Archive for October, 2016

PostHeaderIcon How to Craft the Best Damn E-commerce Page on the Web – Whiteboard Friday



Posted by randfish

From your top-level nav to your seal-the-deal content, there are endless considerations when it comes to crafting your ecommerce page. Using one of his personal favorite examples, Rand takes you step by detailed step through the process of creating a truly superb ecommerce page in today’s Whiteboard Friday.

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

Video Transcription

Howdy all and welcome to a special edition of Whiteboard Friday. My name is Rand Fishkin. I’m the founder of Moz, and today I want to talk with you about how to craft the best damn ecommerce page on the web. I’m actually going to be using the example of one of my very favorite ecommerce pages. That is the Bellroy Slim Wallet page. Now, Bellroy, actually, all of their pages, Bellroy makes wallets and they market them online primarily. They make some fantastic products. I’ve been an owner of one for a long time, and it was this very page that convinced me to buy it. So what better example to use?

So what I want to do today is walk us through the elements of a fantastic ecommerce page, talk about some things where I think perhaps even Bellroy could improve, and then walk through, at the very end, the process for improving your own ecommerce page.

The elements of a fantastic e-commerce page

So let’s start with number one, the very first thing which a lot of folks, unfortunately, don’t talk about but is critical to a great ecommerce process and a great ecommerce page, and that is…

1. The navigation at the very top

The navigation at the top needs to do a few things. It’s got to help people:

  • Understand and know where they are in the site structure, especially if you have a more complex site. In Bellroy’s case, they don’t really need to highlight anything. You know you’re on a wallet page. That’s probably in Shop, right? But for Amazon, this is critically important. For Best Buy, this is hugely important. Even for places like Samsung and Apple, critical to understand where I am in the site structure.
  • I want to know something about the brand itself. So if this is the first time that someone is visiting the website, which is very often the case with ecommerce pages, they’re often entry points for the first exposure that you have to a brand. Let’s recall, from what we know about conversion rate optimization, it is uncommon, unusual for someone to convert on their first visit to a brand or a website’s page, but you can make a great first impression, and part of that is what your top navigation needs to do. So it should help people identify with the brand, get a sense for the style and the details of who you are.
  • You need to know where, broadly, you can go in the website. Where can I explore from here? If this is my first visit or if this is my second visit and I’m trying to learn a little bit more about the company, I want to be able to easily get to places like About, or I want to be able to easily learn more about their products or what they do, learn more about the potential solutions, learn more about their collections and what other things they offer me.
  • I also, especially for ecommerce repeat visitors and for folks who are buying more than one thing, I want to have this simple navigation around Cart. I don’t, in fact, love how Bellroy minimizes this, but you want to make sure that the Search bar is there as well. Search is actually a function. About 10% to 12% of visitors on average to ecommerce pages will use Search as their primary navigation function. So if you make that really subtle or hard to find or difficult to use, the Search feature can really limit the impact that you can have with that group.
  • I want that info about the shopping process that comes from having the Cart. In Bellroy’s case, I love what they do. They actually put “Free shipping in the United States” in their nav on every page, which I think, clearly for them, it must be one of the key questions that they get all the time. I have no doubt that they’ve done some A/B testing and optimization to make sure, “Hey, you know what? Let’s just put it in front of everyone because it doesn’t hurt and it helps to improve our conversion rates.”

2. Core product information

Core product information tends to be that above-the-fold key part here. In Bellroy’s case, it’s very minimalist. We’re just talking about a photo of the wallet itself, and then you can click left or right, or I think sometimes it auto-scrolls as well on desktop but not mobile. I can see a lot more photos of how many cards the wallet can hold and what it looks like in my pants, how it measures up compared to a ruler, and all that kind of stuff. So there’s some great photography in here and that’s important, as well as the name and the price.These core details may differ from product to product. For example, if you are selling a more complex piece of technology, the core features may, in fact, be fairly substantive, and that’s okay. But we are trying to help. With this core product information, we’re trying to help people understand what the product is and what it does. So wallet, very, very obvious. If we’re talking about lab equipment or scientific machinery, well, a little more complicated. We better make sure that we’re communicating that. We want…

