mardi 7 août 2018
lundi 6 août 2018
Take the 2018 Moz Local Search Marketing Industry Survey
Posted by MiriamEllis
Local search marketing is a dynamic and exciting discipline, but like many digital professions, it can be a bit isolating. You may find yourself running into questions that don't have a ready answer, things like...
- What sort of benchmarks should I be measuring my daily work by?
- Do my clients’ needs align with what my colleagues are seeing?
- Am I over/undervaluing the role of Google in my future work?
Here’s a chance to find out what your peers are observing and doing on a day-to-day basis.
The Moz Local Search Marketing Industry Survey will dive into job descriptions, industries served, most effective tactics, tool usage, and the non-stop growth of Google’s local features. We'll even touch on how folks may have been impacted by the recent August 1 algorithm update, if at all. In-house local SEOs, agency local SEOs, and other digital marketers are all welcome! All participants will be entered into a drawing for a $100 Amazon gift card. The winner will be notified on 8/27/18.
Give just 5 minutes of your time and you’ll get insights and quotable statistics back when we publish the survey results. Be sure to participate by 8/24/2018. We sincerely appreciate your contributions!
Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!
vendredi 3 août 2018
Calculated Fields in Google Data Studio - Whiteboard Friday
Posted by DiTomaso
Google Data Studio is a powerful tool to have in your SEO kit. Knowing how to get the most out of its power begins with understanding how to use calculated fields to apply good old-fashioned math to your data. In this week's Whiteboard Friday, we're delighted to welcome guest host Dana DiTomaso as she takes us through how to use calculated fields in Google Data Studio to uncover more value in your data and improve your reports.
Click on the whiteboard image above to open a high-resolution version in a new tab!
Video Transcription
Hi, Moz fans. I'm Dana DiTomaso, President and partner at Kick Point, and we love Google Data Studio at Kick Point. You may not love Google Data Studio yet, but after you watch this I think you probably will.
One of the first things that you think about Google Data Studio is: Why would I use this? It's just charts. It's the same thing I can get in Analytics or a billion other dashboarding tools out there. But one of the things that I really like about Google Data Studio is math. You can do lots of different stuff in Data Studio, and I'm going to go through four of the basic types in Data Studio and then how you can use that to improve your reports, just as you sort of dip your toes into the Google Data Studio pool. What I've done here is I have written out a lot of the formulas that you're going to be using.
The types
It's a lot of obviously written out formulas, but when you get into Data Studio, you should be able to type these in and they'll work. Let's start at the beginning with the types.
- Basic math. This is pretty obvious. 1 + 1 = 2. Phone calls plus emails equals this, for example. You can add together different fields.
- Transforms. Let's say people are really bad at writing some things upper case and some things lower case. You have a problem with URLs being written a couple of different ways. You can use a transform to transform upper case into lower case. That's pretty nice.
- Formulas. Formulas is where you're saying only show this subset of the data. Or how often does this happen? That could be things like the Count function, so count how many times this occurs, for example, and present that as a totally separate metric, which can be really useful for things like when you want to count the number of times an event occurs and then compare that against something else. It can just pull out that kind of data.
- Logic. This is the more complex one. If X, then Y. If this happens, then that's going to happen. There's a lot of really complex stuff in there. But if you're just getting started, start with this, and then look at the Google Data Studio documentation. You'll find some cooler stuff in there.
1. Basic math
Here are some examples of how we use this in our Google Data Studio dashboards. So basic math, one of the things that a lot of people care about is: Are people getting in touch with me?
This is the basics of the reason why we do marketing. Are people getting in touch? So, for example, you can do some basic math and say, "All right. So I know on our website in Google Tag Manager, we have a trigger that fires whenever somebody taps or clicks a MailTo link on the site." In addition to that, we're tracking how many people submit a form, as you should.
Instead of reporting these separately, really they're kind of the same thing. They're emailing one way or the other. Why don't we just submit them as one metric? So in that case, you can say grab all the mail to form completions and then grab all the form goal completions, and now you have a total email requests or total requests or whatever you might want to call it. You can do the same thing where it's like, well, phone calls and emails, does it really matter if they're in separate buckets?
Just put them all in one. The same thing with the basic math. Just add it all together and then you've got one total metric you can present to the client. Here's how much money we made for you. Boom. That's a nice one. The next thing — I'm just going to flip over here — is formulas.
2. Formulas
Okay, so formulas, one of the things that I really like doing is looking at your Google Search Console data. This is in Data Studio. You're going to use Search Console for this, which is a nice data source. We all know Search Console data is not necessarily 100% accurate, but there's always lots of keyword treasure in there to be found if it's easy to find, which the Search Console interface isn't super great.
