Google AdWords Contact Form Extensions Beta : CPC Based CPA

The PPC Hero blog discovered a new beta by Google AdWords named contact form extensions. It basically lets AdWords advertisers have the chance to show a lead capture form in the Google ads shown in the search results. Here is a picture, because a picture will explain this in a second:

Google AdWords Contact Form

As you can see, the ad has a plus box, clicking it, opens a lead capture form.

The interesting parts are that:

(1) Google is charging the maximum cost-per-click on each lead captured. So they are charging a CPC based price for a CPA-like lead.

(2) Google is handling the leads much like any lead management company. They make you go through them to contact the lead. In short, Google gives you a lead ID number, you call the Google 800 number and enter the lead ID number into the Google prompt. Then Google connects you to that lead.

PPC Hero has a lot more detail on how this all works. So check it out at PPCHero.com.

Forum discussion at Sphinn.


The PPC Hero blog discovered a new beta by Google AdWords named contact form extensions. It basically lets AdWords advertisers have the chance to show a lead capture form in the Google ads shown in the search results. Here is a picture, because a picture will explain this in a second:

Google AdWords Contact Form

As you can see, the ad has a plus box, clicking it, opens a lead capture form.

The interesting parts are that:

(1) Google is charging the maximum cost-per-click on each lead captured. So they are charging a CPC based price for a CPA-like lead.

(2) Google is handling the leads much like any lead management company. They make you go through them to contact the lead. In short, Google gives you a lead ID number, you call the Google 800 number and enter the lead ID number into the Google prompt. Then Google connects you to that lead.

PPC Hero has a lot more detail on how this all works. So check it out at PPCHero.com.

Forum discussion at Sphinn.



Are Your SEO Resolutions Actionable?

Posted by Dr. Pete

2010 speedometerIt’s that time of year again; the one where we look back on everything we ate during the last two weeks and promise not to do it again in the new year. It’s also the time that many of us set new and ambitious goals for our businesses. Unfortunately, while goals are important and ambition can be admirable, we make the same mistake with our professional resolutions that we do with our personal resolutions. Take the classic weight-loss resolution. The problem with saying that you’re going to lose 20 lbs. in 2010 is simple – it’s just not actionable. At the end of the year, you’ll either have lost 20 lbs. or not, but that outcome is affected by dozens of things beyond your control. What exactly are you going to do to make it happen? If the answer is wait around and wish for the pounds to melt away, best of luck.

Uncontrollable SEO Resolutions

Similarly, our SEO goals are too often beyond our control. If you set a goal like "Rank #1 for Keyword X" (a very common SEO resolution, I’m sure), what does that actually mean in terms of action? Are you going to pray to the Google Gods every morning and say 50 Hail Matts to purge your SEO sins (my apologies to our Catholic readers)? If you’re worth your salt as an SEO, you have actions in mind that you plan to take, so why not resolve to take those actions in a measurable way? It’s fine to have ranking (or weekly searches, CTR, CPC, conversion rate, etc.) as an ultimate objective, but wishing won’t make it happen.

Actionable SEO Resolutions

Before this starts to read like a self-improvement seminar, let’s look at some SEO resolutions that are actionable. These are goals that you can directly control – you’re in charge of whether or not you accomplish them. I’ll break them up into two groups: (1) On-page SEO, and (2) Link-building (with some social networking thrown in). Of course, not every idea is appropriate to every situation – these are just ideas for actionable goals (substitute an appropriate number for "X").

(1) On-page SEO Goals

  • Rewrite X page TITLEs
  • Write X unique META descriptions
  • Create an XML site map
  • Create a custom 404 page
  • Canonicalize problem URLs
  • 301-redirect X broken URLs
  • Remove X low-quality internal links
  • Create a new [cleaner] master CSS

(2) Link-building Goals

  • Find X promising link prospects
  • Send X personalized link requests
  • Dig into analytics and find X hot topics
  • Create X pieces of new content/month
  • Write an e-book or comprehensive guide
  • Spend X minutes/day building up a social profile
  • Comment [thoughtfully] on X industry blogs/day
  • Re-tweet X pieces of great content/day

What Are Your Resolutions?

Of course, these are just a few ideas. Let me open it up to the community – what kind of actionable SEO resolutions have you made for 2010? What can you do that will really kick-start your efforts and make you look like a miracle worker to your clients?