  • Visuals that are going to serve to… in this case, I think they do a great job, but comprehensively communicate the positioning, the positioning of the product itself. So Bellroy is clearly going with minimalist. They’re going with craft. They’re a small, niche shop. They don’t do 10,000 things. They just make wallets, and they are trying to make that very clear. They also are trying to make their quality a big part of this, and they are trying to make the focus of the product itself, the slimness. You can really see that as you go into, well obviously, the naming convention, but also the photography itself, which is showing you just how slim this wallet can be in comparison to bulky other wallets. They take the same number of cards, they put them in two different kinds of wallets, they show you the thickness, and the Bellroy is very, very slim. So that’s clearly what the positioning is going for.
  • Potentially here, we might want video or animation. But I’m going to say that this is only a part of the core content when it truly makes sense. Great example of when it does make sense would be Zappos. Zappos, obviously, has their videos for nearly every shoe and shoe brand that they promote on their website. They saw tremendous conversion rate improvements because people had a lot of questions about how it moves and walks and how it looks with certain pieces of clothing. The detail of having someone explain it to you, as I’m explaining ecommerce pages to you in video form, turned out had a great impact on their conversion rate. You might want to test this, but it’s also the case that this content, that video or animation content might live down below. We’ll talk about how that can live in more of the photos and process at the very bottom at the end of this video.
  • Naming convention. We want price. We want core structural details. I like that Bellroy here has made their core content very, very slim, just the photos, the name, and the price.

3. Clear options to the path to purchase

This is somewhere where, I think, a lot of folks unfortunately get torn by the Amazon model. If you are Amazon.com, which yes, has phenomenal click-through rates, phenomenal engagement rates, phenomenal conversion rates, but you are not Amazon. Repeat after me, “I am not Amazon.” Therefore, one of the things that Amazon does is they clutter this page with hundreds of different things that you could do, and they built that up over decades, literally decades. They built up so that we are all familiar with an Amazon page, ecommerce page, and what we expect on it. We know there’s going to be a lot of clutter. We know there’s going to be a ton of call-to-actions, other things we could buy, things that are often bought with this, and things that could be bundled with this. That is fine for Amazon. It is almost definitely not fine for you unless you are extremely similar to what Amazon does. For that reason, I see many, many folks getting dragged in this direction of, “Hey, I want to have 10 different calls-to-action because people might want to X, Y, and Z.” There are ways to do the “might want to X, Y, and Z” without making those specific calls-to-action in the core part of the landing page for the ecommerce product. I’ll talk about those in just a second.

But what I do want you to do here is:

  • Help people understand what is available. Quick example, you can select the color. That is the only thing you can do with this wallet. There are no different sizes. There are no different materials that they could be made of. There’s just color. Color, Checkout, and by the way, once again, free shipping.
  • I am trying to drive them to the primary action, and that is what this section of your ecommerce page needs to do a great job of. Make the options clear, if there are any, and make the path to purchase really, really simple.
  • We’re trying to eliminate roadblocks, we’re trying to eliminate any questions that might arise, and we want to eliminate any future frustration. So, for example, one of the things that I would do here, that Bellroy does not do, is I would geo-target based on IP address. So I’d look at the IP address of the visitor who’s coming to this page, and I would say, “I am pretty sure you are located in Washington State right now. Therefore, I know that this is the sales tax amount that I need to charge.” Or, “Bellroy isn’t in Washington State. I don’t need to charge you sales tax.” So I might have a little thing here that says, “Sales Tax” and then a little drop-down that’s pre-populated with Washington or pre-populated with the ZIP code if you know that and “$0.” That way it’s predictive. It’s saying already, “Oh, good. I know that the next page I’m going to click on is going to ask me about sales tax, or the page after I enter my credit card is.” You know what, it’s great to have that question answered beforehand. Now, maybe Bellroy has tested this and they found that it doesn’t convert as well, but I would guess that it probably, probably would convert even better with that messaging on there.

