Tag Archive | "Custom"

Custom Extraction Using an SEO Crawler for CRO and UX Insights – Whiteboard Friday

Posted by MrLukeCarthy

From e-commerce to listings sites to real estate and myriad verticals beyond, the data you can harness using custom extraction via crawler tools is worth its weight in revenue. With a greater granularity of data at your fingertips, you can uncover CRO and user experience insights that can inform your optimizations and transform your customer experience.

In this episode of Whiteboard Friday, we’re delighted to welcome Luke Carthy to share actionable wisdom from his recent MozCon 2019 presentation, Killer CRO and UX Wins Using an SEO Crawler.

Video Transcription

Hey, Moz. What’s up? Wow, can I just say it’s incredible I’m here in Seattle right now doing a Whiteboard Friday? I can’t wait to share this cool stuff with you. So thanks for joining me.

My name is Luke Carthy. As you can probably tell, I’m from the UK, and I want to talk to you about custom extraction, specifically in the world of e-commerce. However, what I will say is this works beautifully well in many of the verticals as well, so real estate, in job listings. In fact, any website that can pretty much spit out HTML in a web crawler, you can use custom extraction.

What is custom extraction?

Let’s get started. What is custom extraction? Well, as I kind of just alluded to, it allows you, when you’re crawling using like Screaming Frog, for example, or DeepCrawl or whatever it is you want to use, it allows you to grab and extract specific parts of the HTML and export it to a file, a CSV, in Excel, or whatever you prefer.



As a principle, okay, great, but I’m going to give you some really good examples of how you can really leverage that. So e-commerce, right here we’ve got a product page that I’ve beautifully drawn, and everything in red is something that you can potentially extract. Although, as I said, anything on the page you can. These are just some good examples.

Product information + page performance

Think about this for a moment. You’re an e-commerce website, you’re a listing site, and of course you have listing pages, you have product pages. Wouldn’t it be great if you could very quickly, at scale, understand all of your products’ pricing, whether you’ve got stock, whether it’s got an image, whether it’s got a description, how many reviews it has, and of the reviews, what’s the aggregate score, whether it’s four stars, five stars, whatever it is?

That’s really powerful because you can then start to understand how good pages perform based upon the information that they have, based upon traffic, conversion, customer feedback, and all sorts of great stuff, all using custom extraction and spitting it out on say a CSV or an Excel spreadsheet file.

Competitive insights

But where it gets super powerful and you get a lot of insight from is when you start to turn the lens to your competitors and you think about ways in which you can get those really good insights. You may have three competitors. You may have some aspirational competitors. You may have a site that you don’t necessarily compete with, but you use them on a day-to-day basis or you admire how easy their site was to use, and you can go away and do that.

You can fire up a crawl, and there’s no reason why you couldn’t extract that same information from other competitors and see what’s going on, to see what pricing your competitors are selling an item at, do they have that in stock or not, what are the reviews like, what FAQs do people have, can you then leverage that in your own content. 

Examples of how to glean insights from custom extraction in e-commerce

Example 1: Price increases for products competitors don’t stock

Let me give you a perfect example of how I’ve managed to use this.

I’ve managed to identify that a competitor doesn’t have a specific product in stock, and, as a result of that, I’ve been able to increase our prices because they didn’t sell it. We did at that specific time, and we could identify the price point, the fact that they didn’t have any stock, and it was awesome. Think about that. Really powerful insights at massive amounts of scale. 

Example 2: Improving facets and filters on category pages

Another example I wanted to talk to you about. Category pages, again incredibly gorgeous illustrations. So category pages, we have filters, we have a category page, and just to switch things up a little bit I’ve also got like a listings page as well, so whether it’s, as I said, real estate, jobs, or anything in that environment.

If you think about the competition again for a second, there is no reason why you wouldn’t be able to extract via custom extraction the best filters that people use, the top filters, the top facets that people like to select and understand. So you can then see whether you’re using the same kind of combinations of features and facets on your site and maybe improve that.

