As Google's search algorithm evolves, so too must our marketing strategies. SEO experts and business owners alike must stay on top of the latest SEO techniques for better site optimization, improved search rankings, and better conversion rates.

If you're concerned about how these changes will impact your website, worry no further. Below, we're going to provide you with a look at seven emerging technologies in SEO that are changing the way users access information. Some technologies are still being refined, while others are already here in a usable state.

1. Googlebot A/B Testing

If you have any experience in managing a website, creating ads, or creating landing pages, you're already familiar with A/B testing. This is the process of creating two different variations of the same creative. You then divide your web traffic to determine which version performs best with your audience. In this scenario, your campaign is already live and you are spending the budget to gather analytics.

With SEO A/B testing, you are performing the same process but unveiling it to Googlebot first rather than your audience. In addition to this, you are typically only providing one version of the page to compare it to the base version.

A/B testing with Googlebot can be used to analyze a variety of SEO factors including headlines, content variations, meta descriptions, schema markup and rich results, mobile page variations, and much more. You also do not need to worry about hurting your current page rankings so long as you follow Google's recommended guidelines for testing, which you can find here.

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While user A/B testing is valuable and can certainly drive conversions, SEO A/B testing can allow for greater confidence in your results. This is because we are dealing with Google's search algorithm directly and making changes upon actual changes to search traffic, click-through rate, and search engine rankings.

If you're curious where you can begin experimenting with SEO A/B testing, you can take advantage of these features in Google Tag Manager along with Optimize.

2. Google's Multitask Unified Model

In the ongoing effort to be the world's best search engine, Google continues to improve how its algorithm reads and understands search results. Back in 2019, an addition to the algorithm known as BERT (Bidirectional Encoder Representations from Transformers) brought with it natural language processing technology. Since then, Google further improved its ability to understand complex queries with the Multitask Unified Model (MUM).

As smart as artificial intelligence can be, it commonly struggles with understanding user intent. This becomes an issue with how nuanced human language is and how we go about using it when browsing the web. AI is often left to read our search queries as entirely literal, while we as humans can decipher hidden meanings or intent behind a simple phrase. As a result, the user typically makes several searches before finding what they really need.

MUM is changing the game by allowing the algorithm to determine the actual meaning behind a web search. Essentially, the experts at Google trained the algorithm to better understand how users around the globe utilize language for search.

As a quick example, let's say a local store proprietor wants to start selling alcohol. He searches for something to the effect of need alcohol permit store.ā  Based on the search intent and background information, we understand that the store owner wants a link telling him how to get his permit. However, the algorithm would previously interpret this in a number of ways, such as Do I need an alcohol permit? It may also not understand that specifically, a business person is completing this search, not your average citizen.

With the latest advances in machine learning, Google search can now immediately complete a series of complex tasks and derive the actual search intent based upon user behaviors worldwide. It now understands the search intent as we do and provides the most relevant information at the top of results.

MUM takes this even further by providing this level of accuracy across 75 different languages. Google's smart algorithm is able to remove language barriers as a factor and deliver the best information to anyone in the world regardless of the language used. It can deliver information in one language and deliver it in the user's preferred language.

As an SEO, this does not necessarily present new challenges for your existing SEO strategy. However, Google's continuous advances in searching for the most accurate information reinforces our need to optimize our content for this purpose. By delivering the most informative, easy-to-use content possible, we can potentially boost our traffic with users around the world.

3. Allow AI to Write Your First Draft

New AI-driven technology may someday write our SEO content for us entirely. OpenAI, an artificial intelligence research company, unveiled its GPT-3 language generator just over a year ago. This allows users to create some of the most human-like text ever created by machines. We provide the API with the subject we need to focus on, and it quickly creates the content of varying lengths depending on the information it finds around the internet.

However, if you glance at the article above, you will quickly see that this technology is currently posing problems, as well. Due to its complete reliance on existing human behavior only, it's very easy for the AI to deliver content that comes with biases that we do not intend to include in our content. Many tests were quick to deliver hateful, racist messages within the text.

For this reason, GPT-3 is not yet at a place where we can place total reliance on language-learning technology. At best, we can attempt to utilize this AI to create first drafts of content. We then review the copy to see the quality of information gathered, while making the necessary changes and revisions to produce a final copy.

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With that said, it's just a matter of time before text-based content creation is no longer a task performed by humans. As experts in the field continue to train artificial intelligence to better understand the intention, desire, and emotion, robots will be able to apply those factors when creating long-form informational articles.

4. TF-IDF for Keyword Relevance

TF-IDF (Term Frequency Times Inverse Document Frequency) is an equation used to measure the actual importance and relevance of a keyword. This is as opposed to keyword density within a document. This is important for search engine optimization specialists as you can use TF-IDF when researching keywords that are the best fit for your page and website.