So you can make a report in Data Studio and say regex match, and so don't be afraid of regex. I think everyone should learn it. But if you're not super familiar with it, this is a really easy way to do it. Say, okay, every time a keyword contains why, how, can, what, for example, then those are question searches. You may change it to whatever makes sense for you.
But this is just pulling out that subset of data. Then you can see, so if these are question searches, do we have content that answers that question? No. Maybe this is something we need to think about. Or we're getting impressions for this. You could filter it and say only show questions searches where our average rank is below 20. Maybe if we improve this content, this is a featured snippet opportunity for us, for example. That's a real gold mine of data you can play around with.
3. Transforms
The third one is transforms. As I mentioned earlier, this is a really nice way to take Facebook, for example. We had a client who had Facebook in all upper case and Facebook in title case and Facebook in lower case in their sources and mediums, because they were very casual with how they used their UTM codes. We just standardized them all to go to lower, and those are nice text transforms that you can do.
It just makes things look a little bit nicer. I do recommend doing some of this, especially if you have messy data.
4. Logic
Then the big one here. This is logic, and I'm just going to toss over here for a second. Now logic has a lot of different components. What I'm showing you right now is a case when else end transform or logic. We use this to tidy up bad channel data.
So that client that I mentioned, who was just super casual with their UTM tags and they would just put in any old stuff, I think they had retargeting ads as a medium. You can set up channels and whatnot in Google Analytics. But I mean, really, when it comes down to it, not everybody is great at following the rules for UTMs that you've set up. Stuff happens.
It's okay. You can fix it in Data Studio. Especially if you open up Google Analytics and you see that you have this other channel, which I'm sure when we've inherited an Analytics account, we take a look at it, and there's this channel, and it's just a big bag of crap.
You can go in there and turn that into real, useful, actual channel data that matches up with where it should go. What I've got here is a really simple example. This could go on for lines and line and lines. I've just included two lines because this whiteboard is only so big.
So you start off by saying case. It is the case when, is the idea when, and then the first line here is source equals direct and medium equals not set or medium none, then direct. So I'm saying, okay, so this is the basics of how direct traffic happens.
If the source is direct and the medium is not set or the medium is none, like if I have no data whatsoever, now it's direct traffic. Great, that's basically what Google Analytics does. Nothing fancy is going on here. Now here's the next thing. In this case, I'm saying now I'm combining a regex match, which we talked about up here, with the case, and so now what I'm saying is when regex match medium, and then I've got this here.
Don't be scared of this. I know it's regex and maybe you're not super comfortable with it, but this is pretty elementary stuff, and once you do this, you will feel like a data wizard, I guarantee. The first time I did this I stood up from my computer and said "Yes" the first time it worked. Just play with it. It's going to be awesome. So you've got a little ... what's the thing called? You've got a little up arrow thingy there, very bad mediums dollar sign.
What this is saying is that if you've got anything in there that's sort of a weird medium, just write out all the crud that people have put in there over the years, all the weird mediums that totally don't make any sense at all. Just put it all in there and then you can toss it in a bucket say called paid social. You can do the same thing with referral traffic. Or, for example, this is really useful if a client is saying, "Well, I want to know how this set of affiliate traffic compares to say this set of affiliate traffic," then you can separate these out into different buckets.
This isn't just for channel data. I've done this, for example, where we were looking at social data and we were comparing NFL teams as an example for another tool, Rival IQ. What I said was, okay, so these teams here are in the AFC East, and these teams are in the AFC West. If I've screwed up and I said AFC East and West, please don't get mad at me in the comments. I promise I play fantasy football. I just don't remember right now.
But you can combine different areas. This is great for things like sales regions, for example. So North America equals Canada plus the USA plus Mexico, if you're feeling generous. This is NAFTA politics. It really depends on what you want to do with those sales regions and how your data, what is meaningful for you. That's the most important thing about this is that you can change this data to be whatever you need it to be to make that reporting so much easier for you.
I mean, Else then, we don't know if this might actually output. I haven't tried this myself. If it does, please leave a comment and let me know.
Then you end up with an End. When you're in Data Studio, when you're making these calculated formulas, you'll see right away whether or not it works or not. Just keep trying until you see it happen.
One of the great things about Data Studio is that if it's right, you'll see these types of colors, and I've used different color whiteboard markers to indicate how it should look. If you see red where you should be seeing black or green where you should be seeing black, for example, then you know you've typed in something wrong in your formula. For me, typically I find it's a misplaced bracket. Just keep an eye on that.