Equally, you can then start to understand what specific features correlate to sales and performance and impacts and really start to improve the performance of how your website performs and behaves for your customers. The same thing applies to both environments here. 

If you are a listing site and you list jobs or you list products or classified ads, is it location filters that they have at the top? Is it availability? Is it reviews? Is it scores? You can crawl a number of your competitors across a number of areas and identify whether there’s a pattern, see a theme, and then see whether you can leverage and better that and take advantage of that. That’s a great way in which you can use it. 

Example 3: Recommendations, suggestions, and optimization

But on top of that and the one that I am most fascinated with is by far recommendations.

In the MozCon talk I did earlier I had a statistic, and I think I can recall it. It was 35% of what people buy on Amazon comes from recommendations, and 75% of what people watch on Netflix comes from suggestions, from recommendations.

Think about how powerful that is. You can crawl your own site, understand your own recommendations at scale, identify the stock of those recommendations, the price, whether they have images, in what order they are, and you can start to build a really vivid picture as to what products people associate with your items. You can do that on a global scale. You can crawl the entire of your product portfolio or your listing portfolio and get that. 



But again, back to powerful intelligence, your competitors, especially when you have competitors that might have multivariable facets or multivariable recommendations. What I mean by that is we’ve all seen sites where you’ve got multiple carousels. So you’ve got Recommended for You.

You might have People Also Bought, alternative suggestions. The more different types of recommendations you have, the more data you have, the more intelligence you have, the more insight you have. Going back to say a real estate example, you might be looking at a property here. It’s at this price. What is your main aspirational real estate competitor recommending to you that you may not be aware of?

Then you can think about whether the focus is on location, whether it’s on price, whether it’s on number of bedrooms, etc., and you can start to understand and behave how that can work and get some really powerful insights from that. 

Custom extraction is all about granular data at scale

To summarize and bring it all to a close, custom extraction is all about great granular data at scale. The really powerful thing about it is you can do all of this yourself, so there’s no need to have to have meetings, send elaborate emails, get permission from somebody.

Fire up Screaming Frog, fire up DeepCrawl, fire up whatever kind of crawler you want to use, have a look at custom extraction, and see how you can make your business more efficient, find out how you can get some really cool competitive insights, and yeah, hopefully, fingers crossed that works for you guys. Thank you very much.

Bonus resources:

Video transcription by Speechpad.com


This is a meaty topic, we know — if you enjoyed this Whiteboard Friday and find yourself eager to know more, you’re in luck! Luke’s full presentation at MozCon 2019 goes even more in-depth into what custom extraction can do for you. Catch his talk along with 26 other forward-thinking topics from our amazing speakers in the MozCon video bundle:

Access the sessions now!

We recommend sharing them with your team and spreading the learning love. Happy watching!

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Parallel tracking, more custom parameters coming to Microsoft Advertising for improved tracking

Parallel tracking, currently in beta, will be rolling out soon.



Please visit Search Engine Land for the full article.


Search Engine Land: News & Info About SEO, PPC, SEM, Search Engines & Search Marketing

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AMP to supports custom JavaScript with amp-script

To be announced in more detail next week at the AMP Conference, Google is adding JavaScript support to AMP.



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How to Measure Performance with Custom Dimensions in Google Analytics [Tutorial]

Posted by tombennet

Data-driven marketing means understanding what works. This means not only having accurate data, but also having the right data.

Data integrity is obviously critical to good reporting, but Analytics auditing shouldn’t focus solely on the validity of the tracking code. Even amongst digital marketing teams who place importance on reporting, I frequently encounter the attitude that a technically sound, out-of-the-box implementation of Google Analytics will provide all the insight you could require.

Because of this, Google Analytics is rarely used to its full potential. When it comes to deeper insights — analyzing the ROI of top-of-funnel marketing activities, the impact of content engagement on raw business KPIs, or the behavior of certain subsets of your audience, for example — many will overlook the ease with which these can be measured. All it takes is a little investment in your tracking setup and a careful consideration of what insight would be most valuable.

