Posted by Dr-Pete

Summary: RankBrain represents a more advanced way of measuring relevance, built on teaching machines to discover the relationships between words. How should RankBrain change our approach to SEO and specifically to keyword research?

This story starts long before RankBrain, but the action really kicked in around May of 2013, when Google announced conversational search for desktop. At the time, voice search on desktop may have seemed like a gimmick, but in hindsight it was a signal that Google was taking natural language search seriously. Just a few months later the Hummingbird update rewrote Google’s core engine, and much of that rewrite was dedicated to dealing with natural language searches.

Why should you care about voice? For most sites, voice is still a relatively small percentage of searches, and you’ve got other priorities. Here’s the problem, illustrated by the most simplistic Google algorithm diagram I’ve ever created…

If there were two algorithms – one for text search and one for voice search – then, yes, maybe you could drag your feet. The reality, though, is that both text and voice search are powered by the same core algorithm. Every single change Google has made to adapt to natural language searches impacts every search, regardless of the source. Voice has already changed the search landscape irreversibly.

Natural language in action

You may be skeptical, and that’s understandable. So, let’s take a look at what Google is capable of, right now, in 2016. Let’s say you wanted to find the height of Seattle’s iconic Space Needle. As a seasoned searcher, you might try something short and sweet, like this…

“Space Needle height”

Google understands this question well enough to attach it to the corresponding Knowledge Graph entity and return the following:

The corresponding organic results appropriately match the informational query and are about what we’ve come to expect. Google serves this search reasonably well.

“What is the height of the Space Needle?”

Let’s try to shake off our short-form addiction and try a natural language version of the same search. I won’t repeat the screenshot, because it’s very similar, as are the organic results. In 2016, Google understands that these two searches are essentially the same.

“How tall is the Seattle Space Needle in meters?”

Let’s try another variant, switching the “What” question for a “How” question, adding a location, and giving it a metric twist. Here’s what we get back:

Google understands the question and returns the proper units. While the organic results vary a bit on this one, reflecting the form of the question, the matches remain solid. Natural language search has come a long way.

Build great concepts!

This all may be a bit alarming, from a keyword research perspective. Natural language searches represent potentially thousands of variants of even the simplest queries. How can we possibly operate on this scale as search marketers?

The popular notion is that we should stop targeting keywords and start targeting concepts. This approach has a certain logic. The searches above share a general notion of “tallness,” which might look something like this:

“Tall” and “height” are fairly synonymous, words like “size” and “big” are highly related, and units like “feet” and “meters” round out this concept. In theory, this makes perfect sense.

In practice, the advice to target concepts is a bit too much like saying “build great content.” It’s a good goal, in theory, but it’s simply not actionable. How do we build great concepts? We all intuitively understand what a concept is, but how does this translate into specific search marketing tactics?

There’s an even bigger problem, and I can illustrate it with one box:

Ok, one box, a logo, and two buttons. At the end of the day, you can’t type a concept. Search users, whether they’re typing or speaking, have to put words into that box. So, how do concepts, which we all agree exist and are useful, translate into keywords, which I hope we can all agree are still unavoidably necessary?

Language in action, part 2

We need to take a side path on this journey for a moment. Part of rethinking keyword research is understanding that we’re no longer bound by an exact-match world. This isn’t a bad situation to be in, just a complex one. I’d like to tell a story with examples, showing just how far Google has come in understanding the ways that different keywords relate to each other…

Plurals (“scarf” & “proxies”)

While we all know the dangers of keyword stuffing, it originated out of a certain necessity. Search engines simply weren’t capable of equating even simple terms, like plurals. Those days are long behind us. Google understands, for example, that a search for “scarf” should also return results for “scarves”:

In these examples, I’ll be using Google’s own highlighting (the bold text; I’ve added the green boxes) to show where Google seems to understand equivalence or related concepts. Of course, Google’s core relevance engine and highlighting engine are not exactly the same, but I think it’s safe to say that the latter is a useful window into the former.

Google is also fully capable of understanding the reverse. Let’s say, for example, that a “friend” of mine wants to buy proxy IPs. He might search for “proxies”:

Google can easily understand even irregular plurals in both directions.

Stemming (“ballroom dancer”)

Plurals are relatively easy. Let’s step it up a little. Another frequent problem in search is dealing with stemming, which relates to root words and the forms they can take, such as “run” vs. “running.” Here’s a sample search for “ballroom dancer”:

Google is perfectly capable of equating “dancer” to other forms of the word, including “dances,” “dance,” and “dancing.” Once again, keyword stuffing is at best outdated thinking.

Abbreviations (“Dr. Who”)

Can Google recognize common abbreviations? Let’s try a search for our second-favorite doctor (hint, hint, wink), “Dr. Who”:

Google easily makes the connection between “Dr.” and “Doctor.” Interestingly, none of the organic titles or snippets I see on page one contain the word “Dr.”

Acronyms (“SNL skits” & “TARDIS”)

How about acronyms? Here’s a search for “SNL skits”:

Google has no problem interpreting “SNL” as equivalent to “Saturday Night Live.” Interestingly, they also understand that “skits” is synonymous with “sketches.” What if we spell out an acronym that isn’t usually spelled out, such as “Time And Relative Dimension In Space”?

Here, Google is happy to tell us “Hey, nerd, just say ‘TARDIS’ like everyone else.” The six-letter acronym is interchangeable with even the much longer search string.

Acronyms+ (“NJ DMV”)

This is where things get interesting. Here’s a search for “NJ DMV.” Look closely:

Not surprisingly, Google understands that “NJ” equals “New Jersey.” There’s a problem with this search, though – New Jersey doesn’t call their motor vehicle office the DMV, they call it the MVC (Motor Vehicle Commission). Google understands not only how to expand an acronym, but that the acronyms DMV and MVC are conceptually equivalent.

Synonyms (“discount airfare”)

The flip-side of no longer being confined to exact-match keywords is that you might just be finding yourself faced with a lot more competition for any given keyword. Let’s look at a competitive, commercial query, such as “discount airfare”:

Here, “discount airfare” gets matched to “airfare deals,” “discount tickets,” and “cheapest flights,” with even more variations on the rest of page one.

Synonyms+ (“upscale department stores”)

Wait, it gets worse. Google can go beyond traditional synonyms. Consider this search for “upscale department stores” (run from my home-base in the Chicago suburbs):

Answers (“Doctor Who villains”)

We’ve moved from simply synonyms to a world of answers. Here’s another example, a search for “Doctor Who villains”:

It’s a parlor trick to tell you that “villains” is synonymous with “monsters” and “enemies.” What you really want to know is that Doctor Who’s rogue’s gallery includes Daleks, Cybermen, and Weeping Angels. Google can make this connection.

These aren’t just exceptions

It’s easy to cherry-pick examples, but are these edge cases or the new normal? I ran an analysis on 10,000 keywords (page one only) and found that only 57% of results had the search phrase in both the title and snippet. I used a pretty forgiving match (allowing for plurals, for example) and the keyword set in question is mostly shorter terms, not long-tail queries. I also allowed the terms to occur in any order. Keep in mind, too, that display snippets aren’t always META descriptions – they’re chosen by Google to be good matches.

All of this is to say that, even with a fairly forgiving methodology and a loose definition of a “match,” just over half of page-one results in my data set matched the search query. The examples above are not outliers – they are our immediate, unavoidable SEO future.

The Algorithm is learning

This deep into the article, you may be wondering what any of this has to do with RankBrain. There’s been a lot of speculation around RankBrain, and so I’m going to do my best to work from the facts as we understand them. You’re going to need some essential background information…

What, exactly, is deep learning?

First, the one thing we all seem to be able to agree on is that RankBrain uses machine learning, thus the “brain” part. Specifically, RankBrain uses “deep learning.” So, what is deep learning? According to Wikipedia:

Deep learning is a branch of machine learning based on a set of algorithms that attempt to model high-level abstractions in data by using a deep graph with multiple processing layers, composed of multiple linear and non-linear transformations.

