Drive relevancy with the unexpected

Today’s empowered consumer will only invest time in messages that communicate relevancy and drive value, and it’s up to brands to woo customers in order to win their business. In a crowded inbox – 269 billion emails are sent and received each day – uninspiring emails will be tossed into the trash without a second thought.

As marketers, it’s our duty to understand customers and treat them as individuals. And while context in email marketing is king, it’s easy to forget that surprising and delighting customers can also make a lasting impression.

5 tips to blend randomness with relevancy

1. Play with context

Email is your go-to touchpoint for customer interactions, and while it’s important to feature your product offering, it’s more important to showcase your intelligence and understanding of customers; these qualities drive brand credibility and loyalty respectively.

By leveraging rich customer insights – such as buying behaviour and location – you can contextualize messages, tying the customer journey back to the individual’s environment.

Irrelevant messages make email recipients likely to not only ignore email, but to take negative actions such as marking it as spam. Communications that ooze brand personality and resonate with customers are proven to maximize their engagement and prompt them to take the desired action.

A great way to contextualize your email marketing is by sending weather-related messages to contacts based on a live forecast. For example, you can recommend products that complement the weather in real time: barbecues when sunny, raincoats when drizzly and accessories for your snowman to don when the blizzards set in.

With the right level of insight, retailers can use weather rules to populate emails with smart, relevant content that incites emotion and maximizes engagement.

British Heart Foundation does a stellar job of this by sending emails to participants who’ve entered its MyMarathon campaign, letting them know when the weather’s good for a run.

2. Exceed customers’ expectations

To foster genuine advocacy, brands need to continually push the boat out. Today, simply delivering on your brand promise isn’t enough; you need to overdeliver in a meaningful way. Giving subscribers something when they least suspect it can truly enhance their experience.

  • Surprise sign-up gift – thank subscribers for joining your mailing list with a surprise gift. It’s common practice for brands to use incentives as a prop to lure people in at the sign-up stage. However, the positive effect can be greater if you hold back and surprise prospective customers once they’ve joined your list; for instance, by sending them a coupon for £10 off their first order. Subscribers will feel like they’re getting something special for nothing – a gift rather than an exchange for data.
  • Out-of-the-blue freebie – offering a free product (i.e. a sample or voucher to redeem in store) to lapsed customers can awaken their love for your brand. To strike the perfect balance between relevance and randomness, thank the recipient for the last purchase they made using historical ecommerce data. It’s a great talking point and by making someone’s day, you’ll hopefully generate some great exposure for your brand through positive social posts and word-of-mouth recommendations.
  • Rewards for feedback and reviews – to make customers’ experiences more memorable, surprise them with a gift for their feedback.

3. Celebrate random holidays

While it’s common practice for brands to email customers over popular holiday periods – such as Halloween or Valentine’s Day – your messages run the risk of getting lost in all the noise, endangering your engagement metrics. However, capitalizing on a holiday that isn’t as widespread can give you a competitive advantage in a quieter inbox.

In 2009, Chinese ecommerce giant Alibaba adopted ‘Singles Day’ – an anti-Valentine’s Day celebration – as a prime online shopping event during what’s considered a traditionally low volume sales period. Driving relevancy to the millions of singletons in China, Alibaba made a colossal $25.3 billion in sales on Singles Day 2017. This goes to show that brands can popularize unfamiliar holidays and make significant gains.

There are many weird and wacky holidays throughout the year, from ‘Bittersweet Chocolate with Almonds Day’ to ‘Bicarbonate of Soda Day’ (which is on 30th December, if you’re interested).

When applying randomness to your email marketing, it’s important that the topic still resonates with customers. Make sure your holiday of choice:

  • marries up with your brand’s personality
  • provides a topic of conversation that inspires social sharing
  • drives customers to take your desired action

Download our full cheatsheet to get tips on our favorite random holidays – which include dress up your pet day!

