From Editorial Calendars to SEO: Setting Yourself Up to Create Fabulous Content

Posted by Isla_McKetta

Quick note: This article is meant to apply to teams of all sizes, from the sole proprietor who spends all night writing their copy (because they’re doing business during the day) to the copy team who occupies an entire floor and produces thousands of pieces of content per week. So if you run into a section that you feel requires more resources than you can devote just now, that’s okay. Bookmark it and revisit when you can, or scale the step down to a more appropriate size for your team. We believe all the information here is important, but that does not mean you have to do everything right now.

If you thought ideation was fun, get ready for content creation. Sure, we’ve all written some things before, but the creation phase of content marketing is where you get to watch that beloved idea start to take shape.

Before you start creating, though, you want to get (at least a little) organized, and an editorial calendar is the perfect first step.

Editorial calendars

Creativity and organization are not mutually exclusive. In fact, they can feed each other. A solid schedule gives you and your writers the time and space to be wild and creative. If you’re just starting out, this document may be sparse, but it’s no less important. Starting early with your editorial calendar also saves you from creating content willy-nilly and then finding out months later that no one ever finished that pesky (but crucial) “About” page.

There’s no wrong way to set up your editorial calendar, as long as it’s meeting your needs. Remember that an editorial calendar is a living document, and it will need to change as a hot topic comes up or an author drops out.

There are a lot of different types of documents that pass for editorial calendars. You get to pick the one that’s right for your team. The simplest version is a straight-up calendar with post titles written out on each day. You could even use a wall calendar and a Sharpie.

Monday Tuesday Wednesday Thursday Friday
Title
The Five Colors of Oscar Fashion 12 Fabrics We’re Watching for Fall Is Charmeuse the New Corduroy? Hot Right Now: Matching Your Handbag to Your Hatpin Tea-length and Other Fab Vocab You Need to Know
Author Ellie James Marta Laila Alex

Teams who are balancing content for different brands at agencies or other more complex content environments will want to add categories, author information, content type, social promo, and more to their calendars.

Truly complex editorial calendars are more like hybrid content creation/editorial calendars, where each of the steps to create and publish the content are indicated and someone has planned for how long all of that takes. These can be very helpful if the content you’re responsible for crosses a lot of teams and can take a long time to complete. It doesn’t matter if you’re using Excel or a Google Doc, as long as the people who need the calendar can easily access it. Gantt charts can be excellent for this. Here’s a favorite template for creating a Gantt chart in Google Docs (and they only get more sophisticated).

Complex calendars can encompass everything from ideation through writing, legal review, and publishing. You might even add content localization if your empire spans more than one continent to make sure you have the currency, date formatting, and even slang right.

Content governance

Governance outlines who is taking responsibility for your content. Who evaluates your content performance? What about freshness? Who decides to update (or kill) an older post? Who designs and optimizes workflows for your team or chooses and manages your CMS?

All these individual concerns fall into two overarching components to governance: daily maintenance and overall strategy. In the long run it helps if one person has oversight of the whole process, but the smaller steps can easily be split among many team members. Read this to take your governance to the next level.

Finding authors

The scale of your writing enterprise doesn’t have to be limited to the number of authors you have on your team. It’s also important to consider the possibility of working with freelancers and guest authors. Here’s a look at the pros and cons of outsourced versus in-house talent.

In-house authors

Guest authors and freelancers

Responsible to

You

Themselves

Paid by

You (as part of their salary)

You (on a per-piece basis)

Subject matter expertise

Broad but shallow

Deep but narrow

Capacity for extra work

As you wish

Show me the Benjamins

Turnaround time

On a dime

Varies

Communication investment

Less

More

Devoted audience

Smaller

Potentially huge

From that table, it might look like in-house authors have a lot more advantages. That’s somewhat true, but do not underestimate the value of occasionally working with a true industry expert who has name recognition and a huge following. Whichever route you take (and there are plenty of hybrid options), it’s always okay to ask that the writers you are working with be professional about communication, payment, and deadlines. In some industries, guest writers will write for links. Consider yourself lucky if that’s true. Remember, though, that the final paycheck can be great leverage for getting a writer to do exactly what you need them to (such as making their deadlines).

Tools to help with content creation

So those are some things you need to have in place before you create content. Now’s the fun part: getting started. One of the beautiful things about the Internet is that new and exciting tools crop up every day to help make our jobs easier and more efficient. Here are a few of our favorites.

Calendars

You can always use Excel or a Google Doc to set up your editorial calendar, but we really like Trello for the ability to gather a lot of information in one card and then drag and drop it into place. Once there are actual dates attached to your content, you might be happier with something like a Google Calendar.

Ideation and research

If you need a quick fix for ideation, turn your keywords into wacky ideas with Portent’s Title Maker. You probably won’t want to write to the exact title you’re given (although “True Facts about Justin Bieber’s Love of Pickles” does sound pretty fascinating…), but it’s a good way to get loose and look at your topic from a new angle.

Once you’ve got that idea solidified, find out what your audience thinks about it by gathering information with Survey Monkey or your favorite survey tool. Or, use Storify to listen to what people are saying about your topic across a wide variety of platforms. You can also use Storify to save those references and turn them into a piece of content or an illustration for one. Don’t forget that a simple social ask can also do wonders.

Format

Content doesn’t have to be all about the words. Screencasts, Google+ Hangouts, and presentations are all interesting ways to approach content. Remember that not everyone’s a reader. Some of your audience will be more interested in visual or interactive content. Make something for everyone.

