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10 Effective ways to boost click-through rate (CTR) using SERPs

November 25, 2020 No Comments

30-second summary:

  • Search engine ranking pages and algorithms are evolving quickly and you should keep pace with them to succeed.
  • Did you know, 51% of all searches end without a click?
  • Gone are the days when there are only organic text-based results on the page.
  • Today, there are paid listings, zero-click searches, images, videos, maps, featured snippets, people also asked for boxes, and even podcasts that result in dismal click-through rates (CTRs).
  • Branex’s digital marketing strategist, Irfan Ak has created a top 10 list that can boost your CTR in Google SERPs.

If you closely look at the first page of Google for any competitive keyword, you will find tons of elements on it. Gone are the days when there are only organic text-based results on the page. Today, there are images, videos, maps, featured snippets, people also asked for boxes, and even podcasts. Then there are paid listings which are visible on top of organic listings. SEO trends are changing quickly and it is impacting search engine results pages (SERPs). All this translates into declining organic reach, dismal click-through rate (CTR), and the rise of zero-click searches.

In fact, 51% of all searches end without a click. With search engines trying their best to fulfill user needs on search pages itself, fewer users will scroll down and click through your listing as they get the desired answer on the search page.

In this article, you will learn about ten effective ways to boost click-through rate (CTR) using SERPs.

How to increase click-through rate (CTR) - Stats

Source: SparkToro

1. Optimize for featured snippets

The coveted number one spot is no longer the target for digital marketers and digital marketing agencies. The focus has shifted to Position Zero. According to Ahrefs study, 12.3% of search queries have featured snippets. Search engines like Google pull data from the top 10 results to show as a featured snippet. If your blog or website is ranking on the first page of Google, you have an opportunity to grab the featured snippet and boost your visibility.

To do so, you need to understand the purpose of featured snippets. The main reason why search engines show featured snippets is that they want to provide a direct answer to a search query and if your listing does that, you have a bright chance of getting featured on a much sought-after position zero. 

Add featured snippets to increase click-through rate (CTR)

Source: Ahrefs

Secondly, featured snippets are displayed for long-tail keywords or questions-based queries. The focus is usually on offering short and precise answers to the user query and if your listing can do that while optimizing for long-tail keywords, it can rank on featured snippets. 

2. Improve your rankings

According to a study conducted by Backlnko which analyzed 5 million Google search results, moving one spot up can increase your click-through rate by almost 30.8%. Even though, this might vary depending on your current position and the position you have moved to. The same study also found that jumping from 10th position to 7th position did not have the same impact as moving from 6th position to 5th position or 2nd position to 1st position might have on your click-through rate. Instead of striving for ranking on the first page of Google, you should focus on ranking in the top three positions as 75.1% of all clicks go to the top three spots.

Click-through rate (CTR) organic - breakdown stats

Source: Backlinko

3. Write captivating headlines

David Ogilvy, the “Father of Advertising” and Founder of Ogilvy & Mather, once said,

“On the average, five times as many people read the headline as read the body copy. When you have written your headline, you have spent eighty cents out of your dollar.”

What is the first thing that users will read when they look at your listing? It is the headline. It can literally make it or break it for you. That is why it is important to write attention-grabbing headlines. Add an emotional element to your headline as research has shown that including positive or negative sentiments to your headlines can increase its click-through rate by 7%. Backlinko’s study I referenced above also found that titles that contain 15-40 characters have the highest organic click-through rate.

4. Meta description and URL

Have you ever seen a search result closely? What does it contain? A search engine listing usually comprises of three things

  • Title
  • URL
  • Meta Description

After optimizing your title, you should focus on optimizing your URL and meta description for click-through rate. Add your keyword in the URL as it will increase your clickthrough rate by 45% as compared to URLs that don’t contain the keyword.

Just like the title and URL, add your keyword in the meta description as well. Write a meta description in active voice and try to make it as actionable as possible. Don’t forget to add a call to action to persuade users to click on your listings. Make sure all the pages on your website have a meta description because pages that contain the meta description generate 5.8% more clicks than pages without meta description.

5. Add a schema markup

Search engines use a spider to crawl web pages and create an index of all those pages. The easier it is for search engines to crawl your website, the faster they will crawl your website and more likely your website to get indexed and ranked. By adding schema markup to your website, you can make it easy for search engines to understand what your website is all about and how different pages on your website covers.

There are different types of schema markups and implementing the right kind on your website can do wonders. For example, a review schema markup allows search engines to display ratings in your organic results. If your rating is good, it can increase your credibility, build trust, and help you attract new customers while increasing your click-through rate.

6. Optimize for Google My Business

Do you have a Google My Business page? If your answer is no, then you are missing out. Get your business featured on Google My Business and enter all the business details. Whether it is location-based searches, branded searches, or business-related or service-related searches, Google My Business results tend to show up.

Another advantage of using Google My Business is that it allows you to collect reviews and ratings from customers as well as allows your business to answer user questions. Both can help you build trust and win new customers. The more positive reviews your business has or the higher the rating, the better. It also offers some useful features to customers such as sharing business information with others or contacting the business directly.

7. Run well-targeted PPC ads

One of the best ways to overcome declining organic reach is to invest in PPC ads. Yes, they might be expensive in certain industries and might not work that well in other industries but if you are looking for quick results, PPC ads are your best bet, provided your PPC targeting strategy is on the money. Run PPC ads on branded keywords and prevent others from occupying your ad space. 

When you run PPC ads, it attracts targeted traffic that is more likely to convert into paying customers. This means that it not only increases your click-through rate but also increases your conversion rates too. The key to success with PPC ads is to choose the right ad type according to your industry.

8. Optimize images and videos for SEO

As mentioned before, SERPs are no longer limited to showing organic results anymore. They also show images, videos, and featured snippets to name just a few. What’s even more interesting is the fact that SERPs showing images and videos are slowly but surely increasing in number. This means that you can optimize your images and videos to increase your chances of ranking on these SERPs.

Here are some of the ways you can use to optimize images for SEO.

  • Use targeted keywords in image and video title, description, and alternate text
  • Place the image and video in a section of the page or in content where it best matches the keyword intent
  • Compress large size images and videos
  • Add a caption to images
  • Use common image sizes and optimal image formats

9. Give an irresistible limited time offer

Create a sense of urgency and use tactics such as countdown timer or mention the number of items remaining. When a user sees these things on your page, they are rushed into taking the desired action. Give a limited time offer that your target audience cannot resist, and you will see your clickthrough rate shoot through the roof. Don’t forget to add a call to action that tells users which action they should take next.

10. Optimize social media channel to show up in knowledge panels

Last but certainly not least is to optimize social media pages for knowledge panels. Search engines display these knowledge panels in order to present all your business information in a concise way. As a business, you can use this as an opportunity to connect your social media accounts and let users contact you directly from search engine results pages. For this process to work, all your social media accounts should pass the verification by Google. You can also use schema markup to highlight your social media accounts.

How do you boost your click-through rate using search engine result pages? Let us know in the comments section below.

Irfan Ak is an experienced digital marketing strategist, growth hacker, digital transformation expert at Branex. He can be found on Twitter @irrfanAK.

The post 10 Effective ways to boost click-through rate (CTR) using SERPs appeared first on Search Engine Watch.