Have fun with Data Studio. One of the great things too is that you can't mess up your original data when doing calculated fields, so you can go hog wild and it's not going to mess with the original data. I hope you have a great time in Data Studio. Tell me what you've done in the comments, please. Thank you.
Video transcription by Speechpad.com
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jeudi 2 août 2018
mercredi 1 août 2018
Rewriting the Beginner's Guide to SEO, Chapter 3: Keyword Research
Posted by BritneyMuller
Welcome to the draft of Chapter Three of the new and improved Beginner's Guide to SEO! So far you've been generous and energizing with your feedback for our outline, Chapter One, and Chapter Two. We're asking for a little more of your time as we debut the our third chapter on keyword research. Please let us know what you think in the comments!
Chapter 3: Keyword Research
Understand what your audience wants to find.
Now that you’ve learned how to show up in search results, let’s determine which strategic keywords to target in your website’s content, and how to craft that content to satisfy both users and search engines.
The power of keyword research lies in better understanding your target market and how they are searching for your content, services, or products.
Keyword research provides you with specific search data that can help you answer questions like:
- What are people searching for?
- How many people are searching for it?
- In what format do they want that information?
In this chapter, you'll get tools and strategies for uncovering that information, as well as learn tactics that'll help you avoid keyword research foibles and build strong content. Once you uncover how your target audience is searching for your content, you begin to uncover a whole new world of strategic SEO!
What terms are people searching for?
You may know what you do, but how do people search for the product, service, or information you provide? Answering this question is a crucial first step in the keyword research process.
Discovering keywords
You likely have a few keywords in mind that you would like to rank for. These will be things like your products, services, or other topics your website addresses, and they are great seed keywords for your research, so start there! You can enter those keywords into a keyword research tool to discover average monthly search volume and similar keywords. We’ll get into search volume in greater depth in the next section, but during the discovery phase, it can help you determine which variations of your keywords are most popular amongst searchers.
Once you enter in your seed keywords into a keyword research tool, you will begin to discover other keywords, common questions, and topics for your content that you might have otherwise missed.
Let’s use the example of a florist that specializes in weddings.
Typing “wedding” and “florist” into a keyword research tool, you may discover highly relevant, highly searched for related terms such as:
- Wedding bouquets
- Bridal flowers
- Wedding flower shop
In the process of discovering relevant keywords for your content, you will likely notice that the search volume of those keywords varies greatly. While you definitely want to target terms that your audience is searching for, in some cases, it may be more advantageous to target terms with lower search volume because they're far less competitive.
Since both high- and low-competition keywords can be advantageous for your website, learning more about search volume can help you prioritize keywords and pick the ones that will give your website the biggest strategic advantage.
Pro tip: Diversify!
It’s important to note that entire websites don’t rank for keywords, pages do. With big brands, we often see the homepage ranking for many keywords, but for most websites, this isn’t usually the case. Many websites receive more organic traffic to pages other than the homepage, which is why it’s so important to diversify your website’s pages by optimizing each for uniquely valuable keywords.
How often are those terms searched?
Uncovering search volume
The higher the search volume for a given keyword or keyword phrase, the more work is typically required to achieve higher rankings. This is often referred to as keyword difficulty and occasionally incorporates SERP features; for example, if many SERP features (like featured snippets, knowledge graph, carousels, etc) are clogging up a keyword’s result page, difficulty will increase. Big brands often take up the top 10 results for high-volume keywords, so if you’re just starting out on the web and going after the same keywords, the uphill battle for ranking can take years of effort.
Typically, the higher the search volume, the greater the competition and effort required to achieve organic ranking success. Go too low, though, and you risk not drawing any searchers to your site. In many cases, it may be most advantageous to target highly specific, lower competition search terms. In SEO, we call those long-tail keywords.
Understanding the long tail
It would be great to rank #1 for the keyword "shoes"... or would it?
It's wonderful to deal with keywords that have 50,000 searches a month, or even 5,000 searches a month, but in reality, these popular search terms only make up a fraction of all searches performed on the web. In fact, keywords with very high search volumes may even indicate ambiguous intent, which, if you target these terms, it could put you at risk for drawing visitors to your site whose goals don't match the content your page provides.
Does the searcher want to know the nutritional value of pizza? Order a pizza? Find a restaurant to take their family? Google doesn’t know, so they offer these features to help you refine. Targeting “pizza” means that you’re likely casting too wide a net.
The remaining 75% lie in the “chunky middle” and "long tail" of search.