Illustration

Don’t forget to make your content pretty. It’s not that hard to find free stock images online (just make sure you aren’t violating someone’s copyright). We like Morgue File, Free Images, and Flickr’s Creative Commons. If you aren’t into stock images and don’t have access to in-house graphic design, it’s still relatively easy to add images to your content. Pull a screenshot with Skitch or dress up an existing image with Pixlr. You can also use something like Canva to create custom graphics.

Don’t stop with static graphics, though. There are so many tools out there to help you create gifs, quizzes and polls, maps, and even interactive timelines. Dream it, then search for it. Chances are whatever you’re thinking of is doable.

Quality, not quantity

Mediocre content will hurt your cause

Less is more. That’s not an excuse to pare your blog down to one post per month (check out our publishing cadence experiment), but it is an important reminder that if you’re writing “How to Properly Install a Toilet Seat” two days after publishing “Toilet Seat Installation for Dummies,” you might want to rethink your strategy.

The thing is, and I’m going to use another cliché here to drive home the point, you never get a second chance to make a first impression. Potential customers are roving the Internet right now looking for exactly what you’re selling. And if what they find is an only somewhat informative article stuffed with keywords and awful spelling and grammar mistakes… well, you don’t want that. Oh, and search engines think it’s spammy too…

A word about copyright

We’re not copyright lawyers, so we can’t give you the ins and outs on all the technicalities. What we can tell you (and you already know this) is that it’s not okay to steal someone else’s work. You wouldn’t want them to do it to you. This includes images. So whenever you can, make your own images or find images that you can either purchase the rights to (stock imagery) or license under Creative Commons.

It’s usually okay to quote short portions of text, as long as you attribute the original source (and a link is nice). In general, titles and ideas can’t be copyrighted (though they might be trademarked or patented). When in doubt, asking for permission is smart.

That said, part of the fun of the Internet is the remixing culture which includes using things like memes and gifs. Just know that if you go that route, there is a certain amount of risk involved.

Editing

Your content needs to go through at least one editing cycle by someone other than the original author. There are two types of editing, developmental (which looks at the underlying structure of a piece that happens earlier in the writing cycle) and copy editing (which makes sure all the words are there and spelled right in the final draft).

If you have a very small team or are in a rush (and are working with writers that have some skill), you can often skip the developmental editing phase. But know that an investment in that close read of an early draft is often beneficial to the piece and to the writer’s overall growth.

Many content teams peer-edit work, which can be great. Other organizations prefer to run their work by a dedicated editor. There’s no wrong answer, as long as the work gets edited.

Ensuring proper basic SEO

The good news is that search engines are doing their best to get closer and closer to understanding and processing natural language. So good writing (including the natural use of synonyms rather than repeating those keywords over and over and…) will take you a long way towards SEO mastery.

For that reason (and because it’s easy to get trapped in keyword thinking and veer into keyword stuffing), it’s often nice to think of your SEO check as a further edit of the post rather than something you should think about as you’re writing.

But there are still a few things you can do to help cover those SEO bets. Once you have that draft, do a pass for SEO to make sure you’ve covered the following:

  • Use your keyword in your title
  • Use your keyword (or long-tail keyword phrase) in an H2
  • Make sure the keyword appears at least once (though not more than four times, especially if it’s a phrase) in the body of the post
  • Use image alt text (including the keyword when appropriate)

Finding time to write when you don’t have any

Writing (assuming you’re the one doing the writing) can require a lot of energy—especially if you want to do it well. The best way to find time to write is to break each project down into little tasks. For example, writing a blog post actually breaks down into these steps (though not always in this order):

  • Research
  • Outline
  • Fill in outline
  • Rewrite and finish post
  • Write headline
  • SEO check
  • Final edit
  • Select hero image (optional)

So if you only have random chunks of time, set aside 15-30 minutes one day (when your research is complete) to write a really great outline. Then find an hour the next to fill that outline in. After an additional hour the following day, (unless you’re dealing with a research-heavy post) you should have a solid draft by the end of day three.

The magic of working this way is that you engage your brain and then give it time to work in the background while you accomplish other tasks. Hemingway used to stop mid-sentence at the end of his writing days for the same reason.

Once you have that draft nailed, the rest of the steps are relatively easy (even the headline, which often takes longer to write than any other sentence, is easier after you’ve immersed yourself in the post over a few days).

Working with design/development

Every designer and developer is a little different, so we can’t give you any blanket cure-alls for inter-departmental workarounds (aka “smashing silos”). But here are some suggestions to help you convey your vision while capitalizing on the expertise of your coworkers to make your content truly excellent.

Ask for feedback

From the initial brainstorm to general questions about how to work together, asking your team members what they think and prefer can go a long way. Communicate all the details you have (especially the unspoken expectations) and then listen.

If your designer tells you up front that your color scheme is years out of date, you’re saving time. And if your developer tells you that the interactive version of that timeline will require four times the resources, you have the info you need to fight for more budget (or reassess the project).

Check in

Things change in the design and development process. If you have interim check-ins already set up with everyone who’s working on the project, you’ll avoid the potential for nasty surprises at the end. Like finding out that no one has experience working with that hot new coding language you just read about and they’re trying to do a workaround that isn’t working.

Proofread

Your job isn’t done when you hand over the copy to your designer or developer. Not only might they need help rewriting some of your text so that it fits in certain areas, they will also need you to proofread the final version. Accidents happen in the copy-and-paste process and there’s nothing sadder than a really beautiful (and expensive) piece of content that wraps up with a typo:

Know when to fight for an idea

Conflict isn’t fun, but sometimes it’s necessary. The more people involved in your content, the more watered down the original idea can get and the more roadblocks and conflicting ideas you’ll run into. Some of that is very useful. But sometimes you’ll get pulled off track. Always remember who owns the final product (this may not be you) and be ready to stand up for the idea if it’s starting to get off track.