Search Engine Watch


Guide to using interactive 404s to boost your SEO

September 27, 2020 No Comments

30-second summary:

  • Reducing bad user experience of 404 errors by branding and customizing them.
  • Including links to 404s allow users to navigate the website even when they come across a potential dead end.
  • Boost SEO by placing your sitemap, homepage tab, and search bar.
  • Usage of conversational language along with attractive visuals reduces user’s contempt and frustration.
  • Mention of blog on your customized 404 error page promotes your intellectual prowess for possible users who might be interested in your content.
  • Amanda Jerelyn shares some amazing methods to improve the SEO of your site even through 404 pages.
  • Lastly, some tips to help you avoid 404 errors wherever possible.

Bad user experience can lead to your website’s demise and can also adversely affect your website rankings. This is why 404 errors are considered deplorable when taking into their perspective regarding both user experience and the search engine rankings of your website.

However, there are ways through which you can use 404s to boost your SEO, as in some situations, it is not a broken link but an error by the user that can cause them.

A 404 can be generated when a user types in a faulty address, and this may result in an error being generated on their browser that may look bad, but you can definitely address the situation.

According to a recent study conducted by Gomez, a commercial platform that runs tests for web performance, 88% of online consumers are less likely to return to a website after a bad experience.

In the light of this information, let us take a quick look at some of the ways you can use 404s to negate such inferences and strengthen your SEO.

1. Add links to them

Creating interactive 404s - Add links

Screenshot Credits

Perhaps one of the best ways to make use of 404s is to design them so that it can link random internal pages from your website. This will allow you to get more website pages indexed through your 404 error pages. This can be achieved by running an algorithm that can help you to link out to a random number of internal pages.

Hence whenever a 404 page is generated, the links also change each time. According to Neil Patel’s own practice, he was able to boost TechCrunch search engine traffic by 9% in just a matter of 30 days. As far as search engines go, Google itself encourages developers to create custom 404 pages.

Since it is a standard HTML page, developers can customize it the way they want to, hence adding links to 404 pages shouldn’t be a big hassle.

2. Brand and customize them

Creating interactive 404s - Brand and customize

Screenshot Credits

The inconvenience user experiences when they run into a 404 can be quite infuriating; however, this is also a moment where you can use creativity to capture their attention. By branding and customizing your 404 pages, one can actually boost their website revenues and increase their conversions.

However, this might involve additional effort where a 404 page has to be properly designed and optimized in order to turn lost visitors into loyal customers. A standard 404 page doesn’t look good at all. In fact, it seems like coming for an era that was far less progressive. We understand that visuals play a huge role in attracting customers.

Several social media and marketing statistics proclaim the power of visuals, such as the fact that 96% of online shoppers watch a video about a product or a service before making a decision and that 88% of marketers prefer visuals in their published content.

So why refrain from using visuals and not branding your 404s? The answer is that you should definitely not only brand them but also customize them to make them even more appealing for your users.

3. Put in a search bar

Creating interactive 404s - Add a search bar

Screenshot Credits

Another great tactic to follow with your 404 pages is to add in a search bar. This is further reflected by the study published by the Search Engine Journal, where 81% of users think less of a brand if it’s outdated, and that 40% of users consider search box as the most important feature.

Therefore this should be plenty of reasons for you to make this change happen. A search bar added to your 404 is like sweet candy to a small kid who just dropped their ice-cream.

Surely it is not what they were expecting, but with the power of search in their hands, they can begin their adventure anew. Plus, a nice consolidating message to go along with it would also work wonders.

It is all about compensating for the error they just ran into. Hence you are covering damages and making it easier for your users to recover from them.

4. Include mentions of popular landing pages

Creating interactive 404s - Add popular landing pages to encourage engagement

Screenshot Credits

Remember that your main goal is to create attention for your online users and direct them to your most profitable and viable landing pages. Hence even when your customers accidentally land themselves on a 404 error page, you can continue your efforts to divert their attention from the error and towards your most popular products and services. It is like a never-back down approach.

Sure, you would be offering them some comforting words to soften the impact created by the error. However, marketing is all about never quitting. Hence your 404 actually becomes like a landing page. It is true no one would actually land on a 404 with intention.

However, when they do, you will be prepared for them to divert the traffic to the most popular pages on your website. This can downright act out as a recommendation for your users. According to a recent report by McKinsey and Company, 35% of Amazon’s and 75% of Netflix’s revenues are generated by their recommendation engines, respectively.

5. Place your sitemap

Creating interactive 404s - Place your site map

Screenshot Credits

If you are from the SEO side of things and adept in the knowledge that encircles the mastery of search engine rankings, then you know for sure that sitemaps can be extremely good for your websites. Since they are listed in search control, there is no doubt that Google does pay attention to them. Hence it would be great for your 404s to include a sitemap on them.

This will allow users to easily navigate through your website without leaving your website or going back to the SERPs (search engine result pages) to start their journey all over again. Hence you would be effectively reducing pogo-sticking. This will thus enhance your users’ dwell-time.

6. Use conversational language

Creating interactive 404s - Use conversational language

Screenshot Credits

It must be pretty obvious by now that a remedy for a 404 lies in offering users a human touch that softens their impact, and this can be further augmented with the use of conversational language.

You want your customers and website visitors to feel less infuriated, and in order to do that, you need to spread out some comfort for them so that they do not feel agitated.

This can be reflected by a recent study by Business 2 Community, where they emphasize the use of conversational marketing. According to the study, 79% of consumers are willing to use messaging apps for customer service, 82% consider immediate response as extremely important, and 36% of companies are actively using live chat for marketing and sales.

Hence the idea over here is to make your users feel as if you are directly speaking to them, and this can help break the ice and reduce the tension created.

7. Get to homepage tab

Creating interactive 404s - Homepage tab

Screenshot Credits

Probably one of the easiest get around for your 404 pages is to link back to the homepage. What you are doing is here is giving your customers the easiest route to start their search all over again without letting them go and trying to keep them on your domain.

8.   Mention your blog

Mention your blog

Screenshot Credits

Blogs are considered a good choice for your audiences as well. While they may not be good for directly influencing their behavior, they can certainly create awareness that your domain does publish interesting content that users might find interesting to read.

It’s just a small nudge in the right direction. Obviously, customers who are looking to buy products or hire services would like to be directed to their requested pages, but mentioning your blog on a 404 is like saying, “hey there, we have more in store for you!”

Many students nowadays also go through blogs while they buy research papers online to increase their pool of knowledge relating to their field of study.

9.   Avoiding the 404 Error

Lastly, I would like to share some guidelines with you to help you avoid 404s where you can possibly manage to reduce them. This will only make your user experience skyrocket and help negate dissonance from users. Here are some quick tips:

  • Log into your Google Search Console account.
  • Check the Coverage report to see how many URLs are returning error codes.
  • Use the URL Inspection Tool to find more details about each error.
  • A 301 redirect is considered a good option for rectifying a 404 status.

Why are we doing this after all of the discussion above? This is because having too many 404s can prove to be detrimental to your user’s experience. Hence if you are notified about their existence, you should resolve them.

Conclusion

The 404 error codes undoubtedly leave a negative impact on your users and visitors. However, there are various ways you can make them add value for your customers.

I hope this post was able to offer you some meaningful ways through which you can use 404s in an interactive manner to boost your website’s SEO. For more questions regarding the topic, please feel free to post your queries in the comment section below.

Amanda Jerelyn currently works as a Marketing Manager at Dissertation Assistance, a perfect place for students to buy academic writing services from expert dissertation writers UK.  During her free time, she likes to practice mindful yoga to keep herself fit and healthy.

