Archive for July, 2016

PostHeaderIcon Should SEOs and Marketers Continue to Track and Report on Keyword Rankings? – Whiteboard Friday



Posted by randfish

Is the practice of tracking keywords truly dying? There’s been a great deal of industry discussion around the topic of late, and some key points have been made. In today’s Whiteboard Friday, Rand speaks to the biggest challenges keyword rank tracking faces today and how to solve for them.

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

Video Transcription

Howdy, Moz fans, and welcome to another edition of Whiteboard Friday. This week we’re going to chat about keyword ranking reports. There have been a few articles that have come out recently on a number of big industry sites around whether SEOs should still be tracking their keyword rankings.

I want to be clear: Moz has a little bit of a vested interest here. And so the question is: Can you actually trust me, who obviously I’m a big shareholder in Moz and I’m the founder, and so I care a lot about how Moz does as a software business. We help people track rankings. Does that mean I’m biased? I’m going to do my best not to be. So rather than saying you absolutely should track rankings, I’m instead going to address what most of these articles have brought up as the problems of rank tracking and then talk about some solutions by which you can do this.

My suspicion is you should probably be rank tracking. I think that if you turn it off and you don’t do it, it’s very hard to get a lot of the value that we need as SEOs, a lot of the intelligence. It’s true there are challenges with keyword ranking reports, but not true enough to avoid doing it entirely. We still get too much value from them.

The case against — and solutions for — keyword ranking data

A. People, places, and things

So let’s start with the case against keyword ranking data. First off, “keyword ranking reports are inaccurate.” There’s personalization, localization, and device type, and that biases and has removed what is the “one true ranking.” We’ve done a bunch of analyses of these, and this is absolutely the case.

Personalization, turns out, doesn’t change ranking that much on average. For an individual it can change rankings dramatically. If they visited your website before, they could be historically biased to you. Or if they visited your competitor’s, they could be biased. Their previous search history might have biased them in a single session, those kinds of things. But with the removal of Google+ from search results, personalization is actually not as dramatically changing as it used to be. Localization, though, still huge, absolutely, and device differences, still huge.

Solution

But we can address this, and the way to do that is by tracking these things separately. So here you can see I’ve got a ranking report that shows me my mobile rankings versus my desktop rankings. I think this is absolutely essential. Especially if you’re getting a lot of traffic from both mobile and desktop search, you need to be tracking those separately. Super smart. Of course we should do that.

We can do the same thing on the local side as well. So I can say, “Here, look. This is how I rank in Seattle. Here’s how I rank in Minneapolis. Here’s how I rank in the U.S. with no geographic personalization,” if Google were to do that. Those types of rankings can also be pretty good.

It is true that local ranked tracking has gotten a little more challenging, but we’ve seen that folks like, well Moz itself, but folks like STAT (GetStat), SERPs.com, Search Metrics, they have all adjusted their rank tracking methodologies in order to have accurate local rank tracking. It’s pretty good. Same with device type, pretty darn good.

B. Keyword value estimation

Another big problem that is expressed by a number of folks here is we no longer know how much traffic an individual keyword sends. Because we don’t know how much an individual keyword sends, we can’t really say, “What’s the value of ranking for that keyword?” Therefore, why bother to even track keyword rankings?

I think this is a little bit of spurious logic. The leap there doesn’t quite make sense to me. But I will say this. If you don’t know which keywords are sending you traffic specifically, you still know which pages are receiving search traffic. That is reported. You can get it in your Google Analytics, your Omniture report, whatever you’re using, and then you can tie that back to keyword ranking reports showing which pages are receiving traffic from which keywords.

Most all of the ranked tracking platforms, Moz included, has a report that shows you something like this. It says, “Here are the keywords that we believe are likely to have sent these percentages of traffic to this page based on the keywords that you’re tracking, based on the pages that are ranking for them, and how much search traffic those pages receive.”

Solution

So let’s track that. We can look at pages receiving visits from search, and we can look at which keywords they rank for. Then we can tie those together, which gives us the ability to then make not only a report like this, but a report that estimates the value contributed by content and by pages rather than by individual keywords.

In a lot of ways, this is almost superior to our previous methodology of tracking by keyword. Keyword can still be estimated through AdWords, through paid search, but this can be estimated on a content basis, which means you get credit for how much value the page has created, based on all the search traffic that’s flowed to it, and where that’s at in your attribution lifecycle of people visiting those pages.