You will need to implement your usual SEO strategy and create the content you want to analyze with TF-IDF. Then, your TF-IDF tool will rapidly compare your document to high-quality information that exists online. This will highlight high-quality terms and phrases present in other content that can support and improve your own.

To further explain, every piece of content will generally contain common words or phrases. Because these words appear with a high frequency, TF-IDF determines that they are less relevant as they are not unique to the subject. However, less frequent terms that only appear in related topics are more valuable and have higher relevancy. This creates a list of the terms you should focus on and eliminates those you can ignore.

No longer do you need to leave the task of researching every piece of high-ranking content to determine gaps in your own. You can utilize tools online like TF-IDF Tool or Ryte.

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5. Automated Content Research and Optimization

Businesses and marketers are already taking advantage of automated content research and optimization tools for efficient content creation. You no longer need to enlist dedicated content writers that need to spend hours researching, writing, and refining text to perfection. You simply enter your target keyword or subject, allow the tool to grab the most relevant data, and then get to compiling it into your new article.

These state-of-the-art tools rapidly check the internet for relevant articles at the top of search results as well as the People Also Ask section. It's also become sophisticated enough to discover popular questions and answers from major sites such as Reddit, Answers.com, Quora, or Wikipedia.

There is a wide variety of tools and platforms for you to choose from for your content research. This includes sites like Ubersuggest, BuzzSumo, and Content Harmony.

Source: Ubersuggest

6. Search Driven by Image and Video

While informative content is king in marketing, high-quality images and video become increasingly more valuable for SEO over time. Not only does it enhance the quality of your content and make it more engaging for your users, but it may also one day take precedence over text entirely in some cases.

Earlier in this article, we discussed a new level of sophistication that's reached Google's search algorithm through MUM. Not only does this technology help the algorithm under search intent, but it is also gaining the ability to recognize dynamic media and generate relevant results based upon what's shown in a picture or a video. Users can already utilize media as a search query and receive a list of results that Google determines is relevant.

While image and video optimization are already essential for SEO, they will continue to gain added importance for every website. Media optimization already improves site speeds, mobile friendliness, and user retention, but it may become a determining factor in whether or not your content successfully outranks your competitor's.

Google provides explicit guidelines as to what you should do for best practices when it comes to images, video, and rich media files. Free options for editing and optimizing images and videos include Canva and Invideo. If your SEO strategy does not already include plans for an emphasis on media, understand that it will continue to be a significant factor in search rankings.

7. Users will Learn More from AI Conversations (LaMDA)

The researchers at Google are not stopping at improving the quality of its search results. One of its latest technological advances is known as LaMDA, also known as Language Model for Dialogue Applications,ā  may change the way we access information forever.

LaMDA follows in the footsteps of other language models mentioned in this article like BERT and GPT-3. The difference for this piece of technology is that its training is geared toward learning the principles of human conversation and interaction. While many of us may already use some form of voice-activated software such as Amazon's Alexa or Apple's Siri, those robots primarily seek out relevant search results to provide answers. Other responses are primarily scripted and will trigger when given the right inputs.

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This new technology seeks to provide relevant information in a more conversational approach as opposed to simply pulling up the top-ranked results. The current task ahead is to maintain its compelling level of relatability, while still staying true to informational accuracy. It also faces the same challenges mentioned with other language models for its ability to be misused for harmful or hateful purposes.

Nevertheless, it is inevitable that we all will be able to access any information we desire by simply asking a robot a question. How this will directly affect our SEO strategies remains to be seen, but key practices will still remain. This means that our focus should still be to follow Google's guidelines when it comes to creating valuable, factual content.

Any information published on your website should follow Google's EAT (Expertise, Authority, Trustworthiness) principle. By providing reliable information that Google can use in its automated processes, we will continue to receive the SEO benefits we need and see our websites rank as more valuable in the eyes of the Google algorithm. However, we will need to keep a close eye on how conversational AI changes the way we format and present our data to search engines.

Conclusion - Emerging SEO Technologies Will Forever Change How We Access Information

While some of these technologies may yet be years away, many are already here and being used by business owners and marketers alike. You may no longer need to spend hours researching keywords and information for your articles but can utilize sophisticated tools that automatically bring you the data you need for valuable content.

Search engines are also continuously improving their machine learning algorithms and changing the way search engines read and deliver results. In time, we may be able to access all of the information we need to make a consumer decision by conversing with artificial intelligence just as we would with a sales representative.

Finally, media will continue to be a significant factor when determining what constitutes a valuable search result. Your SEO strategy should place even greater emphasis on video and image optimization that supports any text on a given webpage. The on-page content itself should factor in Google's EAT principle to demonstrate expertise, authority, and trustworthiness regarding any subject matter.

