Is Google Judging You Based on a Template?

Posted by ajfried

Thinking in templates

We all judge people on first impressions. When we see someone for the first time, we're quick to decide what type of person they are — based on the clothes they wear, how they style their hair, and anything else we notice that immediately puts them in a group.

It’s certainly not fair, but it’s human nature. And I'd like to keep my faith in humanity and argue that lots of us try NOT to prejudge others.

Google is judging you

Believe it or not, Google is the same. It judges, too. Some might disagree with this theory, but our internal research supports it, as you'll see in the data below. Google pre-classifies every single search term into a group for later recall.

Is that fair?

Is Google fair about how it does this?

Imagine, for a moment, that you're about to walk onto the stage of MozCon. You've spent months preparing and you have new and thought-provoking research to share. You are legend and you're about to blow everyone’s mind. And as you make your way up... SPLAT! You fall right on your face. I mean, really wipe out.

You'll probably recover, because you're dynamic and you'll still nail your presentation. However, you'll also be forever stamped as the one that fell on your face during the conference.

Is it fair that people treat us this way? Or how about Google? Is it fair that Google judges us like this, that we're classified into select groups, or that Google may show years-old negative content about us or our clients?

I think most people would agree: it’s not. Something that's truly not relevant to an individual's or brand’s storyline shouldn't be appearing prominently in a query for their name. An event that's nothing more than a blip on the radar shouldn't become the most important thing you see about them.

Yet, often it is. More often than you think. Some of the biggest brands in the world are dealing with this problem — having unfavorable content appearing for their name — and desperately try to get rid of it.

How does Google feel about ranking content?

On Google’s About page, Larry Page describes a perfect search engine as something that "understands exactly what you mean and gives you back exactly what you want."

As an example, it states: "This means making search smarter and faster, so it can understand that when you type in [jaguar] you’re looking for the car, not photos of the animal."

Well, first of all, they might want to find a different example, because queries without context can't hint at intent, as you'll see below.

Intent is really difficult

It’s a basic issue of not knowing what the context is for the query. And, arguably, some of the most important searches don’t have context. A brand? An individual? There's nothing necessarily unique about these searches to give them context. For example, if I search for "Applebee's" from my phone, there's context behind it. I'm on my phone, I'm in the vicinity of a restaurant, I'm probably hungry. But a query for, say, a gentleman named "James Young" is useless, as it gives Google no context or basis for figuring out which results might be most relevant. Do I want to know where he lives? When he was born? What kind of work he's in?

Arguably, these queries without context are the most important queries, and they're where audiences form opinions about brands. [Tweet this]

So, is Google out to get you?

Sometimes, it can seem like it is when your search results don’t reflect who you are or the content you're putting out into the world. Truth is, though, Google's probably not out to get you — in reality, it's an emotionless machine.

As I've mentioned previously, I don't believe it's evil. I think it's a machine controlled by an algorithm, with imperfections and flaws. Choices must be made based on the information available. Sometimes there isn’t enough to work with, or the right information that it'd like to show is missing, so it makes the wrong choices.

So... How do we change what Google wants to show?

Learning from Google’s templates

Google’s job is to show you what you're looking for. This can only be done by finding patterns and trends. Behind all the search results are templates that every query needs to fit in to.

When you perform a search in Google, you're effectively seeing whatever information it wants to show you on that day. It's a ton of information — but it’s not data. If you're able to collect all that information and trend it, an unbelievable amount can be learned.

For example, among the top 100 hedge funds:

• 74% have their homepage at position 1
• 72% have a knowledge graph
• 38% have Wikipedia at average position 4.41
• 74% have LinkedIn on page 1

Having this data, you start to uncover a deeper meaning behind the search results. You expose the template Google has created for this "type" of query. It should come as no surprise that these templates will change from industry to industry.

Understanding search result templates and trends by industry

The graph below gives a breakdown of what shows up in search results for these industries. (Note: the percentages are the percentage of Google page 1 results.)

Some notable observations:

• Telecommunications companies have more results that are corporate on page 1 of Google than pharmaceutical companies do.
• Pharmaceutical companies will have significantly more media content appearing in their search results than an engineering/construction company.
• Food/drug stores don't usually get stock quotes appearing in their results.

Using data to create the content Google wants to show

Armed with this information, you can now identify what kind of content Google wants to show for you or your brand.

While we've all heard a million times that "content is king" and we should create more content, the reality is that only the RIGHT content is what’s going to make the difference. Content is not churning out post after post after post of products and other junk. Rather, content is about creating an impression that enhances the brand in the viewer's mind.

Practically, this idea of templates becomes extremely important in planning the right content for your brand. If you can use these templates to identify certain trends appearing for brands similar to your own, you can create the content Google wants to show.