Photo licensed from iStockPhoto.com (Created by Chris Lamphear).

Do you like this post? Yes No

Posted by Dr. Pete

2010 speedometerIt’s that time of year again; the one where we look back on everything we ate during the last two weeks and promise not to do it again in the new year. It’s also the time that many of us set new and ambitious goals for our businesses. Unfortunately, while goals are important and ambition can be admirable, we make the same mistake with our professional resolutions that we do with our personal resolutions. Take the classic weight-loss resolution. The problem with saying that you’re going to lose 20 lbs. in 2010 is simple – it’s just not actionable. At the end of the year, you’ll either have lost 20 lbs. or not, but that outcome is affected by dozens of things beyond your control. What exactly are you going to do to make it happen? If the answer is wait around and wish for the pounds to melt away, best of luck.

Uncontrollable SEO Resolutions

Similarly, our SEO goals are too often beyond our control. If you set a goal like "Rank #1 for Keyword X" (a very common SEO resolution, I’m sure), what does that actually mean in terms of action? Are you going to pray to the Google Gods every morning and say 50 Hail Matts to purge your SEO sins (my apologies to our Catholic readers)? If you’re worth your salt as an SEO, you have actions in mind that you plan to take, so why not resolve to take those actions in a measurable way? It’s fine to have ranking (or weekly searches, CTR, CPC, conversion rate, etc.) as an ultimate objective, but wishing won’t make it happen.

Actionable SEO Resolutions

Before this starts to read like a self-improvement seminar, let’s look at some SEO resolutions that are actionable. These are goals that you can directly control – you’re in charge of whether or not you accomplish them. I’ll break them up into two groups: (1) On-page SEO, and (2) Link-building (with some social networking thrown in). Of course, not every idea is appropriate to every situation – these are just ideas for actionable goals (substitute an appropriate number for "X").

(1) On-page SEO Goals

  • Rewrite X page TITLEs
  • Write X unique META descriptions
  • Create an XML site map
  • Create a custom 404 page
  • Canonicalize problem URLs
  • 301-redirect X broken URLs
  • Remove X low-quality internal links
  • Create a new [cleaner] master CSS

(2) Link-building Goals

  • Find X promising link prospects
  • Send X personalized link requests
  • Dig into analytics and find X hot topics
  • Create X pieces of new content/month
  • Write an e-book or comprehensive guide
  • Spend X minutes/day building up a social profile
  • Comment [thoughtfully] on X industry blogs/day
  • Re-tweet X pieces of great content/day

What Are Your Resolutions?

Of course, these are just a few ideas. Let me open it up to the community – what kind of actionable SEO resolutions have you made for 2010? What can you do that will really kick-start your efforts and make you look like a miracle worker to your clients?

Photo licensed from iStockPhoto.com (Created by Chris Lamphear).

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Kelsey Group Local Media Forecast #ILM09

Liveblogging Matt Booth’s & Neal Polachek’s forecast for SMB/Local media spending.  Enjoy:
Total U.S. Local Ad Spend should grow from $136B in 2010 to $144B in 2013.  Scary looking drop from $155B in 2008 to $141B in 2009.  A result of the economy and shift to digital.
Local Ad Spend by Medium: All mediums losing share except [...]

Liveblogging Matt Booth’s & Neal Polachek’s forecast for SMB/Local media spending.  Enjoy:

Total U.S. Local Ad Spend should grow from $136B in 2010 to $144B in 2013.  Scary looking drop from $155B in 2008 to $141B in 2009.  A result of the economy and shift to digital.

Local Ad Spend by Medium: All mediums losing share except for digital/online

2013 Interactive Ad Market $58.57B -Search= about $26B of that

2009:
- Mobiie, email, reputation management, video, display about where they thought they would be
- Estimating search at $13.9B to $15,5B

- Total searh query volume exceeding targets

- CPC down 3.3 to 1.0% from 2008

- CTR down 12.4% to 3% from 2008 but GOOG rebounding

- Ad coverage up 2.7%

Local search:

- Off $350MM-$100MM from previous forecast

- CPC down -4.8% from 2008; pull back of SMBs of 30% in mid-year

- CTR down 10.6% from 2008; result of advertiser pull back

- Ad coverage down 2.6% from 2008

- Revenue showing robust growth; range 9.6% to 17.8% from 2008

- Expectations is that end of Q3 is when turnaround will be in full swing

Classifieds & Verticals

- Down $1B from 2008

- Classifieds performance terrible -30% Q2 Y/Y; Overall down -21% from 2008

- Non-Auto/RE vertical markets were strong

SMB Ad Spending

- Spending is down 23.5% from August 2008 to Q2 2009, but this appears to be turning around