4. Employ game mechanics

For an email to draw people in – over and above visual appeal – you need to invite them to participate and connect with you in an innovative, playful way. Gaming urges subscribers to interact beyond the bounds of a simple call-to-action, which can be uninspiring by comparison.

Capitalizing on the relevancy of the message can spur people to take an action; for example, associating the game with customers’ previous behaviors (sign-up, purchase etc.) makes an exchange of their time more appealing. You’ll need to ensure the game has that fun-appeal and is benefit-driven, otherwise subscribers won’t view it as worthwhile.

To gamify your email marketing strategy, explore activities that are all about chance:

  • Puzzles – encourage subscribers to unlock potential offers/win gifts
  • Spinning wheels – let customers gamble for discount types and amounts (i.e. percentage, money-off)
  • Online board games – prompt players to roll the dice in an attempt to win different prizes and advance various stages to enter exclusive competition draws

These techniques can enhance your KPIs – such as click-to-open and conversion rates – and boost revenue. What’s more, encouraging interaction in email can have a positive impact on your deliverability; email clients such as Gmail will attribute higher engagement rates to your domain, improving your sender reputation and inbox placement.

5. Shake up your subject lines

First impressions matter. The subject line is the first prompt for subscribers to either open, ignore or trash your email; 50% of recipients open emails based on subject line alone, whereas 69% report emails as spam on the same basis.

So, how do we incentivize the reader to open? Should the subject line mirror what’s in the email or should it just be completely random? Although some marketers opt for something outlandish that catches the reader’s eye, the subject line should echo the email’s contents, otherwise it could be damaging to click-through rates.

Brands are increasingly adopting subject lines based on context. By leveraging your real-time customer insights, you can drive out-of-the-blue messages with a well-timed tease that rouses interest and triggers those all-important opens.

People’s attention spans have, in the past, been likened to that of a goldfish. And the sheer volume of email traffic makes it an even tougher job for marketers to grab the reader’s eye. The key is to tap into those powerful emotions and feelings: urgency, curiosity, excitement and joy. To achieve this, you’ll have to be data-driven, original and conversational.

Download our cheatsheet for a deep-dive into contextual and captivating subject lines.

Give randomness a go!

As busy, always-on individuals, we’ve no time for meaningless communications. Today’s savvy consumers want to be treated like individuals through conversations that are thought-provoking and original. Don’t neglect your indispensable customer insight – which is your greatest asset – in place of a flat, uninspiring email strategy. Driving relevance on the premise of being unpredictable will win consumers over, every time.

For more insights into driving relevancy with the unexpected, download our cheatsheet here.

 

The post Drive relevancy with the unexpected appeared first on The Marketing Automation Blog.

Reblogged 3 months ago from blog.dotmailer.com

8 Ways Content Marketers Can Hack Facebook Multi-Product Ads

Posted by Alan_Coleman

The trick most content marketers are missing

Creating great content is the first half of success in content marketing. Getting quality content read by, and amplified to, a relevant audience is the oft overlooked second half of success. Facebook can be a content marketer’s best friend for this challenge. For reach, relevance and amplification potential, Facebook is unrivaled.

  1. Reach: 1 in 6 mobile minutes on planet earth is somebody reading something on Facebook.
  2. Relevance: Facebook is a lean mean interest and demo targeting machine. There is no online or offline media that owns as much juicy interest and demographic information on its audience and certainly no media has allowed advertisers to utilise this information as effectively as Facebook has.
  3. Amplification: Facebook is literally built to encourage sharing. Here’s the first 10 words from their mission statement: “Facebook’s mission is to give people the power to share…”, Enough said!

Because of these three digital marketing truths, if a content marketer gets their paid promotion* right on Facebook, the battle for eyeballs and amplification is already won.

For this reason it’s crucial that content marketers keep a close eye on Facebook advertising innovations and seek out ways to use them in new and creative ways.