Crystal clear, right? To understand deep learning and the state of modern machine learning, you have to understand neural networks. Let’s start with a simple neural network, the kind that were popular in the early 1990s:

Neural networks were built on a basic understanding of the human brain as a system of “nodes” (neurons) and connections between those nodes. At scale, the human brain is capable of learning incredibly complex ideas using this system of nodes and connections.

So, how do we put this model to work? Let’s start with what’s known as “supervised learning.” In a neural network like this, we have a known set of inputs and a desired set of outputs. Given a certain X, we want to teach the system to return Y. We use these inputs and outputs to train the system, gradually weighting the connections. The hidden layer adds computational complexity, giving the machine enough connections to encode interesting data.

Training itself uses methods that are cousins of linear regression (at the risk of oversimplification). Over a large set of inputs and output, we want to minimize the error of our model. In some cases, we work backward from the output(s) back to the input(s), in much the same way you might work a difficult paper maze from the finish back to the start.

Why go to all this trouble? If we know the inputs and outputs (sticking just to supervised learning, to keep this simple), why don’t we just have a lookup table? If X, then Y – simple. What happens when we get an input that isn’t in the table? The system fails. The magic of neural networks is that, if the system is properly trained, it can return outputs for completely new inputs.

To make a very long story only medium-long, these simple neural networks were interesting playthings, but weren’t capable of solving many complex problems. So, we put them aside. Then, the inevitable happened – computing power increased exponentially and got cheaper (thanks, Gordon Moore!). Specifically, we invented the GPU. You might think of the GPU as something built for gamers, but it is, in essence, a very powerful math machine.

At some point, simple neural networks scaled up massively, and I mean massively – on the order of 1,000,000X larger. These new machines were able to perform much more interesting tasks, and a new age of neural networks was born. These new machines required more complex methods, and thus, at the risk of oversimplifying a very complex topic, deep learning was born.

How does Google use deep learning?

Fortunately, we know a bit more about RankBrain. In Steven Levy’s excellent article about Google’s machine-learning ambitions, he quotes the following from Jeff Dean, head of the broader Google Brain group…

By early 2014, Google’s machine learning masters believed [Amit’s approach] should change. “We had a series of discussions with the ranking team,” says Dean. “We said we should at least try this and see, is there any gain to be had.” The experiment his team had in mind turned out to be central to search: how well a document in the ranking matches a query (as measured by whether the user clicks on it). “We sort of just said, let’s try to compute this extra score from the neural net and see if that’s a useful score.”

Amit Singhal, the head of Google’s Search team until early 2016, pioneered the heuristic approach – what we might call the “ranking factors.” Machine learning (ML) advocates at Google eventually were able to convince the team to test ML in a ranking context. By all accounts, that experiment went very well and the score was indeed useful.

It’s also worth noting that Amit, who was reported to be skeptical of using ML in organic search, left Google and was replaced by John Giannandrea, who was instrumental in many ML projects at Google. I won’t speculate on Amit’s motivations, but the shift in leadership to a strong ML advocate clearly implies that Google considered the RankBrain experiment a success.

Of course, it begs the question: How exactly are ML and deep learning in play in organic search? Google teaches a deep learning course on Udacity, and I was intrigued to find this screenshot in a quiz. The quiz asked how Google might use deep learning in rankings, and this was the answer:

When we train an ML model, the “classifier” is essentially the resulting decision machine. In this case, that classifier takes in a search term and web page as inputs and decides how relevant they are to each other.

Two things are worth nothing in this deceptively simple screenshot. First, ML is being used as a relevance engine. I think it’s safe to say that the quiz is not entirely hypothetical. Second, notice the query and the matching page. The query is “Udacity deep learning”, but the matching result title contains the related phrases “machine learning” and “supervised learning.” This is starting to look like some of the examples we saw earlier.

Another resource we have is the original Bloomberg article about RankBrain, which is still one of the more comprehensive pieces on the subject. The article quotes senior Google research scientist Greg Corrado and makes the following very specific claim:

RankBrain uses artificial intelligence to embed vast amounts of written language into mathematical entities – called vectors – that the computer can understand. If RankBrain sees a word or phrase it isn’t familiar with, the machine can make a guess as to what words or phrases might have a similar meaning and filter the result accordingly, making it more effective at handling never-before-seen search queries.

Again, RankBrain is being called out as essentially a relevance engine, a machine for better understanding the similarities and relationships between words. What are these vectors the article mentions, though? In the general sense, vectors are a mathematical concept – a point in space with both direction and magnitude. Vectors are a way of encoding complex information.

Thankfully, we have another clue, from Google’s public ML project, TensorFlow. One of Google’s side projects is a library called Word2Vec that, as the name implies, uses ML to convert words into vectors. Traditional methods of encoding words for information retrieval can deal with simple problems like pluralization and stemming, but have little or no sense of relationships. Word2Vec and similar models are capable of learning relationships like the examples below (Source: Tensorflow.org, ©2016 Google):

Here, Word2Vec has learned that the relationship between man and woman is the same as the relationship between king and queen (encoded in the direction of the vector). Similarly, the relationship between the verb tense walking to walked is the same as the relationship between swimming and swam. More importantly, these rules didn’t need to be specified. The machine learned them by studying large collections of real words in context.

Google’s actual algorithms are almost certainly more complex than the publicly available Word2Vec library, and researchers have combined vector-based approaches with other approaches, such as the more familiar LDA (latent dirichlet allocation), but it seems very likely that an approach like this is in play in RankBrain.

RankBrain is NOT query translation

It’s easy to mistakenly jump to the conclusion that RankBrain simply translates unfamiliar queries into more familiar ones, or long queries into short queries. This is not the case. RankBrain seems to operate in real-time and can compare multiple versions of a search phrase at once.

If I mistakenly type a search like “Benedict Crumblebatch,” Google will tell me this:

In this case, Google has tried to interpret my intent and has replaced my query with what it thinks is a better version. This is query translation. In this case, all of the results match the translated query and it overrules my original search.

Revisiting an example from above, if I search for “scarf,” I can get back matches on both “scarf” and “scarves” (even in the same result):

Google is not translating “scarf” –> “scarves” and then returning matches on the new term. Google is applying a powerful relevance engine that recognizes these matches in real-time.

Are we sure it’s RankBrain?

Let me be clear on one thing – relevance is a very complex process, and it’s hard to know for sure where traditional information retrieval methods end and RankBrain begins. I can’t say with certainty that all of the examples I showed previously represent RankBrain in action.

However, there is one more piece of evidence. Remember the “NJ DMV” example? Google was able to understand that “DMV” (Department of Motor Vehicles) and “MVC” (Motor Vehicle Commission) are equivalent concepts in New Jersey.

Our data science team, led by Matt Peters, put together an ML prototype that uses a method similar to Word2Vec. If you input search terms into this tool, it looks at the corresponding Google results and calculates the similarity between those results and the original query:

This screenshot has been edited, but the data is real. What the tool is saying is that a page with the title “State of New Jersey – Motor Vehicle Commission” is a good match (93%, although the system is a little forgiving) for “NJ DMV.” The fact that we can train an ML system to perform this task doesn’t prove RankBrain does it, but it does at least show that it is well within Google’s ML capabilities.

When did RankBrain roll out?

Please note that RankBrain is often tied to the announcement date in October of 2015, but that article also says that RankBrain was in play “for the past few months.” Steven Levy’s article on ML in Google gives a date of April 2015 for the rollout, and we believe that timeline is accurate. RankBrain has probably been in play for at least 1 1/2 years at the time of this writing.

How do we adapt to RankBrain?

In a world where Google can understand stemming, synonyms, and even answers, how do we approach keyword research? Let’s go back to our Space Needle example. I’m going to use Moz’s Keyword Explorer as a backdrop for the rest of this discussion. Let’s say I fire up my trusty keyword research tool and enter the phrase “space needle height”:

Even out of the gate, we’ve got 1,000 keywords to deal with, many of which are fairly similar. How do we go about targeting these 1,000 variations?