- Direct mail seems to be coming back

- 6% of SMBs tried PPC this year down from 9% last year, but PPC appears to be coming back

- 8% bought print ads in 2009 v. 13% in 2008

Newer businesses much more oriented to Online Media but newer businesses spend less

- Businesses 0-3 yrs old spend 30% of ad budget online v. businesses 11+ years old spending 13% online

49% of SMBs buy ads themselves (down from 57% last year)

24% buy ads via Print Yellow Pages/IYP sales forces (up from 16% last year)

9% buy via Radio/TV Sales up from 3% last year

8% buy via an agency up from 3% last year

New content models based on analytics such as Associated Content, DemandMedia & Examiner.com are going to be a big trend going forward.

SMBs that intend to use a page on a social site in the next 12 months:
- 44% of new SMBs say yes

- 18-22% of older SMBs say yes

Online Media Usage Reaches Parity with Traditional Media.  Kelsey expects Online to eclipse Traditional over the coming year.

ROI pereception

1. Email

2. Direct mail

3. PPC

4. IYP

5. Print YP

16% of businesses that are <3 yrs old have self-enrolled in Twitter

not even going to try and interpret the chart that’s up there now :)

Neal pushing Presence (you need to be where people are looking), Performance (you need to be able to convert & vehicles that help you convert are important) & Permanance

THE BIG TAKEAWAYS

  • Massive shift to digital; “The Cliff” is here
  • Search is already rebounding; expecting growth to continue CAGR ~15% through 2013
  • Geo-targeted display, video, mobile, email & reputation management all meeting expectations
  • Traditional sales forces more competitive with each other.  Digital divide is closing
  • Overall 2010 will be strong for interactive SMB marketing

Neal thinks the broadcast industry will be much more tied to the mobile experience in the future.

Google AdWords Team Points Out Flaw in Google Keyword Tool

A Google AdWords API Help thread estimated position or average CPC being returned by the AdWords API differs from that of the Google Keyword Tool.

Eric Koleda from the Google AdWords API Team replied basically pointing fault at the tool.

I think the problem here lies in the Keyword Tool’s web interface.

You’ll notice that changing the match type drop down from Broad to Phrase or Exact does not change the estimated position or average CPC. It is unlikely that the match type has no effect on these parameters, and in the API changing the match type does change the returned position and CPC values. My guess is that the web tool is always using the Broad match type for getting estimates, and that the numbers returned by the API are accurate.

I validated that the Google keyword tool does not change the estimated position or average CPC when you change the match type from broad, exact, or phrase types. Logically, it would make sense that this means the keyword tool is off when reporting on those factors and narrowing the results by match type.

It seems if you want to get more accurate numbers for estimated position or average CPC you would have to use the AdWords API.

Forum discussion at Google AdWords API Help.


A Google AdWords API Help thread estimated position or average CPC being returned by the AdWords API differs from that of the Google Keyword Tool.

Eric Koleda from the Google AdWords API Team replied basically pointing fault at the tool.

I think the problem here lies in the Keyword Tool’s web interface.

You’ll notice that changing the match type drop down from Broad to Phrase or Exact does not change the estimated position or average CPC. It is unlikely that the match type has no effect on these parameters, and in the API changing the match type does change the returned position and CPC values. My guess is that the web tool is always using the Broad match type for getting estimates, and that the numbers returned by the API are accurate.

I validated that the Google keyword tool does not change the estimated position or average CPC when you change the match type from broad, exact, or phrase types. Logically, it would make sense that this means the keyword tool is off when reporting on those factors and narrowing the results by match type.

It seems if you want to get more accurate numbers for estimated position or average CPC you would have to use the AdWords API.

Forum discussion at Google AdWords API Help.



Charting ‘Unique Keyphrases’ Using Advanced Segments

Posted by RobOusbey

A useful indicator of SEO success is the number of unique keyphrases that send traffic to a website. An increase in this number is a reflection of increased trust in the site by search-engines.