The post Guide to using interactive 404s to boost your SEO appeared first on Search Engine Watch.

Search Engine Watch


Testimonial link building: Using real experiences for success

July 18, 2020 No Comments

30-second summary:

  • Link building is one of the most crucial yet most difficult aspects of SEO but testimonial link building can solve that problem for you.
  • Testimonial link building is seen as a great way to harness this raw strength of positive experiences by customers. 
  • Giving a testimonial to a company you have availed service from or purchased from can be a great way to get a link back to your site.  
  • It’s such a simple and straightforward method, which may be one of the reasons why your business should implement testimonials and reviews into your link building strategy. 

In this analytical age, brands are competing on the minutest details. Targeting the right keywords, creating campaigns targeting the right demographic, coming up with effective CTAs, and all those technicalities. However, amidst all that, there is still an element that cannot be measured using an existing tool. That’s where testimonial link building comes into the picture.

Word of mouth from customers can end up making or breaking all the efforts brands put in their campaigns. You as a brand can do everything right but a negative experience by a customer can create negative brand equity that’ll be hard to shed. In the same way, positive word of mouth can boost up your sales manifolds. This why testimonial link building is seen as a great way to harness this raw strength of positive experiences by customers. 

Continue reading below to learn what exactly is testimonial link building, how to get started, and what rules you need to abide by during the entire process. 

What is testimonial link building?

In laymen terms, testimonial link building is using a positive comment from customers that have used your service or product and featuring them on your website. At its core, testimonial link building is meant to provide genuine positive word of mouth for website owners in exchange for a link. In the end, everyone’s happy and it helps brands grow and gain brand recognition. 

There are some finer details involved too such as relevance. Think about it, if you’re a software company, do you want a testimonial from a café from a completely different country? Relevance is key. Just like textual content, you can’t overdo the use of testimonial link building as it’ll end up hurting both parties instead of helping them. There’s no perfect recipe for success in testimonial link building apart from ensuring clarity and relevance. 

Jayson Demers, CEO of Email Analytics says testimonials really fruitful strategy to build links,

“With every testimonial, you will receive Search Engine Crawlers will recognize that your site has an authority” 

Perfection on those true fronts will yield great results for both parties. So, how does it work, and more importantly, how do you get started? Continue reading below to learn more. 

How to build testimonial links 

Without beating around the bush, the whole process boils down to 5 crucial steps that anyone can follow. These are as follows: 

1. Create a target list of products/services

This is where you’ll need to do the most homework. I’d advise you to keep your range of targets as wide as possible but avoid venturing into irrelevant fields. 

Some other things to keep in mind include targeting solution-based products and services. The potential customers looking at this are already at a high engagement point and they’re more likely to convert. I’d also advise making sure you target products and services that you’ve actually used. It would be futile to skip this part as it is a legal requirement. You can still choose to move ahead with this but it’s unlikely any product or service will entertain your testimonial requests if you’re not an existing customer.

Jay Eckert, Founder of Parachute Design also recommends using testimonials for your services,

When you write honest reviews for products or services you are using, it is ultimately benefiting your website’s exposure and visibility in the form of backlinks or through Brand mentions”  

2. Find their contact information 

Once you’ve identified the best possible leads, it’s time to start contacting them. Again, this step requires a lot of elbow grease, so bear that in mind. However, some extensions and tools can help you in this regard and make your job a little easier. 

For instance, ’FindThatLead’ is a tool that  allows you to find your target’s contact details almost at a click of a single button. Just enter the domain you’re targeting and it’ll provide you the details of the right person to contact for your request. Some other similar apps include Hunter.io and Voila Norbert. 

3. Pitch your testimonial via email

This is a crucial part that a lot of people mess up. This is the point where you pitch your testimonial, do not send your testimonial. There is a clear difference between the two and it could save you a lot of time. 

You’re supposed to pitch the idea of giving them a testimonial on the site. While nothing is stopping you from writing up a testimonial and sending it to them, if they reject it, you’ve wasted all that hard work for nothing. 

Write a short and to-the-point email to pitch your testimonial and how it can add value to their overall site. 

4. Write a relevant testimonial

Once you’ve received a green-light to go ahead with a testimonial, you can start working on it. The intent of each testimonial matters a lot, so you must understand what the site owner’s intent is. For instance, if they’re a no-profit organization, they don’t want to sell anything but rather raise awareness. Similarly, a start-up would want to encourage a maximum of new customers. 

Tailor your testimonial based on what the intent of that testimonial on the site is supposed to be. 

5. Create a video backing up that testimonial 

Okay, fair disclaimer, this last step is more of a bonus step. You can skip it if you want but I’d advise against it. There’s a pearl of old internet wisdom to be skeptical of everything you see on the Internet. Put yourself in the shoes of a potential customer. If you’re someone that’s looking at these testimonials, how do you know they’re real. Yes, they all sound convincing and they have the verification mark guaranteeing they’re real customers. However, there will still be an iota of doubt in their minds. This doubt can be the obstacle between a potential customer converting into an actual customer. You can use video or visual testimonial as well. 

Laws and regulations to consider

Even though testimonials present a tremendous opportunity to sell your product and service using your previous sales’ as proof, there are some strict guidelines on how you need to present them. 

The Federal Trade Commission has an entire set of laws on how businesses can use endorsements and testimonials in their advertising. I wouldn’t go as far as to call these to be stifling but they do require some strict criterion to be followed. The entire document can be found and studied here. 

But in case you’re looking for a short rundown of what this means, there are three things you need to be careful about when using testimonials. 

The context needs to be clear. You can’t throw in a testimonial that was given to you for a different version of the service or the app for instance. If you still want to use that testimonial then you’ll have to specify the details. This is primarily why on the App Store when reading reviews for apps, you’ll find reviews marked “review for a different version” 

In case the testimonials were for quid pro quo, you can still use them but you’ll have to provide all customers full disclosure. This means any behind the scenes deals to prop each other up by brands is a big no-no. 

This should go without saying, but all testimonials you choose to use must be genuine. If found guilty of cultivating fake testimonials, your brand can face heavy fines depending on which state you’re in. Steer clear of quantities when it comes to testimonials and focus on delivering quality and earning genuine, organic testimonials that you can use.

The post Testimonial link building: Using real experiences for success appeared first on Search Engine Watch.

Search Engine Watch


Job Search Engine Using Occupation Vectors

June 1, 2020 No Comments

I worked for the Courts of Delaware at Superior Court.

I started working there as the Assistant Criminal Deputy Prothonotary.

I changed positions after 7 years there, and I became a Mini/Micro Computer Network Administrator.

The Court used an old English title for that first position which meant that I supervised Court Clerks in the Criminal Department of the Court. In the second position, I never saw a mini/micro-computer but it was a much more technical position. I was reminded of those titles when writing this post.

What unusual job titles might you have held in the past?

A Job Search Engine Based on Occupation Vectors and a Job Identification Model

An Example of Job Search at Google:

job search example

For two weeks, Google was granted patents with the same name each of those 2 weeks. This is the first of the two patents during that period granted under the name “Search Engine.”

It is about a specific type of search engine. One that focuses upon a specific search vertical – A Job Search Engine.

The second patent granted under the name “Search Engine,” was one that focused upon indexing data related to applications on mobile devices. I wrote about it in the post A Native Application Vertical Search Engine at Google

The reason why I find it important to learn about and understand how these new “Search Engine” patents work is that they adopt some newer approaches to answering searches than some of the previous vertical search engines developed by Google. Understanding how they work may provide some ideas about how older searches at Google may have changed.