We’re confident this list will set you on the right path to creating some really awesome content, but is there more you’d like to know? Ask us your questions in the comments.

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Reblogged 2 years ago from tracking.feedpress.it

Spam Score: Moz’s New Metric to Measure Penalization Risk

Posted by randfish

Today, I’m very excited to announce that Moz’s Spam Score, an R&D project we’ve worked on for nearly a year, is finally going live. In this post, you can learn more about how we’re calculating spam score, what it means, and how you can potentially use it in your SEO work.

How does Spam Score work?

Over the last year, our data science team, led by 
Dr. Matt Peters, examined a great number of potential factors that predicted that a site might be penalized or banned by Google. We found strong correlations with 17 unique factors we call “spam flags,” and turned them into a score.

Almost every subdomain in 
Mozscape (our web index) now has a Spam Score attached to it, and this score is viewable inside Open Site Explorer (and soon, the MozBar and other tools). The score is simple; it just records the quantity of spam flags the subdomain triggers. Our correlations showed that no particular flag was more likely than others to mean a domain was penalized/banned in Google, but firing many flags had a very strong correlation (you can see the math below).

Spam Score currently operates only on the subdomain level—we don’t have it for pages or root domains. It’s been my experience and the experience of many other SEOs in the field that a great deal of link spam is tied to the subdomain-level. There are plenty of exceptions—manipulative links can and do live on plenty of high-quality sites—but as we’ve tested, we found that subdomain-level Spam Score was the best solution we could create at web scale. It does a solid job with the most obvious, nastiest spam, and a decent job highlighting risk in other areas, too.

How to access Spam Score

Right now, you can find Spam Score inside 
Open Site Explorer, both in the top metrics (just below domain/page authority) and in its own tab labeled “Spam Analysis.” Spam Score is only available for Pro subscribers right now, though in the future, we may make the score in the metrics section available to everyone (if you’re not a subscriber, you can check it out with a free trial). 

The current Spam Analysis page includes a list of subdomains or pages linking to your site. You can toggle the target to look at all links to a given subdomain on your site, given pages, or the entire root domain. You can further toggle source tier to look at the Spam Score for incoming linking pages or subdomains (but in the case of pages, we’re still showing the Spam Score for the subdomain on which that page is hosted).

You can click on any Spam Score row and see the details about which flags were triggered. We’ll bring you to a page like this:

Back on the original Spam Analysis page, at the very bottom of the rows, you’ll find an option to export a disavow file, which is compatible with Google Webmaster Tools. You can choose to filter the file to contain only those sites with a given spam flag count or higher:

Disavow exports usually take less than 3 hours to finish. We can send you an email when it’s ready, too.

WARNING: Please do not export this file and simply upload it to Google! You can really, really hurt your site’s ranking and there may be no way to recover. Instead, carefully sort through the links therein and make sure you really do want to disavow what’s in there. You can easily remove/edit the file to take out links you feel are not spam. When Moz’s Cyrus Shepard disavowed every link to his own site, it took more than a year for his rankings to return!

We’ve actually made the file not-wholly-ready for upload to Google in order to be sure folks aren’t too cavalier with this particular step. You’ll need to open it up and make some edits (specifically to lines at the top of the file) in order to ready it for Webmaster Tools

In the near future, we hope to have Spam Score in the Mozbar as well, which might look like this: 

Sweet, right? 🙂

Potential use cases for Spam Analysis

This list probably isn’t exhaustive, but these are a few of the ways we’ve been playing around with the data:

  1. Checking for spammy links to your own site: Almost every site has at least a few bad links pointing to it, but it’s been hard to know how much or how many potentially harmful links you might have until now. Run a quick spam analysis and see if there’s enough there to cause concern.
  2. Evaluating potential links: This is a big one where we think Spam Score can be helpful. It’s not going to catch every potentially bad link, and you should certainly still use your brain for evaluation too, but as you’re scanning a list of link opportunities or surfing to various sites, having the ability to see if they fire a lot of flags is a great warning sign.
  3. Link cleanup: Link cleanup projects can be messy, involved, precarious, and massively tedious. Spam Score might not catch everything, but sorting links by it can be hugely helpful in identifying potentially nasty stuff, and filtering out the more probably clean links.
  4. Disavow Files: Again, because Spam Score won’t perfectly catch everything, you will likely need to do some additional work here (especially if the site you’re working on has done some link buying on more generally trustworthy domains), but it can save you a heap of time evaluating and listing the worst and most obvious junk.

Over time, we’re also excited about using Spam Score to help improve the PA and DA calculations (it’s not currently in there), as well as adding it to other tools and data sources. We’d love your feedback and insight about where you’d most want to see Spam Score get involved.

Details about Spam Score’s calculation

This section comes courtesy of Moz’s head of data science, Dr. Matt Peters, who created the metric and deserves (at least in my humble opinion) a big round of applause. – Rand

Definition of “spam”

Before diving into the details of the individual spam flags and their calculation, it’s important to first describe our data gathering process and “spam” definition.

For our purposes, we followed Google’s definition of spam and gathered labels for a large number of sites as follows.

  • First, we randomly selected a large number of subdomains from the Mozscape index stratified by mozRank.
  • Then we crawled the subdomains and threw out any that didn’t return a “200 OK” (redirects, errors, etc).
  • Finally, we collected the top 10 de-personalized, geo-agnostic Google-US search results using the full subdomain name as the keyword and checked whether any of those results matched the original keyword. If they did not, we called the subdomain “spam,” otherwise we called it “ham.”

We performed the most recent data collection in November 2014 (after the Penguin 3.0 update) for about 500,000 subdomains.

