Tag Archive | "Performance"

Are your DSAs really outperforming standard ads? Find out with this ad copy length performance analysis script

Here’s a script that pulls a report on ad performance based on copy length.



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How to Monitor Hreflang Performance With Dynamic Tags in STAT

Posted by TheMozTeam

This post was originally published on the STAT blog.


If you’re familiar with hreflang, you’ll know just how essential this teensy bit of code is to a successful international campaign. You’ll also know that it comes with a boatload of moving parts — multiple pages, sections, and subdomains per country.

That’s a lot of data to track. And if you aren’t hyper-organized, it’s easy to miss out on some big time insights.

Lucky for you, there’s a handy way to track your hreflang campaigns: all you need are a few dynamic tags in STAT. And even luckier for you, Dan Nutter, Technical SEO Specialist at twentysix, agreed to share his wisdom on this very subject.

Below, you’ll learn how to set up your own dynamic tags in STAT, monitor all your pages, and even visualize all that data to impress your team, boss, and clients.

The origins of hreflang 

The hreflang attribute, for those unfamiliar, tells Google which language you are using on a specific page. Introduced back in 2011, it essentially allows us to speak to our target audience in different countries in their languages.

Developing it, though, has been described by Google’s John Mueller as one of the most difficult sides to SEO:

While certainly complex, hreflang has been immensely helpful for companies looking to increase their site (or, in our case, our client’s sites) visibility and grow their audience. This is because: when searchers see the right language of content, it helps decrease bounce rate and increase conversions.

Since hreflang requires such a significant amount of time and effort from both SEO and development teams, clients (rightly) want to see tangible benefits post-deployment.

Monitoring hreflang (the standard way) 

To show the benefits of such a massive change to the technical architecture of a site, SEOs can do one of two things — either highlight the increase in the number of hreflang tags or point out the reduction in the number of errors being detected in Google Search Console.

The problem is that telling a valuable story about complex code, one that will resonate with clients, is no easy feat, particularly when the information is being communicated to the C-suite.

This is why dynamic tags in STAT are an incredible tool for SEOs and are invaluable to our team.

Monitoring hreflang with dynamic tags (the easier way) 

For those of you running international SEO campaigns, I highly recommend using STAT’s dynamic tags to monitor changes of ranking URLs after new hreflang deployments.

Not only do dynamic tags allow for a fast diagnosis of potential issues with the hreflang mark-up, they also provide a tangible way to tell a compelling, positive story for our team or a client of twentysix.

In STAT, dynamic tags are automatically populated by a pre-determined criterion — you select them with the filtering options in the Keywords tab at the site level. For instance, you could filter the SERP Features column to see all keywords that generate “People also ask” boxes.

All your tags are then at the ready in the Tags tab, so you can get quick snapshots of how your data is performing.

Creating your hreflang tags in STAT 

To track your new hreflang mark-up with dynamic tags in STAT, your international content must be delivered via either sub-folders or sub-domains on a site using a gTLD (E.g. www.sitename.com/fr-fr/ or fr.sitename.com).

If your international content is served on ccTLDs (i.e. www.sitename.fr), dynamic tags won’t be able to track any incorrectly ranking URLs, as they will be attributed to a different domain.

First, you’ll need to separate the sites in your project for all relevant country and language combinations. To enable this, you simply filter ranking URLs for a specific text string. This will generate tags that can track all the ranking keywords for a particular sub-folder — or even a specific URL — and monitor their performance.

Under the URL column, apply the Wildcard Search and/or Exclusion Search functions. This will allow you to detect any changes in your ranking URLs.

Applying Wildcard Search and Exclusion Search helps to surface any changes in your URLs.

The Wildcard Search filter can locate URLs that include the text string for the correct region, thereby tracking the improvement in the number of correctly ranking URLs.

Sites using sub-folders will require filtering for all URLs, which includes the country and language combination you want to track, such as “/fr-fr/” when tracking URLs for the country France and the language of French.

For sites using sub-domains, you’ll need to filter for the sub-domain and root domain combined, such as “fr.sitename.com.” To track sub-domains, you’ll need to select Ignore “www.” prefix when matching in the site settings.

To track subdomains, you need to select Ignore ‘www.’ prefix when matching in the site settings.

Once you have filtered the URL column for your chosen country, select Tag All Filtered Keywords and create a dynamic tag called “Correct URL.”

If you opt to track the decrease in the number of incorrectly ranking URLs, you’ll need to create a dynamic tag using the exact same steps as above, only this time with the Exclusion Search functionality.

Telling a positive story

When you track the performance of your ranking URLs, it’s easier to demonstrate the value of the changes being implemented to the technical architecture of the site.