4. Detailed descriptions of the features of the product

This is where a lot of the bulk of the content often lives on product pages, on ecommerce pages. In this case, they’ve got a list of features, including all sorts of dimension stuff, how it’s built, what it’s made from, and what it can hold, etc., etc.

What I’m trying to do here is a few things:

  • I want to help people know what to expect from this product. I don’t want high returns. Especially if I’m offering free shipping, I definitely don’t want high returns. I want people to be very satisfied with this product, to know exactly what they’re going to get.
  • I want to help them determine if the product fits their needs, fits what they are trying to accomplish, fits the problem they’re trying to solve.
  • I want to help them, lead them to answers quickly for frequently asked questions. So if I know that lots of people who reach this page have this sort of, “Oh, gosh, you know, I wonder, what is their delivery process like? How long does it take to get to me because I kind of need a wallet for this trip that I’m going on, and, you know, I’m bringing pants that just won’t hold my thick wallet, and that’s what triggered me to search for slim wallets in Google and that’s what led me to this page?” Aha, delivery. Great job. You’ve answered the question before or as they are asking it, and that is really important. We want answers to the unasked questions before people start to panic in the Checkout process.

You can go through this with folks who you say, “Hey, I want you to imagine that you are about to buy this. Give me the 10 things in your head. I want you to say out loud everything that you think when you see this page.” You can do this with actual customers, with customers who are returning, with people who fit your target demographic and target customer profile but have not yet bought from you, with people who’ve bought from your competitors. As you do this, you will find the answers to be very, very similar time after time, and then you can answer them right in this featured content. So warranty is obviously another big one. They note that they have a three-year warranty. You can click plus here, and you can get more information.

I also like that they answer that unasked question. So when they say, “Okay, it’s 80 millimeters by 95 millimeters.” “Man, I don’t know how big a millimeter is. I just can’t hold that information in my head.” But look, they have a link “Compare to Others.” If you click that, it will show you an overlay comparison of this wallet against other wallets that they offer and other wallets that other people offer. Awesome. Fantastic. You are answering that question before I have it.

5. A lot of the seal-the-deal content

When we were talking before about videos or animations or some of the content that maybe belongs in the featured section or possibly could be around Checkout, but doesn’t quite reach the level of importance that we’ve dictated for those, this is where you can put that content. It can live below the fold, scrolling way down. I have yet to see the ecommerce page that has suffered from providing too much detail about things people actually care about. I have seen ecommerce pages suffer from bloating the page with tons of content that no one cares about, especially as it affects page load speed which hurts your conversions on mobile and hurts your rankings in Google because site speed is a real issue. But seal-the-deal content should:

  • Help people get really comfortable and build trust. So if I scroll down here, what I’m seeing is more photos about how the wallet is made, how people are using it. They call this the nude approach, which cleverly titled, I’m sure it makes for a lot of clicks. The nude approach to building a wallet, why the leather is so slender, why it adds so little weight and depth, why it lasts so long, all these kinds of things.
  • It’s trying to use social proof or other psychological triggers to get rid of any remaining skepticism. So if you know what the elements of skepticism are from your potential buyers, you can answer that in this deeper content as people get down and through this.

Now, all right, you might say to yourself, “These all sound like great things. How do I actually run this process, Rand?” The answer is embedded in what we just talked about. You’re going to need to ask your customers, your potential customers, your customers who bought from you before, and customers who did not buy from you but ended up buying from a competitor, about these elements. You’re going to need to test, which means that you need some infrastructure, something like an Unbounce or an Optimizely, or your own testing platform if you feel like building one, your engineers do, in order to be able to change out elements and see how well they convert, change out pieces of information. But it is not helpful to change things like button color, or to change lists of features, or to change out the specific photos when the problem is, overall, you have not solved these problems. If you don’t solve these problems, the best button color in the world will not help your conversion rate nearly enough, which is why we need to form theories and have hypotheses about what’s stopping people from buying. That should be informed by our real research.

