SEO (Search Engine Optimization) realm has witnessed enormous changes with the advancement of Artificial Intelligence (AI). B2B marketers need to be aware of the latest developments in the AI industry & upgrade their SEO strategies to comply with the latest developments in machine learning, deep learning in particular.
Deep learning, also known as hierarchical learning or deep structured learning is a sub-branch of machine learning that leverages artificial neural networks. These neural networks are much like the neurons in the human brain & are capable of self-learning, decision making & evolution based on past memories. Deep learning can be supervised, semi-supervised or unsupervised.
Artificial Neural Networks (ANNs) or connectionist systems are the computing systems that work similar to biological human brains’ neural networks & operate via task-specific programming. They can be used to process images & aid to other tasks associated with rule-based programming wherein, conventional algorithms fail. Unlike biological brains which are dynamic & analog, the neural networks tend to be static & symbolic.
Deep learning as a sub-class of machine learning facilitates the use of multiple layers to derive higher-level insights from raw data. These often include activities such as image processing; lower edges can identify edges while higher layers can demarcate items useful for humans such as digits, letters or faces. When it comes to B2B marketing deep learning can aid in SEO keyword research, link building, and intent targeting & even can conduct the psychographic analysis of audiences for targeted content creation. The start of deep learning can be attributed to Canadian Scientist Geoffrey Hinton who in the 1970s popularized the concept which got academic acceptance only in 2004 once he along with other researchers employed “backpropagation” algorithms to research about artificial neural networks & deep learning.
SEO is the process of improving the quality & quantity of website traffic by increasing the visibility of a website across the web search engines. SEO has undergone many transformations over the years starting from the simple optimization of landing pages to device based optimization and several on & off page optimization technics which take several months to pay off.
Though the basic SEO practices remain evergreen as ever, viz. key-word consistent content, relevant content, link building, promotion of long-tail-keywords & optimized meta-tags; other strategic factors have also be added as SEO has evolved. These include an optimized site for mobile users, strategies towards optimizing User Experience (UX), & social media marketing.
According to Adam Audette, Senior Vice President & Head of Global SEO at Merkle, “The days of SEO being a game outsmarting algorithms are over. Today content strategy and valuable, sustainable strategies are essential, not just tricks and links.”
SEO specialists were bamboozled when in 2016, Google introduced a deep learning algorithm called RankBrain which uses patterns & bucket data to process insights. The marketers were freaked out realizing that the new algorithm analyzes all Google searches & makes it the third most important ranking factor. Similar chaos was created when Google introduced the Hummingbird algorithm which worked on intent-based targeting & not just prioritized the keywords. The anxiety of marketers was further aggravated when industry experts such as Steve Jobs & renounced scientists such as Stephen Hawkins commented assertively about AI being a threat to human civilization. The evolving deep learning algorithms, though, till date, have only helped the SEO strategists & while the traditional SEO practices were still the same & relevant, they only evolved for better with deep learning algorithms.
Deep learning is all set to define & dictate the future of SEO & is all set to stir all the aspects of SEO, amalgamating both on & off page optimization viz. Content SEO, technical SEO, Video SEO, link building strategies. Deep learning may be a relatively new concept for marketers in comparison to Artificial Intelligence (AI) or Big Data; however, industry mammoths such as Google, Apple, Facebook & Microsoft have incorporated deep learning much earlier and are continuing to improve them to improve their deliverables for the clients. Panda & Penguin updates were beginning of a new era for those understanding Search Engine Optimization (SEO).
Let’s now try to scrutinize how deep learning is contributing to evolving SEO strategies:
1. Helps in Improving Rankings:
In 2015, Google introduced its deep learning algorithm RankBrain to supplement Hummingbird. Rank Brain works on intent-based targeting & also to repurpose & disperse 15% of the 3 billion searches that Google processes each day which goes in vain without any visibility (Source: searchengineland.com). Rank Brain is an algorithm designed by machine learning so we haven’t yet been completely able to understand what will be the threshold of hyper-targeting.
RankBrain, though has only revolutionized SEO practices, for good, for better. John Rampton, the founder of Due, stated that RankBrain assists boost SEO ranking based on the texture of content if it matches those of higher-ranking domains & tactics like backlinks can further help the cause. On the flip side, WordStream Founder Lary Kim warned that marketers need to be cautious that they don’t link back to domains having irrelevant content as it might adversely impact their own SEO rankings & domain authority.
While relevance, quality & value of content will continue to evergreen SEO practices Google is also trying to make Hummingbird complex enough to psychoanalyze its users for more relevant results. Marketers will have shift the focus from keyword-based content to contextual content & writing featured snippets & conversational content will further do good for SEO practices.