Relationship between number of flags and spam

The overall Spam Score is currently an aggregate of 17 different “flags.” You can think of each flag a potential “warning sign” that signals that a site may be spammy. The overall likelihood of spam increases as a site accumulates more and more flags, so that the total number of flags is a strong predictor of spam. Accordingly, the flags are designed to be used together—no single flag, or even a few flags, is cause for concern (and indeed most sites will trigger at least a few flags).

The following table shows the relationship between the number of flags and percent of sites with those flags that we found Google had penalized or banned:

ABOVE: The overall probability of spam vs. the number of spam flags. Data collected in Nov. 2014 for approximately 500K subdomains. The table also highlights the three overall danger levels: low/green (< 10%) moderate/yellow (10-50%) and high/red (>50%)

The overall spam percent averaged across a large number of sites increases in lock step with the number of flags; however there are outliers in every category. For example, there are a small number of sites with very few flags that are tagged as spam by Google and conversely a small number of sites with many flags that are not spam.

Spam flag details

The individual spam flags capture a wide range of spam signals link profiles, anchor text, on page signals and properties of the domain name. At a high level the process to determine the spam flags for each subdomain is:

  • Collect link metrics from Mozscape (mozRank, mozTrust, number of linking domains, etc).
  • Collect anchor text metrics from Mozscape (top anchor text phrases sorted by number of links)
  • Collect the top five pages by Page Authority on the subdomain from Mozscape
  • Crawl the top five pages plus the home page and process to extract on page signals
  • Provide the output for Mozscape to include in the next index release cycle

Since the spam flags are incorporated into in the Mozscape index, fresh data is released with each new index. Right now, we crawl and process the spam flags for each subdomains every two – three months although this may change in the future.

Link flags

The following table lists the link and anchor text related flags with the the odds ratio for each flag. For each flag, we can compute two percents: the percent of sites with that flag that are penalized by Google and the percent of sites with that flag that were not penalized. The odds ratio is the ratio of these percents and gives the increase in likelihood that a site is spam if it has the flag. For example, the first row says that a site with this flag is 12.4 times more likely to be spam than one without the flag.

ABOVE: Description and odds ratio of link and anchor text related spam flags. In addition to a description, it lists the odds ratio for each flag which gives the overall increase in spam likelihood if the flag is present).

Working down the table, the flags are:

  • Low mozTrust to mozRank ratio: Sites with low mozTrust compared to mozRank are likely to be spam.
  • Large site with few links: Large sites with many pages tend to also have many links and large sites without a corresponding large number of links are likely to be spam.
  • Site link diversity is low: If a large percentage of links to a site are from a few domains it is likely to be spam.
  • Ratio of followed to nofollowed subdomains/domains (two separate flags): Sites with a large number of followed links relative to nofollowed are likely to be spam.
  • Small proportion of branded links (anchor text): Organically occurring links tend to contain a disproportionate amount of banded keywords. If a site does not have a lot of branded anchor text, it’s a signal the links are not organic.

On-page flags

Similar to the link flags, the following table lists the on page and domain name related flags:

ABOVE: Description and odds ratio of on page and domain name related spam flags. In addition to a description, it lists the odds ratio for each flag which gives the overall increase in spam likelihood if the flag is present).

  • Thin content: If a site has a relatively small ratio of content to navigation chrome it’s likely to be spam.
  • Site mark-up is abnormally small: Non-spam sites tend to invest in rich user experiences with CSS, Javascript and extensive mark-up. Accordingly, a large ratio of text to mark-up is a spam signal.
  • Large number of external links: A site with a large number of external links may look spammy.
  • Low number of internal links: Real sites tend to link heavily to themselves via internal navigation and a relative lack of internal links is a spam signal.
  • Anchor text-heavy page: Sites with a lot of anchor text are more likely to be spam then those with more content and less links.
  • External links in navigation: Spam sites may hide external links in the sidebar or footer.
  • No contact info: Real sites prominently display their social and other contact information.
  • Low number of pages found: A site with only one or a few pages is more likely to be spam than one with many pages.
  • TLD correlated with spam domains: Certain TLDs are more spammy than others (e.g. pw).
  • Domain name length: A long subdomain name like “bycheapviagra.freeshipping.onlinepharmacy.com” may indicate keyword stuffing.
  • Domain name contains numerals: domain names with numerals may be automatically generated and therefore spam.

If you’d like some more details on the technical aspects of the spam score, check out the 
video of Matt’s 2012 MozCon talk about Algorithmic Spam Detection or the slides (many of the details have evolved, but the overall ideas are the same):

We’d love your feedback

As with all metrics, Spam Score won’t be perfect. We’d love to hear your feedback and ideas for improving the score as well as what you’d like to see from it’s in-product application in the future. Feel free to leave comments on this post, or to email Matt (matt at moz dot com) and me (rand at moz dot com) privately with any suggestions.

Good luck cleaning up and preventing link spam!



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Reblogged 3 years ago from tracking.feedpress.it

Understand and Harness the Power of Archetypes in Marketing

Posted by gfiorelli1

Roger Dooley, neuromarketing expert, reminds us in his book Brainfluence that in 80% of cases we make a decision before being rationally aware of it.

Although Dooley explains this effect in terms of how our brain works, in my opinion, distinctly separating neuroscience and the theory of archetypes would be incorrect. On the contrary, I believe that these two aspects of the study of the human mind are complementary.

According to
Jung, archetypes are “[…] forms or images of a collective nature which occur practically all over the Earth as constituents of myths and—at the same time—as individual products of unconscious”. He then, added something that interests us greatly: “The [forms and images] are imprinted and hardwired into out psyches”.