While there are still unknowns in regard to how changing technologies may impact SEO and search rankings, we still know to focus on these fundamental principles to continuously improve our site quality ranking. SEO and digital marketing will always be an ever-evolving landscape and it's up to us to stay on top of the latest trends to reap the greatest results possible.

Digital marketing is constantly changing. The needs of our clients evolve as the pace and competitiveness of social marketing and paid search make it difficult for small businesses to stay on target. They need personalized solutions, continuous optimizations through real-time analysis, and automated solutions to improve to nurture those leads.

That's exactly what machine learning is doing for companies in 2021 and beyond.

If your current strategies are proving ineffective, or if you need actionable solutions to give you an advantage over your competitors, take a look at how machine learning will bolster your digital marketing strategies and ensure that your business continues to be a leader in your industry for the foreseeable future.

What is Machine Learning for Digital Marketing?

Machine learning is a system, or systems, that utilize artificial intelligence to gather analytics and present actionable solutions based on the findings. As your audience engages with your advertisements or shared content, knowledge about each user and their behaviors feeds into an algorithm. The more data that the algorithm receives, the more accurate and effective the proposed solutions will be.

There are two major types of machine learning that experts use to gather and interpret data sets:

Guided Machine Learning

A machine learning system will generally have a difficult time gathering and interpreting data without first receiving the help of human intelligence. In digital marketing, experts will instruct the system on what specific data to track as well as how to look out for patterns of note. You can do this by supplying it with data previously gathered manually from past marketing campaigns. For example, if you’re analyzing the math tutor cost across different regions, you can train the system with historical pricing data to identify trends and predict future costs. The machine learning system interprets this data and applies it to data gathered from.

The machine learning system interprets this data and applies it to data gathered from future marketing campaigns and experiments.

Unguided Machine Learning

This type of machine learning system is exactly the opposite. Experts allow the system to gather data from users in real-time without receiving the knowledge of previous user patterns or behaviors. Artificial intelligence is left to its own devices to sort out the gathered data and come up with solutions to improve its processes as time passes.

The Importance of Artificial Intelligence in Marketing

As a marketing professional, you may be thinking that you already have no shortage of tools to help you gather data. However, the true problem is finding the time and resources necessary to effectively sort through all of this valuable data to present meaningful solutions that get your clients real results.

Artificial intelligence is able to interpret and organize vast amounts of information in a fraction of the time it would take a human employee. In fact, as long as enough data is being fed into the algorithm, the results are virtually instant.

This means that machine learning development services can free up countless billable hours for your digital marketing agency. With the help of artificial intelligence, you can run any number of experiments with the right tools, focus your efforts on other tasks in the meantime, and return to find meticulously organized and accurate information to perform effective optimizations.

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Machine learning is not only faster but also eliminates the potential for human error. It is effectively improving the digital marketing process for every business in the world.

How to Use Machine Learning to Improve Your Digital Marketing?

Now that you better understand what machine learning is, we wanted to walk through the various ways you can utilize machine learning marketing to improve virtually every aspect of your agency. Below, you can find a list of the most important ways that the top experts are utilizing the best tools to help their teams prove more efficient:

1. Personalizing the User Experience

If you compare your Amazon shopping account with a friend's, you're guaranteed to observe two very different experiences. That's because the website is utilizing algorithms to constantly observe and track user behavior while they are utilizing their platform. As a result, you get personalized product recommendations, unique search predictions, and unique listing rankings.

The same is true for just about every platform you can think of - Netflix, Facebook, Instagram, YouTube, and many others.

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Your business or marketing agency can utilize machine learning to the same effect. You can utilize these systems to create personalized homepages or platforms for customers using your service. You could also personalize your paid ad or email marketing campaigns to better target users that take unique routes throughout their buyer's journey with your company.

2. Analyzing Your Data

Does your team currently utilize Google Analytics or Facebook Business Manager for your marketing goals? If you answered yes, you're already utilizing machine learning to improve your marketing processes.

These machine learning systems are able to gather vast amounts of data from your audience at a faster rate than humans and do so while retaining accuracy. Your team will quickly learn about customer demographics, bounce rates, retention time, clickthrough rates, etc.

Machine learning can also conduct experiments for you by segmenting your audience into different groups and observing which strategies perform best. It will also be able to automatically determine when its learning efforts are complete and automatically turn off experiments, optimizing the use of your advertising budget without input from an employee. This approach is similar to how data-driven platforms in other industries—like custom assignment writing services—track user preferences and adapt content delivery for improved engagement and outcomes.

This powerful method of data analysis outclasses anything you can do manually, and will effectively improve every aspect of your marketing services without question.

