Posted by chelseascholz
Webinars are an incredibly popular lead-gen tool in most marketersâ toolkits. However, times have changed (and viewer attention spans have changed with it). Rather than try and force your audience to show up on time for live events and stay for a full hour (ainât nobody got time for that), it’s time to consider delivering content they can watch anytime they want (just like their Netflix experience). We’re talking on-demand video.
Now I know âon-demandâ is an all-the-rage word as of late, but I really mean it. When is the last time you showed up for a live event or watched a television show on time? Can you even remember? I canât. (Except for that time I bought expensive tickets to Wicked.) Now you can bet Iâm showing up on time for that, because I paid for it. But if itâs free, my pulled-in-one-million-directions brain is going to forgo the things that arenât urgent (or costly) â which means all those webinars I signed up for are lost conversions for the marketers who run them.
By thinking and delivering on-demand content like Netflix, the power is put in the hands of your audience to consume on their time â giving the audience edu-taining content to watch when they feel like it and giving us the ability to collect more leads and product sign ups than demanding live events.
Webinars vs. on-demand content
Now as a marketer at Unbounce, I also realize that webinars are a very powerful and well-used channel. Webinars were our bread and butter for a long time, as they are for many other marketing teams, but the shift in attention spans and the way marketers consume content (both professionally and personally) means that we tried to adapt our video content with it and saw great results when we launched The Landing Page Sessions in 2015.
We bounced around the idea of producing pre-recorded videos for our audience, which we saw as having a few benefits over webinars:
- They give you more time to focus on high production value and fancy video editing
- They allow the presenter to talk on-screen directly to the audience, as opposed to (less human) full-screen webinar slides
- They relieve much of the stress caused by technical glitches associated with live webinars
- Theyâre a great way to focus on showcasing your product with explainer videos and demos â showing spectators why they should buy your product
- They have the potential to bring in leads and product signups for months without much active effort after the initial launch. No more breaking your back only to rely on the ROI of a very specific time slot
After all was said and done, this one series with 12 episodes has become an ongoing source of leads for us and brought in 87% more product signups than our webinars over the course of four months. Can I get a âheck yeah!â?!
The Landing Page Sessions was built with the goal of showcasing our product, Unbounce, in a way that was valuable to viewers and great for explaining the use of landing pages. During each episode of LPS, Unbounce co-founder Oli Gardner breaks down a full marketing campaign from start to finish and all the videos live on their own microsite where they can be accessed all day, every day.
This is a big change from traditional webinars which, as you probably know, include registering for a live event that largely entails 1â3 people chatting over a slide deck for about 30â45 minutes. Not exactly entertaining, but some companies pull them off really well. The problem for us was that while our webinars were well-produced, they had a declining registration rate and, subsequently, attendance rate. As you can imagine, this also lead to a declining amount of leads and product sign ups. The shift to on-demand content was intimidating, but we were pleasantly surprised. There is more work up front with pre-recorded content, but then it lives forever and you can drive as much or as little traffic to it as you want. Letâs break down some of the key benefits of using on-demand content over webinars.
3 benefits of on-demand content
1. Avoid technical snafus that go into running a live event.
A big win from switching over to on-demand content is that we avoid the technical snafus that can often happen in live content. With pre-recorded content you donât have to worry about GoToWebinar going down, mics going amiss, ill-fitting slides, or power outages.
I used to run webinars at Unbounce when I first started, and I canât tell you how many near-heart attacks I almost had because of the technical glitches with live events. Ainât nobody got time for that.
We used pre-recorded video hosted with Wistia, and aside from avoiding live technical glitches, we were also able to optimize our video as we saw fit without the pressure of only getting one go at it. We would adjust our turnstiles and call-to-actions based on real-time stats, like average watch time and which of the episodes were most frequently clicked on.
2. Create more areas for conversion opportunities (turnstiles, overlays, and demo requests, oh my!).
And speaking of optimization, on-demand video also gives you the ability to create a ton of opportunity for conversions that’s otherwise pretty limited with live events (because you only capture when you collect registrations). There are sometimes opportunities post-webinar, but at Unbounce weâve seen a pattern emerge: most people donât convert after watching. They often sign up to get the recording but donât end up watching that either, so whatever post-work you do can often be fruitless. Bummer.
With LPS we capture leads through many different avenues, including:
- Wistia (lead-generating) turnstiles on each individual episode;
- An exit overlay on the homepage of the show to remind people to sign up for new episode notifications;
- A landing page where we collected submissions (to be featured on the show) before, during and after the season went live;
- and through a call-to-action to start a free trial of Unbounce at the end of every episode.