C. Tracking rankings and keyword relevancy

Pages often rank for keywords that they aren’t specifically targeting, because Google has gotten way better with user intent. So it can be hard or even impossible to track those rankings, because we don’t know what to look for.

Well, okay, I hear you. That is a challenge. This means basically what we have to do is broaden the set of keywords that we look at and deal with the fact that we’re going to have to do sampling. We can’t track every possible keyword, unless you have a crazy budget, in which case go talk to Rob Bucci up at STAT, and he will set you up with a huge campaign to track all your millions of keywords.

Solution

If you have a smaller budget, what you have to do is sample, and you sample by sets of keywords. Like these are my high conversion keywords — I’m going to assume I have a flower delivery business — so flower delivery and floral gifts and flower arrangements for offices. My long tail keywords, like artisan rose varieties and floral alternatives for special occasions, and my branded keywords, like Rand’s Flowers or Flowers by Rand.

I can create a bunch of different buckets like this, sample the keywords that are in them, and then I can track each of these separately. Now I can see, ah, these are sets of keywords where I’ve generally been moving up and receiving more traffic. These are sets of keywords where I’ve generally been moving down. These are sets of keywords that perform better or worse on mobile or desktop, or better or worse in these geographic areas. Right now I can really start to get true intelligence from there.

Don’t let your keyword targeting — your keyword targeting meaning what keywords you’re targeting on which pages — determine what you rank track. Don’t let it do that exclusively. Sure, go ahead and take that list and put that in there, but then also do some more expansive keyword research to find those broad sets of search terms and phrases that you should be monitoring. Now we can really solve this issue.

D. Keyword rank tracking with a purpose

This one I think is a pretty insidious problem. But for many organizations ranking reports are more of a historical artifact. We’re not tracking them for a particular reason. We’re tracking them because that’s what we’ve always tracked and/or because we think we’re supposed to track them. Those are terrible reasons to track things. You should be looking for reasons of real value and actionability. Let’s give some examples here.

Solution

What I want you to do is identify the goals of rank tracking first, like: What do I want to solve? What would I do differently based on whether this data came back to me in one way or another?

If you don’t have a great answer to that question, definitely don’t bother tracking that thing. That should be the rule of all analytics.

So if your goal is to say, “Hey, I want to be able to attribute a search traffic gain or a search traffic loss to what I’ve done on my site or what Google has changed out there,” that is crucially important. I think that’s core to SEO. If you don’t have that, I’m not sure how we can possibly do our jobs.

We attribute search traffic gains and losses by tracking broadly, a broad enough set of keywords, hopefully in enough buckets, to be able to get a good sample set; by tracking the pages that receive that traffic so we can see if a page goes way down in its search visits. We can look at, “Oh, what was that page ranking for? Oh, it was ranking for these keywords. Oh, they dropped.” Or, “No, they didn’t drop. But you know what? We looked in Google Trends, and the traffic demand for those keywords dropped,” and so we know that this is a seasonality thing, or a fluctuation in demand, or those types of things.

And we can track by geography and device, so that we can say, “Hey, we lost a bunch of traffic. Oh, we’re no longer mobile-friendly.” That is a problem. Or, “Hey, we’re tracking and, hey, we’re no longer ranking in this geography. Oh, that’s because these two competitors came in and they took over that market from us.”

We could look at would be something like identify pages that are in need of work, but they only require a small amount of work to have a big change in traffic. So we could do things like track pages that rank on page two for given keywords. If we have a bunch of those, we can say, “Hey, maybe just a few on-page tweaks, a few links to these pages, and we could move up substantially.” We had a Whiteboard Friday where we talked about how you could do that with internal linking previously and have seen some remarkable results there.

We can track keywords that rank in position four to seven on average. Those are your big wins, because if you can move up from position four, five, six, seven to one, two, three, you can double or triple your search traffic that you’re receiving from keywords like that.

You should also track long tail, untargeted keywords. If you’ve got a long tail bucket, like we’ve got up here, I can then say, “Aha, I don’t have a page that’s even targeting any of these keywords. I should make one. I could probably rank very easily because I have an authoritative website and some good content,” and that’s really all you might need.