This Job Search Engine patent works with a job identification model to enhance job search by improving the quality of search results in response to a job search query.

We are told that the job identification model can identify relevant job postings that could otherwise go unnoticed by conventional algorithms due to inherent limitations of keyword-based searching. What implications does this have for organic search at Google that has focused upon keyword searches?

This job search may use methods in addition to conventional keyword-based searching. It uses an identification model that can identify relevant job postings which include job titles that do not match the keywords of a received job search query.

So, the patent tells us that in a query using the words “Patent Guru,” the job identification model may identify postings related to a:

  • “Patent Attorney”
  • “Intellectual Property Attorney”
  • “Attorney”
  • the like

The method behind job searching may include (remember the word “vector.” It is one I am seeing from Google a lot lately):

  • Defining a vector vocabulary
  • Defining an occupation taxonomy includings multiple different occupations
  • Obtaining multiple labeled training data items, wherein each labeled training data item is associated with at least:
    • (i) a job title
    • (ii) an occupation
  • Generating an occupation vector which includes a feature weight for each respective term in the vector vocabulary
  • Associating each respective occupation vector with an occupation in the occupation taxonomy based on the occupation of the labeled training data item used to generate the occupation vector
  • Receiving a search query that includes a string related to a characteristic of one or more potential job opportunities, generating a first vector based on the received query
  • Determining, for each respective occupation of the multiple occupations in the occupation taxonomy, a confidence score that is indicative of whether the query vector is correctly classified in the respective occupation
  • Selecting the particular occupation that is associated with the highest confidence score
  • Obtaining one or more job postings using the selected occupation
  • Providing the obtained job postings in a set of search results in response to the search query

These operations may include:

  • Receiving a search query that includes a string related to a characteristic of one or more job opportunities
  • Generating, based on the query, a query vector that includes a feature weight for each respective term in a predetermined vector vocabulary
  • Determining, for each respective occupation of the multiple occupations in the occupation taxonomy, a confidence score that is indicative of whether the query vector is correctly classified in the respective occupation
  • Selecting the particular occupation that is associated with the highest confidence score
  • Obtaining one or more job postings using the selected occupation, and providing the obtained job postings in a set of search results in response to the search query
  • Feature Weights for Terms in Vector Vocabularies

    It sounds like Google is trying to understand job position titles and how they may be connected, and developing a vector vocabulary, and build ontologies of related positions

    A feature weight may be based on:

    • A term frequency determined on several occurrences of each term in the job title of the training data item
    • An inverse occupation frequency that is determined based on many occupations in the occupation taxonomy where each respective term in the job title of the respective training data item is present.
    • An occupation derivative based on a density of each respective term in the job title of the respective training data item across each of the respective occupations in the occupation taxonomy
    • Both (i) a second value representing the inverse occupation frequency that is determined based, at least in part, on several occupations in the occupation taxonomy where each respective term in the job title of the respective training data item is present and (ii) a third value representing an occupation derivative that is based, at least in part, on a density of each respective term in the job title of the respective training data item across each of the respective occupations in the occupation taxonomy
    • A sum of (i) the second value representing the inverse occupation frequency, and (ii) one-third of the third value representing the occupation derivative

    The predetermined vector vocabulary may include terms that are present in training data items stored in a text corpus and terms that are not present in at least one training data item stored in the text corpus.

    This Job Search Engine Patent can be found at:

    Search engine
    Inventors: Ye Tian, Seyed Reza Mir Ghaderi, Xuejun Tao), Matthew Courtney, Pei-Chun Chen, and Christian Posse
    Assignee: Google LLC
    US Patent: 10,643,183
    Granted: May 5, 2020
    Filed: October 18, 2016

    Abstract

    Methods, systems, and apparatus, including computer programs encoded on storage devices, for performing a job opportunity search. In one aspect, a system includes a data processing apparatus, and a computer-readable storage device having stored thereon instructions that, when executed by the data processing apparatus, cause the data processing apparatus to perform operations.

    The operations include defining a vector vocabulary, defining an occupation taxonomy that includes multiple different occupations, obtaining multiple labeled training data items, wherein each labeled training data item is associated with at least (i) a job title, and (ii) an occupation, generating, for each of the respective labeled training data items, an occupation vector that includes a feature weight for each respective term in the vector vocabulary and associating each respective occupation vector with an occupation in the occupation taxonomy based on the occupation of the labeled training data item used to generate the occupation vector.

    The Job Identification Model

    Job identification model

    Job postings from many different sources may be related to one or more occupations.

    An occupation may include a particular category that encompasses one or more job titles that describe the same profession.

    Two or more of the obtained job postings may be related to the same, or substantially similar, occupation while using different terminology to describe a job title for each of the two or more particular job postings.

    Such differences in the terminology used to describe a particular job title of a job posting may arise for a variety of different reasons:

    • Different people from different employers draft each respective job posting
    • Unique job titles may be based on the culture of the employer’s company, the employer’s marketing strategy, or the like

    occupation taxonomy

    How an Job Identification Model May Work

    An example:

    1. At a first hair salon marketed as a rugged barbershop, advertises a job posting for a “barber”
    2. At a second hair salon marketed as a trendy beauty salon, advertises a job posting for a “stylist”
    3. At both, the job posting seeks a person for the occupation of a “hairdresser” who cuts and styles hair
    4. In a search system limited to keyword-based searching, a searcher seeking job opportunities for a “hairdresser” searchings for job opportunities using the term “barber” may not receive available job postings for a “stylist,” “hairdresser,” or the like if those job postings do not include the term “barber”
    5. The process in this patent uses a job identification model seeking to address this problem

    The job occupation model includes:

    • A classification unit
    • An occupation taxonomy

    The occupation taxonomy associates known job titles from existing job posts with one or more particular occupations.

    During training, the job identification model associates each occupation vector that was generated for an obtained job posting with an occupation in the occupation taxonomy.

    The classification unit may receive the search query and generate a query vector.

    The classification unit may access the occupation taxonomy and calculate, for each particular occupation in the occupation taxonomy, a confidence score that is indicative of the likelihood that the query vector is properly classified into each particular occupation of the multiple occupations in the occupation taxonomy.

    Then, the classification unit may select the occupation associated with the highest confidence score as the occupation that is related to the query vector and provide the selected occupation to the job identification model.

    An Example of a Search Under this Job Opportunities Search Engine:

    1. A searcher queries “Software Guru” into a search box
    2. The search query may be received by the job identification model
    3. The job identification model provides an input to the classification unit including the query
    4. The classification unit generates a query vector
    5. The classification unit analyzes the query vector given the one or more occupation vectors that were generated and associated with each particular occupation in the occupation taxonomy such as occupation vectors
    6. The classification unit may then determine that the query vector is associated with a particular occupation based on a calculated confidence score, and select the particular occupation
    7. The job identification model may receive the particular occupation from the classification unit
    8. Alternatively, or besides, the output from the classification unit may include a confidence score that indicates the likelihood that the query vector is related to the occupation output by the occupation taxonomy
    9. The occupation output from the occupation taxonomy can be used to retrieve relevant job postings
    10. Specifically, given the output of a particular occupation, the job identification model can retrieve one or more job postings using a job posting index that stores references to job postings based on occupation type

    11. The references to job postings that were identified using the job posting index are returned to the user device
    12. The obtained references to job postings may be displayed on the graphical user interface
    13. The obtained references to job postings may be presented as search results and include references to job postings for a “Senior Programmer,” a “Software Engineer,” a “Software Ninja,” or the like
    14. The job postings included in the search results were determined to be responsive to the search query “Software Guru” based at least in part on the vector analysis of the query vector and one or more occupation vectors used to train the occupation taxonomy and not merely based on keyword searching alone

    Takeaways About this Job Search Engine

    In addition to the details about, the patent tells us how an occupation taxonomy may be trained, using training data. It also provides more details about the Job identification model. And then tells us about how a job search is performed using that job identification model.