These were all things we couldnât have done (or done very well) with live shows before, because there just wasnât room. And if we were putting all this effort into running a show, why shouldnât we see a good return on it?
Now, with all this space for opportunity to convert, you still have to be careful youâre not being a marketing jerk. Itâs easy to overwhelm the viewer, and we experienced that first hand because we were a little âconversion-happy.â Remember that there are people on the other end trying to watch your awesome content, so try and place your calls-to-action strategically so they arenât overwhelmed, and then subsequently bounce. So play it cool, folks, but take advantage of all the room for activities!
3. Create content with higher production value (even if the costs are relatively the same!) that people want to watch
And finally, your production value can be a lot higher (even with a budget thatâs the same as what you were running webinars with).
Here are a few takeaways about how to build your own high-quality, on-demand production without it feeling daunting:
The draw of webinars are not after theyâve happened, itâs during (as much as weâd like to believe our webinar recordings provide a ton of value, the fact of the matter is that they often donât). Take what you know people like about those webinars and build that into your pre-recorded productions! If youâve run a webinar, for example, where people really liked when a guest dissected email copy, create a short series around that topic.
Listen to your audience and ask them questions about what theyâd like to see, then do it. Crowdsourcing is definitely underutilized, and sometimes as marketers we can over-complicate a situation. The easiest thing to do when deciding on new marketing channels is to ask the opinion of those who already love you. I learned this when I sent an email last year just asking âWhat do you need to get more out of landing pages?â, rather than assuming I knew what everyoneâs issue or need was. And the result? I found myself a little surprised by some of the answers, and I was able to craft that into some stories for the show.
Create a production schedule and stick to it. Nothing is worse than putting more effort in than necessary for little to no return (this is the danger of on-demand content, and I get asked this a lot: “When are you done?”). Giving yourself a schedule allows you to build better productions without perfecting them until the end of time. For the landing page sessions, it took us about 3â4 months to build, promote, and release the season, for example.
And finally, a pro-tip: If youâve got something to show off, do it! Showcase your product! Pre-recorded video is a great way to do that without having the pressure of a live demo.
A new era of content production
All this means that you can get more conversions with on-demand video because it puts the user first. On-demand video lets the consumer watch what they want and when they want â and thatâs the whole point, folks. People who watch on their own time are more likely to convert because theyâve taken a vested interest in seeking out (or saving your content) to watch at a time that suits them best. This means they’re already in a position to find more value in what youâre serving up, and reduce friction to converting. So you can create a high-quality production that takes the stress out of those live events and serves up highly relevant calls-to-action for highly motivated watchers. A match made in marketing heaven!
Wanna know a little more about our results?
Crunch the numbers
Compared to Unbounce webinars that were run over the same four months that The Landing Page Sessions was running, the landing page sessions had 41 more product sign-ups than the approximate 4 webinars we ran at the same time (47 product sign ups vs. 88 product sign ups). The Landing Page Sessions also brought in close to 2500 leads in that four months as well (which blew what webinars would usually bring in out of the water). Initial effort was higher for LPS, so that needs to be taken into account, but webinars are not consistent in their results month-to-month, either.
This really highlighted a point that Wistia preaches â people like to watch a video before they buy a product. We showcased Unbounce and made it clear how landing pages can be valuable for anyoneâs marketing campaigns by breaking them down and seeing how all the pieces drive to them for optimal conversions.
My learning: Running continual seasons of LPS (now that weâre off the ground) will be more valuable and less effort in the long run than running monthly webinars, based on the combined effort and return on investment.
Additionally, because this content is pre-recorded, we have a ton of ability to milk it for all itâs worth and give it life even months after itâs debuted.
Optimize, optimize, optimize!
On-demand content can live forever. This means you can continue to drive conversions much longer than a traditional live production recording. The conversion opportunities arenât limited just to where you can add more, but the time period in which you find them!
Things weâve tried to do with LPS that you can try too include:
- Continuing to drive traffic to your page and build social hype â leads beget more leads!
- Using some paid traffic (Outbrain/Taboola) if you have budget to attract fresh users (but be targeted about it). You want the new watchers to be just as interested as your current audience.
- If you collect emails, create a nurture campaign to talk to those people based on their interests and needs. Continue serving them relevant content, like an ebook or bonus episodes if youâve got more footage!