In this post I will share with you eight ways we’ve hacked a new Facebook ad format to deliver content marketing success.

Multi-Product Ads (MPAs)

In 2014, Facebook unveiled multi-product ads (MPAs) for US advertisers, we got them in Europe earlier this year. They allow retailers to show multiple products in a carousel-type ad unit.

They look like this:

If the user clicks on the featured product, they are guided directly to the landing page for that specific product, from where they can make a purchase.

You could say MPAs are Facebook’s answer to Google Shopping.

Facebook’s mistake is a content marketer’s gain

I believe Facebook has misunderstood how people want to use their social network and the transaction-focused format is OK at best for selling products. People aren’t really on Facebook to hit the “buy now” button. I’m a daily Facebook user and I can’t recall a time this year where I have gone directly from Facebook to an e-commerce website and transacted. Can you remember a recent time when you did?

So, this isn’t an innovation that removes a layer of friction from something that we are all doing online already (as the most effective innovations do). Instead, it’s a bit of a “hit and hope” that, by providing this functionality, Facebook would encourage people to try to buy online in a way they never have before.

The Wolfgang crew felt the MPA format would be much more useful to marketers and users if they were leveraging Facebook for the behaviour we all demonstrate on the platform every day, guiding users to relevant content. We attempted to see if Facebook Ads Manager would accept MPAs promoting content rather than products. We plugged in the images, copy and landing pages, hit “place order”, and lo and behold the ads became active. We’re happy to say that the engagement rates, and more importantly the amplification rates, are fantastic!

Multi-Content Ads

We’ve re-invented the MPA format for multi-advertisers in multi-ways, eight ways to be exact! Here’s eight MPA Hacks that have worked well for us. All eight hacks use the MPA format to promote content rather than promote products.

Hack #1: Multi-Package Ads

Our first variation wasn’t a million miles away from multi-product ads; we were promoting the various packages offered by a travel operator.

By looking at the number of likes, comments, and shares (in blue below the ads) you can see the ads were a hit with Facebook users and they earned lots of free engagement and amplification.

NB: If you have selected “clicks to website” as your advertising objective, all those likes, comments and shares are free!

Independent Travel Multi Product Ad

The ad sparked plenty of conversation amongst Facebook friends in the comments section.

Comments on a Facebook MPA

Hack #2: Multi-Offer Ads

Everybody knows the Internet loves a bargain. So we decided to try another variation moving away from specific packages, focusing instead on deals for a different travel operator.

Here’s how the ads looked:

These ads got valuable amplification beyond the share. In the comments section, you can see people tagging specific friends. This led to the MPAs receiving further amplification, and a very targeted and personalised form of amplification to boot.

Abbey Travel Facebook Ad Comments

Word of mouth referrals have been a trader’s best friend since the stone age. These “personalised” word of mouth referrals en masse are a powerful marketing proposition. It’s worth mentioning again that those engagements are free!

Hack #3: Multi-Locations Ads

Putting the Lo in SOLOMO.

This multi-product feed ad was hacked to promote numerous locations of a waterpark. “Where to go?” is among the first questions somebody asks when researching a holiday. In creating this top of funnel content, we can communicate with our target audience at the very beginning of their research process. A simple truth of digital marketing is: the more interactions you have with your target market on their journey to purchase, the more likely they are to seal the deal with you when it comes time to hit the “buy now” button. Starting your relationship early gives you an advantage over those competitors who are hanging around the bottom of the purchase funnel hoping to make a quick and easy conversion.

Abbey Travel SplashWorld Facebook MPA

What was surprising here, was that because we expected to reach people at the very beginning of their research journey, we expected the booking enquiries to be some time away. What actually happened was these ads sparked an enquiry frenzy as Facebook users could see other people enquiring and the holidays selling out in real time.

Abbey Travel comments and replies

In fact nearly all of the 35 comments on this ad were booking enquiries. This means what we were measuring as an “engagement” was actually a cold hard “conversion”! You don’t need me to tell you a booking enquiry is far closer to the money than a Facebook like.