SEO for ecommerce pages

SEO for ecommerce pages is based on only a few very, very simple things. Our SEO elements here are keywords, content, engagement, links, and in some cases freshness. You hit these five and you’ve basically nailed it.

  • Keywords, do you call your products the same thing people call your products when they search for them? If the answer is no, you have an opportunity to improve. Even if you want to use a branded name, I would suggest combining that with the name that everyone else calls your things. So if this is the slim sleeve wallet, if historically Bellroy had called this the sleeve wallet, I would highly recommend to them, “Hey, people are searching for slim wallet. How about we find a way to merge those things?”
  • Content is around what is on this page, and Google is looking for content that solves the searcher’s problem, the searcher’s issue. That means doing all of these things right and having it in a format that Google can actually read. Video is great. Transcripts of the video should also be available. Visuals are great. Descriptions should also be available. Google needs that text content.
  • Engagement, that is going to come from people visiting this page and not clicking the back button and going back to Google and searching for other stuff and clicking on your competitor’s links. It’s going to come from people clicking that Checkout button or browsing deeper in the website and from engaging with this page by spending time on the site and not bouncing. That’s your job and responsibility, and this stuff can all help.
  • Links come from press. It can come from blogs. It can come from some high-quality directories. Be very careful in the directory link-building world. It can come from partnerships. It can come from suppliers. It can come from fans of the product. It can come from reviews. All that kind of stuff. People who give you their testimonials, you can potentially ask them for links, so all that kind of stuff. Those links, if they are from diverse sets of domains and they contain good anchor text, meaning the name of your actual product, and they are pointing specifically to this page, they will tremendously help you rank above your competition.
  • Freshness. In some industries and in some cases, when you know that there is a lot of demand for the latest and greatest, you should be updating this page as frequently as you can with the new information that is most pertinent and relevant to your audience.

You do these things, and you do these things, and you will have the best damn ecommerce page on the web.
All right, everyone, thanks for joining us. We’ll see you again hopefully on Whiteboard Friday. Take care.

Video transcription by Speechpad.com

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PostHeaderIcon How to Use Search Analytics in Google Sheets for Better SEO Insights



Posted by mihai.aperghis

This post was originally in YouMoz, and was promoted to the main blog because it provides great value and interest to our community. The author’s views are entirely his or her own and may not reflect the views of Moz, Inc.

As an SEO, whether you’re working in-house or handling many clients in an agency, you’ve likely been using this tool for a bunch of reasons. Whether it’s diagnosing traffic and position changes or finding opportunities for optimizations and content ideas, Google Search Console’s Search Search Analytics has been at the core of most SEOs’ toolset.

The scope of this small guide is to give you a few ideas on how to use Search Analytics together with Google Sheets to help you in your SEO work. As with the guide on how to do competitive analysis in Excel, this one is also focused around a tool that I’ve built to help me get the most of Search Analytics: Search Analytics for Sheets.

The problem with the Search Analytics UI

Sorting out and managing data in the Google Search Console Search Analytics web UI in order to get meaningful insights is often difficult to do, and even the CSV downloads don’t make it much easier.

The main problem with the Search Analytics UI is grouping.

If you’d like to see a list of all the keywords in Search Analytics and, at the same time, get their corresponding landing pages, you can’t do that. You instead need to filter query-by-query (to see their associated landing pages), or page-by-page (to see their associated queries). And this is just one example.

Search Analytics Grouping

Basically, with the Search Analytics UI, you can’t do any sort of grouping on a large scale. You have to filter by each keyword, each landing page, each country etc. in order to get the data you need, which would take a LOT of time (and possible a part of your sanity as well).

In comes the API for the save

Almost one year ago (and after quite a bit of pressure from webmasters), Google launched the official API for Search Analytics.

Official Google Webmaster Central Blog Search Analytics API

With it, you can do pretty much anything you can do with the web UI, with the added benefit of applying any sort of grouping and/or filtering.

Excited yet?

Imagine you can now have one column filled with keywords, the next column with their corresponding landing pages, then maybe the next one with their corresponding countries or devices, and have impressions, clicks, CTR, and positions for each combination.