Don’t underestimate these less popular keywords. Long tail keywords with lower search volume often convert better, because searchers are more specific and intentional in their searches. For example, a person searching for "shoes" is probably just browsing. Whereas, someone searching for "best price red womens size 7 running shoe,” practically has their wallet out!
Pro tip: Questions are SEO gold!
Discovering what questions people are asking in your space, and adding those questions and their answers to an FAQ page, can yield incredible organic traffic for your website.
Getting strategic with search volume
Now that you’ve discovered relevant search terms for your site and their corresponding search volumes, you can get even more strategic by looking at your competitors and figuring out how searches might differ by season or location.
Keywords by competitor
You’ll likely compile a lot of keywords. How do you know which to tackle first? It could be a good idea to prioritize high-volume keywords that your competitors are not currently ranking for. On the flip side, you could also see which keywords from your list your competitors are already ranking for and prioritize those. The former is great when you want to take advantage of your competitors’ missed opportunities, while the latter is an aggressive strategy that sets you up to compete for keywords your competitors are already performing well for.
Keywords by season
Knowing about seasonal trends can be advantageous in setting a content strategy. For example, if you know that “christmas box” starts to spike in October through December in the United Kingdom, you can prepare content months in advance and give it a big push around those months.
Keywords by region
You can more strategically target a specific location by narrowing down your keyword research to specific towns, counties, or states in the Google Keyword Planner, or evaluate "interest by subregion" in Google Trends. Geo-specific research can help make your content more relevant to your target audience. For example, you might find out that in Texas, the preferred term for a large truck is “big rig,” while in New York, “tractor trailer” is the preferred terminology.
Which format best suits the searcher's intent?
In Chapter 2, we learned about SERP features. That background is going to help us understand how searchers want to consume information for a particular keyword. The format in which Google chooses to display search results depends on intent, and every query has a unique one. While there are thousands of of possible search types, there are five major categories to be aware of:
1. Informational queries: The searcher needs information, such as the name of a band or the height of the Empire State Building.
3. Transactional queries: The searcher wants to do something, such as buy a plane ticket or listen to a song.
4. Commercial investigation: The searcher wants to compare products and find the best one for their specific needs.
5. Local queries: The searcher wants to find something locally, such as a nearby coffee shop, doctor, or music venue.
An important step in the keyword research process is surveying the SERP landscape for the keyword you want to target in order to get a better gauge of searcher intent. If you want to know what type of content your target audience wants, look to the SERPs!
Google has closely evaluated the behavior of trillions of searches in an attempt to provide the most desired content for each specific keyword search.
Take the search “dresses,” for example:
By the shopping carousel, you can infer that Google has determined many people who search for “dresses” want to shop for dresses online.
There is also a Local Pack feature for this keyword, indicating Google’s desire to help searchers who may be looking for local dress retailers.
If the query is ambiguous, Google will also sometimes include the “refine by” feature to help searchers specify what they’re looking for further. By doing so, the search engine can provide results that better help the searcher accomplish their task.
Google has a wide array of result types it can serve up depending on the query, so if you’re going to target a keyword, look to the SERP to understand what type of content you need to create.
Tools for determining the value of a keyword
How much value would a keyword add to your website? These tools can help you answer that question, so they’d make great additions to your keyword research arsenal:
- Moz Keyword Explorer - Our own Moz Keyword Explorer tool extracts accurate search volume data, keyword difficulty, and keyword opportunity metrics by using live clickstream data. To learn more about how we're producing our keyword data, check out Announcing Keyword Explorer.
- Google Keyword Planner - Google's AdWords Keyword Planner has historically been the most common starting point for SEO keyword research. However, Keyword Planner does restrict search volume data by lumping keywords together into large search volume range buckets. To learn more, check out Google Keyword Planner’s Dirty Secrets.
- Google Trends - Google’s keyword trend tool is great for finding seasonal keyword fluctuations. For example, “funny halloween costume ideas” will peak in the weeks before Halloween.
- AnswerThePublic - This free tool populates commonly searched for questions around a specific keyword. Bonus! You can use this tool in tandem with another free tool, Keywords Everywhere, to prioritize ATP’s suggestions by search volume.
- SpyFu Keyword Research Tool - Provides some really neat competitive keyword data.
Download our free keyword research template!
Keyword research can yield a ton of data. Stay organized by downloading our free keyword research template. You can customize the template to fit your unique needs (ex: remove the “Seasonal Trends” column), sort keywords by volume, and categorize by Priority Score. Happy keyword researching!
Now that you know how to uncover what your target audience is searching for and how often, it’s time to move onto the next step: crafting pages in a way that users will love and search engines can understand.
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