3. Automated Customer Service

An estimated 85% of all customer service interactions online will be resolved with an AI chatbot by the end of 2021. The statistics show that businesses and users alike enjoy the benefits of chatbots for the following reasons:

• Immediate response times
• Available 24/7 – no waiting for business hours
• Immediate solution suggestions
• Ability to sort customer queries and direct complex issues to human experts
• Ability to assist hundreds of customers simultaneously

While you will always have a share of consumers who insist upon human interaction, most are simply looking for their problems to be resolved as quickly as possible. As a result, businesses can utilize chatbots to handle billing and payments, subscriptions, account-related issues, and so much more.

A chatbot driven by machine learning can also sort through a vast library of help articles to provide the right solution to the user immediately. Additionally, if the chatbot is unable to help a user, it still gathers the data and offers your team insights on how to improve the automated customer experience.

Automated customer service can also potentially save your business thousands of dollars annually.

4. Improve Your Website and Landing Page Designs

Before machine learning, web designers were largely left to guesswork when it came to optimizing webpage layouts. With these new AI systems, you can learn everything you need to know about user activity on your site.

Web designers can now take advantage of heat mapping, which tracks which sections of the page receive more clicks as well as how long their eyes stay on a particular segment. Sections of the page that are ā€�hotā€¯ are safe to call keepers, while notably ā€�coldā€¯ sections likely need a redesign.

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Businesses and marketers can also take advantage of A/B testing, which allows you to direct your audience to two different versions of the same website. Machine learning will automatically track user behavior on each page, calculate which performs best, and automatically redirect users to the better page when enough data is gathered.

You will once again save time and money by performing optimizations backed by data from real users that want to engage with your content.

5. Optimize Your PPC Campaigns

Every business has a set budget when it comes to monthly digital advertising, so it's essential that you don't leave it up to guesswork. Machine learning now outperforms manual decision-making by helping experts choose the best types of ads, where and when to launch them, and how much of your budget you should use to boost engagement.

AI-driven machine learning will save you countless dollars and work to lower your cost-per-lead month after month (Are you beginning to see the pattern?)

For example, many social media platforms that offer to advertise can accept your previous campaign data to guide future efforts. The algorithm takes previous metrics, applies that data to users on the platform, and automatically generate what’s known as a “lookalike audience” to reach new customers that are most likely to convert.

Machine learning systems can also take over and autopilot the bidding process, adjusting bids according to your set limits, and knowing when to cease budget use when keyword costs become too competitive.

6. Improve Your Presence on Social Media

More than half of the world is now participating in social media. That statistic alone describes how necessary it is for every business to market themselves through those platforms.

With the help of machine learning marketing, you can easily turn Facebook, Instagram, Twitter, LinkedIn, and more into tools for success. Similar to the methods mentioned above, machine learning systems can automatically track and compile data from your audience to determine what types of content foster higher levels of engagement and impressions.

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Something that is unique to social media is knowing what days of the week to post as well as the best times to catch your audience's attention. Machine learning utilizes that same data from your audience to create an easy-to-read map of the best times to share your content on each social platform. User behavior greatly fluctuates depending on where you're posting, and AI-driven marketing provides you with immediate answers.

7. Machine Learning is Now Mandatory for SEO

Experts are no longer combing through each of your business's web pages with a fine-tooth comb. If you're not already, you need to be taking advantage of the world's top SEO tools including SEMrush, Ahrefs, KWFinder, and Moz - all of which utilize machine learning.

Once again, these AI systems are able to scan, track, and identify SEO errors across each page of your site with almost zero waiting period. These error reports will also come with proposed solutions that your team of experts can put into effect. This allows for more effective optimizations that in turn help your brand become more competitive in search rankings no matter how new your website is.

Additionally, these automated SEO reports can help dictate which type of content will best help improve website traffic and engagement. You will be able to track content keywords your audience is using and create articles, videos, or images for your site that naturally satisfies the demand.

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Conclusion - Adapt to Machine Learning Marketing or Be Left Behind

Machine learning marketing doesn't eliminate the need for intelligent, seasoned marketing experts. It simply takes over the role of completing the necessary, yet time-consuming, trivial tasks, and does so faster and with greater accuracy.

The role of future marketers is not to complete hours of menial tasks, but to utilize the tremendously beneficial insights that artificial intelligence can provide. The most competitive brands will utilize these tools in their marketing arsenal to continuously optimize web design, content creation, paid campaigns, search rankings, and everything else that goes into your overall business success.

By adapting to machine learning, you will save thousands of dollars, free up countless hours for tasks that can actually enhance your business, and do so while putting out better content than any of your competitors. If you've yet to embrace it, you're already late. Adapt now, or get left behind for good.