    I mentioned above that this job search engine patent and the application search engine patent are using methods that we may see in other search verticals at Google. I have written about one approach that could be used in Organic search in the post Google Using Website Representation Vectors to Classify with Expertise and Authority

    Another one of those may involve image searching at Google. I’ve written about Google Image Search Labels Becoming More Semantic?

    I will be posting more soon about how Google Image search is using neural networks to categorize and cluster Images to return in search results.


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    Create Google Display Countdown Ads Using Rules: Getting Creative With Ad Customizers

    May 26, 2020 No Comments

    Want to create urgency to purchase with your display ads? With a little creativity, you can create countdown ads even though it’s not a default option!

    Read more at PPCHero.com
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    Job Search Engine Using Occupation Vectors

    May 23, 2020 No Comments

    I worked for the Courts of Delaware at Superior Court.

    I started working there as the Assistant Criminal Deputy Prothonotary.

    I changed positions after 7 years there, and I became a Mini/Micro Computer Network Administrator.

    The Court used an old English title for that first position which meant that I supervised Court Clerks in the Criminal Department of the Court. In the second position, I never ever saw a mini/micro-computer but it was a much more technical position. I was reminded of those titles when writing this post.

    What unusual job titles might you have held in the past?

    A Job Search Engine Based on Occupation Vectors and a Job Identification Model

    An Example of Job Search at Google:

    job search example

    For a two week period, Google was granted patents with the same name each of those 2 weeks. This is the first of the two patents during that period granted under the name “Search Engine.”

    It is about a specific type of search engine. One that focuses upon a specific search vertical – A Job Search Engine.

    The second patent granted under the name “Search Engine,” was one that focused upon indexing data related to applications on mobile devices. I wrote about it in the post A Native Application Vertical Search Engine at Google

    The reason why I find it important to learn about and understand how these new “Search Engine” patents work is that they adopt some newer approaches to answering searches than some of the previous vertical search engines developed by Google. Understanding how they work may provide some ideas about how older searches at Google may have changed.

    This Job Search Engine patent works with a job identification model to enhance job search by improving the quality of search results in response to a job search query.

    We are told that the job identification model can identify relevant job postings that could otherwise go unnoticed by conventional algorithms due to inherent limitations of keyword-based searching. What implications does this have for organic search at Google that has focused upon keyword search?

    This job search may use methods in addition to conventional keyword-based searching. It uses an identification model that can identify relevant job postings which include job titles that do not match the keywords of a received job search query.

    So, the patent tells us that in a query using the words “Patent Guru,” the job identification model may identify postings related to a:

    • “Patent Attorney”
    • “Intellectual Property Attorney”
    • “Attorney”
    • the like

    The method behind job searching may include (remember the word “vector.” It is one I am seeing from Google a lot lately):

    • Defining a vector vocabulary
    • Defining an occupation taxonomy includings multiple different occupations
    • Obtaining multiple labeled training data items, wherein each labeled training data item is associated with at least:
      • (i) a job title
      • (ii) an occupation
    • Generating an occupation vector which includes a feature weight for each respective term in the vector vocabulary
    • Associating each respective occupation vector with an occupation in the occupation taxonomy based on the occupation of the labeled training data item used to generate the occupation vector
    • Receiving a search query that includes a string related to a characteristic of one or more potential job opportunities, generating a first vector based on the received query
    • Determining, for each respective occupation of the multiple occupations in the occupation taxonomy, a confidence score that is indicative of whether the query vector is correctly classified in the respective occupation
    • Selecting the particular occupation that is associated with the highest confidence score
    • Obtaining one or more job postings using the selected occupation
    • Providing the obtained job postings in a set of search results in response to the search query

    These operations may include:

  • Receiving a search query that includes a string related to a characteristic of one or more job opportunities
  • Generating, based on the query, a query vector that includes a feature weight for each respective term in a predetermined vector vocabulary
  • Determining, for each respective occupation of the multiple occupations in the occupation taxonomy, a confidence score that is indicative of whether the query vector is correctly classified in the respective occupation
  • Selecting the particular occupation that is associated with the highest confidence score
  • Obtaining one or more job postings using the selected occupation, and providing the obtained job postings in a set of search results in response to the search query
  • Feature Weights for Terms in Vector Vocabularies

    It sounds like Google is trying to understand job position titles and how they may be connected with each other, and developing a vector vocabulary, and build ontologies of related positions

    A feature weight may be based on:

    • A term frequency determined on a number of occurrences of each term in the job title of the training data item
    • An inverse occupation frequency that is determined based on a number of occupations in the occupation taxonomy where each respective term in the job title of the respective training data item is present.
    • An occupation derivative based on a density of each respective term in the job title of the respective training data item across each of the respective occupations in the occupation taxonomy
    • Both (i) a second value representing the inverse occupation frequency that is determined based, at least in part, on a number of occupations in the occupation taxonomy where each respective term in the job title of the respective training data item is present and (ii) a third value representing an occupation derivative that is based, at least in part, on a density of each respective term in the job title of the respective training data item across each of the respective occupations in the occupation taxonomy
    • A sum of (i) the second value representing the inverse occupation frequency, and (ii) one-third of the third value representing the occupation derivative

    The predetermined vector vocabulary may include terms that are present in training data items stored in a text corpus and terms that are not present in at least one training data item stored in the text corpus.

    This Job Search Engine Patent can be found at:

    Search engine
    Inventors: Ye Tian, Seyed Reza Mir Ghaderi, Xuejun Tao), Matthew Courtney, Pei-Chun Chen, and Christian Posse
    Assignee: Google LLC
    US Patent: 10,643,183
    Granted: May 5, 2020
    Filed: October 18, 2016

    Abstract

    Methods, systems, and apparatus, including computer programs encoded on storage devices, for performing a job opportunity search. In one aspect, a system includes a data processing apparatus, and a computer-readable storage device having stored thereon instructions that, when executed by the data processing apparatus, cause the data processing apparatus to perform operations.

    The operations include defining a vector vocabulary, defining an occupation taxonomy that includes multiple different occupations, obtaining multiple labeled training data items, wherein each labeled training data item is associated with at least (i) a job title, and (ii) an occupation, generating, for each of the respective labeled training data items, an occupation vector that includes a feature weight for each respective term in the vector vocabulary and associating each respective occupation vector with an occupation in the occupation taxonomy based on the occupation of the labeled training data item used to generate the occupation vector.

    The Job Identification Model

    Job identification model

    Job postings from many different sources may be related to one or more occupations.

    An occupation may include a particular category that encompasses one or more job titles that describe the same profession.

    Two or more of the obtained job postings may be related to the same, or substantially similar, occupation while using different terminology to describe a job title for each of the two or more particular job postings.