Option 1 is to write 1,000 pages, each laser-targeted at a single phrase. We know, practically, that either this is going to be a huge amount of work or is going to lead to thin content. Sites filled with templated pages that only vary by a few keywords are a lousy user experience and prime bait for Google’s Panda algorithm.

Option 2 is to take as many of these phrases as possible and just stuff them into a single paragraph. I’ve done this for you, and here’s the kind of result you can expect:

SPACE NEEDLE HEIGHT
The Space Needle height (Seattle) is 605 feet. The Space Needle height in stories is just over 60. It’s interesting to note that the Space Needle height comparison to the Empire State Building is about half as high. In contrast, the Seattle Space Needle height comparison to Chicago’s Willis Tower is only about one-third the height.

The bolded phrases are my target phrases. I hope we can all agree that this isn’t optimal content crafting if our goal is to convince our audience that we’re a credible source of information.

I propose a third option. You may have noticed a pulldown in Keyword Explorer for [Group Keywords]. This does exactly what it sounds like it does. Let’s take all of these very similar keywords (and you could do this by hand as well, if you’re willing to put in the time) and try to group them. We end up with something like this:

The system has tried to bucket the keywords into broader, more useful groups, allowing us to ignore some of the minor variants. So, let’s pick three groups from this list:

1. “space needle height”
2. “space needle height in stories”
3. “space needle how tall”

What if we chose representative, natural language phrases within each of these groups? Think of them as exemplars of the group. We might pick something like this:

1. “height of the Space Needle”
2. “Space Needle is ___ stories”
3. “How tall is the Space Needle?”

Now, let’s craft a paragraph around these more natural, diverse phrases:

HOW TALL IS THE SPACE NEEDLE?
The height of the Space Needle in Seattle, Washington is 605 ft. (184 m), including the antenna. Interestingly, while the Space Needle is approximately 60 stories tall, it only occupies 6 floors, with most of the tower being structural. While it was once the tallest building in Seattle, the Space Needle now ranks only 7th.

Not only have we written a paragraph that might actually be valuable to humans, but we’ve covered our three target phrases and even had room for a fourth (“tallest building in Seattle”). What’s more, each of these phrases represent groups of dozens or hundreds of similar keywords. By writing to the groups or broader concepts instead of narrowly targeted phrases, we’re able to cover many keyword variants efficiently.

3 Gs: Gather, Group, Generate

I’ve taken to calling this approach to keyword research the 3 Gs, and it goes likes this:

1. Gather keywords
2. Group keywords into clusters
3. Generate exemplars

Another way to think of this process is that we’re grouping keywords into concepts, and then converting each concept back into a representative keyword/phrase: Keyword –> Concept –> Keyword*. The result is a specific search phrase to target, but that phrase represents potentially dozens or hundreds of similar keywords.

Let’s work through another example, but one with commercial intent. Pretend you’re working in the Seattle apartment space and are looking to write an article about rental costs. Just to pick a starting point, you enter “Seattle rental prices” into your keyword research tool of choice and gather your keyword list:

Naturally, we get back a list of related but sometimes very similar keywords. Even in this list, we can start to see some interesting variations (“average rent”, prices by year, mapped prices, etc.), but let’s take it to step two and group these keywords:

In a real-world keyword research scenario, we’d want to thoroughly explore all of the groups, but I’ve picked three for now that caught my eye (underlined in green). They are:

1. “Seattle average rent by neighborhood”
2. “Seattle housing prices skyrocket”
3. “cheapest Seattle apartments”

How do we go about generating an exemplar from each group? Sometimes, intuition is fine. For example, the keywords our system has grouped under #2 turn out to be a bit of an odd mix, but I really like how “skyrocket” resonates and “housing prices” is a good keyword variant, so I’ll pick a phrase. For something like #3, we may choose to just see what variation has the highest potential for traffic. In Keyword Explorer, we can simply expand that group, select the keywords, and add all of them to a list, like this:

Once the stats for the list are collected, we can take a look and see that “cheapest apartments in Seattle” has both the highest traffic volume and Keyword Potential, according to our metrics:

For the final group (“Seattle average rent by neighborhood”), I browsed the grouped keywords, and one caught my eye: “average rent downtown seattle.” I like this one because it’s specific to an actual neighborhood, although we might choose to craft content around some kind of neighborhood-by-neighborhood theme as well. What I like about trying to understand our keywords as groups/clusters is that it’s also a great process for generating content ideas.

So, let’s put some exemplars against our three groups. We might end up with something like this:

1. “average rent in downtown Seattle”
2. “Seattle housing prices are skyrocketing”
3. “cheapest apartments in Seattle”

These are all rich phrases that we can use to craft content, and they’re built on a logical framework of keyword research. Even using just this single list, our system claims these three groups represent at least 64 keyword phrases. Factoring in the long-tail, they potentially represent hundreds more.

Eventually, we may have ML tools that can take large groups of related phrases and help find the perfect exemplar. Even now, Keyword Explorer’s grouping engine is built on ML. There will come a time very soon when ML is part of our everyday work as SEOs.

There’s a fourth, unofficial G: Gap. As our British friends might say, mind the gap. The exemplars you build in this process are meant to be natural-language phrases that represent dozens of keywords, but our understanding of a concept and Google’s won’t always match, and some searches you hoped you’d rank for will fall through the cracks. It’s important to continue to monitor and track a large set of keywords. If you see that some aren’t improving, consider generating new exemplars or targeting them separately. This is an iterative process, and we still have to get our hands dirty with real searches every day.

Bonus: Keyword brainstorming

Here’s something fun to try. In Keyword Explorer, you can specifically request keyword phrases that contain none of the words in your original phrase. Why would you want to do this? It can help you find related concepts that you might not have considered.

From the [Display keyword suggestions that] pulldown, select “exclude your query terms to get broader ideas.” Here are some of the results I get on a search for “Seattle rental prices” with grouping on (I’ve edited this list a bit just to show some of the more interesting results in the space allowed):

Some of these are obvious (although still interesting), like searches that use specific neigbhorhood names (e.g. “best Capitol Hill apartments”). Some are less obvious and open up some new avenues. “Kirkland apartments under $1000” reminds us that both neighborhood and price sensitivity matter in similar searches. These are aspects we can’t ignore in our broader keyword research on this topic.

The second to the last is really interesting, IMO: “apartments near Amazon headquarters.” Being such a big employer (we know all too well, given the competition for talent in Seattle), a content focus on just apartments near Amazon’s headquarters could get a lot of traction. Finally, while it’s not the most useful topic or keyword to target, “too damn expensive” is certainly a good headline phrase to tuck away.

Why not just write for people?

If Google is really understanding natural language searches and becoming more intelligent, why don’t we just write content for people and forget about this whole process? It’s a fair question. If your choices are 2005-era keyword stuffing and thin content or writing for people, then please, for the love of all that this is holy, write for your human site users (and, by extension, search users).

There’s a problem, though, and it’s probably easier to show than tell…

Google has come a long way in their journey from a heuristic-based approach to a machine learning approach, but where we’re at in 2016 is still a long way from human language comprehension. To really be effective as SEOs, we still need to understand how this machine thinks, and where it falls short of human behavior. If you want to do truly next-level keyword research, your approach can be more human, but your process should replicate the machine’s understanding as much as possible.

I hope you’ll give the 3 Gs a try and let me know what you think. I’ll freely admit I’m biased and hope you’ll also give Keyword Explorer a try, if you haven’t yet (and if you have, test out some of the new tricks I’ve talked about).

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Posted by MiriamEllis

Two dates to know: August 4, 2010 – the day Google enabled owner responses to Google My Business reviews; November 17, 2016 – the day Moz enabled incredibly easy GMB owner response functionality in the Moz Local dashboard. Why are these noteworthy events in Local Search history?