The three examples outlined so far are for travel companies. Travel is a great fit for Facebook as it sits naturally in the Facebook feed, my Facebook feed is full of envy-inducing friends’ holiday pictures right now. Another interesting reason why travel is a great fit for Facebook ads is because typically there are multiple parties to a travel purchase. What happened here is the comments section actually became a very visible and measurable forum for discussion between friends and family before becoming a stampede inducing medium of enquiry.

So, stepping outside of the travel industry, how do other industries fare with hacked MPAs?

Hack #3a: Multi-Location Ads (combined with location targeting)

Location, location, location. For a property listings website, we applied location targeting and repeated our Multi-Location Ad format to advertise properties for sale to people in and around that location.

Hack #4: Multi-Big Content Ad

“The future of big content is multi platform”

– Cyrus Shepard

The same property website had produced a report and an accompanying infographic to provide their audience with unique and up-to-the-minute market information via their blog. We used the MPA format to promote the report, the infographic and the search rentals page of the website. This brought their big content piece to a larger audience via a new platform.

Rental Report Multi Product Ad

Hack #5: Multi-Episode Ad

This MPA hack was for an online TV player. As you can see we advertised the most recent episodes of a TV show set in a fictional Dublin police station, Red Rock.

Engagement was high, opinion was divided.

TV3s Red Rock viewer feedback

LOL.

Hack #6: Multi-People Ads

In the cosmetic surgery world, past patients’ stories are valuable marketing material. Particularly when the past patients are celebrities. We recycled some previously published stories from celebrity patients using multi-people ads and targeted them to a very specific audience.

Avoca Clinic Multi People Ads

Hack #7: Multi-UGC Ads

Have you witnessed the power of user generated content (UGC) in your marketing yet? We’ve found interaction rates with authentic UGC images can be up to 10 fold of those of the usual stylised images. In order to encourage further UGC, we posted a number of customer’s images in our Multi-UGC Ads.

The CTR on the above ads was 6% (2% is the average CTR for Facebook News feed ads according to our study). Strong CTRs earn you more traffic for your budget. Facebook’s relevancy score lowers your CPC as your CTR increases.

When it comes to the conversion, UGC is a power player, we’ve learned that “customers attracting new customers” is a powerful acquisition tool.

Hack #8: Target past customers for amplification

“Who will support and amplify this content and why?”

– Rand Fishkin

Your happy customers Rand, that’s the who and the why! Check out these Multi-Package Ads targeted to past customers via custom audiences. The Camino walkers have already told all their friends about their great trip, now allow them to share their great experiences on Facebook and connect the tour operator with their Facebook friends via a valuable word of mouth referral. Just look at the ratio of share:likes and shares:comments. Astonishingly sharable ads!

Camino Ways Mulit Product Ads

Targeting past converters in an intelligent manner is a super smart way to find an audience ready to share your content.

How will hacking Multi-Product Ads work for you?

People don’t share ads, but they do share great content. So why not hack MPAs to promote your content and reap the rewards of the world’s greatest content sharing machine: Facebook.

MPAs allow you to tell a richer story by allowing you to promote multiple pieces of content simultaneously. So consider which pieces of content you have that will work well as “content bundles” and who the relevant audience for each “content bundle” is.

As Hack #8 above illustrates, the big wins come when you match a smart use of the format with the clever and relevant targeting Facebook allows. We’re massive fans of custom audiences so if you aren’t sure where to start, I’d suggest starting there.

So ponder your upcoming content pieces, consider your older content you’d like to breathe some new life into and perhaps you could become a Facebook Ads Hacker.

I’d love to hear about your ideas for turning Multi-Product Ads into Multi-Content Ads in the comments section below.

We could even take the conversation offline at Mozcon!

Happy hacking.