2. Optimizes User-Experience:
User experience is one of the top priorities for Google when it comes to ranking a site & they have employed several artificial algorithms to optimize the users’ experience (UX). Some of them are as follows:
- Pigeon stressed on & improved local search results
- Top Heavy assisted in avoiding pages studded with ads
- Mobile Friendly prioritized Mobile Rankings
- Penguin & Panda, introduced by Google in 2015 are real-time penalty tools & along with Hummingbird, they help in fighting with Spams. These algorithms lessen poor quality & irrelevant backlinks
As quoted by Debra Mastaler, president of Alliance-Link: “Since people tend to share links that affect them emotionally, it’s more important than ever to understand the demographic you’re selling to.”
Featuring high on local searches not only increases the visibility of marketers amongst relevant persona but also helps in improving Google Rankings & Domain Authority. Some simple link-building fixes:
- Limit backlinking only to the same niche
- Build backlinks only to reputable websites
- Encourage linking to websites with high credibility such as scientific journals & well-known news publishers.
- Identify influencers & trace out the linking opportunities to their websites & social media platforms
Incorporating healthy link building practices helps in optimizing the user experience to help the marketers achieve their ultimate aim of Conversion Rate Optimization (CRO).
3.Helps Establish Brand Equity:
The Knowledge Graph launched by Google assimilates data from Wikipedia, Wikidata & CIA World Facebook which not only allows the storage of data in form of sidebars but also equips the audiences to find the latest professional information about the companies in the first go. It thus assists both the rankings & Brand Equity establishment. The dedicated sidebar displays brand-related data from Wikipedia, Wikidata platform, Google Plus & other social media channels & is highly important for marketers to feature themselves on.
4. Helps in Optimizing Mobile Pages for Search Engines:
According to a study by Emarketer, 86% of Americans spend their time on smartphone apps. Apple alone has over 2 million app users & according to Adweek, Apple Search Ads took off with 50% conversions initially. Most big brands in the marketplace already have optimized their mobile pages for bringing up the users’ experience (UX) to acme.
5. Employing Virtual Voice Assistant:
Incorporating virtual assistant for voice searches not only assists in targeting & defining personas on the basis of voice searches, but also assists SEO strategists to think on the lines of voice search optimization or optimizing their strategies for personas who prefer voice searches.
6.Optimizing for Videos & Images (Visual Content):
In a major breakthrough Google on 28th September 2016 announced YouTube-8M which used the Inception V3 image annotation model. This created a video labeling system comprised of 8 million YouTube Videos which are equivalent to 500K hours of videos, are all labeled & have 4,800 Knowledge Graph entities. This was an excellent example of training a TensorFlow model using a single Graphical process Unit (GPU).
According to a report by Renderforest.com by 2019, 80% of the global internet consumption will depend on video-based content. Hence, it is imperative for videographers, SEO strategists & marketers alike to work on strategies to boost their video content as well as on strategies to optimize other forms of visual content such as images.
Since YouTube is the second largest Search Engine channel & solely deals with videos, optimizing the YouTube channel should be the top priority for B2B marketers; not only to rank high on Google but also to appeal to a greater proportion of video-consuming persona.
Strategizing & optimizing visual content with the help of deep learning can bring a renaissance in the field of B2B marketing.
7. Incorporating k-Means for clustering search queries helps in optimizing Click Through Rates (CTR):
K-Means Clustering is one of the simplest & most essential unsupervised machine learning algorithms that allow markers to segment their personas or target audiences on the basis of several intents signaling from first & third-party tools as well as from the data-points coalescing demographic, technographic, firmographic, fit-data & psychographic analysis of personas. While machine learning doesn’t require manual planning & leverages the ability of machines to learn & evolve via Artificial Neural Networks; choosing data points & curating them in the dataset for machines to learn is one of the most important activities in machine learning.
Personalized targeting & serving relevant ads to prospects helps in optimizing the CTR & in turn, also helps in the optimization of sales conversions.
To Sum It All:
Deep learning algorithms have made SEO evolve & while the standard practices of SEO are still the same, SEO has become more resourceful than ever to incorporate contextual marketing, mobile-targeting & several automated tools in the equation for defining & targeting personas. Deep learning boosts Content SEO as well as technical SEO.
As stated by Adam Audette, Senior Vice President, Head of Global SEO at Merkle:
“Content is anything that creates a compelling experience. But it’s so much more because you quickly realize that you can’t really know which content types to create until you understand which content types people want.”
If the marketers always focus on targeting relevant audiences & help them through their problem areas (pain-points), deep learning algorithms will aid them to improve their Google rankings & also will enable them to build stronger Brand Equity.
We, at Valasys Media, give high impetus to targeted campaigns for lead generation. We also provide content syndication & contact discovery services. Our hyper-targeted pieces of content help B2B marketers in achieving their bottom-line goal of Conversion Rate Optimization (CRO).
For more information on our services, feel free to contact us.