, “Which ones do I think I could create content around? Which ones do they have really old content that they haven’t updated since 2010 or 2011?” Those types of content opportunities can be a golden chance for you to find an audience that is likely to be the right types of customers for your business. That’s a pretty exciting thing.

So, in addition to these, there’s a ton of other uses. I’m sure over the next few months we’ll be talking more about them here on Whiteboard Friday and here on the Moz blog. But for now, I would love to hear your uses for tools like SEMrush and the Ahrefs keyword universe feature and Moz’s keyword universe feature, which is called Keywords by Site. Hopefully, 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 image badges, Google Search Console beta reports & keyword research

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

The post SearchCap: Google image badges, Google Search Console beta reports & keyword research appeared first on Search Engine Land.



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The Lazy Writer’s Guide to 30-Minute Keyword Research

Posted by BritneyMuller

You, a content marketing ninja, are able to wield immense SEO reach with your content in ways most SEOs (*cough* like myself) can only dream of.

BUT, you’re not leveraging keyword research to your advantage!

The fact that you can discover how many people per month are searching for something, what words they’re using, and what questions they’re asking still blows my mind!

Keyword research doesn’t have to be a marathon bender. A brisk 30-minute walk can provide incredible insights — insights that connect you with a wider audience on a deeper level.


Why keyword research is essential [Case Study]

My previous company, Pryde Marketing, was not founded on out-of-this-world high-quality content. It was founded on leveraging online data strategically for private medical practices.

When we were hired to do keyword research for an MRI company, we discovered that hundreds of people a month were searching “open vs closed mri” but no one was providing any good answers, content, or photos for these searchers.

We decided to create an “Open Vs. Closed MRI” page for our client that, to our surprise, continues to see over double the traffic of the homepage. Plus, it’s brought in over 50k+ unique visitors.

We were not successful because we thought of this content idea.

We were successful because we listened to the keyword data.


5 keyword research hacks in under 30 minutes

Example client: Hunter & Company (Wedding & Event Planning)

Objective: Write better content for their website and assist with digital marketing efforts.

#1: Blog category keyword research

Having five to ten data-driven blog categories can help you rank for popular topics, allow readers to find more relevant content, and help to organize your blog.

Evaluate top industry websites (10 mins)

Identify the most common navigation items and blog categories on leading industry sites.

Top Wedding Site Eval.png

Advanced search operators (3 mins)

While exploring top websites, you can use advanced Google operators to dig deeper.

Example: Bride.com has topic pages like /topic/wedding-beauty. To view all of Bride.com’s topics search this: site:brides.com/topic

Wedding advanced search operator.png

Google Suggest (10 mins)

Google “wedding” and don’t hit enter!

Instead, make note of the drop-down search suggestions. You can also search “wedding a” [don’t hit enter], “wedding b” [don’t hit enter], all the way through to z to get the most popular and/or trending wedding-related searches.

Screen Shot 2017-03-13 at 11.20.18 AM.png

Now that we have aggregated keywords from the above tactics, we have a solid list:

wedding venues, wedding photographers, wedding dj, wedding beauty, wedding videographers, wedding bands, wedding budget, wedding invitations, wedding registry, wedding colors, wedding decorations, wedding party, wedding ideas, wedding cakes, wedding centerpieces, wedding hairstyles, wedding bouquets, engagement rings, wedding dresses, bridesmaid dresses, mother of the bride dresses, wedding rings, flower girl dresses, wedding accessories, wedding jewelry, wedding tuxedos, wedding registry, wedding ceremony, wedding reception, wedding cake, wedding food, wedding favors, wedding flowers

Keep up the pace — we can’t stop here!

Next, let’s determine which categories are most popular by average monthly Google searches.

There are two primary tools to view average monthly search volume (AKA to know how many times a query like “wedding flowers” are searched per month): Google Keyword Planner and Moz Keyword Explorer. (Check out GKP vs. MKE to learn more.)

Google Keyword Planner (5 mins)

Step 1: Paste your saved keyword list into the box under “Enter one or more of the following” and click “Get Ideas”:

Step 2: Evaluate and save search volume data while being mindful of the large search data ranges and limited data:Screen Shot 2017-03-14 at 10.09.51 AM.png

Note: Google will occasionally change your keywords to something different; “wedding videographers” was changed to “wedding videos” in this case. It’s important to be mindful of this as you’re deciding on the exact category names.

You should also explore the keywords below your immediate keyword search section. Sort by average monthly searches (highest to lowest) to make sure you aren’t missing any other big category items.

Moz Keyword Explorer (5 mins)

Step 1: Create a new list.

Step 2: Paste your keyword list into the “Enter Keywords” box:

Step 3: Take a quick water break, because KWE will take a minute to gather data. Once the data is in view, sort by and evaluate average monthly search volume:

Woohoo! We reached the finish line with two minutes to spare.

To finalize our blog categories, we need to ask ourselves two things: Which topics are the most popular and the most relevant to a wedding planner site?

With that in mind, you’ve chosen six of the most popular wedding topics and have nested several sub-categories within “Wedding Decorations” — brilliant!

  • Wedding Dresses
  • Wedding Invitations
  • Wedding Photography
  • Wedding Cakes
  • Wedding Venues
  • Wedding Decorations
    • Wedding Flowers
    • Wedding Colors
    • Wedding Centerpieces
    • Wedding Venues

#2: FAQ keyword research

Answering the most commonly searched-for questions about your product/service will provide value to your readers and solidify you as an industry expert.