We might look at some up-and-coming competitors. I want to track who’s in my space, who might be creeping up there. So I should track the most common domains that rank on page one or two across my keyword sets.

I can track specific competitors. I might say, “Hey, Joel’s Flower Delivery Service looks like it’s doing really well. I’m going to set them up as a competitor, and I’m going to track their rankings specifically, or I’m going to see…” You could use something like SEMrush and see specifically: What are all the keywords they rank for that you don’t rank for?

This type of data, in my view, is still tremendously important to SEO, no matter what platform you’re using. But if you’re having these problems or if these problems are being expressed to you, now you have some solutions.

I look forward to your comments. We’ll see you again next week for another edition of Whiteboard Friday. Take care.

Video transcription by Speechpad.com

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PostHeaderIcon A Guide to Sampling in Google Analytics



Posted by Tom.Capper

Sampling is a process used in statistics when it’s unfeasible or impractical to analyse all the data that exists. Instead, a small, randomly selected subset is used to keep things manageable. Many analytics platforms use some sort of sampling to keep report loading times in check, and there seem to be three schools of thought when it comes to sampling in analytics. There are those who are terrified of it, insisting in unsampled versions of any report. Then there are those who are relaxed about it, trusting the statistical logic. And then, lastly, there are those who are oblivious.

All three are misguided.

Sampling isn’t something to fear, but, in Google Analytics in particular, it can’t always be trusted. Because of that, it’s definitely worth your time to understand when it occurs, how it affects your work, and how it can be avoided.

When it happens

You can always tell when sampling is being used, because of this line at the top of every report:

If the percentage is less than 100%, then sampling is in progress. You’ll notice above that I’ve produced a report based on more than half a billion sessions without any sampling — sampling isn’t just about the sheer number of sessions involved in a report. It’s about the complexity of what you’re asking the platform to report on. Contrast the below (apologies for the small screenshots; I wanted to make sure the whole context was included, so have added captions explaining just what you’re looking at):

No segment applied, report based on 100% of sessions

Segment applied, report based on 0.17% of sessions

The two are identical apart from the use of a segment in the second case. Google Analytics can always provide unsampled data for top-line totals like that first case, but segments in particular are very prone to prompting sampling.

The exact same level of sampling can also be induced through use of a secondary dimension:

Secondary dimension applied, report based on 0.17% of sessions

A few other specialised reports are also prone to this level of sampling, most notably:

  • The Ecommerce Overview
  • “Flow Reports”

Report based on 0.17% of sessions

Report based on <0.1% of sessions

To summarise so far, sampling can happen when we use:

  • A segment
  • More than one dimension
  • Certain detailed reports (including Ecommerce Overview and AdWords Campaigns)
  • “Flow” reports

The accuracy of sampling

Sampling, for the most part, is actually pretty reliable. Take the below two numbers for organic traffic over the same period, one taken from a tiny 0.17% sample, and one taken without sampling:

Report based on 0.17% of sessions, reports 303,384,785 sessions via organic

Report based on 100% of sessions, reports 296,387,352 sessions via organic

The difference is just 2.4%, from a sample of 0.17% of actual sessions. Interestingly, when I repeated this comparison over a shorter period (last quarter), the size of the sample went up to 71.3%, but the margin of error was fairly similar at 2.3%.

It’s worth noting, of course, that the deeper you dig into your data, the smaller the effective sample becomes. If you’re looking at a sample of 1% of data and you notice a landing page with 100 sessions in a report, that’s based on 1 visit — simply because 1 is 1% of 100. For example, take the below:

Report based on 45 sessions

Eight percent of a whole year’s traffic to Distilled is a lot, but 8% of organic traffic to my profile page is not, so we end up viewing a report (above) based on 45 visits. Whether or not this should concern you depends on the size of the changes you’re looking to detect and your threshold for acceptable levels of uncertainty. These topics will be familiar to those with experience in CRO, but I recommend this tool to get your started, and I’ve written about some of the key concepts here.

In extreme cases like the one above, though, your intuition should suffice – that click-through from my /about/ page to /resources/…tup-guide/ claims to feature in 12 sessions, and is based on 8.11% of sessions. As 12 is roughly 8% of 100, we know that this is in fact based on 1 session. Not something you’d want to base a strategy on.