Case studies and analysis

To help articulate this point, I want to share a few case studies.

Case study #1: The not-for-profit president that seems unfavorable

Take, for example, a client we had in the not-for-profit industry. He was the president of an organization and notable enough to have a Wikipedia profile, as did all of his competitors. His corporate site and social profiles were ranking relatively consistently with everyone else, and he authored content regularly. However, he had a disproportionate amount of media coverage about him compared to his competitors, causing negative content to rank prominently.

What became clear was that all the authored content was on his corporate sites, as opposed to a leading industry publication. Content creation was happening, but it was being put in the wrong place. According to the data, someone like this individual should be generating content on reputable industry publications.

Result: We worked to migrate some of his content to relevant publications. With a few relevant links, it began ranking within a few weeks.

Case study #2: The CEO gets all the news!

Another example was the CEO of an asset management company who had a disproportionate amount of news content appearing about them, some of which was negative. This caused frequent changes to the search results for the individual's name and a lack of branding around their name.

When you examine the results closer, you notice that on average, the CEO of a company like this would have two non-owned, executive-style profiles on sites like Forbes, Bloomberg, or Fortune.

Result: This individual was missing from notable lists, specifically the Forbes billionaire list. Working with the communications team, he was included in the list, displacing some of the negative content.

Case study #3: The need for more ownership

The final example I'll offer was of a client who had been trying to brand themselves through the use of content, blogging, press releases, and other similar information.

The biggest problem they had? They already had a nice amount of “ownership” within their search results. That means they had full and total control over half of the results appearing. Based on the peer analysis, it was going to be highly unlikely that they'd get more than that.

However, when we ran a frequency analysis, we noticed that every single one of their competitors has a GuideStar profile appearing.

The only differentiator between our client and their competitors was the level of their profile, which is earned by completing it. They were at silver, while everyone else had gold status (Note: there's some speculation about the level of status).

Once we helped them build up their profile to gold, we added a few easily-attainable and relevant links pointing to the profile. Easy ones, like from their corporate website. It doesn’t get more legit than that.

Result: Within a matter of weeks, we saw the profile ranking at the bottom of page 1, displacing negative content about the brand.

Practically using this information

At the end of the day, Google is nothing more than an organized system. We sometimes give it too much credit because it happens to be REALLY good at understanding what we want and mean. But this is based on an organized understanding of how we (all humans that use Google) use the search engine.

Not all content can rank for all types of queries. Just because a certain result appears for one query doesn’t mean that another will; randomly creating a bunch of profiles is not going the solution. For example, if you happen to be one of the 200 richest Americans in the world, Pinterest is not likely to rank for you. (It appears for 3 of them on page 2: Randa Williams, Milane Frantz, and H. Ross Perot Sr).

Using historical and competitor analysis, understanding what type of content is frequently appearing will give you tremendous insight into the kind of content you should be building to fit into the template Google has built for your brand.

One final note

The only loose end in this process is the thought that you're now "stuck" in a template. Once Google perceives you a certain way, is that it? Are you stuck? Can the CEO who loves arts and crafts convince Google that Pinterest should rank prominently for queries with their name?

There is some subjectivity to this, to be sure, but the entire process above is by far the path of least resistance. This is the content Google wants to show for queries about you or your brand, based on trends of others in your industry.

If you create an experience on that network that's highly popular, engaging, and something in which you invest a lot of time and effort, I think it's fair to say that it could change how search engines classify you. But convincing someone to blog or use social media when it’s not something they'll do aggressively or passionately usually doesn’t end well. Most people have these profiles, but that doesn’t mean they actively use them.

These templates exist because of the type of information that typically shows for these queries. It’s low-hanging fruit. If you have info that doesn’t make sense for who you are, it likely won’t appear right away without really hard work.

Work with the algorithm and make sense of which content it's clear that the search engine wants to show. If you create that content, it will rank.

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Accidental SEO Tests: How 301 Redirects Are Likely Impacting Your Brand

Posted by Wayfair

This post was originally in YouMoz, and was promoted to the main blog because it provides great value and interest to our community. The author's views are entirely his or her own and may not reflect the views of Moz, Inc.

At Wayfair.com, we conduct a lot of SEO tests. We're constantly measuring and evaluating our strategies, some of which were shared in our last post for YouMoz, Accidental SEO Tests: When On-Page Optimization Ceases to Matter. Sometimes, however, we stumble across what we call "accidental SEO tests." This typically happens when a bad code deploy unintentionally hurts our SEO, and we end up learning something useful from our mistake.

Tens of thousands of 301 redirects

One of our accidental tests involved regularly 301-redirecting large batches (i.e., tens of thousands) of product pages. On average, we found a consistent (and essentially permanent) traffic loss of about 15% for 301-redirected URLs.