In addition, when that value is visually represented — like in a graph — it provides clients with a clear idea of just how effective a technical change is, and that can be communicated clearly throughout all levels of their business.This shows the increase in any correctly ranking URLs.

After your tags have been created, you can monitor the increase in correctly ranking URLs using the Dashboard tab.

The bonus round 

An unexpected benefit of tracking the success of a hreflang deployment? It highlights any changes made to the technical setup of a site, which can prevent the hreflang from functioning correctly.

For instance, during a recent campaign, our team noticed an increase in the number of incorrectly ranking URLs, indicating that a site-level change had negatively impacted the hreflang markup.

At the time, Google Search Console was experiencing a number of time-lag errors, which meant that if we weren’t keeping a close eye on things, we would have missed the issue entirely. With our dynamic tags set up in STAT, we were able to pick up on these changes before Google Search Console.

Using STAT’s dynamic tags, Dan was able to catch the error before Google Search Console.

By leveraging STAT’s dynamic tags, we were able to catch the increase and our team rectified the issue before any long-term damage was done.

Liked what you read?

Want to know your best and worst-performing tags? Keen to compare all their metrics side-by-side?

If you answered yes to both and you’re a STAT client, then check out our Tags tab to see what kinds of insights you can uncover for your international (and national) campaigns.

Not a STAT client (yet)? Book a demo to get a customized walkthrough. You can also chat with our team at MozCon to see it up close and personal! 

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SMXcast: Tactics to improve your YouTube video ad performance

Ashley Mo discusses how to run video and search ads together to increase conversions.



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Google Search Console Performance Report Now Consolidated To Canonical

In February, Google announced that they would be consolidating the data in the performance report to the canonical. Meaning the AMP, mobile, etc will all be counted towards the main URL’s data in the performance report. This was live in two different views but now the old view is gone.


Search Engine Roundtable

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Google Search Console Performance Reports & Search Analytics One Day Off Still

Back in January, we reported that when you look at the new Google Search Console Performance report and compare it to the old Search Analytics report, they do have the same data but the day they plot the data is a day off from each other. With Google shutting down the old Search Analytics report in two days from now, this is a concern for some.


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SearchCap: Google update still rolling out, Bing adds hotel booking, page speed performance & more

Here’s our recap of what happened in online marketing today, as reported on Marketing Land and other places across the web



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If Content Is a Performance, Is It Ever Authentic?

Producing more effective content that helps you build an audience of interested prospects is a common theme in my articles. In the past few months, I’ve written about ways to show how likable you are and how to make your writing personal, but not self-indulgent. And I realized that neither of those posts mentioned authenticity,
Read More…

The post If Content Is a Performance, Is It Ever Authentic? appeared first on Copyblogger.


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2-step methodology for dealing with PPC performance downturns

What happens when your paid search campaigns are experiencing a sudden and unexpected performance drop? Columnist Jeff Baum shows how to handle this situation — without losing your clients’ trust.

The post 2-step methodology for dealing with PPC performance downturns appeared first on Search…



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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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How to Improve Your Site’s Performance When Using GIFs

Posted by Web_Perfectionist

The GIF (Graphics Interchange Format) format was originally developed in 1987. Debuted by Steve Wilhite of Compuserve, GIFs improved on the black-and-white images in use during that time by allowing the use of 256 colors while maintaining a compressed format that could still be loaded by those utilizing slow modems. Furthermore, web developers and designers could create animations via timed delays. And to this day, little has changed regarding GIFs.

Due to its simplicity, the widespread support for this format, and the ease with which it can be used to stream video clips, the GIF format is the oldest file format still commonly used today. This frame animation feature of GIFs ensures that the format remains popular, despite the rise of JPEG and PNG images.

How to Improve Your Site’s Performance When Using GIFs

In spite of their popularity and ubiquitousness on the Internet (especially with regards to animated GIFs), GIFs are not the most performant of image options. If you are using GIFs on your sites, it’s important that you take care to optimize your GIFs so that they do not create too much overhead.

This article will cover ways to optimize your GIFs, both static and animated, and will offer an excellent alternative you can use to eliminate the page bloat resulting from use of GIFs as animation.

Why should you optimize your GIFs?

Performance matters when it comes to designing your web pages, and GIFs are not the most performant of image options. While they are excellent for capturing your user’s attention and are universally liked for providing short bursts of information in an entertaining way, GIFs were not designed for animation (despite them being commonly used for such). As such, usage of GIFs leads to heavy page weights and poor user experiences resulting from slow page load speeds.

How to improve the performance of your site while using GIFs

In this section, we’ll cover several ways you can improve the performance of your site with regards to using GIFs. We’ll first dig into ways to handle static GIFs, and we’ll end by discussing ways to minimize the overhead resulting from animated GIFs.