    Such differences in the terminology used to describe a particular job title of a job posting may arise for a variety of different reasons:

    • Different people from different employers draft each respective job posting
    • Unique job titles may be based on the culture of the employer’s company, the employer’s marketing strategy, or the like

    occupation taxonomy

    How an Job Identification Model May Work

    An example:

    1. At a first hair salon marketed as a rugged barbershop, advertises a job posting for a “barber”
    2. At a second hair salon marketed as a trendy beauty salon, advertises a job posting for a “stylist”
    3. At both, the job posting seeks a person for the occupation of a “hairdresser” who cuts and styles hair
    4. In a search system limited to keyword-based searching, a searcher seeking job opportunities for a “hairdresser” searchings for job opportunities using the term “barber” may not receive available job postings for a “stylist,” “hairdresser,” or the like if those job postings do not include the term “barber”
    5. The process in this patent uses a job identification model seeking to address this problem

    The job occupation model includes:

    • A classification unit
    • An occupation taxonomy

    The occupation taxonomy associates known job titles from existing job posts with one or more particular occupations.

    During training, the job identification model associates each occupation vector that was generated for an obtained job posting with an occupation in the occupation taxonomy.

    The classification unit may receive the search query and generate a query vector.

    The classification unit may access the occupation taxonomy and calculate, for each particular occupation in the occupation taxonomy, a confidence score that is indicative of the likelihood that the query vector is properly classified into each particular occupation of the multiple occupations in the occupation taxonomy.

    Then, the classification unit may select the occupation associated with the highest confidence score as the occupation that is related to the query vector and provide the selected occupation to the job identification model.

    An Example of a Search Under this Job Opportunities Search Engine:

    1. A searcher queries “Software Guru” into a search box
    2. The search query may be received by the job identification model
    3. The job identification model provides an input to the classification unit including the query
    4. The classification unit generates a query vector
    5. The classification unit analyzes the query vector in view of the one or more occupation vectors that were generated and associated with each particular occupation in the occupation taxonomy such as occupation vectors
    6. The classification unit may then determine that the query vector is associated with a particular occupation based on a calculated confidence score, and select the particular occupation
    7. The job identification model may receive the particular occupation from the classification unit
    8. Alternatively, or in addition, the output from the classification unit may include a confidence score that indicates the likelihood that the query vector is related to the occupation output by the occupation taxonomy
    9. The occupation output from the occupation taxonomy can be used to retrieve relevant job postings
    10. Specifically, given the output of a particular occupation, the job identification model can retrieve one or more job postings using a job posting index that stores references to job postings based on occupation type

    11. The references to job postings that were identified using the job posting index are returned to the user device
    12. The obtained references to job postings may be displayed on the graphical user interface
    13. The obtained references to job postings may be presented as search results and include references to job postings for a “Senior Programmer,” a “Software Engineer,” a “Software Ninja,” or the like
    14. The job postings included in the search results were determined to be responsive to the search query “Software Guru” based at least in part on the vector analysis of the query vector and one or more occupation vectors used to train the occupation taxonomy and not merely based on keyword searching alone

    Takeaways About this Job Search Engine

    In addition to the details about, the patent tells us how an occupation taxonomy may be trained, using training data. It also provides more details about the Job identification model. And then tells us about how a job search is performed using that job identification model.

    I mentioned above that this job search engine patent and the application search engine patent are using methods that we may see in other search verticals at Google. I have written about one approach that could be used in Organic search in the post Google Using Website Representation Vectors to Classify with Expertise and Authority

    Another one of those may involve image searching at Google. I’ve written about Google Image Search Labels Becoming More Semantic?

    I will be posting more soon about how Google Image search is using neural networks to categorize and cluster Images to return in search results.


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    Hallway creates a ‘virtual break room’ for remote workers using scheduled video chats

    April 14, 2020 No Comments

    The coronavirus outbreak has forced millions of U.S. employees to work from home — many for the first time. But remote work can be lonely and isolating, as people feel disconnected from their team and co-workers due to the lack of face-to-face conversations. That’s where the new startup, Hallway, aims to help. The service re-creates the break-room experience and the serendipity of random hallway conversations with its new app aimed at Slack users.

    The app allows companies to schedule 10-minute video chats within Slack channels, where colleagues can catch up with one another outside of more formal web meetings.

    The startup was co-founded by Parthi Loganathan, a former product manager at Google who launched Google Chat and Google Go; and Kunal Jasty, a former associate at private equity firm Insight Partners.

    The two were originally working on a product called Across that would help teams provide customer support in shared Slack channels. But when the shelter-in-place was brought into effect in San Francisco, things quickly changed.

    “It forced a lot of companies that were unprepared for remote work to go remote overnight,” Loganathan explains. Meanwhile, his roommate complained he was going stir-crazy working from home and missed talking to his team.

    “Hallway seemed like a simple and fun way to tackle that problem, so we built it in a couple of days,” Loganathan says.

    The founders already had first-hand experience with the challenges involved in dealing with remote teams, as half their team was based in India. And they had experience building Slack apps, not only with Across but with others similar to Hallway, as well.

    As a result, Hallway was built quickly, with only four days in between the idea and the first user, Loganathan says.

    To use Hallway, you can either add it to Slack from the Hallway website or from the Slack app directory. (To install it, you may need admin approval if you don’t have permission to add apps to your Slack workspace.)

    There’s no front-end for the app — everything is user-facing in Slack, including the login process, onboarding experience and the settings user interface. Once installed, you’re given the onboarding instructions over direct message within Slack. You can then invite the Hallway bot to any Slack channel by typing /invite @hallway. This kicks off the bot to start creating break rooms on a recurring basis automatically, which are announced by way of an @here message.

    By default, Hallway’s break rooms are scheduled every two hours between 9 AM and 6 PM Monday through Friday, but users can adjust the timezone and adjust the frequency of the breaks by typing in /hallway in a Slack channel to customize the settings.

    You can opt to use your own Zoom or Google Meet links with Hallway. But the experience works better with Hallway’s timed video chat rooms, which are powered by daily.co’s video infrastructure.

    The service itself is free for up to two slack channels, but only offers 10 of its timed video chats before you have to either switch to using your own web meeting links or have to upgrade.

    Hallway’s “team” pricing plan for larger companies supports up to five channels and offers an unlimited number of video chat rooms, as well as the customization options, for $ 30 per month. For more than five channels, enterprise pricing is available upon request.

    Since launching just a few weeks ago, Hallway has quickly grown its customer base.

    The service is now being used by more than 170 teams at companies like Nextdoor, Productboard, Bank Novo, Pivotal, Coursera and others. The majority of users are on the free plan for now. However, companies in need of an upgrade can access more flexible pricing if users are willing to share the service with friends.

    For the time being, the co-founders want to focus on improving the Hallway experience in Slack, but they’re already thinking about what comes next.

    “We’re solving the problem of keeping teams connected and reducing workplace loneliness while working remotely. Right now, we’re improving the core experience of spontaneous timed video chats and giving users more options to customize them,” says Loganathan. “We’re looking into specific use cases we can help companies with, like team building and employee onboarding for remote teams,” he notes.

    The company may also consider a solution for Microsoft Teams in the future, he says.

    Hallway has raised an undisclosed amount of pre-seed funding.


    Social – TechCrunch


    Target Competitors On Facebook Using Interest Based Audiences

    March 3, 2020 No Comments

    Facebook doesn’t give you the option to directly target the fans of any specific page, but that doesn’t mean you can’t target a competitor.