In this article, I’ll be exploring the ways in which the Custom dimensions feature can be used to supercharge your Google Analytics reporting setup. We’ll run through some practical examples before diving into the various options for implementation. By the end, you’ll be equipped to apply these techniques to your own reporting, and use them to prove your prowess to your clients or bosses.

What are custom dimensions?

In a nutshell, they enable you to record additional, non-standard data in Google Analytics. You can then pivot or segment your data based on these dimensions, similarly to how you would with standard dimensions like source, medium, city, or browser. Custom dimensions can even be used as filters at the View-level, allowing you to isolate a specific subset of your audience or traffic for deeper analysis.

In contrast to the Content Grouping feature — which allows you to bucket your existing pages into logical groups — custom dimensions let you attach entirely new data to hits, sessions, or users. This last point is critical; custom dimensions can take advantage of the different levels of scope offered by Google Analytics. This means your new dimension can apply to an individual user and all their subsequent interactions on your website, or to a single pageview hit.

For the purposes of this tutorial, we’re going to imagine a simple scenario: You run a popular e-commerce website with a content marketing strategy that hinges around your blog. We’ll start by illustrating some of the ways in which custom dimensions can provide a new perspective.

1. User engagement

You publish a series of tutorials on your blog, and while they perform well in organic search and in social, you struggle to demonstrate the monetary value of your continued efforts. You suspect that engagement with the tutorials correlates positively with eventual high-value purchases, and wish to demonstrate this in Analytics. By configuring a user-level custom dimension called “Commenter” which communicates a true/false depending on whether the user has ever commented on your blog, you can track the behavior of these engaged users.

2. User demographics

User login status is frequently recommended as a custom dimension, since it allows you to isolate your existing customers or loyal visitors. This can be a great source of insight, but we can take this one step further: Assuming that you collect additional (anonymous) data during the user registration process, why not fire this information to Analytics as a user-level custom dimension? In the case of our example website, let’s imagine that your user registration form includes a drop-down menu for occupation. By communicating users’ selections to Analytics, you can compare the purchase patterns of different professions.

3. Out-of-stock products

Most e-commerce sites have, at one time or another, encountered the SEO conundrum of product retirement. What should you do with product URLs that no longer exist? This is often framed as a question of whether to leave them online, redirect them, or 404 them. Less frequently investigated is their impact on conversion, or of the wider behavioral effects of stock level in general. By capturing out-of-stock pageviews as a custom dimension, we can justify our actions with data.

Now that we have a clear idea of the potential of custom dimensions, let’s dive into the process of implementation.

How to implement custom dimensions

All custom dimensions must first be created in the Google Analytics Admin interface. They exist on the Property level, not the View level, and non-premium Google Analytics accounts are allowed up to 20 custom dimensions per Property. Expand Custom Definitions, hit Custom Dimensions, and then the red New Custom Dimension button.

C:\Users\ThomasB.BUILTVISIBLE\AppData\Local\Microsoft\Windows\INetCache\Content.Word\creating-custom-dimensions-1.png

In the next screen, you’ll need to give your dimension a name, select a Scope (hit, session, user, or — for enhanced e-commerce implementations — product), and check the Active box to enable it. Hit Create, and you’ll be shown a boilerplate version of the code necessary to start collecting data.

C:\Users\ThomasB.BUILTVISIBLE\AppData\Local\Microsoft\Windows\INetCache\Content.Word\our-custom-dimension.png

The code — which is documented fully on Google Developers and Google Support — is very simple:

var mozDimensionValue = 'Howdy Moz Fans';
ga('set', 'dimension1', mozDimensionValue);

As you can see, we’re defining the value of our dimension in a JavaScript variable, then using the set method with the ga() command queue to pass that variable to Analytics as a custom dimension. All subsequent hits on the page (pageviews, events, etc) would then include this custom dimension. Note that we refer to our dimension by its index number, which in this instance is 1; return to the main Custom Dimensions screen in the Admin area to see the index number which Analytics assigned to your new dimension.