If any of the above concerns you, then I’ve some solutions later in this post. Either way, there’s one more thing you should know about. Check out the below screenshot:

Report based on 100% of sessions, but “All Users” only accounts for 38.81% “of Total”

There’s no sampling here, but the number displayed for “All Users” in fact only contains 38.8% of sessions. This is because of the combination of there being more than 1,000,000 rows (as indicated by the yellow “high-cardinality” warning at the top of the report) and the use of a segment. This is because of the effect of those rows grouped into “(other)”, which are hidden when a segment is active. Regardless of any sampling, the numbers in the rows below will be as accurate as they would be otherwise (apart from the fact that “(other)” is missing), but the segment totals at the top end up of limited use.

So, we’ve now gone over:

  • Sampling is generally pretty accurate (+/- 2.5% in the examples above).
  • When you’re looking at small numbers in reports with a high level of sampling, you can work out how many reports they’re based on.
    • For example, 1% sampling showing 100 sessions means 1 session was the basis of the number in the report.
  • You should keep an eye out for that yellow high-cardinality warning when also using segments.

What you can do about it

Often it’s possible to recreate the key data you want in alternative ways that do not trigger sampling. Mainly this means avoiding segments and secondary dimensions. For example, if we wanted to view the session counts for the top organic landing pages, we might ordinarily use the Landing Pages report and apply a segment:

Landing Pages report with Organic Traffic segment, based on 71.27% of sessions

In the above report, I’ve simply applied a segment to the landing pages report, resulting in sampling. However, I can get the same data unsampled — in the below case, I’ve instead gone to the “Channels” report and clicked on “Organic Search” in the report:

Channels > Organic Search report, with primary dimension “Landing Page”, based on 100% of sessions

This takes me to a report where I’m only looking at organic search sessions, and I can pick a primary dimension of my choice — in this case, Landing Page. It’s worth noting, however, that this trick does not function reliably — when I replicated the same method starting from the “Source / Medium” report, I still ended up with sampling.

A similar trick applies to custom segments — if I wanted to create a segment to show me only visits to certain landing pages, I could instead write a regex advanced filter to replicate the functionality with less chance of sampling:

Lastly, there are a few more extreme solutions. Firstly, you can create duplicate views, then apply view-level filters, to replicate segment functionality (permanently for that view):

Secondly, you can use the API and Google Sheets to break up a report into smaller date ranges, then aggregate them. My colleague Tian Wang wrote about that tool here.

Lastly, there’s GA Premium, which for a not inconsiderable cost, gets you this button:

So lastly, here’s how you can avoid sampling:

  • You can construct reports differently to avoid segments or secondary dimensions and thus reduce the chance of sampling being triggered.
  • You can create duplicate views to show you subsets of your data that you’d otherwise have to view sampled.
  • You can use the GA API to request large numbers of smaller reports then aggregate them in Google Sheets.
  • For larger businesses, there’s always the option of GA Premium to receive unsampled reports.

Discussion

I hope you’ve found this post useful. I’d love to read your thoughts and suggestions in the comments below.

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PostHeaderIcon HTTPS Tops 30%: How Google Is Winning the Long War



Posted by Dr-Pete

[Estimated read time: 6 minutes]

It’s been almost two years (August 2014) since Google announced that HTTPS was a ranking signal. Speculation ran rampant, as usual, with some suggesting there was little or no benefit to switching (and possibly significant risk) while others rushed to sell customers on making the HTTPS switch. Two years later, I believe the data speaks for itself — Google is fighting, and winning, a long war.

What’s happened since?

If you only consider the impact of Google’s original HTTPS update, I understand your skepticism. Prior to the update, our 10,000-keyword tracking system (think of it as a laboratory for studying Google searches) showed that roughly 7% of page-1 Google results used the “https:” protocol. A week after the update announcement, that number had increased only slightly, to just over 8%:

The blue/purple show the before/after based on the announcement date. As you can see, the update probably rolled out over the course of a few days. Even over a 2-week period, though, the impact appears to be fairly small. This led many of us to downplay Google’s statements and ignore HTTPS for a while. The next graph is our wake-up call:

As of late June, our tracking data shows that 32.5% (almost one-third) of page-1 Google results now use the “https:” protocol. The tiny bump on the far left (above “A-14” = August 2014) is the original HTTPS algorithm update. The much larger bump in the middle is when Wikipedia switched to HTTPS. This goes to show the impact that one powerhouse can have on SERPs, but that’s a story for another time.