In the past, Google has said a small amount of PageRank is lost through a 301 redirect, which is the same as through a link. Now, for the first time, we can put a hard number to how much that loss is.

Structure of an accidental SEO test

Like any good SEO team, our product pages were set to use the name of the product in the URL. Furthermore, if for any reason a product URL was changed, the old URL was set to automatically redirect to the new one.

What we didn’t realize, though, is that our merchandising teams were also busy being good at their jobs, part of which involved changing the naming standards of products on a regular basis. Every change they made was good for the customer. But when the the naming standards changed, it caused thousands of products to change names. This, in turn, updated the URLs of those product pages, triggering a 301 redirect on every page.

For example, when updating for the purpose of having a consistent style, the merchandising team changed “barstools” to the more accurate two-word version of the product name, “bar stools.” Wayfair had over 8,000 bar stools, all of which 301-redirected to a new URL following the name change. Then, a couple of months later, the merchandising team found that they were getting better results by including the height of the bar stool in the product name, so they updated the product names again, which resulted in the product pages 301-updating once more to a brand new set of URLs.

This process of updating product names was being implemented across dozens of different product classes, with multiple updates per month. It quickly added up to a lot of 301 redirects.

Measuring the impact

After reshaping our URL logic to prevent the constant redirects, we realized that we had a great opportunity to find out exactly how 301 redirects affect organic traffic. Nailing down data was easy. We had the exact dates of the changes; groups of thousands to tens of thousands of pages, with tens of thousands of organic visits; and could compare those classes against others that we knew didn’t change to exclude the impact of Wayfair’s overall increase in organic traffic.

We found with surprising consistency that we had a drop very close to 15% of organic traffic for any product class that changed URLs. In our bar stools example, we lost just under 15% of organic traffic at the first change. When the URL changed again over a month later, we lost another 15%.

Every product class we looked at showed the same drop within one to two weeks of the change. Sometimes the drop was almost immediate (like with bar stools); other times, however, it was spread out over a couple weeks (e.g., area rugs, with over 30,000 products).

We did not see any evidence of recovery from the impact of the 301 redirects, even after many months. There was the appearance of recovery — class traffic levels eventually returned to where they started — but that was because our overall organic traffic was increasing across the entire site. We were still 15% below where we would have been without the redirects.

What’s particularly fascinating about this number, 15%, is that it is exactly the amount of PageRank loss Google described in the original PageRank paper. So our measured results matched theory with surprising precision. Perhaps the broader authority signals Google now measures follow the same logic for flowing through pages as they did in 1998? Or perhaps it’s just a happy coincidence.

What it means

We’ve always known there was a “small” cost to implementing a 301 redirect, but our accidental SEO test showed us that the cost is quite significant, and it becomes much greater with every hop in a redirect chain.

It’s worth stressing, however, that we are not saying that 301-redirecting any particular page is going to cost you 15% of your organic traffic. If you rank in position #1 for competitive terms, a redirect could drop you to position #2 or #4. That would cost you far more than 15% of your organic traffic. On the other hand, your page could be so strong that you may not not see any loss in rankings after redirecting it.

What our data suggests is that, on average, there’s a 15% traffic loss following a 301 redirect; but any individual redirect could be much better, or much worse.

While 301-redirecting a dead or changed page to the new location is still good practice, the best practice of all is not to change your URL in the first place.

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Leverage This Social Network Mind Trick for More Effective Influencer Marketing

Posted by KelseyLibert

Did it feel like everyone you knew was watching “Making a Murderer” at the same time? It may have just been an illusion, thanks to a few key members of your social network.

Researchers at the University of Southern California recently uncovered that when something appears more popular than it actually is, it can create the right conditions for it to be widely spread. They named this social network phenomenon the majority illusion, which happens due to highly-connected individuals within a social network skewing the group’s perception. These findings explain something we already knew — well-connected individuals can wield extraordinary influence. The majority illusion may also explain why it can take only a handful of the right influencers to make something go viral.

Marketers can leverage the majority illusion to create the tipping point needed to drive action or spread a message far and wide. It starts with identifying influencers who have the potential to create the majority illusion among your target demographic, and then encouraging those influencers to help amplify your message.

How social influencers can create the illusion of popularity

Are you surprised when your non-marketer friends are completely unaware of something that was major news in the marketing world? You may think it’s popular because you kept seeing it discussed by key members of your network, which can give the impression that it’s universally popular.

Image source

Let’s say that in the figure above, each of the colored nodes is a Nickelback fan. The networks are identical, except different people are Nickelback fans in each figure. Since the Nickelback fans in figure A have more connections, it may appear to their network that Nickelback’s music is popular. This is how the majority illusion can create the impression within a group that an idea, behavior, or attribute is common, even if the opposite is true.

