How to go above and beyond with your content

We’re creating a lot of content these days. It’s everywhere. Everyone is writing; everyone has a blog. I’m truly waiting for the day when my mom asks me how she can start a blog to impart her wisdom about how to behave properly in a restaurant.

With the nonstop stream of content being created, it sometimes seems like not everyone is really thinking about how to make their content stand out. I remember that a few years ago, a friend asked me why I hadn’t written a piece about some SEO topic that everyone else was writing about. I explained that I didn’t think I had anything to add to what was out there. If everyone else is saying it, why would you? Wouldn’t you rather say something else, or something better?

For example, around Halloween I was searching for lists of the scariest movies ever made. I kept finding great lists full of movies I’d never even heard of, but one big thing was missing: none that I found showed you where you could stream the films or rent/buy them.

All these articles had some unique perspectives to them, too. Some listed the trailers for the films. Some were filled with recommendations from famous actors and directors. However, for me, as a big fan of streaming services, I was quite disappointed to not see any that told me where to find them and linked to those sources. This definitely stood out as something that I’d have added myself.

Let’s take a look at this article from GQ: “The 7 Best Scary Movies You Can Watch on Netflix.”

It’s even about Netflix, but instead of giving you a link to the movie on that site, they show you the trailers. I mean I’m certainly capable of searching for a movie on Netflix (in fact, I’m pretty close to an expert on it) but as a link builder all I think is, “This is a wasted chance to link.” You see the section about the movie “Creep?” Wouldn’t it be nice if they’d linked to it on Netflix?

Here’s another example, from Thrillist, where the author could have linked out more: “15 Terrifying Movies That Prey On Your Phobias”

So they do tell you where to get the film, but they don’t link to it! Why not? And in the “Honorable Mentions” sections, they list other films but leave it up to you to go search for them. If I had a horror movie site, and someone approached me with an alternative piece that linked to where to find these films, I’d favor that over this one any day.

We can do better

The beauty of a tool like BuzzSumo or Ahrefs Content Explorer is that you can easily see what content is performing well on what platforms. If you see several articles getting a lot of traction on Twitter, and you have a very similar piece in the works, look at what they don’t have and add it to your own.

Notice how this POPSUGAR article on the best national parks links to the parks mentioned, as it should. You get great photos, too.

Now, take a look at this article on dog-friendly national parks. It gives great info, but I think they could do more.

This article has over 3700 shares, according to BuzzSumo.

To give you an example of how someone could use this idea and go above and beyond, here’s a great content opportunity for a site that sells dog collars to do a nice blog post on that same topic, linking to the parks themselves. Maybe they ask for visitors to send in photos of their dogs in these parks, wearing the collars they sell. That would be a nice way to get some great social shares, wouldn’t it?

Let’s go forward with that more specific niche and find one more example of something that could be made better.

Consider this article: “Which National Parks Are Dog-Friendly?” Again, wouldn’t this one be better if the article linked out to the parks it lists?

They do include some nice info, though. They provide a list of free admission dates for the year (the article was from 2016, so it’s for that year), and they have summarized the pet policies for each park, which is pretty nice. They don’t have a photo of each park, though, and since a national park is such a visual experience, all I’m thinking is, “Why not?”

It has 212 total shares according to BuzzSumo, but I think it would have had more if it had contained outbound links and more photos.

Now, even if you’re not trying to create new content, you could surely look at all of this and see that other articles about dog-friendly national parks did contain links and photos, and you could thus update your piece and re-socialize it. Maybe you could add videos of drone footage of the parks or give tips on the best times to visit each one. What about linking to camping options or other accommodations for each park?

For one thing, if you have content that doesn’t stand out for having all it could have, you’re opening yourself up to potentially losing that link to someone else. It’s like broken link building, really. “We noticed you have a link to X piece, but our Y piece actually gives more information — so would you think about replacing the old link with ours?”

I recently received an email asking me if I’d consider updating an old article where I linked to a tool review. The person reaching out said that on her blog, they had recently reviewed this tool and wondered if I could change my link to their review instead, as it was much more comprehensive and reviewed several new features. If I weren’t such a lazy person, I might be tempted.

So, what can you add to make your content better?

And last, but not least… outbound links! Don’t ever be afraid to link out if it helps your audience.

Some opinions expressed in this article may be those of a guest author and not necessarily Search Engine Land. Staff authors are listed here.

About The Author

Julie Joyce owns the link development firm Link Fish Media and is one of the founding members of the SEO Chicks blog. Julie began working in search marketing in 2002 and soon became head of search for a small IT firm. Eventually, she started Link Fish Media, where she now serves as Director Of Operations, focusing on working with clients in ultra-competitive niches all over the world.