Because reviews and owner responses are direct reputation management, free marketing, free advertising, damage control, and quality control all wrapped up in one multi-voice song about your brand.

What’s missing from the picture of this free-for-all of voices caroling sentiment about your brand? You are — the conductor! If you’re not leading the tune — from setting customer service policies, to training staff, to managing complaints, to engaging directly with consumers online — you’re giving up available reputation management controls.

Make no mistake: No brand can prevent every sour note, but with owner response functionality, you can not only retune relationships with valuable customers, but can also protect revenue by keeping those customers instead of having to invest 25x as much in obtaining new ones. Owner response mastery is, indeed, smart business.

For the past six years, since Google launched owner responses as part of its local product, I’ve been studying them and acting as a consultant to a variety of local business owners and agencies regarding effective usage of this remarkable capability. Today, in celebration of Moz Local’s support of this function, I’m going to break down the types of reviews into 5 categories and offer you my tips for skilled management. With reputation and revenue on the line, every local brand needs an intelligent strategy!

Getting up-to-speed on owner responses

During our recent launch, a Moz community member let us know he’d never heard of owner responses before, so real quick: Many review platforms give you the option, as the business owner, to respond to reviews your customers have left you. This is normally done from within your dashboard on that platform, or, in some cases, via mobile apps.

In the Moz Local dashboard, the Google My Business owner response function is a real time-saver. We alert you when new reviews come in, and you simply click the ‘reply’ link to write your response. A little form pops up in which you can type away handily:

Now let’s delve into responding to the five basic types of reviews most local brands can expect to receive.

Type 1: “I love you!”

Real-world example:

Diagnosis: This is the customer every brand wants to have: the delighted evangelist who goes to the lengths of saying that nothing else on the local scene can compare to what the business offers. Honestly, reviews like this are like beautiful greeting cards validating that your business is getting it right on all points. Pure music to your ears!

Owner response strategy:

Many business owners ask if it’s necessary to respond to positive reviews. My short answer is yes, if you wish your business to come across as courteous and engaged. Part of conducting the flow of your reputation is acknowledging customer satisfaction and thanking them for the time they invest in writing such nice things about your company. It’s just good manners.

Having said this, I’ll qualify it by mentioning scale. If your enterprise has 100+ locations which each have 100+ positive Google My Business reviews, responding to every single one may not be the best use of your resources. Prevent the appearance of ungrateful neglect by aiming for a percentage — maybe 10% — of ‘thank yous’ in response to your best reviews.

Pro tips:

• Your thanks can be brief, but avoid repetitiousness. Write a unique response each time. There are owner response profiles out there that have made me strongly suspect robots manage them, as in ‘thank you for your review’ written on 30 different responses. Avoid that.
• Remember that owner responses are content consumers read. They are, in essence, free advertising space. Don’t go over the top with this, but if a customer mentions something they love, latch onto that. In our sample review above, the owner could mention that comments like this one inspired them to bottle their hot sauce for retail sales, or they could mention that they actually just won a best-in-Bay-Area award from X publication. Think products, services, and hyperlocal/local terminology. No, don’t put the hard sell on the customer in the owner response, but use this real estate with savvy. If there’s something you think a happy customer would be excited to know, promote it in a nice, friendly way!
• Positive reviews indicate that a customer is already in a good, receptive mood. The more personable your owner response, the more of an impression your business can make, encouraging the customer to come back for more. Here, company culture, personality, and fun can shine. Your customer thinks you are special — act like it in the response.

Suggested owner response:

Hi Charley!

We were just thrilled by your review — in fact, we showed it to Chef Rosa, because the pique sauce you love is based on her grandmother’s traditional recipe brought from Puerto Rico in the 1930s. It’s the real deal, and we’re actually offering it bottled for retail now right next to the hostess stand at both our San Rafael and San Francisco locations, based on diner requests. Hint: one secret ingredient is apple cider vinegar, but that’s all we can say! We’d love to see you back soon, and Chef Rosa says, “Thank you for the lovely compliment.” ‘Best in the Bay Area’ makes us all proud!

Good Eating!

Marta Sanchez, Owner

Type 2: “My mind isn’t made up yet.”

Real-world example:

Diagnosis: A 3-star rating is the hallmark of the consumer who likes some things about your business, but isn’t totally loyal yet. They may/may not return and may/may not recommend you to others. Undecided patrons represent an exciting challenge to transform dissatisfactory aspects of your business and specific consumer sentiment, all at the same time.

Owner response strategy:

The honesty of a less-than-5-star review, when written in detail, delivers two valuable assets to your brand: it tells you where you’re hitting and where you’re missing, giving you the opportunity to improve and turn a lukewarm consumer into a loyal one.

Strategy for the owner response involves thanking for praise, accepting responsibility for faults, apologizing for disappointments, and making some kind of an offer. This offer, meant to sweeten the pitch that you hope the consumer will give your company a second chance, could be a comp or a coupon for future use, or it could simply be an explanation of how you have heard their feedback and made changes.

Pro tips:

• Express gratitude for consumer complaints — they are valuable. Do not attempt to shift blame onto anyone else, including the customer or staff members.
• Document both the positive and negative sentiment of so-so reviews and use it as your playbook for keeping what’s good and improving what isn’t excellent.
• Be sure the customer feels heard. Cite their complaints back to them. By doing so, you are demonstrating to all future potential customers that your brand is responsive to feedback.

Suggested owner response:

Dear Yesenia,

We’re so grateful to you for letting us know that our prices, staff, and in-hotel restaurants pleased you, and, I also want to express my thanks to you for mentioning that the housekeeping wasn’t exceptional. I need to hear that, and take full responsibility for the dusty room. I have been trying a variety of cleaning services this past year, with the goal of finding the best.

While I want to be sure that every guest knows we honor any requests during their stay (just dial 9 on your in-room phone), I also want to let you know that, based on your comments, I held an all-staff meeting with our current cleaning service and have issued a new 10-point cleaning checklist (including dusting all surfaces) for each housekeeper. Should you honor us with a second stay, I personally guarantee you will find your room immaculate, and I would also like to offer your party a free breakfast in the Palm Room, as you enjoyed our restaurants. Just tell them Rob sent you, and it will be our pleasure to serve you! Thank you for your valuable and honest review.

Cordially,

Rob Brown, Owner

Type 3: “There was hair in my taco…”

Real-world example:

Diagnosis: The dreaded 1-star review! The customer has a specific, legitimate complaint, and your job as the owner is to address their dissatisfaction, take responsibility, and, whenever possible, make an offer to make things right. A negative review is likely the last life preserver an unhappy customer will throw you — a last chance to earn them back with superior responsiveness. Given the cost of replacing them, rewards for the effort can be great. When a customer ‘saves you’ by making their complaints known, an adept response from you may ‘save them’ in return, earning their repeat business.

Pro tips:

• Apologize!!! Say the words, “I’m sorry, I apologize.”
• No blame shifting, no lectures — just total accountability, humility, and a willingness to learn.
• Be as honest as possible about whatever circumstance led to the customer’s bad experience, and state what you’re doing to improve that circumstance. Sometimes, the circumstances may include faults on the customer’s part. If you have to mention these in order to be honest, do so with great care and no blame, as in the sample response below.
• Negative reviews often run on for agonizing paragraphs and chapters, but your response should not. Be thorough, but concise.
• Offer something, even if it’s just a few minutes of your time on the phone, to try to make it right.
• Aim for a ‘wow’ factor — as in you want future potential customers to say, “Wow, this business really cares!” when they read the response.
• For more tips on managing negative reviews, please read Diagramming The Story of a 1 Star Review.
• Document all complaints; they are incredibly valuable both in terms of damage control and quality control. Consider doing a full review audit on a set schedule to catch emerging problems and resolve them.

Suggested owner response:

Type 4: “I’m actually your competitor.”