*Yes I did say paid promotion, it’s no secret that Facebook’s organic reach continues to dwindle. The cold commercial reality is you need to pay to play on FB. The good news is that if you select ‘website clicks’ as your objective you only pay for website traffic and engagement while amplification by likes, comments, and shares are free! Those website clicks you pay for are typically substantially cheaper than Adwords, Taboola, Outbrain, Twitter or LinkedIn. How does it compare to display? It doesn’t. Paying for clicks is always preferable to paying for impressions. If you are spending money on display advertising I’d urge you to fling a few spondoolas towards Facebook ads and compare results. You will be pleasantly surprised.

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Big Data, Big Problems: 4 Major Link Indexes Compared

Posted by russangular

Given this blog’s readership, chances are good you will spend some time this week looking at backlinks in one of the growing number of link data tools. We know backlinks continue to be one of, if not the most important
parts of Google’s ranking algorithm. We tend to take these link data sets at face value, though, in part because they are all we have. But when your rankings are on the line, is there a better way to get at which data set is the best? How should we go
about assessing these different link indexes like
Moz,
Majestic, Ahrefs and SEMrush for quality? Historically, there have been 4 common approaches to this question of index quality…

  • Breadth: We might choose to look at the number of linking root domains any given service reports. We know
    that referring domains correlates strongly with search rankings, so it makes sense to judge a link index by how many unique domains it has
    discovered and indexed.
  • Depth: We also might choose to look at how deep the web has been crawled, looking more at the total number of URLs
    in the index, rather than the diversity of referring domains.
  • Link Overlap: A more sophisticated approach might count the number of links an index has in common with Google Webmaster
    Tools.
  • Freshness: Finally, we might choose to look at the freshness of the index. What percentage of links in the index are
    still live?

There are a number of really good studies (some newer than others) using these techniques that are worth checking out when you get a chance:

  • BuiltVisible analysis of Moz, Majestic, GWT, Ahrefs and Search Metrics
  • SEOBook comparison of Moz, Majestic, Ahrefs, and Ayima
  • MatthewWoodward
    study of Ahrefs, Majestic, Moz, Raven and SEO Spyglass
  • Marketing Signals analysis of Moz, Majestic, Ahrefs, and GWT
  • RankAbove comparison of Moz, Majestic, Ahrefs and Link Research Tools
  • StoneTemple study of Moz and Majestic

While these are all excellent at addressing the methodologies above, there is a particular limitation with all of them. They miss one of the
most important metrics we need to determine the value of a link index: proportional representation to Google’s link graph
. So here at Angular Marketing, we decided to take a closer look.

Proportional representation to Google Search Console data

So, why is it important to determine proportional representation? Many of the most important and valued metrics we use are built on proportional
models. PageRank, MozRank, CitationFlow and Ahrefs Rank are proportional in nature. The score of any one URL in the data set is relative to the
other URLs in the data set. If the data set is biased, the results are biased.

A Visualization

Link graphs are biased by their crawl prioritization. Because there is no full representation of the Internet, every link graph, even Google’s,
is a biased sample of the web. Imagine for a second that the picture below is of the web. Each dot represents a page on the Internet,
and the dots surrounded by green represent a fictitious index by Google of certain sections of the web.

Of course, Google isn’t the only organization that crawls the web. Other organizations like Moz,
Majestic, Ahrefs, and SEMrush
have their own crawl prioritizations which result in different link indexes.

In the example above, you can see different link providers trying to index the web like Google. Link data provider 1 (purple) does a good job
of building a model that is similar to Google. It isn’t very big, but it is proportional. Link data provider 2 (blue) has a much larger index,
and likely has more links in common with Google that link data provider 1, but it is highly disproportional. So, how would we go about measuring
this proportionality? And which data set is the most proportional to Google?

Methodology

The first step is to determine a measurement of relativity for analysis. Google doesn’t give us very much information about their link graph.
All we have is what is in Google Search Console. The best source we can use is referring domain counts. In particular, we want to look at
what we call
referring domain link pairs. A referring domain link pair would be something like ask.com->mlb.com: 9,444 which means
that ask.com links to mlb.com 9,444 times.