Everything in one API call


Query Page Country Device Clicks Impressions CTR Position
keyword 1 https://domain.com/us/page/ usa DESKTOP 92 2,565 3.59% 7.3
keyword 1 https://domain.com/us/page/ usa MOBILE 51 1,122 4.55% 6.2
keyword 2 https://domain.com/gb/ gbr DESKTOP 39 342 11.4% 3.8
keyword 1 https://domain.com/au/page/ aus DESKTOP 21 55 38.18% 1.7
keyword 3 https://domain.com/us/page/ usa MOBILE 20 122 16.39% 3.6

Getting the data into Google Sheets

I have traditionally enjoyed using Excel but have since migrated over to Google Sheets due to its cloud nature (which means easier sharing with my co-workers) and expandability via scripts, libraries, and add-ons.

After being heavily inspired by Seer Interactive’s SEO Toolbox (an open-source Google Sheets library that offers some very nice functions for daily SEO tasks), I decided to build a Sheets script that would use the Search Analytics API.

I liked the idea of speeding up and improving my daily monitoring and diagnosing for traffic and ranking changes.

Also, using the API gave me the pretty useful feature of automatically backing up your GSC data once a month. (Before, you needed to do this manually, use a paid Sheets add-on or a Python script.)

Once things started to take shape with the script, I realized I could take this public by publishing it into an add-on.

What is Search Analytics for sheets?

Simply put, Search Analytics for Sheets is a (completely free) Google Sheets add-on that allows you to fetch data from GSC (via its API), grouped and filtered to your liking, and create automated monthly backups.

If your interest is piqued, installing the add-on is fairly simple. Either install it from the Chrome Web Store, or:

  • Open a Google spreadsheet
  • Go to Add-ons -> Get add-ons
  • Search for Search Analytics for Sheets
  • Install it (It’ll ask you to authorize a bunch of stuff, but you can sleep safe: The add-on has been reviewed by Google and no data is being saved/monitored/used in any other way except grabbing it and putting it in your spreadsheets).

Once that’s done, open a spreadsheet where you’d like to use the add-on and:

Search Analytics for Sheets Install

  • Go to Add-ons -> Search Analytics for Sheets -> Open Sidebar
  • Authorize it with your GSC account (make sure you’re logged in Sheets with your GSC account, then close the window once it says it was successful)

You’ll only have to do this once per user account, so once you install it, the add-on will be available for all your spreadsheets.

PS: You’ll get an error if you don’t have any websites verified on your logged in account.

How Search Analytics for Sheets can help you

Next, I’ll give you some examples on what you can use the add-on for, based on how I mainly use it.

Grab information on queries and their associated landing pages

Whether it is to diagnose traffic changes, find content optimization opportunities, or check for appropriate landing pages, getting data on both queries and landing pages at the same time can usually provide instant insights. Other than automated backups, this is by far the feature that I use the most, especially since it’s fairly hard to replicate the process using the standard web UI.

Best of all, it’s quite straightforward to do this and requires only a few clicks:

  • Select the website
  • Select your preferred date interval (by default it will grab the minimum and maximum dates available in GSC)
  • In the Group field, select “Query,” then “Page”
  • Click “Request Data”

That’s it.

You’ll now have a new sheet containing a list of queries, their associated landing pages, and information about impressions, clicks, CTR, and position for each query-page pair.

Search Analytics for Sheets Example 1

What you do with the data is up to you:

  • Check keyword opportunities

Use a sheets filter to only show rows with positions between 10 and 21 (usually second-page results) and see whether landing pages can be further optimized to push those queries to the first page. Maybe work a bit on the title tag, content and internal linking to those pages.

  • Diagnose landing page performance

Check position 20+ rows to see whether there’s a mismatch between the query and its landing page. Perhaps you should create more landing pages, or there are pages that target those queries but aren’t accessible by Google.

  • Improve CTR

Look closely at position and CTR. Check low-CTR rows with associated high position values and see if there’s any way to improve titles and meta descriptions for those pages (a call-to-action might help), or maybe even add some rich snippets (they’re pretty effective in raising CTR without much work).