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How machine learning impacts the need for quality content

Back in August, I posited the concept of a two-factor ranking model for SEO. The idea was to greatly simplify SEO for most publishers and to remind them that the finer points of SEO don’t matter if you don’t get the basics right. This concept leads to a basic ranking model that looks like this:

To look at it a little differently, here is a way of assessing the importance of content quality:

The reason that machine learning is important to this picture is that search engines are investing heavily in improving their understanding of language. Hummingbird was the first algorithm publicly announced by Google that focused largely on addressing an understanding of natural language, and RankBrain was the next such algorithm.

I believe that these investments are focused on goals such as these:

1. Better understanding user intent
2. Better evaluating content quality

We also know that Google (and other engines) are interested in leveraging user satisfaction/user engagement data as well. Though it’s less clear exactly what signals they will key in on, it seems likely that this is another place for machine learning to play a role.

Today, I’m going to explore the state of the state as it relates to content quality, and how I think machine learning is likely to drive the evolution of that.

Content quality improvement case studies

A large number of the sites that we see continue to under-invest in adding content to their pages. This is very common with e-commerce sites. Too many of them create their pages, add the products and product descriptions, and then think they are done. This is a mistake.

For example, adding unique user reviews specific to the products on the page is very effective. At Stone Temple, we worked on one site where adding user reviews led to a traffic increase of 45 percent on the pages included in the test.

We also did a test where we took existing text on category pages that had originally been crafted as “SEO text” and replaced it. The so-called SEO text was not written with users in mind and hence added little value to the page. We replaced the SEO text with a true mini-guide specific to the categories on which the content resided. We saw a gain of 68 percent to the traffic on those pages. We also had some control pages for which we made no changes, and traffic to those dropped 11 percent, so the net gain was just shy of 80 percent:

Note that our text was handcrafted and tuned with an explicit goal of adding value to the tested pages. So this wasn’t cheap or easy to implement, but it was still quite cost-effective, given that we did this on major category pages for the site.

These two examples show us that investing in improving content quality can offer significant benefits. Now let’s explore how machine learning may make this even more important.

Impact of machine learning

Let’s start by looking at our major ranking factors and see how machine learning might change them.

Content quality

Showing high-quality content in search results will remain critical to the search engines. Machine learning algorithms like RankBrain have improved their ability to understand human language. One example of this is the query that Gary Illyes shared with me: “can you get 100% score on Super Mario without walkthrough.”

Prior to RankBrain, the word “without” was ignored by the Google algorithm, causing it to return examples of walkthroughs, when what the user wanted was to be able to get a result telling them how to do it without a walkthrough. RankBrain was largely focused on long-tail search queries and represented a good step forward in understanding user intent for such queries.

But Google has a long way to go. For example, consider the following query:

In this query, Google appears unclear on how the word “best” is being used. The query is not about the best down comforters, but instead is about why down comforters are better than other types of comforters.

Let’s take a look at another example:

See how the article identifies that the coldest day in US history occurred in Alaska, but then doesn’t actually provide the detailed answer in the Featured Snippet? The interesting thing here is that the article Google pulled the answer from actually does tell you both the date and the temperature of the coldest day in the US — Google just missed it.

These things are not that complicated, when you look at them one at a time, for Google to fix. The current limitations arise because of the complexity of language and the scale of machine learning required to fix it. The approach to fixing it requires building larger and larger sets of examples like the two I shared above, then using them to help train better machine learning-derived algorithms.

RankBrain was one major step forward for Google, but the work is ongoing. The company is making massive investments in taking their understanding of language forward in dramatic ways. The following excerpt, from USA Today, starts with a quote from Google’s senior program manager, Linne Ha, who runs the Pygmalion team of linguists at the company:

“We’re coming up with rules and exceptions to train the computer,” Ha says. “Why do we say ‘the president of the United States?’ And why do we not say ‘the president of the France?’ There are all sorts of inconsistencies within our language and within every language. For humans it seems obvious and natural, but for machines it’s actually quite difficult.”

The Pygmalion team at Google is the one that is focused on improving Google’s understanding of natural language. Some of the things that will improve at the same time are their understanding of:

1. what pages on the web best match the user’s intent as implied by the query.
2. how comprehensive a page is in addressing the user’s needs.

As they do that, their capabilities for measuring the quality of content and how well it addresses the user intent will grow, and this will therefore become a larger and larger ranking factor over time.