    Read more at PPCHero.com
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    Content optimization using entities: An actionable guide

    December 24, 2019 No Comments

    They’re by no means a secret, and entities’ role in SEO has been heavily documented – entity optimization just isn’t the trendy topic you might see every time you check your Twitter timeline.

    We’d much rather discuss less impactful concepts, like whether content within a subfolder will rank better than a subdomain or whether it’s important for an SEO to learn Python (am I right?).

    But entity optimization should be getting the same amount of press as the other topics and concepts we SEO’s drive into the ground week after week. I want to help us understand why, and how to approach content with entities in mind.

    What is an entity?

    Google defines an entity as, “A thing or concept that is singular, unique, well-defined and distinguishable.” An entity can be an event, idea, book, person, company, place, brand, a domain, and so much more. You might ask, “Isn’t that the definition of a keyword? What’s the difference?”

    An entity isn’t bound by language or spelling, but rather a universally understood concept or thing. And at the core of an entity is its relation to other entities. Google uses an illustration of “nodes” and “edges” to explain entities, with entities as nodes and relationships as edges. Let’s look at a search to see how this plays out:

    How Google uses entities example Justin Trudeau search

    How Google uses entities example 2 Justin Trudeau search

    A search for “Justin Trudeau” displays a knowledge panel where he carries the title “Prime Minister of Canada”. And a search for “prime minister of Canada” displays a knowledge panel of Justin Trudeau. So we know that Justin Trudeau is associated with Prime Minister of Canada and vice versa. Trudeau is the current prime minister, so what if we search for the same entities with a different relationship?

    Example searching same entities with a different relationship

    Here we see a different set of results, based on a different relationship between the nodes.

    How are entities used by search engines?

    We believe Google uses a model called Word2Vec (referenced in this patent regarding keyword extraction) to break down entities, map them to a graph, and assign a unique ID. In a sense, Word2Vec turns language into a mathematical computation, allowing Google to properly identify concepts and map them appropriately – regardless of language – in a way traditional models simply can’t.

    We don’t know exactly how entities fit into search results right now but based on a model introduced in a patent titled “Ranking search results based on entity metrics“, we know one of the biggest factors is relatedness.

    Relatedness is judged primarily by something called co-occurrence (the linked patent is still pending, but helpful in understanding co-occurrence). Co-occurrence judges the strength of relationships based on the frequency of the entities appearing together in documents around the web. The more frequently two entities are mentioned together, and the more authoritative the document that mentions them, the stronger the relation.

    Are entities a ranking factor?

    Entities aren’t necessarily a ranking factor – at least in the traditional sense. And we don’t really know exactly how much weight they carry as quality signals. But we know there are two key categories of ranking factors (among many others) heavily influenced by the entity graph.

    Content

    Keywords have historically been the judge of the relevance and quality of content. Keywords aren’t dead, but entities give better insight to search engines on the relationship between words in a search.

    For example, let’s look at the search “best shoes for basketball in Atlanta.” Sure, we could create a post and stuff it with the keyphrase. But in a world of entity-based indexing, Google is looking for semantics around each of these entities, and signals that indicate their relationships.

    You might recall the explosion of “LSI keywords”. Whether or not latent semantic indexing is used in Google’s algorithm, this fascination with semantics is rooted in entities. All search is now semantic.

    Links

    It’s pretty common knowledge in the world of SEO that not all links are created equal. Entity-based indexing amplifies this sentiment. A post aiming to rank for “best shoes for basketball in Atlanta” needs links and references from authoritative sources on shoes, basketball, and the city of Atlanta in order to really own that SERP.

    How long have entities been used in algorithms?

    We’ve seen patents on entities surfacing for over ten years, and most believe entities have played a role in search algorithms for quite a long time. The question is when did entities become core to indexing?

    Cindy Crum of Mobile Moxie wrote a brilliant five-part series on entities. She makes a strong case for entities becoming a strong ranking signal at the same time as Google rolled out Mobile-First Indexing. In fact, she terms the entire update Entity-First Indexing.

    BERT and entities

    Did BERT have anything to do with entities? Though I believe BERT got a little more attention than it probably deserved, its use in Google’s algorithm can help us understand the importance of entities.

    BERT (Bidirectional Encoder Representations from Transformers) is a Natural Language Processing model that Google introduced in 2018 and began rolling out in October 2019. BERT has the ability to consider the full context of a word based on the words that come before or after named entities.

    We won’t dive deep, but we’ll look at an example Google gave to help us understand what BERT means for search. Google called out the query “2019 Brazil traveler to USA needs a visa” in a recent post. The preposition “to” is crucial here, and more crucial is its relationship to the entities found before and after it. Before BERT, Google would have returned results about US citizens traveling to Brazil. Post-BERT, Google can recognize that nuance and return a more relevant and helpful result:

    2019 Brazil traveler to USA needs a visa before and after BERT

    Source

    Entities are at the core of Natural Language Processing models like BERT.

    How to optimize content for entities

    Before we dive into some actionable tips, know that entities have far more implications than content. Entity optimization is crucial for building brands, establishing domains, and all kinds of other online endeavors. Having said that, there are massive implications for content.

    *Quick preface: I’ve used this approach to rank articles and have seen success, but this is by no means foolproof and battle-tested. I don’t at this time have or know of research that proves a direct correlation between an approach like this and high rankings. Nonetheless, I believe in it and believe a knowledge of entities gives SEOs a leg up.

    Choose and research a topic

    For starters, we need a topic and keyphrase for which we want to rank. We won’t dive into how to do keyword research or topic research, but let’s stick with our example above and aim to rank for “best shoes for basketball.”

    If we want to aim to rank for this keyphrase, we need to gather insight on what other topics and concepts Google deems related in their entity graph. Where can we gain insight like this? A few places:

    Wikipedia: We know entities are the foundation of Google’s Knowledge Graph – and we know Wikipedia fuels a lot of their knowledge on entities. We can assume that if Google leans on Wikipedia to help them understand topics, the attributes and sources found within Wikipedia may help guide our content.

    Google images is another goldmine for entity insight:

    Using Google images for entities

    Beneath the search bar, we find entities Google positively associates with “best shoes for basketball.” These aren’t the shoes or attributes of shoes you must list in your article, but logic would say the mentioning of these topics will help Google associate your article with them.

    “People Also Ask” is another helpful source for entity optimization. These are the other topics and questions Google associates with your target keyphrase:

    Example of using "People Also Ask"

    Use Google’s NLP API demo to analyze the competition

    Identify the top two or three ranking articles for your target keyphrase. Now we will look at how Google views the entities found within their articles. We’re going to use Google’s NLP API demo:

    Google's NLP API demo

    This is just a sample demo of their NLP cloud product. Nonetheless, it provides really valuable data. Before we dive in, we need to define a key term.

    Google’s API demo looks at a handful of things: salience, sentiment, syntax, and categories. We’re really only focusing on salience in this article.

    Salience is a score of how important the entity is in the context of the whole text. The higher the score, the more salient the entity is. We’ll use salience to help guide our content. Here’s what to do:

    1. Click on one of your competing posts in the SERP
    2. Copy and paste the content into the demo editor
    3. Click “Analyze”
    4. Check out for which entities Google reveals high salience

    Google's NLP API demo

    We see the entities with the highest salience are “player,” “best basketball shoes,” and “basketball shoes.” Seeing as Google ranks this page well for the keyphrase we desire, we can conclude these are entities we should seek to optimize for in our post.

