Taking Advantage of Google's Bias Toward Hyper-Fresh Content - Whiteboard Friday

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Taking Advantage of Google's Bias Toward Hyper-Fresh Content - Whiteboard Friday Posted: 03 Oct 2013 04:08 PM PDT Posted by randfish In the last year or so, Google has increasingly displayed hyper-fresh content in SERPs, leading many marketers to think about how they can take advantage of that preference. In today's Whiteboard Friday, Rand explains a few ways to go about that without risking penalties. For reference, here's a still image of this week's whiteboard: Video Transcription Howdy Moz fans, and welcome to another edition of Whiteboard Friday. This week I want to talk a little bit about Google's strange and overwhelming in some cases bias to fresh content. I want to give a shout out to Glen Allsopp who had talked about this a little bit and written some blog posts exposing some of Google's priorities around freshness or what feel like priorities for them around freshness. Google's been biasing to fresh content, trying to show more and more fresh results, recently published results in their SERPs for several years now, but it's gotten particularly strong in the last 12 months in certain sectors. I think Glen had noticed it very strongly in some of the sectors that he was watching for some of his clients. We have seen it in some places very heavily, in other places not as much. But you can definitely feel it. There are places like Shakespeare plays. This is a search result that a few years ago, even 6 to 12 months ago probably you would not have seen much freshness, and now you're starting to see more and more of these types of things, results that call out when they were published, a feeling that things that are published more recently, even if they don't have as many links or as good of keyword targeting or as authoritative a website, those kinds of things are ranking a little bit higher. You're seeing news results in there, which is a relatively new development, especially on a phrase like this which the intent one might interpret as "well, they're probably looking for a list or maybe they're looking for plays in their area." So more and more of these cases Google is biasing to show recently published results, and, because of that, there are some opportunities for folks in the SEO field. If you're seeing this kind of thing in the results that you're looking at, seeing a lot of dates, especially a lot of recent dates, in particular recent dates on published content that seems to not have the ranking ability that you would expect of the rest of the pages, you could use something like the keyword difficulty SERPs analysis tool from Moz to kind of try and figure that out. This may be a real opportunity for you, and there are a few ways that you can take advantage. Number one, I suggest these kind of anyway. This isn't a, "Oh, I want to exploit something in Google's algorithm where they're weak, and I'm black hat, gray hat, and I'm trying to exploit it." This is actually Google saying, "Hey, we think users want fresh content, and so publishers please produce it because we're willing to put it in front of our audience." I think that's just fine. It could be that Google's a little over the line right now. Maybe they'll swing that pendulum back over time. But number one, find keywords and terms and phrases with fresh results, like we talked about here, and then target them with some new content. Give this a try. Essentially, if you're looking out and you're saying, "Gosh, this is a hyper-competitive keyword. I'm not sure that I can normally rank here. Let me see if I can get there for a day or a couple of days. Do I have the ability to start ranking on fresh stuff?" If you can't hit the front page, the first page of results with that particular phrase, try a little bit longer tail keyword term. Number two. If you have some old content, I think this is something that many of us experience. We have older content that's targeting valuable keywords, important keywords that are critical to our brand to attracting the visitors that we want, and those have fallen down in the rankings. It may be that you used to be in the top three or four, and now you're in the bottom half of the top ten results or on page two or three. Consider an update. I've done this several times and had a lot of success with it. Just updating an old blog post or an old resource, making it fresh again, adding new things, things that have emerged or come to light over the past few months or few years. Then a republication or promotion. The critical thing here is to think about: Do you want to produce that at the same URL, or do you want to do a redirect? This is a little bit tough because, generally speaking, what I like to do is keep these at the same URL if they are outside of an RSS feed. So, essentially, not a blog post or not a news item or those kinds of things. I like to do the redirection when it's, "Hey, I'm rewriting this old blog post. I've got a new version of it. You know what? I'm going to 301 redirect that old version to the new version." Or if I really want to keep it available at the old URL, I'll use rel=canonical to say, "Hey, this is the more updated version. This is essentially a duplicate, just a more recent duplicate, and here's the old one if you want to see that." Number three. If there are some hyper-valuable keywords that are consistently showing fresh results, you're just seeing this over and over and over again, well, maybe it's time for a regularly updated series. Think about columnists who do syndication, or they write a weekly column on a particular topic or around a specific subject or they do something once a month. This might be a big opportunity for you to say, "Hey, you know what? What's a piece of content that we could refresh every month, that would be on this topic, and we could consistently be in those fresh results and we could always be delivering the most recent, most valuable stuff?" Good example is in the sports world. The sports world changes so fast. There are different scores, different teams, rankings, standings. An old page is nearly useless. Unless you're updating that page every time there's new information, it's not that valuable. So I think those are exactly the kinds of places where you might consider some form of regularly updated either series, new posts, new publications, or a single page that you're regularly updating. Then number four, in terms of doing some research to try and find these types of phrases, obviously you can check out the SERPs if you're tracking in Moz