There are two methods for compressing images:

One of the primary methods for optimizing GIFs is to compress them. There are two methods of compression that are commonly used:

  • Lossy compression: Lossy compression removes some of the data from the original file, resulting in an image with a reduced file size. However, every time you save the file after compression, the quality of the graphic degrades somewhat, which can result in a fuzzy, pixelated image over time.
  • Lossless compression: Lossless compression preserves all of the data from the original file, which means that the compressed file can be uncompressed to gain the original file. While your file size remains larger than if you had used lossy compression, your image’s quality does not degrade over time.

Later on in this post, we’ll cover the impact of both types of optimization on GIFs.

Improve the performance of sites that are using static GIFs by converting to PNG.

The easiest way to improve the performance of your site is to render your image using the PNG format instead of the GIF format. While the two formats are very similar in terms of being good choices for displaying simple graphics, PNG files have the advantage of being able to compress to a size 5–25% smaller than the equivalent GIF file. GIFs were originally created to use a lossless compression technique called the Lempel-Ziv-Welch (LZW) algorithm, which was defined in the 1970s. However, modern compression techniques are much more performant than LZW, and you can take advantage of this by using formats that utilize these techniques, such as PNGs.

Such file format conversions are pretty easy to do, and there are an abundance of software options you can choose from, including free web-based utilities such as the ones from Pic.io and Convertio.

Improve the performance of sites that are using animated GIFs one of two ways:

Animated GIFs, while extremely popular, can be huge files that require lengthy load times. For example, a GIF that is just a few seconds long can be a few megabytes in size. To improve the performance of your site, use one of the following techniques:

  • Lossy optimization
  • Converting your animated GIF to a HTML5 video

Lossy optimization on animated GIFs

Because the vast majority of data comprising animated GIFs is graphical data, and because lossless optimizations cannot modify graphical data, you have only one viable option when it comes to optimizing an animated GIF beyond the bare minimum: lossy optimization techniques.

Lossy optimizations work because the human eye does not do a very good job at distinguishing between subtle changes in color. For example, an image might contain thousands of shades of one color, with one pixel showing as only slightly different from the ones next to it. Because your eye won’t be able to differentiate between the two shades, the image file can easily be manipulated: One of the colors replaces the other, making the file smaller.

Because animated GIFs are essentially a series of individual GIFs, you can utilize these techniques to decrease the size of your animated file. By making each individual file smaller, your overall file is smaller as well. One way you can do this is by utilizing a simple software suite that can automatically perform such compressions (such as a modified version of gifsicle).

Converting animated GIFs to HTML5 videos

While you can minimize the size of an animated GIF, you may still end up with a file that is larger than it needs to be. GIFs were never intended to store video, and what is now considered animation is really the result of an attempt to reduce overhead on the storage and transmission of multiple images that share identical metadata. Today, however, we have another option that could potentially make your GIFs up to 95% smaller: converting your animated GIFs to HTML5 video.

HTML5 video is a catch-all term for a modern web browser’s ability to play video content using the <video> tag without needing to use external plugins. When this feature was first released in 2009, there was a lot of debate over how such videos would be stored and how they would be encoded. Today, though, the accepted standard is an H.264-encoded video stored in an MP4 container file (which, for simplicity’s sake, we’ll refer to as an MP4 video from here on out). In addition to looking a lot better due to its being designed to stream video, MP4 files are much smaller as well:

Over 90% of modern web browsers support MP4 videos.

There are many ways to convert your animated GIF to MP4, such as the popular open-source command-line tool ffmpeg and the web-based utility Cloud Convert. Using the latter, you can see the file size savings possible by making the conversion.

Here’s the original animated GIF:

sven.gif

Here is the MP4 video that’s created from the GIF:

Sadly, your browser doesn’t support the video tag. This is a smooth MP4 video of the above GIF, which features Oaken from Disney’s Frozen.

Looking at the sizes of the files, we see that the original was 100 KB. By converting the GIF to MP4, we end up with a file that is just 23 KB, which is 75% smaller:

Conclusion

GIFs are the oldest file format still commonly used today due to their simplicity, near-universal support, and ability to be used as animation. Despite these positive features, GIFs tend to be large files, resulting in page bloat that can negatively impact the performance of your webpages and lead to poor user experiences. As such, you should consider serious optimization of static GIFs, moving away from animated GIFs, and implementing video clips using more modern techniques such as HTML5/MP4 videos. And for additional in-depth information on implementing these changes, download Rigor’s free ebook, The Book of GIF: A Comprehensive Guide to Optimizing GIFs.

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