Google Analytics can show you the total number of unique organic keyphrases at a glance, on the Traffic Sources ⇒ Keywords page. (Make sure you select ‘non-paid’ to exclude any CPC campaigns.)

This post will show you how to break that down to a more useful level of granularity and help you to create a table such as the following:

We’ll aim to categorise traffic into three buckets: ‘branded’, ‘head terms’ and ‘mid-long tail terms’. (In reality, we’ll actually calculate the first two, and the third one will be ‘everything that is left’.)

As we often can’t export enough keywords from Google Analytics to do the analysis offline, we will have to use ‘Advanced Segments’ to do this. This means that we can only group together ‘branded terms’ and ‘head terms’ in ways that we can explain through AND and OR statements.

The process for doing this goes like this:

  1. Plan to create advanced segments that define each group of keywords you want to track
  2. Define rules using ‘AND’ & ‘OR’ statements that describe which keywords should be in each group
  3. Apply these groups each month, one at a time, to the previous month’s data, in order to reveal the number of unique keywords.

Since this ‘rule defining’ will take place in Google Analytics’ Advanced Segments feature, we’ll be using ‘regular expressions’ – a clever but pretty technical method of defining which items in a set should be included in a particular subset. (More details about them at this site.)

The next sections may have particular appeal to the more ‘techie’ readers (or just those people feeling brave) – so do feel free to just skip down to the end to see screen-shots of these segments applied to the keywords report, if the nitty-gritty isn’t your cup of tea.

Creating the ‘Branded Terms’ Segment

If you’ve not really implemented Advanced Segments before, I suggest starting with Google Analytics’ help pages on the topic, but also having a play with the feature, to see how it works. (Really, do have a play. I’m going to assume you at least have understood what most of the main buttons do, and that’s a great way to find out.)

Planning the Segment

Let’s use a fictional company, TechNet, who make a product called the Vox9000. Their segment for ‘branded terms’ will include anything that mentions these terms.

Define the Rules, Create the Segment

To create the segment for branded terms, begin by clicking ‘Advanced Segments’ ⇒ ‘Create new custom segment’.

In the first ‘dimension or metric’ space, add a ‘Medium’ block (found under ‘Dimensions’) and set Condition to ‘Matches exactly’ and Value to ‘organic’. Then hit ‘and‘ to add another section. Place a ‘Keywords’ block here, with Condition as ‘Matches regular expression’ and a value that is all your branded terms, separated by the pipe character: |

(NB: the pipe acts as an ‘OR’ in these regular expressions.)

As an example, for TechNet (which people often search for it with a spaces, as ‘Tech Net’) that makes a product called ‘Vox9000′ (sometimes searched for as ‘Vox 9000′) would use the following string here: technet|tech net|vox9000|vox 9000

Give the segment a name, and save it.

Creating the ‘Head Terms’ Segment

Planning the Segment

The next segment – the head terms – is a bit more complicated, and you’ll see why it’s important for us to to specify rules that will define the head keyphrases.

Let’s imagine that TechNet sells laptops and notebooks in Philadelphia and Baltimore. (Therefore head terms will be those such as ‘notebooks’ or ‘laptops in philadelphia’)

In this example, the rules to define head terms might be:

  • the phrase can’t mention any branded terms
  • it must mention one of their product groups (laptop, notebook)
  • it can only have two words of 3+ characters (this allows for some short linking words, such as a, in, at, etcetera)
  • it can only have a maximum of four words in total.

Define the Rules, Create the Segment

The last two rules can be the trickiest to implement, so we’ll look at these first. Two insights help us solve these requirements:

Insight 1: Combining the two rules, and using S and L to indicate short words (1 or 2 characters) and long words (3+ characters) we see that the only twenty possible structures for keyphrases are: L, LS, SL, LL, LSS, SLS, SSL, LLS, LSL, SLL, LSSS, SLSS, SSLS, SSSL, LLSS, LSLS, LSSL, SLLS, SLSL, SSLL

Insight 2: The regular expression: \b[^ ]{3,50}\b matches a word of between 3 & 50 characters. It’s also necessary to know that ^ matches something at the beginning of an expression, and $ matches at the end. (Seriously, they do. Start by going through the examples at this site if you want to know why that’s the case.)