While your developer will typically handle the nuts and bolts of implementation — namely working out how best to pass your desired value into a JavaScript variable — the syntax is simple enough that it can be modified with ease. Using the first of our examples from earlier — tracking commenters — we want to send a value of ‘commenter’ to the Dimension 2 slot as part of an event hit which is configured to fire when somebody comments on the blog. With this slot pre-configured as a user-level dimension, we would use:

ga('send', 'event', 'Engagement', 'Blog Comment', {
  'dimension2':  'commenter'
});

This approach is all well and good, but it’s not without its drawbacks. It requires on-page tracking code changes, significant developer involvement, and doesn’t scale particularly well.

Thanks to Google Tag Manager, we can make things much easier.

Implementation with Google Tag Manager

If you use GTM to deploy your Analytics tracking — and for all but the simplest of implementations, I would recommend that you do — then deploying custom dimensions becomes far simpler. For those new to GTM, I gave an introductory talk on the platform at BrightonSEO (slides here), and I’d strongly suggest bookmarking both Google’s official documentation and Simo Ahava’s excellent blog.

For the sake of this tutorial, I’ll assume you’re familiar with the basics of GTM. To add a custom dimension to a particular tag — in this case, our blog comment event tag — simply expand “Custom Dimensions” under More Settings, and enter the index number and value of the dimension you’d like to set. Note that to see the More Settings configuration options, you’ll need to check the “Enable overriding settings in this tag” box if you’re not using a Google Analytics Settings Variable to configure your implementation.

C:\Users\ThomasB.BUILTVISIBLE\AppData\Local\Microsoft\Windows\INetCache\Content.Word\gtm.png

What about our latter two examples, user demographics and out-of-stock products?

Our demographic scenario involved a user registration form which included an “Occupation” field. In contrast to our commenting example, the dimension value in this instance will need to be set programmatically depending on user input — it’s not a simple true/false variable that can be easily attached to a suitable event tag.

While we could use the “DOM Element” variable type to scrape the value of the “Occupation” drop-down field directly off the page, such an approach is not particularly scalable. A far better solution would be to fire the value of the field — along with the values of any other fields you feel may offer — to your website’s data layer.

Attention, people who don’t yet use a data layer:

While your development team will need to be involved in the implementation of a data layer, it’s well worth the effort. The advantages for your reporting can be huge, particularly for larger organizations. Defining the contents of your site’s data layer is a great opportunity for cross-team collaboration, and means that all potentially insightful data points are accessible in a machine-readable and platform-agnostic format, ready to be fired to GA. It’s also less subject to mistakes than ad-hoc tracking code. Much like how CSS separates out style from content, the data layer isolates your data.

Your developer will need to make the required information available in the data layer before you can define it as a Data Layer Variable in GTM and start using it in your tags. In the example below, imagine that the JavaScript variable ‘myValue’ has been configured to return the occupation entered by the user, as a string. We push it to the data layer, then define it as a Data Layer Variable in GTM:

var myValue = 'Professional Juggler';
dataLayer.push({'userOccupation': 'myValue'});

C:\Users\ThomasB.BUILTVISIBLE\AppData\Local\Microsoft\Windows\INetCache\Content.Word\gtm-dlv.png

Attach a custom dimension to your User Registration event tag, as before, then simply reference this Data Layer Variable as the dimension value. Done!

Our third example follows the exact same principles: Having identified product-in-stock status as a hit-level datapoint with potential reporting insight, and with our data layer configured to return this as a variable on product pages, we simply configure our pageview tag to use this variable as the value for a new custom dimension.

C:\Users\ThomasB.BUILTVISIBLE\AppData\Local\Microsoft\Windows\INetCache\Content.Word\gtm-stock.png

Reporting & analysis

The simplest way to view custom dimension data in Analytics is to apply a secondary dimension to a standard report. In the example below, we’ve set our new “User Occupation” dimension as the secondary dimension in a New/Returning visitor report, allowing us to identify the professions of our newest users, and those of our frequent visitors.