User engagement/satisfaction

As already noted, we know that search engines use various methods for measuring user engagement. They’ve already publicly revealed that they use CTR as a quality control factor, and many believe that they use it as a direct ranking factor. Regardless, it’s reasonable to expect that search engines will continue to seek out more useful ways to have user signals play a bigger role in search ranking.

There is a type of machine learning called “reinforcement learning” that may come into play here. What if you could try different sets of search results, see how they perform, and then use that as input to directly refine and improve the search results in an automated way? In other words, could you simply collect user engagement signals and use them to dynamically try different types of search results for queries, and then keep tweaking them until you find the best set of results?

But it turns out that this is a very hard problem to solve. Jeff Dean, who many consider one of the leaders of the machine learning efforts at Google, had this to say about measuring user engagement in a recent interview he did with Fortune:

An example of a messier reinforcement learning problem is perhaps trying to use it in what search results should I show. There’s a much broader set of search results I can show in response to different queries, and the reward signal is a little noisy. Like if a user looks at a search result and likes it or doesn’t like it, that’s not that obvious.

Nonetheless, I expect that this is a continuing area of investment by Google. And, if you think about it, user engagement and satisfaction has an important interaction with content quality. In fact, it helps us think about what content quality really represents: web pages that meet the needs of a significant portion of the people who land on them. This means several things:

1. The product/service/information they are looking for is present on the page.
2. They can find it with relative ease on the page.
3. Supporting products/services/information they want can also be easily found on the page.
4. The page/website gives them confidence that you’re a reputable source to interact with.
5. The overall design offers an engaging experience.

As Google’s machine learning capabilities advance, they will get better at measuring the page quality itself, or various types of user engagement signals that show what users think about the page quality. This means that you will need to invest in creating pages that fit the criteria laid out in the five points above. If you do, it will give you an edge in your digital marketing strategies — and if you don’t, you’ll end up suffering a a result.

Summary

There are huge changes in the wind, and they’re going to dramatically impact your approach to digital marketing. Your basic priorities won’t change, as you’ll still need to:

1. create high-quality content.
2. measure and continuously improve user satisfaction with your site.
3. establish authority with links.

The big question is, are you really doing enough of these things today? In my experience, most companies under-invest in the continuous improvement of content quality and improving user satisfaction. It’s time to start putting more focus on these things. As Google and other search engines get better at determining content quality, the winners and losers in the search results will begin to shift in dramatic ways.

Google’s focus is on providing better and better results, as this leads to more market share for them and thus higher levels of revenue. Best to get on board the content quality train now — before it leaves the station and leaves you behind!

Some opinions expressed in this article may be those of a guest author and not necessarily Search Engine Land. Staff authors are listed here.

About The Author

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Author: Eric Enge

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AdWords IF functions roll out for ad customization as Standard Text Ads sunset

First, a moment of silence for the Standard Text Ad format that held on for 15+ years. Today marks the end. And with that, Google is rolling out AdWords IF functions globally to give advertisers the ability to customize their ads in much the same way ad customizers allow, but without the feed.

With IF functions,text ads can be tailored based on whether users are on mobile and/or a member of an audience list. For example, Frederick Vallaeys wrote in his column about using the IF function for mobile last fall when the feature was first announced as a way for advertisers who were running mobile preferred Standard Text Ads to continue customizing ads for mobile users.

In the example below from Google, an If function is used to customize the description offer based on whether a user is in the advertiser’s “Cart Abanodoners” retargeting list. If they on the list, users will see a “15% off” promotion; if not, they’ll get a “10% off” offer.

Syntax

Broken down, the syntax for IF functions is:

1. Start with “{=IF”
2. Add an open “(” after IF
3. Follow with the targeting of “device=mobile” or “audience IN”
   1. If you’re using audience targeting, put the list you want to target inside parentheses. If you are targeting multiple audience lists, separate them with a comma.
4. Put a comma after the targeting
5. Add the text to insert when targeting criteria is met
6. Close “)”
7. Follow with a colon “:”
8. After the colon, add the default text that will be used when the targeting criteria is not met
9. End with the closing curly bracket “}”

Put together it looks like this:

{=IF(device=mobile or audience IN(audiencelist1,audiencelist2), Custom Text): Default Text}

A few more things to note

If you’re creating ads in the web UI, the IF function option will become available when you enter a curly bracket “{“. However, for now at least, it defaults to the mobile targeting syntax: {=IF(device=mobile,insert text):default text}. You’ll have to change it for audience targeting, and be sure to use the exact list name.

IF functions can be used anywhere in an Expanded Text Ad except for the final URL. They are only eligible to run on the Search Network.