Real-world example:

Diagnosis: Unfortunately, fake reviews happen. They may stem from unscrupulous competitors, disgruntled past employees, or individuals with personal grudges against someone at the company. The line to walk here is whether the reviews are simply false (warranting a response + Google action) or citing such defamatory or illegal practices that you should consult with a lawyer before taking any further action. Our real-world example is of the former kind — it illustrates what a fake review might look like with sentiment that is negative but not accusing the business of criminal activity.

Pro tips:

• If research has made you aware that a review has been left by a competitor or by someone who is not a customer, that’s a violation of Google’s Review Policy.
• First, leave a brief owner response to the review (as shown in my sample response below) to alert consumers to the falsity of the review. Note: I don’t advise ‘outing’ the bad actor — it’s not professional.
• Second, follow Google’s steps for flagging the review. I suggest waiting 24 hours after doing this before moving on.
• Next, on that same page, you will see options for speaking directly with Google via phone, chat, or email. Contact Google to let them know about the fake review you have flagged. Hopefully, they will be able to rectify this for you and remove the review.
• However, if you get a rep who doesn’t seem to understand your issue, turn to the Google My Business Community, post the complete details of your scenario, and beg for a Top Contributor to help escalate your issue.
• Don’t expect a quick fix. You may have to be persistent to obtain resolution.
• But, again, please don’t take these steps if a review accuses your business of something illegal. We’ll cover that, below, in Type 5.

Suggested owner response:

To Our Valued Customers,

Sadly, after researching this, our company discovered that this review was left by a competitor. We are taking the appropriate steps to report this to Google, and we hope having this fake review removed will encourage this unfortunate competitor to seek other, more honest forms of promoting his business. If he persists, we will engage appropriate legal counsel.

SMH,

Jim Davis, Owner

Type 5: “I’m citing illegal stuff.”

Real-world example:

Diagnosis: Whether a negative review is true or false, any time illegal or dangerous behavior is cited, it’s a cue to you that you need to speak with an attorney before taking any further steps. Don’t respond and don’t attempt to have the review removed, as both could be used as evidence in a court of law. Seek an attorney well-versed in cyber law and act on his or her advice, rather than on any advice you may read on the Internet or receive from marketers, friends, etc. And if you run an SEO agency, I urge you not to advise clients on Type 5 reviews — we’re SEOs, not attorneys, and shouldn’t be consulting on legal matters.

Orchestrating the ideal owner response environment

If you already have an excellent customer service training program in place at your business, chances are good that you will mostly be managing Type 1 and Type 2 reviews with only the occasional Type 3. Types 4 and 5 will hopefully be the exception rather than the rule. Given that one 2016 survey found that 57% of consumer complaints relate to employee behavior, we can estimate that at least half of your reputation is anchored to the quality of your staff hiring and training practices. So, definitely place first and fundamental focus there, and then manage the ensuing consumer sentiment as it flows in with these tips:

• Observe the typical rate at which you normally receive reviews. It could be a few per week, or if you’re managing multiple locations, numerous reviews per day.
• What you observe dictates how frequently you need to monitor your reviews. If you’re a Moz Local customer, we’ll conveniently alert you as each new review comes in, and you can check that as often as makes sense.
• Avoid unnecessary customer frustration and bad reviews stemming from bad data. There must be literally millions of negative reviews on the web citing wrong phone numbers, wrong hours of operations, wrong addresses. Do a quick citation health check to see if your major local business listings are fomenting negative sentiment. Correct problems.
• I’ve seen various theories about how quickly an owner should respond to reviews; my own opinion is ASAP, particularly when it comes to Type 2 and Type 3 reviews. If you are trying to catch complaints for the purpose of resolving them and winning back unhappy customers, there may be circumstances (like our example with the puppy shots) that make it vital to respond quickly to avoid customer loss.
• While it may be ideal to have owners be the authors of all owner responses, scale may make that an untenable situation. If you are designating a staff member or marketer to represent the owner, prevent mistakes by clearly outlining company policies, voice, permissions, and objectives with that person.
• Responsiveness can be a competitive difference maker. Observe your direct competitors; if they are careless about active management of reviews, you can take advantage by making your brand the one that always responds, demonstrating care and accessibility.
• Know that expert owner responders experience thrilling victories, like having an unhappy customer update their review and raise their star ratings after receiving a great owner reply. These are rewards that make the input of effort well worth it!

Six years into Google’s rollout of the owner response function, I still encounter many business owners expressing fear of reviews. At the root of this, I often find that they feel powerless and overwhelmed by the prospect of managing their brand’s reputation.

It’s my hope that this post signals to every local business owner that you do, indeed, have significant power in this regard. Via the the right combination of skilled customer service and active review management, you can orchestrate an exceptional online reputation for your brand in concert with your customers, in harmony with your professional goals and dreams.

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!

Posted by MiriamEllis

Two dates to know: August 4, 2010 – the day Google enabled owner responses to Google My Business reviews; November 17, 2016 – the day Moz enabled incredibly easy GMB owner response functionality in the Moz Local dashboard. Why are these noteworthy events in Local Search history?

Because reviews and owner responses are direct reputation management, free marketing, free advertising, damage control, and quality control all wrapped up in one multi-voice song about your brand.

What’s missing from the picture of this free-for-all of voices caroling sentiment about your brand? You are — the conductor! If you’re not leading the tune — from setting customer service policies, to training staff, to managing complaints, to engaging directly with consumers online — you’re giving up available reputation management controls.

Make no mistake: No brand can prevent every sour note, but with owner response functionality, you can not only retune relationships with valuable customers, but can also protect revenue by keeping those customers instead of having to invest 25x as much in obtaining new ones. Owner response mastery is, indeed, smart business.

For the past six years, since Google launched owner responses as part of its local product, I’ve been studying them and acting as a consultant to a variety of local business owners and agencies regarding effective usage of this remarkable capability. Today, in celebration of Moz Local’s support of this function, I’m going to break down the types of reviews into 5 categories and offer you my tips for skilled management. With reputation and revenue on the line, every local brand needs an intelligent strategy!

Getting up-to-speed on owner responses

During our recent launch, a Moz community member let us know he’d never heard of owner responses before, so real quick: Many review platforms give you the option, as the business owner, to respond to reviews your customers have left you. This is normally done from within your dashboard on that platform, or, in some cases, via mobile apps.

In the Moz Local dashboard, the Google My Business owner response function is a real time-saver. We alert you when new reviews come in, and you simply click the ‘reply’ link to write your response. A little form pops up in which you can type away handily:

Now let’s delve into responding to the five basic types of reviews most local brands can expect to receive.

Type 1: “I love you!”

Real-world example:

Diagnosis: This is the customer every brand wants to have: the delighted evangelist who goes to the lengths of saying that nothing else on the local scene can compare to what the business offers. Honestly, reviews like this are like beautiful greeting cards validating that your business is getting it right on all points. Pure music to your ears!

Owner response strategy:

Many business owners ask if it’s necessary to respond to positive reviews. My short answer is yes, if you wish your business to come across as courteous and engaged. Part of conducting the flow of your reputation is acknowledging customer satisfaction and thanking them for the time they invest in writing such nice things about your company. It’s just good manners.

Having said this, I’ll qualify it by mentioning scale. If your enterprise has 100+ locations which each have 100+ positive Google My Business reviews, responding to every single one may not be the best use of your resources. Prevent the appearance of ungrateful neglect by aiming for a percentage — maybe 10% — of ‘thank yous’ in response to your best reviews.

Pro tips:

• Your thanks can be brief, but avoid repetitiousness. Write a unique response each time. There are owner response profiles out there that have made me strongly suspect robots manage them, as in ‘thank you for your review’ written on 30 different responses. Avoid that.
• Remember that owner responses are content consumers read. They are, in essence, free advertising space. Don’t go over the top with this, but if a customer mentions something they love, latch onto that. In our sample review above, the owner could mention that comments like this one inspired them to bottle their hot sauce for retail sales, or they could mention that they actually just won a best-in-Bay-Area award from X publication. Think products, services, and hyperlocal/local terminology. No, don’t put the hard sell on the customer in the owner response, but use this real estate with savvy. If there’s something you think a happy customer would be excited to know, promote it in a nice, friendly way!
• Positive reviews indicate that a customer is already in a good, receptive mood. The more personable your owner response, the more of an impression your business can make, encouraging the customer to come back for more. Here, company culture, personality, and fun can shine. Your customer thinks you are special — act like it in the response.