- Using social share buttons throughout your video (or on the landing page that itâs hosted on) with relevant and unique hashtags. If people like what theyâre watching, theyâll share and drive more traffic back to your site through their own social channels.
- We keep our submissions page for the show live all the time to encourage people to submit pages for critique 24/7. And we still get submissions daily even though we havenât finished our second season yet. This is great because it continues to list-build if you do a show where you can crowdsource content, and you can talk to them so they donât go cold before the next show.
And donât forget to keep an eye on it! If you notice that there are opportunities for improvement with what youâve got right now, test them out. Thereâs an ease for testing with on-demand content because you arenât pressured by a live time box. Things weâve tried with LPS include gating specific high-traffic episodes, driving more traffic to a high-performing episode through specific paid channels that have done really well, and using The Landing Page Sessions as a nurture tactic for nurturing our subscribers into qualified leads.
So whenâs the next episode?
We are going to be working on a season 2 this quarter and are experimenting with things like:
- Releasing all the episodes at once instead of dripping week over week (this will reduce effort on production/promotion and satisfy the binge-watch culture of our consumers, while letting us sit back and relax)
- Creating a version of LPS specifically for customers (ungated and used to create some evangelism in our community)
- Optimize the request-a-demo portion of the site and ensure a smoother episode-to-Unbounce journey
So remember, donât be afraid of trying out on-demand content in a webinar-soaked world. It can actually generate some long-lasting conversion channels with a higher production value and less effort. If youâre interested in doing some on-demand content, take a gander at what we put together at unbounce.com/lp-sessions.
Take a page out of Netflixâs playbook and provide your users with timely content they can consume at their leisure, and watch the relationship bloom between your audience and your product. Now is the time to binge watch everything from cat videos on Youtube to your favorite marketing Podcasts, so donât wait for anybody to register to give them what they need.
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Posted by mark-johnstone
A few weeks ago, a post was published entitled The SEO Myth of Going Viral. It referenced 8 pieces of content across 4 different sites that went viral and, most importantly for SEO, gained hundreds of linking root domains. I was the creative director on a lot of those campaigns while working as the VP of Creative at Distilled. Today, Iâd like to add some important context and detail to the original post.
I actually agree with much of what it said. However, it’s based on the assumption that one big viral piece of content would result in a visible jump in rankings across the domain within about 3 months of the content being released. There are a few challenges with this as a basis for measuring success.
I wouldnât advise setting your hopes on one big viral hit boosting your rankings across the domain. Not by itself. However, if that viral hit is part of ongoing link building efforts in which you build lots of links to lots of pieces of content, you can begin to see an upwards trend.
“Trend” is the important word here. If youâre looking for a dramatic step or jump as a direct result of one piece of viral content, this could cause you to overlook a positive trend in the right direction, and even tempt you to conclude that this form of content-based link building doesnât work.
With regards to this type of link building and its impact on domain-wide rankings, Iâd like to focus on the follow 4 points:
- How success really looks
- Why success looks like it does
- Other factors you need to consider
- How we can improve our approach
What successful link building really looks like
Simply Business was held up in the SEO myth post as an example of this kind of link building not working. I would argue the opposite, holding it up as an example of it working. So how can this be?
I believe it stems from a misunderstanding of what success looks like.
The post highlighted three of the most successful pieces of content Distilled created for Simply Business. However, focusing on those three pieces of content doesnât provide the full picture. We didnât make just three pieces of content; we made twenty-one. Here are the results of those pieces:
Thatâs links from 1466 domains built to 19 pieces of content over a period of 3 years.
The myth in question is as follows:
Building lots of links to one piece of content will result in a jump in domain-wide rankings within a reasonable timeframe, e.g. 3 months.
Though this wasnât the hypothesis explicitly stated at the start of the post, it was later clarified in a comment. However, thatâs not necessarily how this works.
An accurate description of what works would be:
Building lots of links to lots of pieces of content sustainably, while taking other important factors into consideration, can result in an increase in domain-wide rankings over time.
To hold up, the myth required a directly attributable jump in rankings and organic traffic within approximately 3 months of the release of each piece of content. So where was the bump? The anticipated reward for all those links?
No. The movement weâre looking for is here:
Not a jump, but a general trend. Up and to the right.
Below is a SEMRush graph from the original post, showing estimated organic traffic to the Simply Business site:
At first glance, the graph between 2012 and 2014 might look unremarkable, but thatâs because the four large spikes on the right-hand side push the rest of the chart down, creating a flattening effect. There’s actually a 170% rise in traffic from June 2012 to June 2014. To see that more clearly, hereâs the same data (up to June 2014) on a different scale:
Paints quite a different picture, donât you think?