And last but not least, with the default text provided with IF functions, advertisers don’t have to have an ad that doesn’t use customizers ad in their ad groups.

About The Author

As Third Door Media’s paid media reporter, Ginny Marvin writes about paid online marketing topics including paid search, paid social, display and retargeting for Search Engine Land and Marketing Land. With more than 15 years of marketing experience, Ginny has held both in-house and agency management positions. She provides search marketing and demand generation advice for ecommerce companies and can be found on Twitter as @ginnymarvin.

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How martech has made ABM-at-scale possible

Account-Based Marketing (ABM) isn’t a new thing.

The idea that B2B salespeople target a few key corporate accounts — using spears instead of marketing’s widely-cast nets, as some have metaphorized — has been around for a while.

What is relatively new is the ability to do this at scale, intelligently and automatically. When the definitive history of marketing technology is written, the creation of this army of spears will be one of its most important consequences.

Major marketing platform Marketo, for instance, added ABM to its resume in 2013 when it bought Insightera. From Marketo’s website:

“Because ABM requires more account-level personalization than traditional marketing it has historically cost more to implement. However, advances in marketing technology have enabled marketers to employ ABM for much less than previously possible and at much greater scale.”

In part because of the tech tools available, ABM is now common. A 2016 report from SiriusDecisions on the “State of ABM,” for instance, found that over 70 percent of B2B firms have now completely or partially adopted ABM as a strategy.

In a way, the adoption of ABM is a counter-movement to two other marketing and sales strategies: inbound marketing, which uses content and other means to drive leads to sales, and the age-old technique of marketing based on customer personas, which has largely been based on demographic assumptions about customer types.

[Read the full article on MarTech Today.]

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About The Author

Barry Levine covers marketing technology for Third Door Media. Previously, he covered this space as a Senior Writer for VentureBeat, and he has written about these and other tech subjects for such publications as CMSWire and NewsFactor. He founded and led the web site/unit at PBS station Thirteen/WNET; worked as an online Senior Producer/writer for Viacom; created a successful interactive game, PLAY IT BY EAR: The First CD Game; founded and led an independent film showcase, CENTER SCREEN, based at Harvard and M.I.T.; and served over five years as a consultant to the M.I.T. Media Lab. You can find him at LinkedIn, and on Twitter at xBarryLevine.

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Author: Barry Levine

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The 3 challenges all social CMI professionals face (and how to overcome them)

Fact: Social insights offer value to many areas across the enterprise.

This fact indicates the need for a dedicated social consumer market insights professional (social CMI) within the enterprise. In my previous article, I outlined the shift of this relatively new position from a “nice-to-have” to a “must-have” in order to achieve higher business goals.

The incredible impact social data has on marketing efforts (traditionally what it has been used for) is shifting to support every team outside of the boardroom — including customer service, product development, human resources and beyond. But this powerful role does not come without its challenges. This article in our series will explore three of the hurdles faced by social CMI professionals and tips to managing them.

Getting executive buy-in

The social CMI professional equips organizations with insights that allow functions across the business to drive better results and meet market needs more intelligently. This matters to the C-suite. But until the folks in the boardroom recognize this role as instrumental and impactful on the bottom line, it might be a tough sell.

It’s an ambitious role — high-level and demanding, with the potential for a strong business impact that requires a specific skill set. So how do you get executive buy-in?

Provide solid, tangible proof.

We recently sat down with CMI leaders from some of the world’s biggest brands and agencies, and everyone agreed: Based on the experience within their organizations, the use of social data for collecting consumer insights proves invaluable for uncovering the unfiltered voice of the customer. This asset provides organizations with a deeper understanding of the market from a holistic level.

Sharing data around growth and success stories that tie directly back to the role of the social CMI professional can help the board and top executives understand why now is the time to take a chance on adding the position.

Proving the value of social insights across the enterprise

Previously, we discussed the importance of the social CMO and how social insights proved its ROI as it related to the marketing world. The social CMI professional marks the evolution of this success.

Based on the key learnings from leveraging social data to drive marketing initiatives, it’s clear that social data is ready for prime time. Providing examples of the impact this data had on marketing based on real experiences is key to helping break down the walls that have long existed between departments.

Educate disparate departments about the power of social data, and how it opens up a world of unprompted, detailed consumer opinions, needs and motivations for needle-moving results. Along with education, it’s vital to understand the social acumen of these disparate department heads.

Tailor your messaging around social to address varying levels of understanding to get social beginners excited.