Steps

  1. Determine the root linking domain pairs and values to 100+ sites in Google Search Console
  2. Determine the same for Ahrefs, Moz, Majestic Fresh, Majestic Historic, SEMrush
  3. Compare the referring domain link pairs of each data set to Google, assuming a
    Poisson Distribution
  4. Run simulations of each data set’s performance against each other (ie: Moz vs Maj, Ahrefs vs SEMrush, Moz vs SEMrush, et al.)
  5. Analyze the results

Results

When placed head-to-head, there seem to be some clear winners at first glance. In head-to-head, Moz edges out Ahrefs, but across the board, Moz and Ahrefs fare quite evenly. Moz, Ahrefs and SEMrush seem to be far better than Majestic Fresh and Majestic Historic. Is that really the case? And why?

It turns out there is an inversely proportional relationship between index size and proportional relevancy. This might seem counterintuitive,
shouldn’t the bigger indexes be closer to Google? Not Exactly.

What does this mean?

Each organization has to create a crawl prioritization strategy. When you discover millions of links, you have to prioritize which ones you
might crawl next. Google has a crawl prioritization, so does Moz, Majestic, Ahrefs and SEMrush. There are lots of different things you might
choose to prioritize…

  • You might prioritize link discovery. If you want to build a very large index, you could prioritize crawling pages on sites that
    have historically provided new links.
  • You might prioritize content uniqueness. If you want to build a search engine, you might prioritize finding pages that are unlike
    any you have seen before. You could choose to crawl domains that historically provide unique data and little duplicate content.
  • You might prioritize content freshness. If you want to keep your search engine recent, you might prioritize crawling pages that
    change frequently.
  • You might prioritize content value, crawling the most important URLs first based on the number of inbound links to that page.

Chances are, an organization’s crawl priority will blend some of these features, but it’s difficult to design one exactly like Google. Imagine
for a moment that instead of crawling the web, you want to climb a tree. You have to come up with a tree climbing strategy.

  • You decide to climb the longest branch you see at each intersection.
  • One friend of yours decides to climb the first new branch he reaches, regardless of how long it is.
  • Your other friend decides to climb the first new branch she reaches only if she sees another branch coming off of it.

Despite having different climb strategies, everyone chooses the same first branch, and everyone chooses the same second branch. There are only
so many different options early on.

But as the climbers go further and further along, their choices eventually produce differing results. This is exactly the same for web crawlers
like Google, Moz, Majestic, Ahrefs and SEMrush. The bigger the crawl, the more the crawl prioritization will cause disparities. This is not a
deficiency; this is just the nature of the beast. However, we aren’t completely lost. Once we know how index size is related to disparity, we
can make some inferences about how similar a crawl priority may be to Google.

Unfortunately, we have to be careful in our conclusions. We only have a few data points with which to work, so it is very difficult to be
certain regarding this part of the analysis. In particular, it seems strange that Majestic would get better relative to its index size as it grows,
unless Google holds on to old data (which might be an important discovery in and of itself). It is most likely that at this point we can’t make
this level of conclusion.

So what do we do?

Let’s say you have a list of domains or URLs for which you would like to know their relative values. Your process might look something like
this…

  • Check Open Site Explorer to see if all URLs are in their index. If so, you are looking metrics most likely to be proportional to Google’s link graph.
  • If any of the links do not occur in the index, move to Ahrefs and use their Ahrefs ranking if all you need is a single PageRank-like metric.
  • If any of the links are missing from Ahrefs’s index, or you need something related to trust, move on to Majestic Fresh.
  • Finally, use Majestic Historic for (by leaps and bounds) the largest coverage available.