We’re now in a position to take the list of combinations from ‘Insight 1′ and replace ‘S’ with \b[^ ]{1,2}\b (matching words with 1/2 characters) and ‘L’ with \b[^ ]{3,50}\b, putting spaces in-between, wrapping in parentheses, and matching at beginning and end. Missed that? OK, here are examples of some of the resulting statements:

L becomes ^(\b[^ ]{3,50}\b)$
SL becomes ^(\b[^ ]{1,2}\b \b[^ ]{3,50}\b)$
LSL becomes ^(\b[^ ]{3,50}\b \b[^ ]{3,50}\b \b[^ ]{1,2}\b)$
etc.

You should join the twenty created expressions together using a pipe character, to create the resulting, massive, expression. To save space, I won’t post the whole expression in, but you can see what it looks like if you hover your mouse over this text.

NB: There seems to be a limit to the number of parts to an expression that you can put into Google Analytics, so I tend to break this up into two parts – say, those matching on three or less words, and those matching four – and put them as ‘OR’ alternatives in one section. I’ve done that below to demonstrate.

The resultant segment rules for ‘Branded Keyphrases’ look like this:

The image shown above reads:

    • Dimension: Medium, Condition: Matches exactly, Value: organic
  • AND
    • Dimension: Keyword, Condition: Does not match regular expression, Value: technet|tech net|vox9000|vox 9000
  • AND
  • AND
    • Dimension: Keyword, Condition: Matches regular expression, Value: laptop|notebook

Collecting the numbers

With our two Advanced Segments defined, we can head back to the ‘keywords’ page and set the date range to the last month. Click each image to see it full size.

We can apply each custom segment in turn, in order to collect the following numbers for September:

  • Total keyphrases: 64,278
  • Branded keyphrases: 393
  • Head keyphrases: 2,835
  • Other keyphrases: 61,050 (calculated from the previous three numbers)

You can now put these numbers in a spreadsheet in order to chart the change in number of unique keyphrases as months go by.

You can use these basic techniques to create and report on even more well defined segments of keyphrases (for example: you could group keyphrases by competitiveness, department, intent, etc.) If there are particular steps here that require more explanation, or you’re looking for more ideas about how to apply this to your SEO reporting structure, drop a comment below.

Do you like this post? Yes No

Posted by RobOusbey

A useful indicator of SEO success is the number of unique keyphrases that send traffic to a website. An increase in this number is a reflection of increased trust in the site by search-engines.

Google Analytics can show you the total number of unique organic keyphrases at a glance, on the Traffic Sources ⇒ Keywords page. (Make sure you select ‘non-paid’ to exclude any CPC campaigns.)

This post will show you how to break that down to a more useful level of granularity and help you to create a table such as the following:

We’ll aim to categorise traffic into three buckets: ‘branded’, ‘head terms’ and ‘mid-long tail terms’. (In reality, we’ll actually calculate the first two, and the third one will be ‘everything that is left’.)

As we often can’t export enough keywords from Google Analytics to do the analysis offline, we will have to use ‘Advanced Segments’ to do this. This means that we can only group together ‘branded terms’ and ‘head terms’ in ways that we can explain through AND and OR statements.

The process for doing this goes like this:

  1. Plan to create advanced segments that define each group of keywords you want to track
  2. Define rules using ‘AND’ & ‘OR’ statements that describe which keywords should be in each group
  3. Apply these groups each month, one at a time, to the previous month’s data, in order to reveal the number of unique keywords.

Since this ‘rule defining’ will take place in Google Analytics’ Advanced Segments feature, we’ll be using ‘regular expressions’ – a clever but pretty technical method of defining which items in a set should be included in a particular subset. (More details about them at this site.)

The next sections may have particular appeal to the more ‘techie’ readers (or just those people feeling brave) – so do feel free to just skip down to the end to see screen-shots of these segments applied to the keywords report, if the nitty-gritty isn’t your cup of tea.

Creating the ‘Branded Terms’ Segment

If you’ve not really implemented Advanced Segments before, I suggest starting with Google Analytics’ help pages on the topic, but also having a play with the feature, to see how it works. (Really, do have a play. I’m going to assume you at least have understood what most of the main buttons do, and that’s a great way to find out.)

Planning the Segment

Let’s use a fictional company, TechNet, who make a product called the Vox9000. Their segment for ‘branded terms’ will include anything that mentions these terms.

Define the Rules, Create the Segment

To create the segment for branded terms, begin by clicking ‘Advanced Segments’ ⇒ ‘Create new custom segment’.