Being able to design a brand personality around an archetype that connects unconsciously with our audience is a big first step for: brand loyalty, community creation, engagement, conversions.

The Slender Man is the “Internet age” version of the archetype figure of the Shadow

Archetypes can be also used for differentiating our brand and its messaging from others in our same market niche and to give that brand a unique voice.

If we put users at the center of our marketing strategy, then
we cannot limit ourselves in knowing how they search, how they talk on social media, what they like to share or what their demographics are.

No,
we should also understand the deep psychological reasons why they desire something they search for, talk the way they talk, share what they share, and their psychological relation with the environment and society they live in.

Knowing that,
we can use archetypes to create a deep emotional connection with our audience and earn their strong positive attitude toward us thanks to the empathy that is created between them and us.

Narrative modes, then, help us in shaping in a structured way a brand storytelling able to guide and engage the users, and not simply selling or creating content narrative doomed to fail.

The 12 archetypes




graph by Emily Bennet

The chart above presents the 12 Jungian archetypes (i.e: Hero), to what principal human desire (i.e.: leave a mark on the world) they correspond and what is the main behavior each one uses for achieving that desire (i.e.: mastery).


Remember: if the audience instinctively recognizes the archetypal figure of the brand and its symbolism and instinctively connect with it, then your audience is more ready to like and trust what your brand proposes
.

On the other hand, it is also a good exercise to experiment with archetypes that we would not think are our brand’s one, expanding the practice of A/B tests to make sure we’re working with the correct archetype. 

The Creator

In my last post I used Lego as example of a brand that is winning Internet marketing thanks to its holistic and synergistic use of offline and online marketing channels.

I explained also how part of its success is due to the fact Lego was able to shape its messages and brand personality around the Creator archetype (sometimes called the “Builder”) which is embodied by their tagline, “let’s build”.

Creators tend to be nonconformist and to enjoy self expression.
A Creator brand, then, will empower and prize its audience as much as it is able to express itself using its products.

The Ruler

The Ruler is the leader, the one setting the rules others will follow, even competitors. Usually it’s paired with an
idea of exclusiveness and status growth.

A brand that presents itself as a Ruler is suggesting to their audience that they can be rulers too.

A classic example of Ruler brand is Mercedes:

The Caregiver

Altruism, compassion, generosity.
Caregiver brands present themselves as someone to trust, because they care and empathize with their audience.

The Caregiver is one of the most positive archetypes, and it is obviously used by nonprofit organizations or governmental institutions like UNICEF, but brands like Johnson & Johnson have also shaped their personality and messages around this figure.

The Innocent

The Innocent finds positive sides in everyone and everything

It sees beauty even in things that others will not even consider, and feels in peace with its inner beauty.

Dove, obviously, is a good representation of the Innocent archetype.

The Sage

The Sages wants to know and understand things. 


The Sage is deeply humanist and believe in the power of humankind to shape a better world through knowledge
.

However, the Sage also has a shadowed side: intolerance to ideas others than their own.

Google, in both cases, is a good example a Sage brand.

The Explorer

The Explorer is adventurous, brave, and loves challenges. He tends to be an individualist too, and loves to challenge himself so as to find his real self.


Explorer brands prompt their audience to challenge themselves and to discover the Explorer within

Red Bull is a classic example of these kinds of brands, but REI and Patagonia are even better representations.

The Hero

In many aspects, the Hero archetype is similar to the Explorer and Outlaw ones, with the difference that the Hero many times never wanted to be the hero, but injustice and external events obliged him to find the courage, braveness, and the honor to become one.

Nike, and also its competitor Adidas, shapes its brand voice around this archetypal figure.

The Magician

The Magician is clever, intelligent, and sometimes his ability can be considered supernatural. 


The Magician is able to make the impossible possible
. Because of that some of the best known technology brands use this archetype as their own to showcase their innovation and how they use their advanced knowledge creatively.

Apple—even if you are not an Apple fan—created a powerful brand by shaping it around this archetype. 

The Outlaw


The Outlaw is the rebel, the one who breaks the rules in order to free his true self
.

The Outlaw goes against the canon and is very aware of the constrictions society creates.

A great example of a brand that very well represents the Outlaw archetype is Betabrand.

The Everyman

It is perfectly fine to be “normal,” and happiness can come from simply sharing things with people we love.


Brands targeting the Everyman audience (and painting themselves as such) craft their messages about the beauty of simple things and daily real life
.

Ikea is probably the brand that’s achieved mastery in the use of this archetype over the past few years.

The Jester 

Fun, irreverent, energetic, impulsive and against the established rules at the same time, the Jester is also the only one who is able to tell the truth with a joke. 

Jesters can be revolutionary too, and their motto could be “a laugh will bury you all.”


A brand that presents itself as the Jester is a brand that wants to make our lives easier and more bearable, providing us joy.

The Lover


Sensuality is the main characteristic of the Lover archetype
, as well as strong physicality, passion, and a need for deep and strong sensations.

But the Lover can be also the idealist, the romantic longing for the perfect love.

Archetypes and brand storytelling

Our brain, as many neuroscientists have proved, is
hard-wired for stories (I suggest you to watch this TEDx too).

Therefore, once we have decided what archetype figure best responds both to our audience and our values as a brand,
we must translate the psychology we created for our brand into
brand storytelling.
That storytelling must then be attuned to the psychology of our audience based on our psychographic analysis of them.

Good (brand) storytelling is very hard to achieve, and most of the time we see brands that miserably fail when trying to tell branded stories.

Introducing the Theory of Literary (or Narrative) Modes

In order to help my clients find the correct narrative, I rely on something that usually is not considered by marketers: the
Theory of Literary Modes.