Analytics and you're looking at your search results. You sort of can see those listed in there. But you might also use, to find some new phrases, things like Google Trends, Ubersuggest, which scrapes Google's suggest results. News sites, a lot of times when things are published that are news oriented, people will be doing searches around them. You can look at aggregators like Reddit or Alltop, social sites, obviously Twitter and Facebook, and these types of things to keep an eye on that. Double Click Ad Planner, which sort of has similar data too, but seems to be slightly different than Google Trends, and sometimes you can see some more stuff there, and Fresh Web Explorer, which of course is part of the Moz Analytics research tools package to find those trends. Last thing I'm going to say on this. There are a few rules that I have for fresh content. First off, fresh content doesn't just mean recycling and republishing. I realize that, because of this bias, sometimes, and Glen pointed this out in some of his posts, that you can take advantage of this simply by republishing similar content again and again. I would highly recommend against doing that. I think you're putting yourself at risk for things like Panda if you do it at a large scale or for manual penalties or for having low click-through, low engagement, high pogo sticking back to the search results. That kind of stuff is dangerous. Make sure you're serving the visitor's intent. Remember that with fresh content there's probably a recency intent on top of whatever other layers. So, if I'm publishing something about Shakespeare's plays, I don't just want to list, "Well, here are all the plays, and they were all written in the 17th century or 16th century, and so they haven't changed. He's not writing any new ones. Yes, but new things are constantly coming out. The news results show different types of stuff. The quotes are showing which ones are popular. There's a movies page that's showing which Shakespearean plays are being made into movies or which new spin offs are being done with Shakespearean concepts in them. So I do recommend that. I also suggest, if you can, get your site, get your feed included in Google news, and if that's not a possibility, at least have an RSS feed and be doing social shares on top of the content that you're publishing. Then last, but not least, be cautious about abusing dates. I realize that there's a few folks in the gray hat, black hat world who have been doing this and been having a little bit of success with it on and off, which is just sort of modify the dates on the page of publication to fool Google. I don't know why it seems to work sometimes. Or fooling them by adding new comments, which is sort of weird. We've seen this a few times with Moz blog posts, where an old blog post gets a comment. That comment has the date of the comment's publication, and that actually will make the results show up with that newer, fresher date, which is a little bit awkward and odd. I don't think that's a bad thing if it's just happening naturally and Google happens to be messing up, but if you're specifically abusing it, I think you could get into trouble. So I look forward to reading some great comments about what you're seeing in fresh results, how you're taking advantage of them. I'm sure you have some great suggestions for our readers as well. Take care. We'll see you again for another edition of Whiteboard Friday. Video transcription by Speechpad.com 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!

Operation Clean Air: Clearing Up Misconceptions of Yelp's Review Filter Posted: 03 Oct 2013 04:48 AM PDT Posted by David-Mihm Last week, the New York Attorney General's "Operation Clean Turf" fined 19 companies a total of $350,000 for writing fake reviews on behalf of their clients. The case sets a laudable precedent not only for the future of local search, but for digital marketing more broadly. While the amount of the fines is hardly Earth-shattering, the outcome of this operation should give pause to any SEO or reputation-management company considering quick-and-dirty, underhanded tactics to boost their clients' rankings, "improve" their clients' reputations, or launch negative attacks on competitors. In the wake of this settlement, however, a wave of media coverage and a study by researchers at the Harvard Business School have clouded the reality of Yelp's review filterâ€"already poorly understood by typical business ownersâ€"even further. In this piece I hope to dispel four misconceptions that it would be easy to conclude from these recent publications. Likely elements of review filters Review characteristics Use of extreme adjectives or profanity in the review Overuse of keywords in the review Inclusion of links in the review 1-star or 5-star rating (see discussion of HBS study below) User characteristics Total number of reviews a user has left on the site Distribution of ratings across all of a user's reviews Distribution of business types among all of a user's reviews Frequency of reviews that a user has left on the site IP address(es) of the user when leaving reviews Business characteristics A sudden burst of reviews preceded by or followed by a long lull between them. Referring URL string to business page (or lack thereof) 1. "Most aggressive" review filter ≠ "most successful" review filter Yelp representatives made little effort to contain their glee at being cited by the NYAG as having the "most aggressive filter" of well-known local review sites. In an interview with Fortune, Yelp's corporate communications VP spun this statement by the NYAG as validation that his company's filter was "presumably the most progressive and successful." As I stated in the same Fortune story, I agree 100% with the NYAG that Yelp's filter is indeed the most aggressive. Unfortunately, this aggressiveness leads, in my experience, to a far higher percentage of false positivesâ€"i.e. legitimate reviews that end up being filteredâ€"than the review filters on other sites. Google, for example, has struggled for almost as long as Yelp to find the perfect balance between algorithmic aggression and giving users (and indirectly, business owners) the benefit of the doubt on "suspicious" reviews. Now that a Google+ account is required to leave a review of a business, I suspect that the corresponding search history and social data of these accounts give Google a huge leg up on Yelp in identifying truly fraudulent reviews. I'm not necessarily saying that Google, TripAdvisor, Yahoo, or any other search engine presents the most representative review corpus, but it's a pretty big stretch for Yelp to equate aggression with success. 