Okay, but what did this do for the company? Did they see an increase in rankings for valuable terms, or just terms related to the content itself?
Over the duration of these link building campaigns, Simply Business saw their most important keywords (“professional indemnity insurance” and “public liability insurance”) move from positions 3 to 1 and 3 to 2, respectively. While writing this post, I contacted Jasper Martens, former Head of Marketing and Communications at Simply Business, now VP of Marketing at PensionBee. Jasper told me:
“A position change from 3 to 1 on our top keyword meant a 15% increase in sales.”
That translates to money. A serious amount of it!
Simply Business also saw ranking improvements for other commercial terms, too. Hereâs a small sample:
Note: This data was taken from a third-party tool, Sistrix. Data from third-party tools, as used both in this post and the original post, should be taken with a grain of salt. They donât provide a totally accurate picture, but they can give you some indication of the direction of movement.
I notice Simply Business still ranks #1 today for some of their top commercial keywords, such as “professional indemnity insurance.” Thatâs pretty incredible in a market filled with some seriously big players, household UK names with familiar TV ads and much bigger budgets.
Why success looks like it does
I remember the first time I was responsible for a piece of content going viral. The social shares, traffic, and links were rolling in. This was it! Link building nirvana! I was sitting back waiting for the rankings, organic traffic, and revenue to follow.
That day didnât come.
I was gutted. I felt robbed!
Iâve come to terms with it now. But at the time, it was a blow.
I assume most SEOs know it doesnât work that way. But maybe they donât. Maybe thereâs an assumption that one big burst in links will result in a jump in rankings, as discussed in the original post. Thatâs the myth it was seeking to dispel. I get it. Iâve been there, too.
It doesnât necessarily work that way. And, actually, it makes sense that it doesnât.
- In two of the examples, the sites in question had one big viral hit, gaining hundreds of linking root domains, but this on its own didnât result in a boost in domain-wide rankings. Thatâs true.
- Google would have pretty volatile search results if every time someone had a viral hit, they jumped up in the rankings for all their head terms.
- But if a site continues to build lots of links regularly over time, like Simply Business did, Google might want that site to be weighted more favorably and worthy of ranking higher.
The Google algorithm is an incredibly complex equation. Itâs tempting to think that you put links in and you get rankings out, and a big jump in one will correspond to a big jump in the other. But the math involved is far more complicated than that. Itâs not that linear.
Other factors to consider
Link building alone wonât improve your rankings.
There are a number of other influential factors at play. At a high level, these include:
- A variety of on-site (and technical) SEO factors
- Algorithmic updates and penalties
- Changes to the SERPs, like the knowledge box and position of paid results
- Competitor activity
Iâm not going to go into great detail here, but I wanted to mention that you need to consider these factors and more when reviewing the impact of link building on a site’s rankings.
Below is the graph from SearchMetrics for Concert Hotels, also via the original post. This is another site to which Distilled built a high volume of links.
As you can possibly tell from the large drop before Distilled started working with Concert Hotels, the site was suffering from an algorithmic penalty. We proceeded under the hypothesis that building high-quality links, alongside other on-site activity, would be important in the siteâs recovery.
However, after three or four large link building successes without any corresponding uplift, we recommended to the client that we stop building links and shift all resources to focus on other activities.
As youâll see at the end of the chart, there appears to be some positive movement happening. If and when the site fully recovers, weâll never be able to tell exactly what contribution, if any, link building made to the siteâs eventual rankings.
You canât take the above as proof that link building doesnât work. You have to consider the other factors that might be affecting a siteâs performance.
How can we improve our approach?
As I mentioned at the start of this post, I actually agree with a lot of the points raised in the original post. In particular, there were some strong points made about the topical relevance of the content you create and the way in which the content sits within the site architecture.
Ideally, the content you create to gain links would be:
- Topically relevant to what you do
- Integrated into the site architecture to distribute link equity
- Valuable in its own right (even if it werenât for links and SEO)
This can be a challenge, though, especially in certain industries, and you might not hit the sweet spot every time.
But letâs look at them in turn.
If you can create a piece of content that gains links and is closely relevant to your product and what you do for customers, thatâs great. Thatâs the ideal.
To give you an example of this, Distilled created a career aptitude test for Rasmussen, a career-focused college in America. This page earned links from 156 linking root domains (according to the Majestic Historic Index), and the site continues to rank well and drive relevant search traffic to the site.