What does it mean?

Has Google rolled out multiple updates, rewarding HTTPS (or punishing the lack of it)? Probably not. If this two-year trend was purely a result of algorithm updates, we would expect to see a series of jumps and new plateaus. Other than the Wikipedia change and two smaller bumps, the graph clearly shows a gradual progression.

It’s possible that people are simply switching to HTTPS for their own reasons, but I strongly believe that this data suggests Google’s PR campaign is working. They’ve successfully led search marketers and site owners to believe that HTTPS will be rewarded, and this has drastically sped up the shift. An algorithm update is risky and can cause collateral damage. Convincing us that change is for our own good is risk-free for Google. Again, Google is fighting the long war.

Is our data accurate?

Of course, our tracking set is just one sample of search data. The trendline is interesting, but it’s possible that our keywords are overstating the prevalence of HTTPS results. I presented a number of roughly 30% at SMX Advanced in mid-June. Later that same day, Google’s Gary Illyes called me out and confirmed that number:

Gary did not give an exact figure, but essentially gave a nod to the number, suggesting that we’re in the general ballpark. A follow-up tweet confirms this interpretation:

This is as close to confirmation as we can reasonably expect, so let’s assume we showed up to the right ballgame and our tickets aren’t counterfeit.

Why does 30% matter?

Ok, so about one-third of results use HTTPS. Simple arithmetic says that two-thirds don’t. Projecting the trend forward, we’ve got about a year and a half (16–17 months) before HTTPS hits 50%. So, is it time to panic? No, probably not, but here’s the piece of the puzzle you may be missing.

Google has to strike a balance. If they reward sites with HTTPS (or dock sites without it) when very few sites are using it, then they risk a lot of collateral damage to good sites that just haven’t made the switch. If, on the other hand, they wait until most sites have switched, a reward is moot. If 100% of sites are on HTTPS and they reward those sites (or dock the 0% without it), nothing happens. They also have to be careful not to set the reward too high, or sites might switch simply to game the system, but not too low, or no one will care. However I feel about Google on any given day, I acknowledge that their job isn’t easy.

If rewarding HTTPS too heavily when adoption is low is risky and rewarding it when adoption is too high is pointless, then, naturally, the perfect time to strike is somewhere in the middle. At 30% adoption, we’re starting to edge into that middle territory. When adoption hits something like 50–60%, I suspect it will make sense for Google to turn up the algorithmic volume on HTTPS.

At the same time, Google has to make sure that most of the major, trusted sites have switched. As of this writing, 4 of the top 5 sites in our tracking data are running on HTTPS (Wikipedia, Amazon, Facebook, and YouTube) with the only straggler being #5, Yelp. The top 5 sites in our tracking account for just over 12% of page-1 results, which is a big bit of real estate for only 5 sites.

Of the top 20 sites in our tracking data, only 7 have gone full HTTPS. That’s 35%, which is pretty close to our overall numbers across all sites. If Google can convince most of those sites to switch, they’ll have covered quite a bit of ground. Focusing on big players and convincing them to switch puts pressure on smaller sites.

In many ways, Google has already been successful. Even without a major, algorithmic HTTPS boost, sites continue to make the switch. As the number climbs, though, the odds of a larger boost increase. I suspect the war is going to be over sooner than the trendline suggests.

What are the risks?

Am I telling you to make the switch? No. While I think there are good reasons to move to HTTPS for some sites and I think most of Google’s motives are sincere on this subject, I also believe Google has been irresponsible about downplaying the risks.

Any major change to sitewide URLs is risky, especially for large sites. If you weigh the time, money, and risk of the switch against what is still a small algorithmic boost, I think it’s a tough sell in many cases. These risks are not theoretical — back in May, Wired.com wrote up the many problems they’ve encountered during their HTTPS switch, a switch that they’ve since paused to reconsider.

Like any major, sitewide change, you have to consider the broader business case, costs, and benefits. I suspect that pressure from Google will increase, especially as adoption increases, and that we’re within a year of a tipping point where half of page-1 results will be running on HTTPS. Be aware of how the adoption rate is moving in your own industry and be alert, because I suspect we could see another HTTPS algorithm update in the next 6–12 months.

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