C:\Users\ThomasB.BUILTVISIBLE\AppData\Local\Microsoft\Windows\INetCache\Content.Word\secondary-dim.png

By cross-referencing your new dimensions with behavioral data — think social share frequency by occupation — you can gain insight into the subsets of your audience who are most likely to engage or convert.

In truth, however, applying a secondary dimension in this manner is rarely conducive to effective analysis. In many instances, this approach will hugely increase the number of rows of data in your report without providing any immediately useful information. As such, it is often necessary to take things one step further: You can export the data into Excel for deeper analysis, or build a custom dashboard to pivot the data exactly the way you want it. In the example below, a chart and table have been configured to show our most viewed out-of-stock products over the course of the last week. Timely, actionable insight!

C:\Users\ThomasB.BUILTVISIBLE\AppData\Local\Microsoft\Windows\INetCache\Content.Word\dashboard.png

Sometimes, it’s necessary to completely isolate a subset of data in a dedicated view. This can be particularly powerful when used with a user-level custom dimension. Let’s say we wish to drill down to show only our most engaged users. We can do this by applying a Filter to a new view. In the following example, we have applied a custom ‘Include’ Filter which specifies a value of ‘commenter’ based on our “Blog Commenter” custom dimension.

C:\Users\ThomasB.BUILTVISIBLE\AppData\Local\Microsoft\Windows\INetCache\Content.Word\filter-include.png

The result? A dedicated view which reports on engaged users only.

For more information on the intricacies of filtering data based on session or user-level custom dimensions — and their implications for your Real Time reports — be sure to check out this great post from LunaMetrics.

Final thoughts

A deeper understanding of your target audience is never a bad thing. Custom dimensions are just one of the many ways in which Google Analytics can be extended beyond its default configuration to provide more granular, actionable insights tailored to the needs of your business.

As with many other advanced Analytics features, execution is everything. It’s better to have no custom dimensions at all than to waste your limited slots with dimensions which are poorly implemented or just plain unnecessary. Planning and implementation should be a collaborative process between your marketing, management, and development teams.

Hopefully this article has given you some ideas for how custom dimensions might offer you a new perspective on your audience.

Thanks for reading!

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Bing Ads piloting in-market & custom audience targeting

Bing Ads is actively working on building out its audience targeting capabilities.

The post Bing Ads piloting in-market & custom audience targeting appeared first on Search Engine Land.



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Bing Ads Editor now supports custom ad copy for native ads on MSN.com

Bing’s latest version of its desktop editor tool, Bing Ads Editor 11.2, supports custom copy development for native ads. Instead of creating one ad to be served in search and native ad placements, advertisers can now create ads specific to native placements on MSN.com in bulk using the tool….



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HTTPS Launched For All Custom Domains On WordPress.com

Automattic announced that they’re launching free HTTPS for all custom domains hosted on WordPress.com. WordPress.com has supported encryption for WordPress.com subdomains since 2014, but now it’s being expanded to over a million custom domains.

The company says users will see secure encryption automatically deployed on every new site within minutes.

“We are closing the door to un-encrypted web traffic (HTTP) at every opportunity,” writes Automattic’s Chief Systems Wrangler.

As he notes, encryption provides more than security.

“Protocol enhancements like SPDY and HTTP/2 have narrowed the performance gap between encrypted and un-encrypted web traffic, with encrypted HTTP/2 outperforming un-encrypted HTTP/1.1 in some cases,” he writes.

Google announced HTTPS as a ranking signal in 2014. Back in December, the search engine started indexing HTTPS versions of URLs by default.

Earlier this year, Moz found that HTTPS URLs made up 25% of page-one Google results across 10,000 queries.

The post HTTPS Launched For All Custom Domains On WordPress.com appeared first on WebProNews.


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New and Improved Custom Reports Added to Moz Analytics

Posted by Miranda.Rensch

Hello everyone! Miranda here. I’m a Product Manager at Moz and I’m excited to announce that we’ve added custom, automated reporting to Moz Analytics. This is something that already existed in PRO (the predecessor to Moz Analytics), but the new version has some cool upgrades I’d like to point out, so here goes a quick walk-through.