Another example would be Mozâs own Search Engine Ranking Factors. Building lots of links to that page will certainly drive relevant and valuable traffic to the Moz site, as well as contributing to the overall strength of the domain.
However, your content doesnât have to be about your product, as long as itâs relevant to your audience. In the case of Simply Business, the core audience (small business owners) doesnât care about insurance as much as it cares about growing its businesses. Thatâs why we created several guides to small business marketing, which also gained lots of links.
As Jasper Martens explains:
âBefore I left Simply Business, the guides we created attracted 15,000 unique visits a month with a healthy CTR to sign-up and sales. It was very effective to move prospects down the funnel and make them sales-ready. It also attracted a lot of small business owners not looking for insurance right now.â
Integrating the content into the site architecture
Distilled often places content outside the main architecture of the site. Iâll accept this isnât optimal, but just for context, let me explain the reasons behind it:
- It creates a more immersive and compelling experience. Consider how impactful New York Timesâ Snowfall would have been if it had to sit inside the normal page layout.
- It prevents conflicts between the siteâs code and the interactive contentâs code. This can be particularly useful for organizations that have restrictive development cycles, making live edits on the site difficult to negotiate. It also helps reduce the time, cost, and frustration on both the client-side and agency-side.
- It looks less branded. If a page looks too commercial, it can deter publishers from linking.
While it worked for Simply Business, it would make sense, where you can, to pull these things into the normal site architecture to help distribute link equity further.
Content that’s valuable in its own right (even if it weren’t for links and SEO)
Google is always changing. Whatâs working now and what’s worked in the past wonât necessarily continue to be the case. The most future-proof way you can build links to your site is via activity thatâs valuable in its own right â activities like PR, branding, and growing your audience online.
So where do we go from here?
Link building via content marketing campaigns can still make a positive impact to domain-wide rankings. However, itâs important to enter any link building campaign with realistic expectations. The results might not be as direct and immediate as you might hope.
You need to be in it for the long haul, and build links to a number of pieces of content over time before youâll really see results. When looking for results, focus on overall trends, not month-to-month movements.
Remember that link building alone wonât solve your SEO. You need to make sure you take other on-site, technical, and algorithmic factors into consideration.
Itâs always worth refining the way youâre building links. The closer the topics are aligned with your product or core audienceâs interests, the more the content is integrated into your siteâs architecture, and the more the content youâre creating is valuable for reasons beyond SEO, the better.
Itâs not easy to manage that every time, but if you can, youâll be in a good position to sustainably build links and improve your siteâs rankings over time.
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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 â one for text search and one for voice search â 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 â 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):
Not only does Google recognize that “upscale” is synonymous with “luxury,” but they’ve matched on actual examples of luxury department stores, including Bergdorf Goodman, Saks Fifth Avenue, and more.
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 â 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 â 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 â 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 â 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 â 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, Googleâs machine learning masters believed [Amit's approach] should change. âWe had a series of discussions with the ranking team,â says Dean. âWe said we should at least try this and see, is there any gain to be had.â 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). âWe sort of just said, letâs try to compute this extra score from the neural net and see if thatâs a useful score.â
Amit Singhal, the head of Google’s Search team until early 2016, pioneered the heuristic approach â 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 noting 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 â called vectors â that the computer can understand. If RankBrain sees a word or phrase it isnât 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 â 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, ÂŠ2016 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 â 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. Itâs 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 Chicagoâs 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:
- “space needle height”
- “space needle height in stories”
- “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:
- “height of the Space Needle”
- “Space Needle is ___ stories”
- âHow tall is the Space Needle?â
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:
- Gather keywords
- Group keywords into clusters
- 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:
- “Seattle average rent by neighborhood”
- “Seattle housing prices skyrocket”
- “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:
- “average rent in downtown Seattle”
- “Seattle housing prices are skyrocketing”
- “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 00″ 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 â the day Google enabled owner responses to Google My Business reviews; November 17, 2016 â 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.
Whatâs missing from the picture of this free-for-all of voices caroling sentiment about your brand? You are â the conductor! If youâre not leading the tune â from setting customer service policies, to training staff, to managing complaints, to engaging directly with consumers online â 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, Iâve 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 Localâs support of this function, Iâm 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 âreplyâ link to write your response. A little form pops up in which you can type away handily:
Now letâs delve into responding to the five basic types of reviews most local brands can expect to receive.