  • Find out why your traffic dropped
    • Had significant changes in traffic? Do two requests (for example, one for the last 30 days and one for the previous 30 days) then use VLOOKUP to compare the data.
    • Positions dropped across the board? Time to check GSC for increased 4xx/5xx errors, manual actions, or faulty site or protocol migrations.
    • Positions haven’t dropped, but clicks and impressions did? Might be seasonality, time to check year-over-year analytics, Google Trends, Keyword Planner.
    • Impressions and positions haven’t dropped, but clicks/CTR did? Manually check those queries, see whether the Google UI has changed (more top ads, featured snippet, AMP carousel, “In the news” box, etc.)

I could go on, but I should probably leave this for a separate post.

Get higher granularity with further grouping and filtering options

Even though I don’t use them as much, the date, country and device groupings let you dive deep into the data, while filtering allows you to fetch specific data to one or more dimensions.

Search Analytics for Sheets Grouping

Date grouping creates a new column with the actual day when the impressions, clicks, CTR, and position were recorded. This is particularly useful together with a filter for a specific query, so you can basically have your own rank tracker.

Grouping by country and device lets you understand where your audience is.

Using country grouping will let you know how your site fares internationally, which is of course highly useful if you target users in more than one country.

However, device grouping is probably something you’ll play more with, given the rise in mobile traffic everywhere. Together with query and/or page grouping, this is useful to know how Google ranks your site on desktop and mobile, and where you might need to improve (generally speaking you’ll probably be more interested in mobile rankings here rather than desktop, since those can pinpoint problems with certain pages on your site and their mobile usability).

Search Analytics for Sheets Grouping Example

Filtering is exactly what it sounds like.

Choose between query, page, country and/or device to select specific information to be retrieved. You can add any number of filters; just remember that, for the time being, multiple filters are added cumulatively (all conditions must be met).

Search Analytics for Sheets Grouping Example

Other than the rank tracking example mentioned earlier, filtering can be useful in other situations as well.

If you’re doing a lot of content marketing, perhaps you’ll use the page filter to only retrieve URLs that contain /blog/ (or whatever subdirectory your content is under), while filtering by country is great for international sites, as you might expect.

Just remember one thing: Search Analytics offers a lot of data, but not all the data. They tend to leave out data that is too individual (as in, very few users can be aggregated in that result, such as, for example, long tail queries).

This also means that, the more you group/filter, the less aggregated the data is, and certain information will not be available. That doesn’t mean you shouldn’t use groups and filters; it’s just something to keep in mind when you’re adding up the numbers.

Saving the best for last: Automated Search Analytics backups

This is the feature that got me into building this add-on.

I use GSC data quite a bit, from client reports to comparing data from multiple time periods. Unless you’ve never used GSC/WMT in the past, it’s highly unlikely you don’t know that the data available in Search Analytics only spans about the last 90 days.

While the guys at Google have mentioned that they’re looking into expanding this window, most SEOs have had to rely on various ways of backing up data in order to access it later.

This usually requires either remembering to manually download the data each month, or using a more complicated (but automated) method such as a Python script.

The Search Analytics for Sheets add-on allows you to do this effortlessly.

Just like when requesting data, select the site and set up any grouping and filtering that you’d like to use. I highly recommend using query and page grouping, and maybe country filtering to cut some of the noise.

Then simply enable the backup.

That’s it.The current spreadsheet will host that backup from now on, until you decide to disable it.

Search Analytics for Sheets Example 2

What happens now is that once per month (typically on the 3rd day of the month) the backup will run automatically and fetch the data for the previous month into the spreadsheet (each month will have its own sheet).

In case there are delays (sometimes Search Analytics data can be delayed even up to a week), the add-on will re-attempt to run the backup every day until it succeeds.

It’ll even keep a log with all backup attempts, and send you an email if you’d like.

Search Analytics for Sheets Backup Log

It’ll also create a separate sheet for monthly aggregated data (the total number of impressions and clicks plus CTR and position data, without any grouping or filtering), so that way you’ll be sure you’re ‘saving’ the real overview information as well.