In the first ‘dimension or metric’ space, add a ‘Medium’ block (found under ‘Dimensions’) and set Condition to ‘Matches exactly’ and Value to ‘organic’. Then hit ‘and‘ to add another section. Place a ‘Keywords’ block here, with Condition as ‘Matches regular expression’ and a value that is all your branded terms, separated by the pipe character: |

(NB: the pipe acts as an ‘OR’ in these regular expressions.)

As an example, for TechNet (which people often search for it with a spaces, as ‘Tech Net’) that makes a product called ‘Vox9000′ (sometimes searched for as ‘Vox 9000′) would use the following string here: technet|tech net|vox9000|vox 9000

Give the segment a name, and save it.

Creating the ‘Head Terms’ Segment

Planning the Segment

The next segment – the head terms – is a bit more complicated, and you’ll see why it’s important for us to to specify rules that will define the head keyphrases.

Let’s imagine that TechNet sells laptops and notebooks in Philadelphia and Baltimore. (Therefore head terms will be those such as ‘notebooks’ or ‘laptops in philadelphia’)

In this example, the rules to define head terms might be:

  • the phrase can’t mention any branded terms
  • it must mention one of their product groups (laptop, notebook)
  • it can only have two words of 3+ characters (this allows for some short linking words, such as a, in, at, etcetera)
  • it can only have a maximum of four words in total.

Define the Rules, Create the Segment

The last two rules can be the trickiest to implement, so we’ll look at these first. Two insights help us solve these requirements:

Insight 1: Combining the two rules, and using S and L to indicate short words (1 or 2 characters) and long words (3+ characters) we see that the only twenty possible structures for keyphrases are: L, LS, SL, LL, LSS, SLS, SSL, LLS, LSL, SLL, LSSS, SLSS, SSLS, SSSL, LLSS, LSLS, LSSL, SLLS, SLSL, SSLL

Insight 2: The regular expression: \b[^ ]{3,50}\b matches a word of between 3 & 50 characters. It’s also necessary to know that ^ matches something at the beginning of an expression, and $ matches at the end. (Seriously, they do. Start by going through the examples at this site if you want to know why that’s the case.)

We’re now in a position to take the list of combinations from ‘Insight 1′ and replace ‘S’ with \b[^ ]{1,2}\b (matching words with 1/2 characters) and ‘L’ with \b[^ ]{3,50}\b, putting spaces in-between, wrapping in parentheses, and matching at beginning and end. Missed that? OK, here are examples of some of the resulting statements:

L becomes ^(\b[^ ]{3,50}\b)$
SL becomes ^(\b[^ ]{1,2}\b \b[^ ]{3,50}\b)$
LSL becomes ^(\b[^ ]{3,50}\b \b[^ ]{3,50}\b \b[^ ]{1,2}\b)$
etc.

You should join the twenty created expressions together using a pipe character, to create the resulting, massive, expression. To save space, I won’t post the whole expression in, but you can see what it looks like if you hover your mouse over this text.

NB: There seems to be a limit to the number of parts to an expression that you can put into Google Analytics, so I tend to break this up into two parts – say, those matching on three or less words, and those matching four – and put them as ‘OR’ alternatives in one section. I’ve done that below to demonstrate.

The resultant segment rules for ‘Branded Keyphrases’ look like this:

The image shown above reads:

    • Dimension: Medium, Condition: Matches exactly, Value: organic
  • AND
    • Dimension: Keyword, Condition: Does not match regular expression, Value: technet|tech net|vox9000|vox 9000
  • AND
  • AND
    • Dimension: Keyword, Condition: Matches regular expression, Value: laptop|notebook

Collecting the numbers

With our two Advanced Segments defined, we can head back to the ‘keywords’ page and set the date range to the last month. Click each image to see it full size.

We can apply each custom segment in turn, in order to collect the following numbers for September:

  • Total keyphrases: 64,278
  • Branded keyphrases: 393
  • Head keyphrases: 2,835
  • Other keyphrases: 61,050 (calculated from the previous three numbers)

You can now put these numbers in a spreadsheet in order to chart the change in number of unique keyphrases as months go by.

You can use these basic techniques to create and report on even more well defined segments of keyphrases (for example: you could group keyphrases by competitiveness, department, intent, etc.) If there are particular steps here that require more explanation, or you’re looking for more ideas about how to apply this to your SEO reporting structure, drop a comment below.

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