Walk-through of the new custom reports

With the new version of custom reports, you can select (almost) any visualization or data list from within Moz Analytics to be included in a custom PDF and emailed regularly.

To access the new reports, just go into any campaign and click “Custom Reports” in the top right and then click “Create / Schedule Report” to get started.

Next, you’ll begin filling in the details of your report. You can give it a name and a description to appear at the top of the PDF:

In the “Add Modules” step you use a left navigation similar to the normal Moz Analytics experience so you can quickly navigate to your favorite data / visualizations and click the + sign to select them. In the next step you’ll be able to organize them and add notes.

In the “Design Report” step, you can re-order your modules, add notes, and if you have access to branded reports, add your brand logo to be printed on the PDF.

In the next step you can preview your report. Click “Generate PDF Report” to view and save as an actual PDF.

Finally, you can schedule the report to be emailed regularly to you and any others that you specify. You can now also customize the text of the email that gets sent out!

When you’ve finished setting up your report, you can see all active reports on the main Custom Reports page. From there you can see the next scheduled send date and edit your reports.

Other new stuff in Moz Analytics

While we’re at it, we’d like to mention a few other improvements in Moz Analytics:

Crawl diagnostics updates

We made some improvements to the design to make it easier to find the issues exposed by our custom crawler. You can now see a breakdown of your top High, Medium, and Low priority issues at the bottom of the Crawl Diagnostics overview page.

You will also see the issue counts included in the issue drop-down.

We’ve also made sure that all of the crawl data is included in the .csv export. We are still working on making views of duplicate pages and titles visible outside of the .csv.

Keyword opportunities improvement

With this smaller update, we added a button to the keyword opportunities report in the rankings section, allowing you to quickly add an attractive keyword to your list for rank tracking.

Fresh Web Explorer alerts

In case you missed it, we also recently released a big update to Fresh Web Explorer that lets you create and save custom alerts. Use it to get prompt alerts when someone publishes content mentioning your brand, your competitors, or even discover interesting link and outreach opportunities. Cyrus even wrote a whole blog post about it.

What’s next for Moz Analytics?

Here are some of the projects that are currently in-progress and up next for Moz Analytics. This is just the top of our list, but we’d love to know what you think! Please let us know in the comments or on our feature request forum.

  • Monthly timeframes: We are still working on adding monthly timeframe options into custom reports and the rest of the Moz Analytics app. We hope to have that in by the end of the year. Also, we are aware that there are some issues currently with monthly custom reports in PRO causing them to be delayed. We hope to build these monthly reports into the new version of custom reports in a more scalable way and we apologize for the issue in PRO.

  • Lots of bug / UX fixes: We’re working on continually responding to feedback and bugs in the new application. We’ve gotten to many, but not all of them. Thank you for your patience!

  • Contextual help: We’re working on ways to bring help guides and videos directly into the app so that when you need help you can find it quick.

  • Add individual keyword history to Custom Reports: There are a couple of modules that can’t be added to custom reports yet—Analyze a Keyword (individual keyword history), Grade a Page, and Analyze Page Issues. We hope to make those available in the next few months as well.

  • Per-page PDF downloads: We are currently working on allowing PDF downloads of any page in the app. We hope to have that done in the next month or so.

  • Customized timeframe options: We’re in the process of researching our ability to provide more customized timeframe options. It’s a bit complicated due to the variety of data we include in our app, but we’re looking at our options.

  • Multi-user accounts: We’re working on supporting multiple users per account.

  • You tell us! If you have any other feedback or ideas for how this software could be better and save you more time, please let us know on our feature request forum!

That’s all! If you have any questions or comments, chances are other people will too, so why not ask it on the Moz Q&A forum! Looking forward to hearing your feedback. If you’d like to volunteer a half-hour to give more in-depth feedback about this section or reporting in general, please email miranda@moz.com.