How a social network is structured

By illustrating how a social network is organized, we can see how an idea can potentially spread across communities or stay within a select group.

We modeled a network graph of 77 Twitter influencers across eight different verticals: automotive, business, entertainment, finance, health, lifestyle, technology, and travel. Influencers were chosen based on criteria including relevance to a vertical and engagement. In order to create a usable graph, we then narrowed down the influencers’ 19 million followers to about 8,600 second-degree influencers. We chose those users based on a set of criteria that signaled mid-level influence: a following greater than 30,000, a follower to following ratio of at least 1:1, and a “lists per followers” rate of at least 6.5 (the number of times they have been added to a Twitter list per thousand of followers). Side note: Wondering why you can’t find Rand? He’s too popular to meet the parameters we set for a “mid-level” influencer.

The resulting network illustrates the hierarchical relationships of first- and second-level influencers within a social network. Click here to see the full interactive graph.

The nodes represent individuals, while the relationships between individuals are expressed as lines. The larger a node, the more relationships the individual has within the network. It’s important to understand this does not mean the large nodes have the most followers within the network; rather, they have the most connections within a particular network (some being first-degree, second-degree, third-degree connections, etc.).

By examining this graph, you can see that social influence is more like six degrees of Kevin Bacon than a popularity contest. Because of this, marketers should focus on getting their message spread by influencers within a focused niche or strategically-positioned influencers to maximize reach, rather than looking for influencers who merely have a large following.

Finding strategically-positioned influencers

Tools such as BuzzSumo and Followerwonk are a good jumping off point for finding influencers within a vertical. But you want to look at more than the number of followers, because influence depends on far more than popularity.

There are three main factors for determining the most powerful members of a network:

• Betweenness Centrality: An individual’s location between different sections of a network
• Degrees: The number of connections, or edges, an individual has
• Closeness: The average number of degrees between the individual and others in the network

So which of these variables are most important? It depends on your goals.

Do you want people to take an action? Niche influencers may be best to create the majority illusion and give the impression of popularity, thus spurring others to mimic their behavior. An influencer’s closeness may be the most important factor in this case, since it signals they share a lot of connections with other individuals in their network. When you consider all of the common relationships within a niche group, it’s easy to see how these groups are susceptible to the majority illusion effect.

Are the goals for your content expanding brand awareness or increasing viral potential? Influencers with connections to other communities may be most effective for reaching a large audience. Betweenness centrality is the greatest signal of strategic positioning, since it shows the individual’s potential to influence and connect different groups.

Influencing a niche group

If you want to create the majority illusion within a niche-focused group, target influencers with followers similar to them who have a low number of followers.

Notice how some groups are isolated on the edges of the graph. We can assume the “majority illusion” is likely to happen within these groups since they have little to no overlap with the other communities.

The researchers found that the majority illusion occurs most frequently in networks where individuals with a low degree of connections tend to connect with individuals with a high degree of connections. Those with a low number of connections may be easier to influence since they aren’t exposed to a wide range of ideas and opinions — plus they have less noise in their stream, so they are likely to see what the influencer posts.

Getting a handful of niche influencers talking about your brand within the same time period may be the key to creating an impression of popularity. I see this happen all the time on niche blogs, where several blogs do a sponsored post or review of the same product within a short time period. It does have the effect of making it feel like you’ve seen something everywhere, even though only a few people are talking about it.

Influencing a wide audience

If you want your content amplified to the widest possible audience, target influencers who are followed by other influencers and have diverse connections across different communities.

The closer an influencer is to the center of the graph, the more visibility they have across multiple verticals. This gives your content a better chance of escaping the echo chamber likely to occur within the more isolated groups. Individuals strategically positioned within their network, rather than those who are the most popular, may be the most effective at influencing a large number of people.

Two great examples of this within our network model are Ann Handley (@MarketingProfs) and Daniel Pink (@DanielPink). Notice how their connections are spread across different groups.

Example: @MarketingProfs

Example: @DanielPink

You don’t need to build your own social network graph to identify influencers with high betweenness centrality. Look for a mix of these two factors to spot strategically-positioned influencers:

1. Influencers who are followed by other influencers. Consider the ripple effect that can happen when an influencer shares something and then other influencers following them share it.
2. Influencers who are followed by people across multiple verticals. Potential reach is greater among influencers who have a diverse following, since their followers can spread things throughout multiple networks.

Need help finding the right influencers? Check out our guide to identifying effective influencers. Once you pinpoint the influencers who can help you achieve your desired goal, be sure to deploy Rand’s advice on getting influencers to amplify your message.