If you’d like more than one backup (either another backup for the same site but with different grouping/filtering options or a new backup for a different site), simply open a new spreadsheet and enable the backup there. You’ll always be able to see a list with all the backups within the “About” tab.

For the moment, only monthly backups are available, though I’m thinking about including a weekly and/or daily option as well. However that might be more complicated, especially in cases where GSC data is delayed.

Going further

I hope you’ll find the tool as useful as I think it is.

There may be some bugs, even though I tried squashing them all (thanks to Russ Jones and Tori Cushing, Barry Schwartz from Search Engine Roundtable, and Cosmin Negrescu from SEOmonitor for helping me test and debug it).

If you do find anything else or have any feature requests, please let me know via the add-on feedback function in Google Sheets or via the form on the official site.

If not, I hope the tool will help you in your day-to-day SEO work as much as it helps me. Looking forward to see more use cases for it in the comments.

PS: The tool doesn’t support more than 5,000 rows at the moment; working on getting that improved!

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PostHeaderIcon SEO Trek: The Search for Google RankBrain* [New Data]



Posted by larry.kim

Rand Fishkin posted another brilliant Whiteboard Friday last week on the topic of optimizing for RankBrain. In it, he explained how RankBrain helps Google select and prioritize signals it uses for ranking.

One of the most important signals Google takes into account is user engagement. As Rand noted, engagement is a “very, very important signal.”

Engagement is a huge but often ignored opportunity. That’s why I’ve been a bit obsessed with improving engagement metrics.

My theory has been that RankBrain *and/or other machine learning elements within Google’s core algorithm are increasingly rewarding pages with high user engagement. Not always, but it’s happening often enough that it’s kind of a huge deal.

Google is looking for unicorns – and I think that machine learning is Google’s ultimate Unicorn Detector.

Now, when I say unicorns, I mean those pages that have magical engagement rates that elevate them above the other donkey pages Google could show for a given query. Like if your page has a 5 percent click-through rate (CTR) when everyone else has a 1 percent CTR.

What is Google’s mission? To provide the best results to searchers. One way Google does this is by looking at engagement data.

If most people are clicking on a particular search result – and then also engaging with that page – these are clear signals to Google that people think this page is fascinating. That it’s a unicorn.

c6i80.gif

RankBrain: Into Darkness

RankBrain, much like Google’s algorithm, is a great mystery. Since Google revealed (in a Bloomberg article just under a year ago) the important role of machine learning and artificial intelligence in its algorithm, RankBrain has been a surprisingly controversial topic, generating speculation and debate within the search industry.

Then, we found out in June that Google RankBrain was no longer just for long-tail queries. It was “involved in every query.”

We learned quite a few things about RankBrain. We were told by Google that you can’t optimize for it. Yet we also learned that Google’s engineers don’t really understand what RankBrain does or how it works.

Some people have even argued that there is absolutely nothing you can do to see Google’s machine learning systems at work.

Give me a break! It’s an algorithm. Granted, a more complex algorithm thanks to machine learning, but an algorithm nonetheless. All algorithms have rules and patterns.

When Google tweaked Panda and Penguin, we saw it. When Google tweaked its exact-match domain algorithm, we saw it. When Google tweaked its mobile algorithm, we saw it.

If you carefully set up an experiment, you should be able to isolate some aspect of what Google is proclaiming as the third most important ranking factor. You should be able to find evidence – a digital fingerprint.

Well, I say it’s time to boldly go where no SEO has gone before. That’s what I’ve attempted to do in this post. Let’s look at some new data.

The search for RankBrain [New Data]

What you’re about to look at is organic search click-through rate vs. the average organic search position for three separate 30-day periods ending April 30, July 12, and September 19 of this year. This data, obtained from the Google Search Console, tracked the same keywords in the Internet marketing niche.

I see some of the most compelling evidence of RankBrain (and/or other machine learning search algorithms!) at work.