Extracting real insights from social noise

The social landscape is a vast sea of data, and social CMI professionals strive to realize actionable insights from this information that can drive business decisions and impact ROI.

Before diving into any data set, identify and articulate specific goals that will serve to drive research efforts. By executing this first essential step of the research process, your team will be able to procure more precise, valuable data and weed out information that is irrelevant to the project.

Determine a question to answer that will help your company understand a customer’s wants and needs and how the business can address those needs — whether it’s in customer service or product development. Make sure that this information is what stakeholders are looking for to ensure it will be useful to them and further strengthen executive buy-in.

Second, determine the role that social data can play within all other marketing tool kits. When can it replace other methods or be directly integrated? Blending social CMI with traditional research methods is key to discovering insights, and the combination can make it far more powerful.

Use social data to inform primary research or add context to existing information. For example, anonymous surveys can be used to gather sensitive information that may be too private for consumers to share on social.

When layered with sentiment data from social, it gives researchers a deeper level of understanding. Social data can also be paired with CRM (customer relationship management) data to enhance information and provide even more insights on an existing database.

As the socially savvy CMI professional role emerges and gains credibility within organizations and in different industries, new challenges will arise. Social CMI professionals will be accountable for proving the value of social research and will need to demonstrate its benefits.

However, the proof is in the pudding. Social insights can positively impact every team within the organization and be used to make powerful business decisions beyond marketing departments.

Now it’s a matter of getting everyone on board and turning those social insights into real, tangible action.

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Some opinions expressed in this article may be those of a guest author and not necessarily Marketing Land. Staff authors are listed here.

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About The Author

Will McInnes is CMO of social intelligence platform Brandwatch. His passion is social data and how it can shape industries, policies, research and innovation. He’s also a board member of the Big Boulder Initiative, whose mission is to establish the foundation for the long-term success of the social data industry. Previously Will co-founded and ran NixonMcInnes, a consultancy which pioneered in early social media marketing and went on to change how more than 30 major corporations, charities and governmental departments behave, particularly in response to social and digital. He authored Culture Shock, a 21st-century handbook for business with an average review of 4.5 stars on Amazon and was a TEDx speaker in 2011.

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Sizmek’s dynamically-assembled ad serving now includes audience segments from DMPs

Sizmek provides a Programmatic Creative ad serving solution, where ads are assembled on-the-fly so that their design and content can be better tailored to specific audiences.

This week, the Austin, Texas-based company is launching a new Data Hub that integrates with data management platforms (DMPs) for the first time.

This means that Sizmek customers can now target these dynamically-assembled ads by DMP-delivered audience segments, which can be enhanced by previous ad history.

A segment of users who have previously visited sports content or sites, for instance, might be shown a different ad from a maker of trucks if they’ve been previously served an ad from that manufacturer, possibly creating a story sequence of several ads. Both the DMP-based audience segment and the use of ad history are new to Sizmek.

[Read the full article on MarTech Today.]

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About The Author

Barry Levine covers marketing technology for Third Door Media. Previously, he covered this space as a Senior Writer for VentureBeat, and he has written about these and other tech subjects for such publications as CMSWire and NewsFactor. He founded and led the web site/unit at PBS station Thirteen/WNET; worked as an online Senior Producer/writer for Viacom; created a successful interactive game, PLAY IT BY EAR: The First CD Game; founded and led an independent film showcase, CENTER SCREEN, based at Harvard and M.I.T.; and served over five years as a consultant to the M.I.T. Media Lab. You can find him at LinkedIn, and on Twitter at xBarryLevine.

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Author: Barry Levine

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Majestic successfully prints the internet in 3-D in outer space

As you may remember, Majestic, an SEO toolset company, set off on a voyage last year to print the internet in 3-D in outer space. Well, we are glad to report that the mission has been a success.

After 18 months, the “Majestic Landscape,” which is a 3-D data visualization sculpture that depicts the internet graph, was printed on a 3-D printer designed to work in zero gravity on the International Space Station.

Matthew Napoli, the VP of In-Space Operations for Made In Space, Inc. said, “The print looks really good. It was exciting to be able to print those complex digital features in microgravity and see the great results.”

Dixon Jones from Majestic said, “The #MajesticInSpace Project has been about expanding ideas, expanding knowledge leadership and about believing that data can be more than just numbers on an [E]xcel spreadsheet. I think that it also inspires people within our industry to say we are doing more [and] there is more that we can do in the world to advance humankind.”

Here is a photo:

Here is a video from Majestic on this mission:

Here is a GIF of it floating in the space station:

About The Author

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Author: Barry Schwartz

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