By visualizing the structure of a social network, you can see that having a lot of followers doesn’t necessarily equate to influence. Influencers within closely-knit groups may be best suited for influencing their followers to take action or adopt an opinion, since this type of group is primed for creating the majority illusion that "everyone’s doing it." To reach a large audience, marketers should enlist the help of influencers who are strategically positioned between social communities, rather than those with a Kardashian-sized following.

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Revisiting "Navigational," "Informational," & "Transactional" Searches in a Post-PageRank World

Posted by Tom-Anthony

SEOs traditionally say that a specific search query can be classified as either navigational, informational, or transactional. The categories were originally published in 2002 in a peer-reviewed paper by Andrei Broder who worked for Altavista (remember them?!) at the time.

The categories that Broder came up with have been invaluable to SEOs for many years, helping many of us explain the different types of search query that we should consider.

However, it's time to revisit these categories to see if we can improve their usefulness in a world of direct answers, apps, intelligent personal assistants, and other developments.

Recap

For those who haven't reminded themselves recently, here is a quick recap of the three categories:

• Transactional – Here the user wants to get to a website where there will be more interaction, e.g. buying something, downloading something, signing up or registering etc.
• Informational – This is when the user is looking for a specific bit of information.
• Navigational – The user is looking to reach a particular website. There's only one likely destination that they're looking to reach.

Google, in their human rater guidelines, call these three categories:

• Do
• Know
• Go

Google also widened the definition of the categories slightly from their original paper. Interestingly, Andrei Broder, who created the original categories, now works at Google.

Beyond the Web

However, what is important to understand is that Broder's was proposing "A taxonomy of Web search" — i.e. the categories were designed for web searches. Even though Google widened the definition of these queries in their Do-Know-Go framework, they also still discuss them in terms of web search.

Here's the thing — so many of the searches we do nowadays are not web searches at all. Various papers have estimated differently, but most estimates (here, here, and here) are that around 50–80% of searches fall into the "informational" category, which is the category that often lends itself to a direct answer:

Furthermore, we are more and more frequently searching, not via a web-powered search bar on a desktop machine, but instead via an Intelligent Personal Assistant app (IPA):

In the most recent revision of their human rater guidelines, Google introduced a new category — Know Simple — for informational queries that can be answered with a short (< 2 sentences) answer that has an uncontroversial answer, i.e. the type of answer that is suited for these direct answer-type responses. You should read this great post on takeaways from the latest quality rater guidelines from Jennifer Slegg to read more about Know Simple and other interesting tidbits from the Google document.

New considerations

Google's addition of Know Simple indicates that Google understands that the Do-Know-Go categories are no longer broad enough for the modern search landscape. However, I believe that, even with the addition of "Know Simple," the model could be improved upon.

SEOs have traditionally used the navigational / informational / transactional framework to classify the searcher's intent. We believe that a large part of this (maybe not all) can be captured by considering how user intents may change and be better served when they've been conducted via an Intelligent Personal Assistant app.

The last couple of years has seen an explosion in the functionality and usage of an increasing number of personal assistants:

• Apple Siri – Built into every iPhone. Now also "Proactive" in a fashion similar to Google Now.
• Google Now –Technically, the name refers to a certain set of functionality, but people are increasingly referring to the "assistant" app and its functionality with this name.
• Microsoft Cortana – Originally just in Windows phones, but now available for Android as well. Microsoft has a great research team and are working hard on Cortana.

There are also a couple of newcomers that look very promising, but which are not fully released yet:

• Facebook M – An interesting cross between Artificial Intelligence and human workers who help with certain tasks, Facebook is looking to really take things to the next level with an assistant that can do things for you.
• SoundHound Hound – A preview video the company put out last year got a lot of attention for Hound's speed of understanding and flexibility with complex chained queries. I've tried it myself and it's pretty awesome.

Upgrading Do-Know-Go

At Distilled, we've been thinking about this a bit, and have gone through many iterations trying to work out how a new model should look. We still aren't sure we've cracked it, but wanted to share what we have so far.

We propose adding a second axis or a second row to the model, such that we have something like this:

Notice we've moved "Go" to the side, because we don't think it changes in a very meaningful way (you're just looking to go to a certain destination, be it app or web or whatever) — but it's also the least interesting category!

The logic of this model is that previously, the navigational / informational / transactional categorization allowed you to two things:

1. Understand the user's intent for a query
2. Frame how an appropriate landing page (or set of landing pages) should be formed for this category of queries on your site

None of that has changed when we're still in the the "web model," but we now need to extend that model so we can do those same two things above when considering IPAs.

In our model, we can see that "Informational/IPA" is where a huge amount of Know Simple queries exist. Then we have a box for "Transactional/IPA," which is also very interesting.