2. "Filtered reviews" ≠ "fraudulent reviews" To Yelp's credit, even they admit that legitimate reviews are sometimes filtered out by their algorithm. But you sure wouldn't know it by reading a recently published study by the Harvard Business School. In a throwaway line that would be easy to miss, the authors state that they "focus on reviews that Yelp's algorithmic indicator has identified as fraudulent. Using this proxy…" they go on to draw fourâ€"actually fiveâ€"conclusions about "fraudulent" reviews: Their star ratings tend to be more extreme than other reviews. They tend to appear more often at restaurants with few reviews or negative reviews. They tend to appear more often on independent restaurants rather than chains. They tend to appear more in competitive markets. "Fraudulent" 5-star reviews tend to appear more on claimed Yelp pages than unclaimed ones. The authors attempt to use statistical equations to justify the foundation of their study, but the fundamental logic of their equations is flawed. I'm by no means a statistical wizard, but the authors suggest that readers like me scan filtered reviews to validate their assumption. I would only highlight my friend Joanne Rollins' Yelp page, and thousands of other business owners' pages just like her, as qualitative evidence to rebut their logic. I don't dispute that Yelp's review filter is directionally accurate, but it's crazy to assume it's anywhere near foolproof to use it as a foundation for a study like this. It leads to self-fulfilling prophecy. In fact, there are five very easy explanations of their conclusions that in no way lead you to believe that the overlap between filtered reviews and fraudulent reviews is even close. Yelp uses star rating as part of its filtering algorithm. This is an interesting finding, but not applicable to "fraudulent" reviews. Restaurants with few reviews or negative reviews are engaging in proactive reputation management by asking customers with positive experiences to review them. This is simply a best practice of online marketing. While it violates Yelp's guidelines, by no means does it indicate that the reviews generated by these campaigns are fraudulent. Independent restaurants tend to be much more engaged in online marketing than chains. Speaking from years of personal experience, chains have by-and-large been very slow to adopt local search marketing best practices, from search-friendly store locators to data management at local search engines to review campaigns. Independent small business owners simply tend to be more engaged in their digital success than corporate managers. Restaurateurs in competitive markets tend to be much savvier about their digital marketing opportunities than those in less-competitive, typically rural markets. Engaged restaurateurs are more likely to pursue proactive reputation management campaigns (see bullet-point number two). While the HBS study highlights a number of interesting attributes of Yelp's review filter, it's simply impossible to draw the kinds of conclusions that the authors do about the truthfulness or fraudulence of filtered reviews. 3. "Filtered reviews" ≠ "useless reviews" I consider my friend Joanne Rollins to be a fairly typical small business owner. She runs a small frame shop with the help of a couple of employees in a residential neighborhood of NW Portland. She's not shy about sharing her ire with Yelp, not only around some of their shady sales practices, but especially about her customers' reviews getting filtered. Trying to explain some of the criteria that cause a review to be filtered simply takes too long, and Joanne is easily frustrated by the fact that a faceless computer algorithm is preventing testimonials from 13+ human beings from persuading future customers to patronize her business. On the customer side, they're usually disappointed that they've wasted time writing comments that no one will ever see. But all is not lost when a review is filtered! With permission from the customer, I encourage you to republish your filtered Yelp reviews on your own website. There's no risk of running afoul of any duplicate content issues, since search engines cannot fill out the CAPTCHA forms required to see filtered reviews. You as the business owner get the advantage of a few (likely) keyword-rich testimonials, and your customers get the satisfaction in knowing that hundreds of future customers will use their feedback in making a purchase decision. Marking these up in schema.org format would be the icing on the cake. 4. "Filtered reviews" ≠ "reviews lost forever" A review once-filtered does not necessarily mean a review filtered-for-alltime. There are steps that I believe will make their review more likely to be promoted from the filter onto your actual business page: Complete their personal Yelp profile, including photo and bio information. Download the Yelp app to their mobile device and sign in. Connect their Facebook account to their Yelp profile. Make friends with at least a handful of other Yelpers. Review at least 8-10 other businesses besides yours. Leave at least one review with each star rating (i.e. 1-, 2-, 3-, 4-, 5-). For those customers who are super-frustrated by Yelp's filtering of their review or with whom you, as a business owner, have particularly a strong relationship, consider requesting that they undertake at least a couple of those tactics. I certainly don't guarantee their success, but it's worth a shot. The reality of Yelp's review filter As the infographic above demonstrates, Yelp's excitement over the citation from the NYAG as having the most aggressive filter underlines a fundamental business problem for the company that I've written about for years. Yelp's fortunes are tied to their success in selling business owners advertising. Yet these same business owners: don't understand how the site works (at best) think that every Yelp salesperson is out to extort them (at worst) Despite commendable efforts like their Small Business Advisory Council, Yelp clearly has a long way to go in educating these business owners. And they certainly have a long way to go with reining in rogue salespeople. But the bigger issue is the consistent disconnect with their customers on the issue most important to their businesses--their guidelines for solicitation and display of reviews. Until they resolve that inherent conflict, I find it hard to see how they'll grow their revenues to the levels that Wall Street clearly expects. 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!

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