    Provide context throughout

    How can you optimize for these entities? As you begin writing, your goal should be to establish the relationship between the entities you’re targeting in your keyphrase and give Google all the context you can to associate your target keywords with their entity graph. This isn’t done by keyword stuffing, but by using some of the language and semantics we’ve gleaned from the above sources.

    Google Images and Wikipedia should help you choose semantically related keywords and language to use throughout your article, while “People Also Ask” can help guide your overall topics and headings. Again, the aim is not to stuff keywords in, but to have a toolbox of individual words, phrases, language, and topics to guide our writing in a way that prioritizes our target entities.

    Once you’ve finished writing, run your own article through Google’s NLP API demo to get a feel for how you stack up. If the desired entities show low salience, it may be worth going back to the drawing board. At the very least, you can analyze articles that show more entity success to gain insight into how Google associates your targets.

    Update content as needed

    Because entity optimization is a bit more complex than keyword optimization, there’s a stronger case for updating content on a regular basis as new topics arise around your entities. For example, as new basketball shoes come out, and Google establishes their place in the entity graph, it would help the salience of your entities to add them to your post.

    BERT is another great example. As it blew up across the internet, if you had a post on Natural Language Processing, Google would expect to see mention of it.

    The future of search

    There is still a lot myself and the industry have to learn on the topic of entity optimization. And again, the implications expand far beyond content optimization.

    But I do believe a focus on entities has already begun, and the signals will only grow in prominence for Google and other search engines.

    Here’s to better content, more relevant SERPs, and the future of search.

    Brooks Manley is a Digital Marketing Specialist and SEO Lead at Engenius, a marketing agency in Greenville, SC. When he’s not panicking about ranking drops and algorithm updates, you can find him watching NBA games and eating tacos.

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    Search Engine Watch


    Five steps to generate tons of backlinks using infographics

    December 8, 2019 No Comments

    Your website needs backlinks the same way plants need water. Getting sufficient backlinks consistently will allow you to flourish your website, while the lack of backlinks will slowly make it wither. 

    Backlinks are still one of the most important factors that Google uses to determine website rankings. When tons of other websites link to you, Google’s algorithm will see that as a sign that you provide valuable and relevant content.

    When talking about generating tons of backlinks, there’s no other tool quite as effective as infographics. 

    Why infographics are so effective?

    1. Humans are visual creatures

    We are naturally visual learners, as we’re attracted more to visuals than text. As a result, infographics have a much higher chance of attracting readers than articles. Indeed, a study found that infographics are 30 times more likely to be read than text-only content. 

    2. Easy to digest

    Still connected to the previous point, people understand a text 323% better if it’s accompanied by an illustration. This applies to infographics too, which is the combination of beautiful visuals and short-written copy. Thanks to the simple and easy to read format, people can read and understand infographics faster and better. 

    3. Highly shareable

    Thanks to its bite-sized nature, infographics are extremely shareable because they can fit on almost any platformㅡ websites, emails, social media platforms, and even on printed advertising material such as brochures and pamphlets. Thanks to this trait, infographics are three times more likely to be shared than any other kind of content.   

    Five steps to backlink generation using infographics

    Now that you know what makes infographics so effective, let’s learn how to use it properly to attract tons of backlinks to grow your website. Here’s the step by step process of using infographics for link building:

    1. Content creation

    The first step is to obviously create the infographic. Not just an infographic, but a valuable and useful one. For starters, don’t waste your money on creating fancy and expensive infographics. Using free and affordable infographic tools and platforms are fine, as long as you can provide valuable content. 

    The more valuable your infographic content is, the more likely people are going to link back. Here are a few tips on creating content that’s valuable:

    • Content that attracts the most backlinks is usually the one that contains data statistics because every marketer needs them to back up their arguments. Conduct your own research, study, or survey and then present the findings via infographic.
    • If you don’t have the time or resources to conduct your own research, you can always make a compilation of data statistics from various sources and present them as one.
    • Creating an ultimate guide about a certain topic also attracts backlinks, because when writers don’t have enough space to explain about something, they can refer to your content for a deeper take on the subject. 

    2. Infographic publication and submission

    After creating the infographic, publish it on your site and infographic directory sites like Pinterest or Infographic Journal. When posting on your own site, remember that page speed is an actual ranking factor. So, make sure to optimize your page speed with these free tools. 

    Moreover, submitting your work on infographic directories will give you free backlinks with relatively minimum effort, though some sites will charge you a certain amount of money to publish your infographic. Here’s the complete list of infographic sharing websites compiled by SEOblog, containing over 150 sites. 

    3. Potential websites search

    Besides infographic directories, you also have to aim to get your infographic published on other websites that have a similar niche to you. How? Well, you need to reach out to them. First, you need to search for the websites to reach out to. We recommend you to use tools like Ahrefs to compile tons of websites in an instant. 

    It’s simple to use, just sign up, go to the “content explorer” section, type in your keyword, and then the tool will give you every web page on the internet that contains that particular keyword. For instance, if your infographic is about summer vacation, the result of the content explorer will show over 30 thousand web pages with that keyword:

    Next, export those web page data and move it to Microsoft Excel or Google Spreadsheet to manage and curate it in an easier manner.

    4. Email addresses collection

    After curating the websites to see which fits to publish your infographic and which doesn’t, the next step is to collect the email addresses of people working on those websites. It could be a writer, content manager, editor or any person that’s responsible for the content of that website. 

    Using tools like FindThatLead can help you collect the email because the tool has the ability to find email addresses based only on domain name and social media link (LinkedIn and Twitter only). It also allows users to verify an address to see whether it’s valid or not.

    5. Email outreach campaign

    With all the verified email addresses, now it’s time to do email outreach to promote your infographic. There are two ways to do it, the first one is by using automated email tools like Mailshake and the second one is by manually sending the emails one by one.

    Each of the methods has its own benefits and weaknesses. Sending emails manually takes a longer time, but you’ll be able to personalize the email more. On the other hand, using automated email tools will allow you to send tons of emails in a short time, but the content of the email will be the same and generic.

    Whatever your method of choice is, remember these tips to increase your email engagement and open rate:

    • Optimize it for mobile, because 46% of people open their email from mobile devices. 
    • Keep your subject line short, because shorter subject lines get much higher open rates
    • Include an emoji in your subject line if you can, because it helps you to stand out from other emails on the recipients’ inbox.
    • Personalize the email beyond just including the recipients’ names on the subject line, although it still helps to increase clickthrough rate.
    • Include a clear CTA at the end of the email, so that the audience knows what to do next.

    One important thing to remember is that no one wants to publish your work for free, so you have to be prepared to give them something in return that benefits both of you. One of the widely used and most effective ways is to offer them a guest post. This way, the recipients get free content for their blogs and you gain a valuable backlink.

    Conclusion

    Backlinks are one of the deciding factors to determine whether you can rank first on the SERP or not. To gain backlinks only by creating valuable infographics is not enough, you also need to promote it. Manual email outreach is the way to go if you don’t want to spend a penny in generating backlinks. All you have to do is to look for potential websites, collect their email addresses, write interesting email copy and offer, and then send them one by one. If you’re still not sure how to make a proper infographic, these infographic templates could certainly help. 

    Brian is a content writer of Milkwhale. He likes to write about infographic and video marketing, as well as other topics in the field of business and marketing.  

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