I use this theory, presented first by
Northrop Frye in it essay Anatomy of Criticism, because it is close to our “technical marketer” mindset.

In fact:

  1. The theory is based on a objective and “scientific” analysis of data (the literary corpus produced by humans);
  2. It refuses “personal taste” as a metric, which in web marketing would be the same as creating a campaign with tactics you like but you don’t really know if your public is interested in. Even worse, it would be like saying “create great content” without defining what that means.

Moreover, the
Theory of Literary Modes is deeply structured and strongly relies on semiotics, which is going to be the natural evolution of how search engines like Google will comprehend the content published in the Internet. Semantic thinking is just the first step as well explained 
Isla McKetta here on Moz few months ago.

Finally, Northrop Fryed
considers also archetypes this theory because of the psychological and semiotic value of the symbolism attached to the archetypal figure.

Therefore, my election to use the Theory of Literary Modes responds 

  1. To the need to translate ideal brand storytelling into something real that can instinctively connect with the brand’s audience;
  2. To make the content based on that storytelling process understandable also by search engines.

The Theory of Literary Modes in marketing

To understand how this works in marketing, we need to dig a little deeper into the theory.

A literary work can be classified in two different but complementary ways:

1) Considering only the
relation between the nature of the main character (the Hero) and the ambient (or environment) where he acts.

2) Considering also
if the Hero is refused or accepted by society (Tragedy and Comedy).

In the
first case, as represented in the schema above, if the Hero:
  1. Is higher by nature than the readers and acts in a completely different ambient than theirs, we have a Romance;
  2. Is higher by nature than the readers, but acts in their same ambient, we have an Epic;
  3. Is someone like the reader and acts in the reader’s own ambient, we are in field of Realism;
  4. Is someone lower by nature than the readers and acts in a different or identical ambient, we are in the realm of Irony, which is meant as “distance.”
A fifth situation exists too, the
Myth, when the nature of the Hero is different than ours and acts in an ambient different than ours. The Hero, in this case, is the God.

If we consider also if society refuses or accepts the hero, we can discover the different versions of Tragedy and Comedy.

I will not enter in the details of Tragedy, because
we will not use its modes for brand storytelling (this is only common in specific cases of political marketing or propaganda, classic examples are the mythology of Nazism or Communism).

On the contrary,
the most common modes used in brand storytelling are related to Comedy, where the Hero, who usually is the target audience, is eventually accepted by society (the archetypal world designed by the brand).

In
Comedy we have several sub modes of storytelling:

  1. “The God Accepted.” The Hero is a god or god-like kind of person who must pass through trials in order to be accepted by the society;
  2. The Idyll, where the Hero uses his skills to explore (or conquer) an ideal world and/or become part of an ideal society. Far West and its heir, Space Opera (think of Interstellar) are classic examples. 
  3. Comedy sees the hero trying to impose his own view of the world, fighting for it and finally being awarded with acceptance of his worldview. A good example of this is every well ending biopic of an entrepreneur, and Comedy is the exact contrary of melodrama. 
  4. On a lower level we can find the Picaresque Comedy, where the hero is by nature inferior to the society, but – thanks to his cleverness – is able to elevate himself to society’s level. Some technology business companies use this narrative mode for telling their users that they can “conquer” their market niche despite not having the same economic possibilities as the big brands (this conquering usually involves the brand’s tools).
  5. Finally we have the Irony Mode of Comedy which is quite complex to define. 
    1. It can represent stories where the hero is actually an antihero, who finally fails in his integration into the society. 
    2. It can also be about inflicting pain on helpless victims, as in mystery novels. 
    3. It can also be Parody.

Some examples

The Magician, gamification, and the Idyllic mode

Consider this brand plot:

The user (the Hero) can become part of a community of users only if he or she passes through a series of tasks, which will award prizes and more capabilities. If the user is able to pass through all the tasks, he will not only be accepted but also may have the opportunity to be among the leaders of the community itself.

And now
consider sites, which are strongly centered on communities like GitHub and Code Academy. Consider also SAAS companies that present the freemium model like Moz or mobile games like Boom Beach, where you can unlock new weapons only if you pass a given trial (or you buy them).

The Magician is usually the archetype of reference for these kinds of brands. The Hero (the user) will be able to dominate a complex art thanks to the help of a Master (the brand), which will offer him instruments (i.e.: tools/courses/weapons). 

Trials are not necessarily tests. A trial can be doing something that will be awarded, for instance, with points (like commenting on a Moz blog post), and the more the points the more the recognition, with all the advantages that it may offer. 

Gamification, then, assumes an even stronger meaning and narrative function when tied to an archetype and literary mode.

Ikea, the Everyman, and the Comedic mode

Another
example is Ikea, which we cited before when talking of the Everyman archetype.

In this case, the Hero is someone like me or you who is not an interior designer or decorator or, maybe, who does not have the money for hiring those professionals or buying very expensive furniture and decoration.

But, faithful to its mission statements (“design for all”, “design your own life”…), Ikea is there to help Everyman kind of people like me and you in every way as we decorate our own houses.

On the practical side, this narrative is delivered in all the possible channels used by Ikea: web site, mobile app, social media (look at its
Twitter profile) and YouTube channel.

Betabrand, the Outlaw, and Picaresque Comedy

A third and last example can be
Betabrand.

In this case both the brand and the audience is portrayed using the
Outlaw archetype, and the brand narrative tend to use the Picaresque mode.

The Heroes is the Betabrand community who does not care what the mainstream concept of fashion is and designs and crowdfounds “its fashion.”

How to use archetypes and narrative modes in your brand storytelling

The first thing you must understand is what archetype best responds to your company tenets and mission. 