Happy reporting!
Miranda Rensch
Product Manager @ Moz

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Maximizing Google Analytics Insight for SEO with Custom Reports

Google Analytics – one of the most powerful tools for any SEO, assuming you know how to get the data you need from it. One of my favorite things about Google Analytics is how many tools that put at your disposal for quickly analyzing the data you care most about. But again, that all assumes you know how to get it.

A custom report in Google Analytics is similar to their custom dashboard features in a lot of ways. Remember, the dashboards are meant as snapshots of what’s going on with your campaign, these custom reports are what you should be using to fully analyze the results.

Custom Report Categories

To start, you should consider setting up Custom Report categories to organize your reports by subject. You will find this to be the most aggravating/irritating/infuriating part of the process as you attempt to drag your first custom report into your new category folder. The secret is to drag your report slightly to the right while hovering over the category you want to place it in. Then let go and hope for the best. Once you have one report in there it gets much easier.

Creating a Custom Report

There are two key components to a custom report:

  1. Metric: a numeric measurement (like number of visits).
  2. Dimension: a description of visits, visitors, pages, products and events.

There are also two types of Custom Reports you can create:

  1. Explorer: Allows you to drill down into sub-dimensions and includes a timeline where you can compare metrics in the same graph.
  2. Table: Allows you to compare dimensions side by side, with metrics also populated within the table. There is no timeline in this report.

Creating the custom report is easy. You choose from a drop-down menu of metrics and dimensions that you’re interested in segmenting your report by.

Creating a Custom Report

You can also create tabs in your report to keep it organized. Any filters you setup on one tab will automatically apply to any other tab that you setup (there isn’t a way to turn them off for the other tabs).

Another great feature of custom reports is your ability to use them cross-profile and to share them. To share a report, all you need to do is click the Actions drop-down menu from the Custom Reports overview page, and click share. You will then be able to share the configuration (not the data) of the custom report you just created.

Sharing Custom Reports

SEO Custom Report Examples

If you’d like to save time in your SEO analysis, consider creating custom reports similar to the ones outlined below. I’ve included the share link for each custom report so you don’t have to rebuild it yourself. I tried to mix up when I’d tailor the report to look at e-commerce data, and when it would only look at goal data. You’ll need to customize those aspects of the report to best meet your needs.

Also, don’t forget to modify the keyword filters I’ve added. You want to make sure to replace our branded keyword (book) with your own.

Audience Custom Report

Understanding your audience’s demographics is an often overlooked SEO practice, but it can go a long way in making certain aspects of SEO (like link building) that much easier.

Audience Custom Report

There are two components to this custom report:

  1. City and Language Overview – this part of the report looks at what cities and languages you receive the most visits from and make the most money off of. You may be surprised to see languages your site isn’t even translated in yet that are very profitable.
  2. Keyword Targeting – this part of the report lets you drill down all the way to the keywords that are used by each country and language visitor demographic, and calls out how profitable they are for you. This is a great way to refine your keyword targeting.

How this can help you from a link building front is seeing what foreign languages your blog/linkbait content is most popular in, and then translating it. You could then distribute the translated content for links to popular industry blogs in that language.

Add the Audience Custom Report to Google Analytics

Content Custom Report

The purpose of the Content Custom Report is to identify which content is performing the best with organic traffic. I’ve set this report up as a Explorer Custom Report so you can drill down and see which keywords are sending traffic to a specific Landing Page. This is a great way to make sure you’re targeting the right keywords on the right pages in your SEO campaign.

Content Custom Report

There are a number of engagement metrics I have this report looking at. One in particular I think is important to have with this report is the Social Actions metric. This is a great way to see if the number of social actions correlates with increases in traffic and conversions.

You might consider adding an additional filter (or creating a new custom report) that only looks at your blog content. I’d keep similar metrics in the report so you can quickly identify which blog posts perform the best so you can try and duplicate the results in future content. You may also want to add any event goals you’ve created to the report, especially if you’ve set up a event to track comments on your posts.