What's fascinating is that, in the case of both "Informational/IPA" and "Transactional/IPA" instances, SEOs don't yet have a good understanding of how to do any sort of optimization of improvements (which is to be expected as they are still developing). Let's discuss each.

Informational/IPA

Google puts their Know Simple queries into this cell but, as you'll see, Informational/IPA also covers slightly more ground.

Know Simple queries are for short, relatively factual searches; a good example is [how old is barack obama], which Google can answer from their own knowledge as it's something that changes infrequently.

However, there are other searches that fall into the Informational/IPA category, such as our example of [are the trains to London on time]. Google says that "queries where different users may want different types of information" are not considered Know Simple, but such queries clearly fit into our structure there.

These latter queries are the interesting ones, as they're the types of queries that search engines will be looking to fill by connecting to APIs. These are very related to "data-driven search." Also worth noting is that if 50–80% of queries are Know queries, we can imagine that this cell could serve a huge number of queries.

An Informational/IPA query via Google, served via the facts in their Knowledge Graph.

An Informational/IPA query via Hound, pulling live and context-based data via an API.

A particularly interesting variant of Informational/IPA queries are those which involve some sort of computation. I don't mean requests such as [the square root of 1764], as they have no "search" aspect. However, a query such as [100 US dollars in British pounds] requires the IPA to fetch the exchange rate for you, and then do something with that answer before giving you a response.

Currently, the capabilities here are still hit and miss; only Amazon's Evi IPA successfully answered my query [is barack obama older than his wife], whilst Google, Siri, Hound, and Cortana all sent me to a web search.

As the capabilities of IPAs improve, you could imagine some complex compound queries that could fit into this category.

Transactional/IPA

Transactional/IPA queries, which are the transactional relative to Informational/IPA, are queries where there's an intent to do something further after getting the query response. The initial response may be served within the IPA where you can do some additional filtering before you move to an app to complete the purchase (though, in the future, that part may be unnecessary), or the initial response may be opening an app right away.

A Transactional/IPA query via Siri; you're able to go several steps into the funnel before finally the "Buy Tickets" button takes you to an app.

This category feels like it's going to become absolutely huge in the near future; currently on iOS, full integration with Siri is only available to selected partners, but it seems likely that wider integration is going to become available. With Google Now and other platforms, we're likely to see similar patterns. Once apps can integrate right into the personal assistant apps and add functionality in terms of being able to do things, then the range of available queries available will explode. Being able to "rank" is going to be very heavily based upon being a flexible and comprehensive service for that niche.

Future and wrap up

It seems inevitable that search is moving away from just being about web search and 10 blue links, and so it seems inevitable that we'll need to update our models to keep up. The original navigational / informational / transactional categories were designed for the web, and the model proposed above was built to allow us to extend that model into this new world.

The original framework was used by SEOs to help us understand and categorize queries and to help educate and persuade clients. This new framework allows us to do these same things, but expand them to cover searches done via Intelligent Personal Assistants.

I would love to hear from everyone on in the comments on whether you think there are more opportunities to improve this model. Distilled's R&D team is working on better understanding how to do SEO in a world of Intelligent Personal Assistants, so be sure to watch this space!

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Content Marketing Tips for B2B Organizations - Whiteboard Friday

Posted by randfish

B2B companies face different challenges than B2C companies. From which stages you target in the funnel to how you measure your success to the team you end up selling to, content marketing can be a horse of a different color when you're business-to-business. In this week's Whiteboard Friday, Rand shares his tips for successful content marketing when you're a B2B.

Click on the whiteboard image above to open a high resolution version in a new tab!

Video Transcription

Howdy, Moz fans, and welcome to another edition of Whiteboard Friday. This week we're going to chat about B2B marketing, specifically B2B content marketing, and some tips that I've got for you that are a little bit different from how we would do B2C or other kinds of content marketing.

I get it. A lot of the examples that you see in the content marketing world are B2C, or they're at B2B companies that are more like Moz where we have a B2C-like community and a B2C-like audience. So I think that when it comes to B2B, because there are some tricky elements, I wanted to try and walk you through a few of those.

Let's start with the funnel.

The B2B funnel is very similar to a B2C funnel. In fact, marketing funnels in general work like this. People become aware of a product. They have some consideration for whether it's something they might actually want to buy. They do some form of comparison against other solutions. They decide to convert or not. Then there's a retention element. Retention element is less true in a lot of B2C fields, especially eCommerce one-time purchases. It's generally more true in the B2B world.