Suggested owner response:

Hi Charley!

We were just thrilled by your review — in fact, we showed it to Chef Rosa, because the pique sauce you love is based on her grandmother’s traditional recipe brought from Puerto Rico in the 1930s. It’s the real deal, and we’re actually offering it bottled for retail now right next to the hostess stand at both our San Rafael and San Francisco locations, based on diner requests. Hint: one secret ingredient is apple cider vinegar, but that’s all we can say! We’d love to see you back soon, and Chef Rosa says, “Thank you for the lovely compliment.” ‘Best in the Bay Area’ makes us all proud!

Good Eating!

Marta Sanchez, Owner

Type 2: “My mind isn’t made up yet.”

Real-world example:

Diagnosis: A 3-star rating is the hallmark of the consumer who likes some things about your business, but isn’t totally loyal yet. They may/may not return and may/may not recommend you to others. Undecided patrons represent an exciting challenge to transform dissatisfactory aspects of your business and specific consumer sentiment, all at the same time.

Owner response strategy:

The honesty of a less-than-5-star review, when written in detail, delivers two valuable assets to your brand: it tells you where you’re hitting and where you’re missing, giving you the opportunity to improve and turn a lukewarm consumer into a loyal one.

Strategy for the owner response involves thanking for praise, accepting responsibility for faults, apologizing for disappointments, and making some kind of an offer. This offer, meant to sweeten the pitch that you hope the consumer will give your company a second chance, could be a comp or a coupon for future use, or it could simply be an explanation of how you have heard their feedback and made changes.

Pro tips:

• Express gratitude for consumer complaints — they are valuable. Do not attempt to shift blame onto anyone else, including the customer or staff members.
• Document both the positive and negative sentiment of so-so reviews and use it as your playbook for keeping what’s good and improving what isn’t excellent.
• Be sure the customer feels heard. Cite their complaints back to them. By doing so, you are demonstrating to all future potential customers that your brand is responsive to feedback.

Suggested owner response:

Dear Yesenia,

We’re so grateful to you for letting us know that our prices, staff, and in-hotel restaurants pleased you, and, I also want to express my thanks to you for mentioning that the housekeeping wasn’t exceptional. I need to hear that, and take full responsibility for the dusty room. I have been trying a variety of cleaning services this past year, with the goal of finding the best.

While I want to be sure that every guest knows we honor any requests during their stay (just dial 9 on your in-room phone), I also want to let you know that, based on your comments, I held an all-staff meeting with our current cleaning service and have issued a new 10-point cleaning checklist (including dusting all surfaces) for each housekeeper. Should you honor us with a second stay, I personally guarantee you will find your room immaculate, and I would also like to offer your party a free breakfast in the Palm Room, as you enjoyed our restaurants. Just tell them Rob sent you, and it will be our pleasure to serve you! Thank you for your valuable and honest review.

Cordially,

Rob Brown, Owner

Type 3: “There was hair in my taco…”

Real-world example:

Diagnosis: The dreaded 1-star review! The customer has a specific, legitimate complaint, and your job as the owner is to address their dissatisfaction, take responsibility, and, whenever possible, make an offer to make things right. A negative review is likely the last life preserver an unhappy customer will throw you — a last chance to earn them back with superior responsiveness. Given the cost of replacing them, rewards for the effort can be great. When a customer ‘saves you’ by making their complaints known, an adept response from you may ‘save them’ in return, earning their repeat business.

Pro tips:

• Apologize!!! Say the words, “I’m sorry, I apologize.”
• No blame shifting, no lectures — just total accountability, humility, and a willingness to learn.
• Be as honest as possible about whatever circumstance led to the customer’s bad experience, and state what you’re doing to improve that circumstance. Sometimes, the circumstances may include faults on the customer’s part. If you have to mention these in order to be honest, do so with great care and no blame, as in the sample response below.
• Negative reviews often run on for agonizing paragraphs and chapters, but your response should not. Be thorough, but concise.
• Offer something, even if it’s just a few minutes of your time on the phone, to try to make it right.
• Aim for a ‘wow’ factor — as in you want future potential customers to say, “Wow, this business really cares!” when they read the response.
• For more tips on managing negative reviews, please read Diagramming The Story of a 1 Star Review.
• Document all complaints; they are incredibly valuable both in terms of damage control and quality control. Consider doing a full review audit on a set schedule to catch emerging problems and resolve them.

Suggested owner response:

Type 4: “I’m actually your competitor.”

Real-world example:

Diagnosis: Unfortunately, fake reviews happen. They may stem from unscrupulous competitors, disgruntled past employees, or individuals with personal grudges against someone at the company. The line to walk here is whether the reviews are simply false (warranting a response + Google action) or citing such defamatory or illegal practices that you should consult with a lawyer before taking any further action. Our real-world example is of the former kind — it illustrates what a fake review might look like with sentiment that is negative but not accusing the business of criminal activity.

Pro tips:

• If research has made you aware that a review has been left by a competitor or by someone who is not a customer, that’s a violation of Google’s Review Policy.
• First, leave a brief owner response to the review (as shown in my sample response below) to alert consumers to the falsity of the review. Note: I don’t advise ‘outing’ the bad actor — it’s not professional.
• Second, follow Google’s steps for flagging the review. I suggest waiting 24 hours after doing this before moving on.
• Next, on that same page, you will see options for speaking directly with Google via phone, chat, or email. Contact Google to let them know about the fake review you have flagged. Hopefully, they will be able to rectify this for you and remove the review.
• However, if you get a rep who doesn’t seem to understand your issue, turn to the Google My Business Community, post the complete details of your scenario, and beg for a Top Contributor to help escalate your issue.
• Don’t expect a quick fix. You may have to be persistent to obtain resolution.
• But, again, please don’t take these steps if a review accuses your business of something illegal. We’ll cover that, below, in Type 5.

Suggested owner response:

To Our Valued Customers,

Sadly, after researching this, our company discovered that this review was left by a competitor. We are taking the appropriate steps to report this to Google, and we hope having this fake review removed will encourage this unfortunate competitor to seek other, more honest forms of promoting his business. If he persists, we will engage appropriate legal counsel.

SMH,

Jim Davis, Owner

Type 5: “I’m citing illegal stuff.”

Real-world example:

Diagnosis: Whether a negative review is true or false, any time illegal or dangerous behavior is cited, it’s a cue to you that you need to speak with an attorney before taking any further steps. Don’t respond and don’t attempt to have the review removed, as both could be used as evidence in a court of law. Seek an attorney well-versed in cyber law and act on his or her advice, rather than on any advice you may read on the Internet or receive from marketers, friends, etc. And if you run an SEO agency, I urge you not to advise clients on Type 5 reviews — we’re SEOs, not attorneys, and shouldn’t be consulting on legal matters.