Usually this is not something an SEO can decide by him- or herself, but it is something that founders, CEOs, and directors of a company can inform.

Oftentimes a small to medium business company can achieve this with a long talk among those company figures and where they are asked to directly define the idealistic “why?” of their company.

In case of bigger companies, defining an archetype can seem almost impossible to do, but the same history of the company and hidden treasure pages like “About Us” can offer clear inspiration.

Look at REI:

Clearly the archetype figure that bests fits REI is the Explorer.

Then, using the information we retrieve when creating the
psychographic of our audience and buyer personas, matching with the characteristics each archetype has, and comparing it with the same brand core values, we can start to understand the archetype and narrative mode. If we look at REI’s audience, then we will see how it also has a certain affinity with the Everyman archetypal figure (and that also explains why REI also dedicates great attention to family as audience).

Once we have defined the best archetype commonly shared by our company and our audience, we must translate this figure and its symbolism into brand storytelling, which in web site includes design, especially the following:

  • Color pattern, because colors have a direct relation with psychological reaction (see this article, especially all the sources it links to)
  • Images, considering that in user-centric marketing the ideal is always to represent our targeted audience (or a credible approximation) as their main characters. I am talking of the so called “hero-shots”, about which Angie Shoetmuller brilliantly discussed in the deck I embed here below:

If you want to dig deeper in discovering the meaning and value of symbols worldwide, I suggest you become member of
Aras.org or to buy the Book of Symbols curated by Aras.

  • Define the best narrative mode to use. REI, again, does this well, using the Idyllic mode where the Hero explores and become part of an ideal society (the REI community, which literally means becoming a member of REI). 

We should, then:

  1. Continue investigating the archetypal nature of our audience conducting surveys
  2. Analyzing the demographic data Google Analytics offers us about our users 
  3. Using GA insights in combination with the data and demographic information offered by social networks’ ad platforms in order to create not only the interest graph of our audience but also to understand the psychology behind those interests 
  4. Doing A/B tests so to see whether symbols, images, and copywriting based on the targeted archetypes work better and if we have the correct archetype.

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What Deep Learning and Machine Learning Mean For the Future of SEO – Whiteboard Friday

Posted by randfish

Imagine a world where even the high-up Google engineers don’t know what’s in the ranking algorithm. We may be moving in that direction. In today’s Whiteboard Friday, Rand explores and explains the concepts of deep learning and machine learning, drawing us a picture of how they could impact our work as SEOs.

For reference, here’s a still of this week’s whiteboard!

Video transcription

Howdy, Moz fans, and welcome to another edition of Whiteboard Friday. This week we are going to take a peek into Google’s future and look at what it could mean as Google advances their machine learning and deep learning capabilities. I know these sound like big, fancy, important words. They’re not actually that tough of topics to understand. In fact, they’re simplistic enough that even a lot of technology firms like Moz do some level of machine learning. We don’t do anything with deep learning and a lot of neural networks. We might be going that direction.

But I found an article that was published in January, absolutely fascinating and I think really worth reading, and I wanted to extract some of the contents here for Whiteboard Friday because I do think this is tactically and strategically important to understand for SEOs and really important for us to understand so that we can explain to our bosses, our teams, our clients how SEO works and will work in the future.

The article is called “Google Search Will Be Your Next Brain.” It’s by Steve Levy. It’s over on Medium. I do encourage you to read it. It’s a relatively lengthy read, but just a fascinating one if you’re interested in search. It starts with a profile of Geoff Hinton, who was a professor in Canada and worked on neural networks for a long time and then came over to Google and is now a distinguished engineer there. As the article says, a quote from the article: “He is versed in the black art of organizing several layers of artificial neurons so that the entire system, the system of neurons, could be trained or even train itself to divine coherence from random inputs.”

This sounds complex, but basically what we’re saying is we’re trying to get machines to come up with outcomes on their own rather than us having to tell them all the inputs to consider and how to process those incomes and the outcome to spit out. So this is essentially machine learning. Google has used this, for example, to figure out when you give it a bunch of photos and it can say, “Oh, this is a landscape photo. Oh, this is an outdoor photo. Oh, this is a photo of a person.” Have you ever had that creepy experience where you upload a photo to Facebook or to Google+ and they say, “Is this your friend so and so?” And you’re like, “God, that’s a terrible shot of my friend. You can barely see most of his face, and he’s wearing glasses which he usually never wears. How in the world could Google+ or Facebook figure out that this is this person?”

That’s what they use, these neural networks, these deep machine learning processes for. So I’ll give you a simple example. Here at MOZ, we do machine learning very simplistically for page authority and domain authority. We take all the inputs — numbers of links, number of linking root domains, every single metric that you could get from MOZ on the page level, on the sub-domain level, on the root-domain level, all these metrics — and then we combine them together and we say, “Hey machine, we want you to build us the algorithm that best correlates with how Google ranks pages, and here’s a bunch of pages that Google has ranked.” I think we use a base set of 10,000, and we do it about quarterly or every 6 months, feed that back into the system and the system pumps out the little algorithm that says, “Here you go. This will give you the best correlating metric with how Google ranks pages.” That’s how you get page authority domain authority.

Cool, really useful, helpful for us to say like, “Okay, this page is probably considered a little more important than this page by Google, and this one a lot more important.” Very cool. But it’s not a particularly advanced system. The more advanced system is to have these kinds of neural nets in layers. So you have a set of networks, and these neural networks, by the way, they’re designed to replicate nodes in the human brain, which is in my opinion a little creepy, but don’t worry. The article does talk about how there’s a board of scientists who make sure Terminator 2 doesn’t happen, or Terminator 1 for that matter. Apparently, no one’s stopping Terminator 4 from happening? That’s the new one that’s coming out.