Target the right stages of the marketing funnel

I think one problem that we have in B2B marketing is a lot of times we target the wrong part of the funnel. This is actually really common. In B2C, usually things that hit on one of these hit on a lot of them. The same things that create awareness about a product or a brand also help with conversion, also might help with comparison because of brand affinity, and also might help with consideration and retention. It's less true in B2B, not to say not true at all, but less true. So I think one of the jobs that we have is to look inside our funnel and then identify which part needs help versus which part works fine.

Another thing that is very important here: For the majority of your content, don't try to target it at more than let's say two of these stages. I might say, "Hey, I've got a piece of content that I think can work really well for awareness and consideration." Or it's much further down the funnel. It's for people who already know us and are already considering us. It's really about comparison and conversion or about conversion and retention. That's fine. I think when you get into trouble is when you say, "Hey, you know what, this is going to help throughout the funnel — awareness, consideration, and conversion." Well, that tends not to be the case. That's not to say it can never happen.

Actually design your content for parts of the funnel that need it

Try to choose. When you're creating your content, when you're designing the strategy for why you're going to produce a particular piece, decide what it's going to help with. Point it at the area of the funnel that is in most need of assistance.

Let me give you a quick example here. There's a company called PivotDesk. They're a fellow at Foundry company. PivotDesk does something really cool. They help small businesses — in particular a lot of startups and early stage companies — but plenty of regular small businesses, to find office space. They're very business-to-business. They're talking to landlords and they're talking to small businesses.

They have a great funnel, but they decide that they need more awareness, which is good. Good job PivotDesk identifying which part of the funnel is the problem. If you've seen that lots of people who are already aware of you and visiting you are converting and getting through this part of the funnel, then you don't need to focus your content efforts there, or maybe less of them. We could think about potentially saying, "Hey, let's say that awareness is our problem. Awareness to whom? Is it awareness to small businesses or is it awareness to the landlords?" Again, two different audiences. In this case, awareness to the landlords perhaps is the problem.

I'm making these up. I don't actually know if PivotDesk has these problems. If that's the case, maybe what we want is an interactive tool that's essentially part survey and part comparison, benchmarking metrics, that a landlord can go in and say, "My space is in Seattle. I have this much square footage of AAA space, and the current price is $31 per square foot triple net," and there's the average me versus what the rest of the Seattle market looks like. Fascinating, I am undercharging or I am overcharging, or I have less square footage than most folks have, or I'm missing these amenities or whatever it is. That could work potentially very well for this stage of the funnel.

This is the process that I'd urge you to use when you're doing that B2B content strategy. Target the right section of the funnel. Make sure it's targeted to the right audience, and then come up with a piece of content that's going to move the needle in the right place.

When you're measuring success in B2B, it is pretty different than B2C. A lot of the time unfortunately the metric by which you will be judged upon is number of leads created. B2B tends to be very leads-driven. There are a few folks who are in B2B who are also self-service, like Moz is. But for the vast majority, it's leads for the sales folks to follow up on.

Because of that, the classic metrics, like how many social shares you got across different networks and how much visibility and raw traffic and engagement and those kinds of things tend to be less important than quantity of leads generated. This is really tough when you get into these areas of the funnel that are not the conversion point. If I'm trying to create raw awareness among my audience, I can really get misjudged if my boss, my team, or my client is only looking at the leads.

What I urge you again to do is to take note of what you're trying to improve and apply the right metrics to it. Don't just take the same metrics that are used for obviously B2C and don't take the same metrics that are judged on conversion for retention or awareness for conversion. This is critically important, or you're going to focus on the wrong parts of the solution you're trying to create.

The overwhelming majority of B2B transactions don't just have a single buyer.

In B2C, it's really simple. I'm selling blue jeans. I'm selling them to a consumer. That consumer tends to be the only person who's in on the consideration. Maybe their partner is also thinking about it. For the vast majority it's just that one person I'm selling to.

That's not the case in B2B, not at all.

Oftentimes the person who ends up buying, who you interact with, who your salesperson reaches out to and has the conversation, that person is just one link in the chain of individuals involved from a corporate ecosystem in who makes the buying decision. For that reason, a lot of times content marketing that reaches this person does a great job of reaching that buyer but does a terrible job of reaching their manager or the CFO and the HR person who are all involved in these decisions as well might be less successful.

This is why we need an overlapping persona analysis when we do our content. It's also why, when we're thinking about the funnel, we can't think about it without regard for which target is in which stage of the buying process. It could be that your buyer is all the way down here, but you have no resources, no content that's going to help convince a CFO and an HR person up here that they should even put you in the consideration set, because you have no comparison against what are their other options and why do you help them save money and those kinds of things.

Be careful with this. Target your content to not only your buyer but other folks as well, especially if your sales folks are giving you feedback that that's where they're getting stymied.