It is important to point out that the likelihood that all the URLs you want to check are in a single index increases as the accuracy of the metric
decreases. Considering the size of Majestic’s data, you can’t ignore them because you are less likely to get null value answers from their data than
the others. If anything rings true, it is that once again it makes sense to get data
from as many sources as possible. You won’t
get the most proportional data without Moz, the broadest data without Majestic, or everything in-between without Ahrefs.

What about SEMrush? They are making progress, but they don’t publish any relative statistics that would be useful in this particular
case. Maybe we can hope to see more from them soon given their already promising index!

Recommendations for the link graphing industry

All we hear about these days is big data; we almost never hear about good data. I know that the teams at Moz,
Majestic, Ahrefs, SEMrush and others are interested in mimicking Google, but I would love to see some organization stand up against the
allure of
more data in favor of better data—data more like Google’s. It could begin with testing various crawl strategies to see if they produce
a result more similar to that of data shared in Google Search Console. Having the most Google-like data is certainly a crown worth winning.

Credits

Thanks to Diana Carter at Angular for assistance with data acquisition and Andrew Cron with statistical analysis. Thanks also to the representatives from Moz, Majestic, Ahrefs, and SEMrush for answering questions about their indices.

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don’t have time to hunt down but want to read!

Reblogged 3 years ago from tracking.feedpress.it

Illustrated Guide to Advanced On-Page Topic Targeting for SEO

Posted by Cyrus-Shepard

Topic n. A subject or theme of a webpage, section, or site.

Several SEOs have recently written about topic modeling and advanced on-page optimization. A few of note:

The concepts themselves are dizzying: LDA, co-occurrence, and entity salience, to name only a few. The question is
“How can I easily incorporate these techniques into my content for higher rankings?”

In fact, you can create optimized pages without understanding complex algorithms. Sites like Wikipedia, IMDB, and Amazon create highly optimized, topic-focused pages almost by default. Utilizing these best practices works exactly the same when you’re creating your own content.

The purpose of this post is to provide a simple
framework for on-page topic targeting in a way that makes optimizing easy and scalable while producing richer content for your audience.

1. Keywords and relationships

No matter what topic modeling technique you choose, all rely on discovering
relationships between words and phrases. As content creators, how we organize words on a page greatly influences how search engines determine the on-page topics.

When we use keywords phrases, search engines hunt for other phrases and concepts that
relate to one another. So our first job is to expand our keywords research to incorporate these related phrases and concepts. Contextually rich content includes:

  • Close variants and synonyms: Includes abbreviations, plurals, and phrases that mean the same thing.
  • Primary related keywords: Words and phrases that relate to the main keyword phrase.
  • Secondary related keywords: Words and phrases that relate to the primary related keywords.
  • Entity relationships: Concept that describe the properties and relationships between people, places, and things. 

A good keyword phrase or entity is one that
predicts the presence of other phrases and entities on the page. For example, a page about “The White House” predicts other phrases like “president,” “Washington,” and “Secret Service.” Incorporating these related phrases may help strengthen the topicality of “White House.”

2. Position, frequency, and distance

How a page is organized can greatly influence how concepts relate to each other.

Once search engines find your keywords on a page, they need to determine which ones are most
important, and which ones actually have the strongest relationships to one another.

Three primary techniques for communicating this include:

  • Position: Keywords placed in important areas like titles, headlines, and higher up in the main body text may carry the most weight.
  • Frequency: Using techniques like TF-IDF, search engines determine important phrases by calculating how often they appear in a document compared to a normal distribution.
  • Distance: Words and phrases that relate to each other are often found close together, or grouped by HTML elements. This means leveraging semantic distance to place related concepts close to one another using paragraphs, lists, and content sectioning.

A great way to organize your on-page content is to employ your primary and secondary related keywords in support of your focus keyword. Each primary related phrase becomes its own subsection, with the secondary related phrases supporting the primary, as illustrated here.