So one layer of the neural net will identify features. Another layer of the neural net might classify the types of features that are coming in. Imagine this for search results. Search results are coming in, and Google’s looking at the features of all the websites and web pages, your websites and pages, to try and consider like, “What are the elements I could pull out from there?”

Well, there’s the link data about it, and there are things that happen on the page. There are user interactions and all sorts of stuff. Then we’re going to classify types of pages, types of searches, and then we’re going to extract the features or metrics that predict the desired result, that a user gets a search result they really like. We have an algorithm that can consistently produce those, and then neural networks are hopefully designed — that’s what Geoff Hinton has been working on — to train themselves to get better. So it’s not like with PA and DA, our data scientist Matt Peters and his team looking at it and going, “I bet we could make this better by doing this.”

This is standing back and the guys at Google just going, “All right machine, you learn.” They figure it out. It’s kind of creepy, right?

In the original system, you needed those people, these individuals here to feed the inputs, to say like, “This is what you can consider, system, and the features that we want you to extract from it.”

Then unsupervised learning, which is kind of this next step, the system figures it out. So this takes us to some interesting places. Imagine the Google algorithm, circa 2005. You had basically a bunch of things in here. Maybe you’d have anchor text, PageRank and you’d have some measure of authority on a domain level. Maybe there are people who are tossing new stuff in there like, “Hey algorithm, let’s consider the location of the searcher. Hey algorithm, let’s consider some user and usage data.” They’re tossing new things into the bucket that the algorithm might consider, and then they’re measuring it, seeing if it improves.

But you get to the algorithm today, and gosh there are going to be a lot of things in there that are driven by machine learning, if not deep learning yet. So there are derivatives of all of these metrics. There are conglomerations of them. There are extracted pieces like, “Hey, we only ant to look and measure anchor text on these types of results when we also see that the anchor text matches up to the search queries that have previously been performed by people who also search for this.” What does that even mean? But that’s what the algorithm is designed to do. The machine learning system figures out things that humans would never extract, metrics that we would never even create from the inputs that they can see.

Then, over time, the idea is that in the future even the inputs aren’t given by human beings. The machine is getting to figure this stuff out itself. That’s weird. That means that if you were to ask a Google engineer in a world where deep learning controls the ranking algorithm, if you were to ask the people who designed the ranking system, “Hey, does it matter if I get more links,” they might be like, “Well, maybe.” But they don’t know, because they don’t know what’s in this algorithm. Only the machine knows, and the machine can’t even really explain it. You could go take a snapshot and look at it, but (a) it’s constantly evolving, and (b) a lot of these metrics are going to be weird conglomerations and derivatives of a bunch of metrics mashed together and torn apart and considered only when certain criteria are fulfilled. Yikes.

So what does that mean for SEOs. Like what do we have to care about from all of these systems and this evolution and this move towards deep learning, which by the way that’s what Jeff Dean, who is, I think, a senior fellow over at Google, he’s the dude that everyone mocks for being the world’s smartest computer scientist over there, and Jeff Dean has basically said, “Hey, we want to put this into search. It’s not there yet, but we want to take these models, these things that Hinton has built, and we want to put them into search.” That for SEOs in the future is going to mean much less distinct universal ranking inputs, ranking factors. We won’t really have ranking factors in the way that we know them today. It won’t be like, “Well, they have more anchor text and so they rank higher.” That might be something we’d still look at and we’d say, “Hey, they have this anchor text. Maybe that’s correlated with what the machine is finding, the system is finding to be useful, and that’s still something I want to care about to a certain extent.”

But we’re going to have to consider those things a lot more seriously. We’re going to have to take another look at them and decide and determine whether the things that we thought were ranking factors still are when the neural network system takes over. It also is going to mean something that I think many, many SEOs have been predicting for a long time and have been working towards, which is more success for websites that satisfy searchers. If the output is successful searches, and that’ s what the system is looking for, and that’s what it’s trying to correlate all its metrics to, if you produce something that means more successful searches for Google searchers when they get to your site, and you ranking in the top means Google searchers are happier, well you know what? The algorithm will catch up to you. That’s kind of a nice thing. It does mean a lot less info from Google about how they rank results.

So today you might hear from someone at Google, “Well, page speed is a very small ranking factor.” In the future they might be, “Well, page speed is like all ranking factors, totally unknown to us.” Because the machine might say, “Well yeah, page speed as a distinct metric, one that a Google engineer could actually look at, looks very small.” But derivatives of things that are connected to page speed may be huge inputs. Maybe page speed is something, that across all of these, is very well connected with happier searchers and successful search results. Weird things that we never thought of before might be connected with them as the machine learning system tries to build all those correlations, and that means potentially many more inputs into the ranking algorithm, things that we would never consider today, things we might consider wholly illogical, like, “What servers do you run on?” Well, that seems ridiculous. Why would Google ever grade you on that?

If human beings are putting factors into the algorithm, they never would. But the neural network doesn’t care. It doesn’t care. It’s a honey badger. It doesn’t care what inputs it collects. It only cares about successful searches, and so if it turns out that Ubuntu is poorly correlated with successful search results, too bad.

This world is not here yet today, but certainly there are elements of it. Google has talked about how Panda and Penguin are based off of machine learning systems like this. I think, given what Geoff Hinton and Jeff Dean are working on at Google, it sounds like this will be making its way more seriously into search and therefore it’s something that we’re really going to have to consider as search marketers.

All right everyone, I hope you’ll join me again next week for another edition of Whiteboard Friday. Take care.

Video transcription by Speechpad.com

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