With B2B, it tends to be the case that you can be much more aggressive with forms of remarketing and retargeting. That means paid content. That means amplification. It means spending dollars to promote the content that you've created. The reason that you can do this as opposed to a lot of B2C is because it tends to be the case that your customer lifetime value is way higher. B2B transactions, we're talking about usually many hundreds, if not many thousands or tens of thousands or even hundreds of thousands of dollars per converted customer.

Cost of Customer Acquisition (CAC)

What you want to be looking at is not just the lifetime value but also the current cost of customer acquisition, or CAC, as it's called. There's a ratio that a lot of folks look at in B2B, which is the CAC to CLTV ratio, essentially how much does it cost us to get a new customer versus how much value does that customer provide. B2C folks look at this too, but B2B folks tend to be obsessed with it.

When I see the ratio is high or the CAC itself is low in comparison, this is, gee, $450 to acquire a customer versus $3,780 CLTV, that's like a 9 to 1 ratio, something like that. I have a ton of room to boost that. I could probably boost that. I could more than double it, and I'd still be fine with a four-to-one ratio or even a three-to-one ratio. I might consider spending a tremendous amount more money to get a customer. If I can see through my funnel that I'm measuring to see how content performs as it pushes people down this funnel and gets them to conversion, if I can see that for every 1,000 views or 10,000 views I'm getting a customer converting, well then I can go and I can amplify through paid channels, through retargeting and remarketing.

I can pay a lot of money to go push that content to more places and to more people. I can probably do things that I would almost never ordinarily do, like even buy paid search ads against a keyword that is very content-focused, not very conversion-focused, that lives up here in the funnel and I can still have success. This is something that very few B2B marketers are doing but some very successful ones are.

Last thing that I'll cover here, most B2B content does this... I don't know. It's like every B2B marketer reads from the same playbook. Look, I go through this process a lot because I'm interested in a lot of B2B content since Moz is a business that I'm trying to grow.

What happens is that the content exposes very little for free. I might hear about something and go, "Oh yeah, I am interested in the average lifetime value of self-service, software as a service companies." That sounds super corporate and boring. I'm deeply interested in it. It really affects Moz's metrics.

I might go look, and then I see I can't really tell what's in here, what's behind the wall. You're not showing me very much.

There's supposedly this amazing content, but I don't see anything there.

Then it asks me for too much in order to get access.

If you fill out all these 10 different form fields about your position at the company, and how much revenue you have, and how many employees you had, and what was your growth rate last year, and which other products in this field have you considered and so on, man, geez, I feel like I just had to sign a lease agreement in order to get a piece of content.

Then, that content is not web accessible.

I have to download it, which is insanely frustrating if I'm on one of these. It sucks. It's a terrible experience on mobile. It's even a bad experience on desktop. I don't want to have to download something and open it back up. That makes it less shareable. It's very hard for me to amplify that content if I'm interested in it. When I want to share it with other people I have to tell them, "Hey, you've got to go to this download link."

What happens? I'll tell you what happens. Every single time I download it and then I attach it in an email and I send it to every relevant person at Moz, that B2B company that made it only gets one email address, and I unsubscribe from their list.

Insanity.

Insanity.

If you can, fix this process by making your content web accessible, making it so that you're providing more of a teaser right on the page here so that more people are likely to go through here. Ask for as little information as you possibly can. You can get more later. You can learn a ton about someone once you have just one piece of information, their correct email address. If you have that, you can learn a tremendous amount about them. You don't need this. You've got tools like FullContact, where you can use the API plugin and email address and they'll give you all sorts of persona-type data about that person. You can go then research the company and get all the facts. Tons of stuff to do.

Then the last thing that I find that's oddly frustrating — I don't know why I'm frustrated about it, but you should be frustrated about it if you're a B2B marketer — is you don't reuse the audience for future content amplification. If you know that I downloaded this piece of content, I think it is perfectly okay to follow up with a personal message the next time you produce a piece of content like this and say, "Hey, we redid it and here it is again." That's not that hard. Hopefully, you haven't auto-subscribed me to an email newsletter and I'm getting tons of pieces of content that I care nothing about. What's far better is if you tell me, "Hey, we redid this piece," or, "Since you liked this piece, you'll probably be very interested in this other piece." That's going to work really well.

You can also do RLSA with this for more paid amplification. I can take a list of emails of all the people who've downloaded this, upload it to Google, upload it to Facebook, and then have this content accessible via these paid formats so that I'm bidding in Google and I'm showing the ads to people on Facebook or Twitter or LinkedIn, all that kind of stuff.

All right, everyone, hope you B2B marketers out there are doing some awesome stuff with your content in the near future. We'll see you again next week for another edition of Whiteboard Friday. Take care.

Video transcription by Speechpad.com

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