Add the Content Custom Report to Google Analytics

Keyword Analysis Custom Report

I think this is one of the most valuable custom reports you can run, and it’s one of the bigger custom reports that I like to create in my accounts. There are three components to the report: targeting, engagement and revenue.

Keyword Analysis Custom Report

Targeting
This part of the report is pretty straight forward. It’s a Flat Table report that places the Page Title and the Keyword that is sending it traffic side-by-side. From there I’ve added a handful of metrics to determine if I am targeting the right keyword on the right page. Perhaps I’m getting a lot of traffic for this particular keyword, but the majority of people are going elsewhere and/or not converting. This may lead me to do some testing around changing which page I’m optimizing for this particular keyword.

Engagement
Similar to the Content Custom Report, this component focuses on how engaging visitors are when they visit the site via a specific keyword. I love traffic just as much as the next guy, but if that traffic isn’t doing anything on my site – what good is it? This report will help you identify problems and opportunities for keywords that have low/high engagement rates.

Revenue
Just how much money is a keyword making you? This component of the report looks at the number of transactions, the revenue generated and the per visit value of organic traffic for each keyword.

Add the Keyword Analysis Custom Report to Google Analytics

Link Analysis Custom Report

Which of the inbound links that you’ve built are sending you the most quality traffic? Don’t forget, there’s much more to links than rankings, they are also opportunities for sending high quality traffic to your site that may even convert.

This custom report looks at which of your referrals are sending you the most engaging traffic. Knowing which links are sending you the most quality traffic will help you determine if you should be going back for more or if you can find other sites just like it to get links set up on.

Link Analysis Custom Report

If you’re investing a lot of time in getting specific links built, you may even consider tagging them with Google’s URL builder tool. This will allow you to track the effectiveness of your link building campaign.

Add the Link Analysis Custom Report to Google Analytics

PPC Content Custom Report

I’m a big fan of using paid search as a way to test which landing pages you want to target your keywords on for relevance. The goal of the test is to determine if you were to target a specific keyword on that page, would the visitor find what they are looking for and convert? This is a great way to minimize the risk of focusing on the wrong keyword on the wrong page and investing months of SEO work to get it traffic.

PPC Content Custom Report

You can use this custom report to look at just that: which keyword/landing page combinations are the most effective from a revenue perspective. Even if you don’t run a test like the one I just described, you can still get a pretty good grasp on this just by pulling the report and looking for these opportunities.

Add the PPC Content Custom Report to Google Analytics

PPC Keywords Custom Report

Continuing with our holistic custom reports, the goal of the PPC keywords custom report is simple: identify high performing keywords from your paid search campaigns that you could consider targeting in your SEO campaign.

PPC Keywords Custom Report

The report calls out a couple qualifier metrics, including how much money bidding on the keyword is costing you, and what your cost per conversion is. This is a great way to decide if you can’t afford to target the keyword via PPC, can you make up the loss of traffic via SEO?

Add the PPC Keywords Custom Report to Google Analytics

Social Media Custom Report

We’ve seen the influence social media has on SEO, and now it’s time to make sure we’re well-informed of any social media data that can be leveraged to improve our campaigns.

This report uses a filter created by Site Visibility to look at all referring traffic from a variety of top social sources. With this filter applied you can look at which social traffic is most engaged with your content.

Social Media Custom Report

If you’re tracking social actions you can quickly see which content you’ve created is being shared the most, so you can figure out what they like about the content and duplicate the results.

I also like to see which social media is converting the best so I can determine if we should be increasing our participation efforts on that social network, or even start experimenting with advertising on that social network.

Add the Social Media Custom Report to Google Analytics

So there you have it, seven custom reports to help you analyze your analytics data faster and easier. What other SEO-focused custom reports have you found valuable?

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SEO Book.com

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Google Indexing Issue With Custom Blogger Domains?

A Google Webmaster Help thread has bloggers who run off the Blogger Custom Domain set up that their new blog posts are not being indexed and ranked in the Google search results…




Search Engine Roundtable

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