Orchestrating the ideal owner response environment

If you already have an excellent customer service training program in place at your business, chances are good that you will mostly be managing Type 1 and Type 2 reviews with only the occasional Type 3. Types 4 and 5 will hopefully be the exception rather than the rule. Given that one 2016 survey found that 57% of consumer complaints relate to employee behavior, we can estimate that at least half of your reputation is anchored to the quality of your staff hiring and training practices. So, definitely place first and fundamental focus there, and then manage the ensuing consumer sentiment as it flows in with these tips:

• Observe the typical rate at which you normally receive reviews. It could be a few per week, or if you’re managing multiple locations, numerous reviews per day.
• What you observe dictates how frequently you need to monitor your reviews. If you’re a Moz Local customer, we’ll conveniently alert you as each new review comes in, and you can check that as often as makes sense.
• Avoid unnecessary customer frustration and bad reviews stemming from bad data. There must be literally millions of negative reviews on the web citing wrong phone numbers, wrong hours of operations, wrong addresses. Do a quick citation health check to see if your major local business listings are fomenting negative sentiment. Correct problems.
• I’ve seen various theories about how quickly an owner should respond to reviews; my own opinion is ASAP, particularly when it comes to Type 2 and Type 3 reviews. If you are trying to catch complaints for the purpose of resolving them and winning back unhappy customers, there may be circumstances (like our example with the puppy shots) that make it vital to respond quickly to avoid customer loss.
• While it may be ideal to have owners be the authors of all owner responses, scale may make that an untenable situation. If you are designating a staff member or marketer to represent the owner, prevent mistakes by clearly outlining company policies, voice, permissions, and objectives with that person.
• Responsiveness can be a competitive difference maker. Observe your direct competitors; if they are careless about active management of reviews, you can take advantage by making your brand the one that always responds, demonstrating care and accessibility.
• Know that expert owner responders experience thrilling victories, like having an unhappy customer update their review and raise their star ratings after receiving a great owner reply. These are rewards that make the input of effort well worth it!

Six years into Google’s rollout of the owner response function, I still encounter many business owners expressing fear of reviews. At the root of this, I often find that they feel powerless and overwhelmed by the prospect of managing their brand’s reputation.

It’s my hope that this post signals to every local business owner that you do, indeed, have significant power in this regard. Via the the right combination of skilled customer service and active review management, you can orchestrate an exceptional online reputation for your brand in concert with your customers, in harmony with your professional goals and dreams.

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!

Posted by randfish

Should you focus on perfecting your H1s and H2s, or should structured data demand all your on-page attention? While Google hasn’t completely pulled the rug out from under us, don’t let the lack of drastic change in page markup fool you. In today’s Whiteboard Friday, Rand outlines where to focus your efforts when it comes to on-page SEO and offers some tools to help with the process.

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 are going to chat about page markup and tags and which ones still matter for SEO.

Now, weirdly enough, you would think that over the last, say, seven or eight years we would’ve had an enormous growth in the number of tags and the optimization options and what you have to do on a page, but that’s not actually the case. Google kind of gave us a few that were important — things like rel=author — and then took some away. So it’s changed a little bit, but it is not as overhauled massively as you might think, and that’s a good thing.

Old-school SEO markup

Old-school SEO best practices were sort of like, okay, I had to worry about my title, my meta description and keywords tag — keywords a little less though, keywords haven’t been worried about for maybe 15 years now — my robots tag certainly, especially if I was controlling bot behavior, rel=canonical and the rel=alternate tag for things like hreflang, which came about six or seven years ago, and my headline tags. Some potential basically markup or text tags that could change the format of text, like strong and bold and EM, these have gotten less important. I’ll talk about that in a sec. Obviously, with URLs worrying about rel=nofollow and other forms of the rel tag, and then image source having the alt attribute.

This was kind of the basic, bare-bones fundamental minimums. There were other tags that some people employed and obviously other tags that Google added and took away over time or that they paid attention to a little bit and then didn’t. But generally speaking, this was the case.

Modern SEO markup

Nowadays there are a few more, but they’re really centered around just a few small items. We do have metadata now. I’m going to call this SEO even though technically it is not just for the search engines. Those are Open Graph, Twitter Cards, and the favicon. I’ll talk about that in a sec why that actually changed even though favicon has been around for a long time. Then, things like the markup for Google itself, the structured data markup that’s part of schema.org that Google is employing.

I want to be clear. Google is not using every form of schema. If you go to schema.org, you can find schema markup for virtually anything. Google only uses a small portion of that. While certain websites have seen an uptick in traffic or in prominence or in their visibility and display in the search engine results, it is not a guaranteed rank booster. Google says they don’t typically use it to boost rankings, but they can use it to better understand content, which in my opinion, better understanding content is something that often leads to better rankings and visibility, so you should be doing it. As a result, many of these old-school tags still apply of course — alt attributes and in the header tag the title and the meta description, meta robots, canonical.

What’s changed?

Really what’s changed, the big things that have changed, added to the header of pages, I would tell you generally speaking that you should think and worry about:

• Twitter Cards
• Open Graph markup
• The favicon

Twitter Cards is pretty obvious. Basically, because Twitter is such a big distribution network for content and can be, it pays to have your cards optimized rather than to just have the URL exist on its own. You can stand out better in Twitter that way.

Open Graph markup, this is basically used by Facebook, an even bigger distribution platform than Twitter, and so of course you want to be able to optimize how you appear in those. Because social media in general is so well correlated with all sorts of positive SEO things, you want to put your best foot forward there. Therefore, I’m going to say this is an SEO best practice as well as a social media marketing one.

Favicon is a little weirder. Favicon’s been around for forever. It’s the little graphic that appears in your browser window or at the top of the browser tab. The reason that it matters is because so many sites — social media platforms and many distribution sites, places like Pocket, places that scrape, places that will show your stuff including sometimes, at least in the past, Google’s knowledge cards — will sometimes use that favicon in their display of your site. For that reason, it certainly can pay to have a good favicon that stands out, that’s obvious and clear, much more so than it was, say, a decade ago.

Not as important…

The H1, H2, and H3

I know what you’re going to say. You’re looking around like, “Wait a minute. I still see a lot of recommendations from tools, even like Moz Pro, that say I should use H1, H2, H3.” It is a best practice. I’d say H1 and H2 are best practices, but they are not going to transform or massively help your rankings. They’re not very well correlated with better rankings. In lots of testing, folks could barely ever observe a true, reconcilable difference between using the headline tag and just having those headlines be big and bold at the top of the page. However, I’m saying this alone. If you are using itemprop to describe a headline, an alternate headline, in your schema.org markup, that actually can be more useful. We do think that Google is at least using that, as they say, to better understand your content. I think that’s a positive thing. Then, there are lots of other sites that can use schema as well. Google is not the only place. That can certainly help your visibility too.

Strong, bold, and EM

It just kind of doesn’t matter as much. With CSS taking things over, you don’t need to worry about visual display of text in your HTML code nearly as much and certainly not from the search engine perspective.

Added to body

I’m adding to the body tag of course all of the schema.org options. I’m just showing the article ones here, but you should consider any of the ones you’ve got — recipes or news or videos or all sorts of stuff.

What about…?

Questions that folks might have around page markup:

• What about other metadata? There’s the Dublin Core Metadata Initiative and other forms of open metadata and other forms of markup that you could put in there. I’m going to say no, don’t bother. Until and unless something gets truly popular and used by a lot of these different services, Google included, it just doesn’t pay, in my opinion, and it adds a little bit of extra weight to a page that just doesn’t matter.
• W3C validation, does it matter if I have valid HTML code that’s sort of very, very perfect? Nope, it doesn’t seem to matter much at all. It didn’t matter back in the day. It doesn’t matter now. I would not worry about it. Most of the most popular and most visible sites in Google do not actually validate at all.
• Schema that Google hasn’t adopted yet? I’m going to be a little controversial and say it’s probably worthwhile. If Schema has already stated this is how this format works, but you don’t yet see Google using it, it could still pay to be an early adopter, because if and when Google does do that, it could bring benefit. Now, if you’re worried about heavy page load or if this is very time-consuming for you or your dev team, don’t worry about it too much. You can certainly wait until Google actually implements something before you go and add that relevant schema to your site.
• Other forms of semantic markup? I know there are lots of people who believe semantic markup is the future and those kinds of things, but I don’t. I don’t think that until and unless the engines adopt it, it probably does not pay. Certainly we have not seen browsers, we have not seen search engines, and we have not seen big organizations that in the social media world start to adopt this semantic markup stuff, so I would worry less about that. I think, to be honest, the engines of the future are worried about parsing the content themselves, not about how you mark it up on your pages.
• Header, footer, sidebar labels in CSS? This was like a spam or manipulation or link counting thing for a long time, where SEOs worried that page markup that called out this is in the header, this is in the footer, this is in the sidebar of the visual of the page, like I’m saying these links are in here or these links are over here or these links are down here, this was a concern. I am less worried about it nowadays. If you are very paranoid or concerned, you certainly could use alternate things. I just wouldn’t worry about it very much.