Type 1: âI love you!â
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 itâs 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. Itâs just good manners.
Having said this, Iâll 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 â maybe 10% â of âthank yousâ in response to your best reviews.
- 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 âthank you for your reviewâ written on 30 different responses. Avoid that.
- Remember that owner responses are content consumers read. They are, in essence, free advertising space. Donât 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, donât put the hard sell on the customer in the owner response, but use this real estate with savvy. If thereâs 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 â act like it in the response.
Suggested owner response:
We were just thrilled by your review â in fact, we showed it to Chef Rosa, because the pique sauce you love is based on her grandmotherâs traditional recipe brought from Puerto Rico in the 1930s. Itâs the real deal, and weâre 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 thatâs all we can say! Weâd love to see you back soon, and Chef Rosa says, âThank you for the lovely compliment.â âBest in the Bay Areaâ makes us all proud!
Marta Sanchez, Owner
Type 2: âMy mind isnât made up yet.â
Diagnosis: A 3-star rating is the hallmark of the consumer who likes some things about your business, but isnât 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.
- Express gratitude for consumer complaints â 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 whatâs good and improving what isnât 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:
Weâre 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 wasnât 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.
Rob Brown, Owner
Type 3: âThere was hair in my taco…â
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 â 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 âsaves youâ by making their complaints known, an adept response from you may âsave themâ in return, earning their repeat business.
- Apologize!!! Say the words, âIâm sorry, I apologize.â
- No blame shifting, no lectures â just total accountability, humility, and a willingness to learn.
- Be as honest as possible about whatever circumstance led to the customerâs bad experience, and state what you’re doing to improve that circumstance. Sometimes, the circumstances may include faults on the customerâs 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 itâs just a few minutes of your time on the phone, to try to make it right.
- Aim for a âwowâ factor â as in you want future potential customers to say, âWow, this business really cares!â 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:
This is Dr. Tom, and I want to begin by apologizing for the inconvenience you experienced. I hate to think of you having wasted both time and gas on this. Iâm so sorry.
I regret that you missed the message about hours for the shot clinic on our homepage, and your review has made me concerned that other patients may be missing it, too. Thanks for alerting me to this. Hereâs what weâve done:
- Enlarged the homepage hours message + included those hours in the header of every website page
- Put this at the top of our Facebook page
- Updated our off-hours phone message to include the info that folks need to come in by 3:00 to ensure walk-in service.
Will you give me a second chance to make this right for you? Itâs so important that your pet gets proper shots. Please phone and let my receptionist know Dr. Tom is offering you a priority appointment, any day of the week, and Iâd like to make friends with your pup by treating him to one of our wonderful new chew toys. Hoping to have the great pleasure of caring for you and your awesome companion animal!
Type 4: âIâm actually your competitor.â
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 â it illustrates what a fake review might look like with sentiment that is negative but not accusing the business of criminal activity.
- If research has made you aware that a review has been left by a competitor or by someone who is not a customer, thatâs a violation of Googleâs 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 donât advise âoutingâ the bad actor â itâs not professional.
- Second, follow Googleâs 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 doesnât 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.
- Donât expect a quick fix. You may have to be persistent to obtain resolution.
- But, again, please donât take these steps if a review accuses your business of something illegal. Weâll 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.
Jim Davis, Owner
Type 5: âIâm citing illegal stuff.â
Diagnosis: Whether a negative review is true or false, any time illegal or dangerous behavior is cited, itâs a cue to you that you need to speak with an attorney before taking any further steps. Donât respond and donât 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 â weâre SEOs, not attorneys, and shouldnât 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 youâre managing multiple locations, numerous reviews per day.
- What you observe dictates how frequently you need to monitor your reviews. If youâre a Moz Local customer, weâll 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.
- Iâve 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 Googleâs 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 brandâs reputation.
Itâs 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.
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.
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 â things like rel=author â 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 â keywords a little less though, keywords haven’t been worried about for maybe 15 years now â 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 â alt attributes and in the header tag the title and the meta description, meta robots, canonical.
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 â 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 â 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 â recipes or news or videos or all sorts of stuff.
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.
The free one I love the most happens to be a Moz tool. I just really like it.
- 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.
With these options, I would love to actually hear from you in the comments if you have seen markup or tag options that are not covered here that you think are influencing SEO for a wide range of folks. Please bring them up. Let’s talk about them. Let’s talk about any of these you disagree with.
We’ll see you again next week for another edition of Whiteboard Friday. Take care.