Keyword Position, Frequency and Distance

As an example, the primary keyword phrase of this page is ‘On-page Topic Targeting‘. Supporting topics include: keywords and relationships, on-page optimization, links, entities, and keyword tools. Each related phrase supports the primary topic, and each becomes its own subsection.

3. Links and supplemental content

Many webmasters overlook the importance of linking as a topic signal.

Several well-known Google
search patents and early research papers describe analyzing a page’s links as a way to determine topic relevancy. These include both internal links to your own pages and external links to other sites, often with relevant anchor text.

Google’s own
Quality Rater Guidelines cites the value external references to other sites. It also describes a page’s supplemental content, which can includes internal links to other sections of your site, as a valuable resource.

Links and Supplemental Content

If you need an example of how relevant linking can help your SEO,
The New York Times
famously saw success, and an increase in traffic, when it started linking out to other sites from its topic pages.

Although this guide discusses
on-page topic optimization, topical external links with relevant anchor text can greatly influence how search engines determine what a page is about. These external signals often carry more weight than on-page cues, but it almost always works best when on-page and off-page signals are in alignment.

4. Entities and semantic markup

Google extracts entities from your webpage automatically,
without any effort on your part. These are people, places and things that have distinct properties and relationships with each other.

• Christopher Nolan (entity, person) stands 5’4″ (property, height) and directed Interstellar (entity, movie)

Even though entity extraction happens automatically, it’s often essential to mark up your content with
Schema for specific supported entities such as business information, reviews, and products. While the ranking benefit of adding Schema isn’t 100% clear, structured data has the advantage of enhanced search results.

Entities and Schema

For a solid guide in implementing schema.org markup, see Builtvisible’s excellent
guide to rich snippets.

5. Crafting the on-page framework

You don’t need to be a search genius or spend hours on complex research to produce high quality, topic optimized content. The beauty of this framework is that it can be used by anyone, from librarians to hobby bloggers to small business owners; even when they aren’t search engine experts.

A good webpage has much in common with a high quality university paper. This includes:

  1. A strong title that communicates the topic
  2. Introductory opening that lays out what the page is about
  3. Content organized into thematic subsections
  4. Exploration of multiple aspects of the topic and answers related questions
  5. Provision of additional resources and external citations

Your webpage doesn’t need to be academic, stuffy, or boring. Some of the most interesting pages on the Internet employ these same techniques while remaining dynamic and entertaining.

Keep in mind that ‘best practices’ don’t apply to every situation, and as
Rand Fishkin says “There’s no such thing as ‘perfectly optimized’ or ‘perfect on-page SEO.'” Pulling everything together looks something like this:

On-page Topic Targeting for SEO

This graphic is highly inspired by Rand Fishkin’s great
Visual Guide to Keyword Targeting and On-Page SEO. This guide doesn’t replace that canonical resource. Instead, it should be considered a supplement to it.

5 alternative tools for related keyword and entity research

For the search professional, there are dozens of tools available for thematic keyword and entity research. This list is not exhaustive by any means, but contains many useful favorites.

1.
Alchemy API

One of the few tools on the market that delivers entity extraction, concept targeting and linked data analysis. This is a great platform for understanding how a modern search engine views your webpage.

2.
SEO Review Tools

The SEO Keyword Suggestion Tools was actually designed to return both primary and secondary related keywords, as well as options for synonyms and country targeting. 

3.
LSIKeywords.com

The LSIKeyword tool performs Latent Semantic Indexing (LSI) on the top pages returned by Google for any given keyword phrase. The tool can go down from time to time, but it’s a great one to bookmark.

4.
Social Mention

Quick and easy, enter any keyword phrase and then check “Top Keywords” to see what words appear most with your primary phrase across the of the platforms that Social Mention monitors. 

5.
Google Trends

Google trends is a powerful related research tool, if you know how to use it. The secret is downloading your results to a CSV (under settings) to get a list up to 50 related keywords per search term.

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Reblogged 4 years ago from feedproxy.google.com