Want to check your pages?

If you want to check these pages, you want to go through a process of actually reviewing all this stuff, there are a few tools that will do all of this stuff for you. They’ll look at all of these different tags and markup options.

• MozBar. You can download it for free. There are almost 400,000 people who use it regularly for free, and that’s awesome. It does have a little on-page checking option. It’ll run through all this different stuff for you.
• View source and do it manually in your browser.
• Google Structured Data Checker tool, which is linked to from the MozBar’s on-page checker, but also you can Google it yourself and then plug stuff into it. You don’t need to be logged in to your Webmaster Tools or Search Console account. It will validate at least the schema.org options that Google considers, which is great, and some ones that they don’t use, but that’s cool too.
• Facebook has the same thing with Open Graph checking.
• Twitter with their Card Validator.

If you want to use a paid service to go crawl your site automatically and surface all these issues for you:

• Moz Pro campaigns do that.
• Onpage.org, a great company out of Germany, and Screaming Frog, a great company out of the UK.

We’ll see you again next week for another edition of Whiteboard Friday. Take care.

Video transcription by Speechpad.com

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Posted by kerryjones

I was in Peru earlier this year for a digital marketing conference, and I overwhelmingly heard the same frustration: “It’s really hard to use outreach to earn links or PR coverage in our country.”

This wasn’t for lack of trying. As I continued to hear this sentiment during my visit, I learned there simply weren’t a lot of opportunities. For one thing, in Peru, there aren’t nearly as many publishers as in more populous countries. Most publishers expected payment for mentioning a brand. Furthermore, journalists did a lot of job-hopping, so maintaining relationships was difficult.

This is a conundrum not limited to Peru. I know many people outside of the US can relate. When you see the Fractl team and others sharing stories about how we earn hundreds of links for a single content piece, you might think it must be nice to do outreach somewhere like the US where online publishers are plentiful and they’ll feature great content with no strings attached. While the work my team does isn’t easy by any means, I do recognize that there are ample opportunities for earning links and press coverage from American publishers.

What can you do if opportunities are scarce in your country?

One solution is focusing your outreach efforts on publishers in neighboring countries or countries with the same language and a similar culture. During conversations with the Attachmedia team (the company hosting the conference I was at), I learned they had much greater success earning media stories and building links outside of Peru because publishers in surrounding South American countries were more receptive to their email pitches and publishing third-party content.

But you may not need to do any international outreach if you know how to create the type of content that will organically attract attention beyond your borders.

At Fractl, many of our top-performing client campaigns have secured a lot of international links even without us doing much, or any, international outreach. To dig deeper, we recently conducted an analysis of 290 top-performing client content campaigns to determine which content naturally attracted coverage from international publishers (and thus, international links). Altogether, these campaigns were featured by publishers in 130 countries, earning more than 4,000 international media stories.

In this post, I’ll share what we found about what causes content to spread around the world.

1. Domestic success was a key factor in driving international placements for Fractl’s campaigns.

For years, we’ve noticed that if content gets enough attention in the US, it will organically begin to receive international press and links. Watch how this happens in the GIF below, which visualizes how one of our campaigns spread globally after reaching critical mass in the US:

Our study confirmed that there’s a correlation between earning a high number of links domestically and earning international links.

When we looked at our 50 most successful client campaigns that have earned the highest number of media stories, we discovered that these campaigns also received the most international coverage. Out of the 4,000 international placements we analyzed, 70 percent of them came from these 50 top-performing campaigns.

We also found that content which earned at least 25 international media pickups also earned at least 25 domestic pickups, so there’s a minimum one-to-one ratio of international to domestic pickups.

2. Overcome language barriers with visual formats that don’t rely on text.

Maps showing a contrast between countries were the visualizations of choice for international publishers.

World maps can be easily understood by global audiences, and make it easy for publishers to find an angle to cover. A client campaign, which looked at how much people eat and drink around the world, included maps highlighting differences between the countries. This was our fourth-highest-performing campaign in terms of international coverage.

It’s easy for a writer whose primary language isn’t English to look at a shaded map like the one above and pick out the story about his or her country. For example, a Belgian publisher who covered the consumption campaign used a headline that roughly translated to “Belgians eat more calories than Americans”:

Images were the second most popular visual format, which tells us that a picture may be worth a thousand words in any language. One great example of this is our “Evolution of Miss Universe” campaign, where we created a series of animated and interactive visualizations using photos of Miss Universe winners since 1952:

The simplicity of the visuals made this content accessible to all viewers regardless of the language they spoke. Paired with the international angle, this helped the campaign gain more than 40 pickups from global sites.

As we move down the rankings, formats that relied on more text, such as infographics, were less popular internationally. No doubt this is because international audiences can’t connect with content they can’t understand.

When creating text-heavy visualizations, consider if someone who speaks a different language can understand it — would it still make sense if you removed all the text?

Pro tip: If your outreach strategy is targeting multiple countries or a country where more than one language is widely spoken, it may be worth the effort to produce text-heavy visuals in multiple languages.

3. Topics that speak to universal human interests performed best internationally.

Our top-performing international campaigns show a clear preference for topics that resonate globally. The six topics that performed best internationally were:

1. Drugs and alcohol
2. Health and fitness
3. Entertainment
4. Sex and relationships
5. Travel
6. Technology

Bear in the mind that these topics are reflective of our client campaigns, so every topic imaginable was not included in this study.

We drilled this down a little more and looked at the specific topics covered in our top 50 campaigns. You’ll notice many of the most popular topics would make your grandma blush.

We know that controversial topics are highly effective in grabbing attention, and the list above confirms that pushing boundaries works on a global scale. (We weren’t exactly surprised that a campaign called “Does Size Matter?” resonated internationally.)

But don’t look at the chart above and assume that you need to make your content about sex, drugs, and rock and roll if you want to gain international attention. As you can see, even pedestrian fare performed well globally. Consider how you can create content that speaks to basic human interests, like technology, food, and … Instagram.

4. A global angle isn’t necessary.

While our top five international campaigns did have a global focus, more than half of our 50 top-performing international campaigns did not have a global angle. This tells us that a geographic angle doesn’t determine international success.

Some examples of non-geographic ideas that performed well are:

• A tool that calculates indirect sexual exposure based on how many partners you’ve had
• The types of white lies people commonly tell and hear
• A face-off between Siri, Cortana, and Google Now performance
• A sampling of how many bacteria and germs are found in hotel rooms

We also found that US-centric campaigns were, unsurprisingly, less likely to succeed. Only three of our campaigns with America-focused titles received more than 25 international placements. If your content topic does have a geographic angle, make sure to broaden it to have a multi-national or worldwide focus.

Pro tip: Consider how you can add an international twist to content ideas that already performed well domestically. The Miss Universe campaign example I shared above? That came to fruition after we successfully did a similar campaign about Miss America. Similarly, we could likely reboot our “Tolerance in America” campaign to look at racism around the world and expect it to be successful, as this topic already proved popular at home and is certainly relevant worldwide.

5. The elements of share-worthy content hold true internationally.

Over the years, we’ve seen time and time again that including certain elements in content greatly increases the chance of success. All of our content that achieved international success included some combination of the following:

• Surprising information
• An emotionally resonant topic
• A universally appealing topic
• Comparison or ranking of multiple places, things, or ideas
• A geographic angle
• A pop culture angle

Look back at the content examples I shared in this post, and make note of how many of the characteristics above are present in each one. To increase the likelihood that your content appeals to global audiences, be sure to read this post about the vital role these elements play in creating content that earns a lot of links and social shares.

What has your experience been like using content to attract international press and links? I’d love to hear what’s worked for you — leave a comment below!

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!