Here’s how to gather the most commonly asked questions on a topic:

AnswerThePublic.com (10 mins)

Search for your product/service.

Screen Shot 2017-03-17 at 10.40.06 AM.png

Screen Shot 2017-03-17 at 10.40.20 AM.png

How cool is this snazzy question wheel?! While the visuals are fun, it’s easier to gather the questions by clicking the top-right yellow “export to csv” button and deleting non-relevant questions in a .csv or Google Sheet.

Moz Keyword Explorer (10 mins)

Step 1: Search and filter “display keyword suggestions” by “are questions”:

Screen Shot 2017-03-17 at 11.09.02 AM.png

Step 2: Add relevant questions to a new keyword list:

Screen Shot 2017-03-17 at 11.12.32 AM.png

Step 3: Add relevant AnswerThePublic questions to list:

Screen Shot 2017-03-17 at 11.06.30 AM.png

Research done!

I wouldn’t worry about evaluating search volume too closely for FAQs because questions are typically more long-tail (meaning they have lower search volume and are usually easier to rank for). In multitudes, these can be very valuable to your site.

Now you can start adding your newly discovered FAQs to an FAQ page (while trying to avoid duplicate types of questions):

Screen Shot 2017-03-17 at 11.19.47 AM.png

#3: Competitive content research

Evaluate your competitor’s 10 most popular pages on SimilarWeb (5 mins)

This uncovers the specific type of content your audience is interested in. Here are the 10 most popular pages for One Fine Day Events:

Screen Shot 2017-03-16 at 9.14.50 PM.png

Evaluate each of the top pages & gather 3 key takeaways (20 mins)

  1. The most popular “Gallery” page confirms that images are extremely popular in the wedding and event space. Maintaining an optimized gallery and incorporating more images into on-page content should be a top digital marketing priority.
  2. Interestingly, the “Preferred Vendors” page is a Category page! It’s something we should consider implementing on Hunter & Co. It would also be a great link building opportunity (to get vendors to link back to Hunter & Co)… but I digress.
  3. Testimonials are also be a top priority and live off the primary navigation.

Pro tip: Use Google Trends to evaluate seasonal searches and prepare competitive content months before it spikes:

#4: Expand your keyword reach

Expanding your page’s topical content will expand your digital SEO reach. This is why you’ll see definitive guides like Moz’s Beginner’s Guide to SEO ranking so well, and for such a wide range of keywords (~1,665!).

Download MozBar (Chrome add-on) (1 minute)

Step 1: Activate MozBar. Enter in your primary keyword and click “optimize.”

Step 2: Click “On-Page Content Suggestions”:

Step 3: View the 23+ content integration ideas for your webpage:

Decide which topics you want to integrate (5 mins)

You never want to force non-relevant content onto a page for SEO reasons. Instead, look through the topics and think about which would provide value to your readers.

Then, devise a plan to naturally integrate those topics into the page’s content.

Topic integrations for the Hunter & Co. homepage:

  • Wedding Planning Checklist (create a checklist page that’s linked to from homepage)
  • Wedding Vendors (confirms our popular page strategy! Add a page link from the homepage)
  • Wedding Venues
  • Couples

#5: Keep up with Google

We are seeing a big rise in “no-click” Google searches.

No-click searches occur when individuals search for something and find their answer, without ever having to click on a search result.

Example: If you search “Denver weather,” Google will show you an 8-day weather forecast for Denver. Most searchers are satisfied with that and leave, resulting in a no-click Google search.

Image from State of Searcher Behavior Revealed

No-click searches are rising because Google continues to provide searchers answers within search features such as featured snippets (answer boxes), People Also Ask boxes, knowledge graphs, weather forecasts, etc.

Know which search features show up most often for your keywords (5 mins)

Knowing which search features occur most frequently for your product/service-related searches can help you to steal search features by optimizing for them. Keep in mind that if you’re ranking on page one or two of a desired featured snippet search, you’re better positioned to steal that featured snippet than if you were on page 3+.

Remember our FAQs about “wedding planning” above? Twenty-four of 28 questions found in Moz Keyword Explorer have featured snippets (answer boxes) in their search results:

Screen Shot 2017-03-17 at 11.04.04 AM.png

RealSimple currently has a large featured snippet for “wedding checklist”:

Screen Shot 2017-03-17 at 11.28.18 AM.png

Looking more closely into that page, you’ll notice RealSimple’s <html> check-box markup and definitive style content.

Brainstorm a better (and more useful) wedding checklist (10 mins)

  • Hire a freelance developer to create a beautiful, printable wedding checklist calendar that, once a reader enters their wedding date, populates with scheduled to-dos.
  • Create an IFTTT (If This Then That) recipe to schedule Google Calendar To-Do Reminders based on the user’s wedding date.
  • Provide a more detailed and more beautiful wedding checklist.

Now, my content marketing ninjas, go forth and tap gloves with a wider audience! Your content deserves it!

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Bing Ads retiring Campaign Planner in favor of Keyword Planner

Keyword Planner will take over at the end of July and offer most of the same capabilities.

The post Bing Ads retiring Campaign Planner in favor of Keyword Planner appeared first on Search Engine Land.



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