The shape of CTR vs. ranking curve is changing every month – for the 30 days ending:

  • April 30, 2016, the average CTR for top position was about 22 percent.
  • July 12, 2016, the average CTR rose to about 24 percent.
  • By September 19, 2016, the average CTR increased to about 27 percent.

The top, most prominent positions are getting even more clicks. Obviously, they were already getting a lot of clicks. But now they’re getting more clicks than they have in recent history.

This is the winner-take-all nature of Google’s organic SERPs today. It’s coming at the expense of Positions 4–10, which are being clicked on much less over time.

Results that are more likely to attract engagement are pushed further up the SERP, while results with lower engagement get pushed further down. That’s what we believe RankBrain is doing.

Going beyond the data

This data is showing us something very interesting. A couple thoughts:

  • This is exactly the fingerprint you would expect to see for a machine learning-based algorithm doing query interpretation that impacts rank based on user engagement metrics, such as CTR.
  • Essentially, machine learning systems move away from serving up 10 blue links and asking a user to choose one of them and toward providing the actual correct answers, further eliminating the need for lower positions.

Could anything else be causing this shift to the click curve? Could it have been the elimination of right rail ads?

No, that happened in February. I was careful to use date ranges that were after the right rail apocalypse.

Could it be more Knowledge Graph elements creeping into the SERPs? If that were the case, it would look like everything got pushed down by one position (e.g., Position 1 becomes Position 2, Position 2 becomes Position 3, and so on).

The data didn’t show that happening. We see a bending of the click curve, not a shifting of the curve.

Behold the awesome power of CTR optimization!

OK, so we’ve looked at the big picture. Now let’s look at the little picture to illustrate the remarkable power of CTR optimization.

Let’s talk about guerrilla marketing. Here are two headlines. Which headline do you think has the higher CTR?

  • Guerrilla Marketing: 20+ Examples and Strategies to Stand Out

This was the original headline for an article published on the WordStream blog in 2014.

  • 20+ Jaw-Dropping Guerrilla Marketing Examples

This is the updated headline, which we changed just a few months ago, in the hopes of increasing the CTR. And yep, we sure did!

Before we updated the headline, the article had a CTR of 1 percent and was ranking in position 8. Nothing awesome.

Since we updated the headline, the article has had a CTR of 4.19 percent and is ranking in position 5. Pretty awesome, no?

Increasingly, we’ve been trying to move away from “SEO titles” that look like the original headline, where you have the primary keyword followed by a colon and the rest of your headline. They aren’t catchy enough.

Yes, you still need to include keywords in your headline. But you don’t have to use this tired format, which will deliver (at best) solid but unspectacular results.

To be clear: we only changed the title tag. No other optimization tactics were used.

We didn’t point any links (internal or external) at it. We didn’t add any images or anything else to the post. Nothing.

Changing the title tag changed the CTR. Which gave it “magical points” that resulted in 97 percent more organic traffic:

What does it all mean?

This example illustrates that if you increase your CTR, you’ll see a nice boost in traffic. Ranking in a better position means more traffic, which means a higher CTR, which also means more traffic.

What’s so remarkable is that this is on-page SEO. No link building was required! Besides, pointing new links to a page wouldn’t result in a higher click-through rate – a catchier headline, however, would result in a higher CTR.

What’s also interesting about this is that RankBrain isn’t like other algorithms, say Panda or Penguin, where it was obvious when you got hit. You lost half your traffic!

If RankBrain or a machine learning algorithm impacts your site due to engagement metrics (positive or negative), it’s a much more subtle shift. All your best pages do better. All your “upper class donkey” pages do slightly worse. Ultimately, the two forces cancel each other out, to some extent, so that the SEO alarms don’t go off.

The final frontier

When it comes to SEO, your mission is to seek out every advantage. It’s my belief that organic CTR and website engagement rates impact organic rankings.

So boldly go where many SEOs are failing to go now. Hop aboard the USS Unicorn, make the jump to warp speed, and discover the wonders of those magical creatures.

Oh, and…

Are you optimizing your click-through rates? If not, why not? If so, what have you been seeing in your analytics?

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