2017 was a relatively calm year, at least in terms of major Google algorithm updates.
In 2016, we saw the advent of Penguin 4.0, Possum, a major Mobile-Friendliness update, and big changes to AdWords, to name a few.
This year, Google’s been relatively quiet since the “Fred” update dropped in March.
What we have witnessed, however, is a redoubled focus on creating the best user experience possible.
Trends like mobile optimization and machine learning aren’t going away anytime soon, which is why you need to understand these five critical SEO concepts as we gear up for 2018.
1. Mobile-First Indexing
You’re probably keenly aware how important it is to have a mobile-friendly website. Over 55 percent of all web traffic comes from mobile devices, and that number is only expected to increase. What you may not be aware of is that having a mobile-friendly site isn’t enough anymore – now you need to be “mobile-first.”
Google announced late last year that mobile-first indexing is going to be the new norm. This means that your ranking signals are now going to come from the mobile version of your site, not the desktop version.
In other words, it’s time to stop thinking of mobile as an adjunct of your desktop site and start prioritizing your mobile SEO first.
Here are a few practical ways to improve your mobile SEO:
- Take the Mobile-Friendly Test.
- Fix broken links and incorrect redirects.
- Compress any uncompressed images.
- Eliminate intrusive pop-ups and interstitials.
- Improve mobile usability (g., text size, viewport configuration, tap target size).
- Run an audit of your mobile site to find any additional site elements (g., structured data, title tags) you can optimize for mobile.
2. Semantic Search
The goal of Google’s Hummingbird update in 2013 was to improve search accuracy by better understanding searcher intent.
Today, semantic search has evolved even more, and search engines are better than ever at understanding query context and the relationships between words.
The goal of semantic search is for search engines to understand natural language queries better. So if a user asks Google “what’s it rated?” and they’re standing in front of a French bistro, ideally Google would be able to know that in this context “it” refers to the bistro and the searcher wants to know a star rating.
There are many subtle nuances to the mechanics of semantic search, but ultimately what it means for you is that an authoritative page that dives into one specific topic in-depth will usually rank better than dozens of pages built around different keywords.
That’s because one comprehensive resource is better at giving Google (and, by proxy, its users) all the context it needs to satisfy searcher intent.
Here’s how to build content that embraces semantic SEO better:
- Choose a broad topic that’s relevant to your audience. For example, a pet adoption center might create a page about different dog breeds.
- Ask questions that will help you discern searcher intent. For example, the page on dog breeds might aim to answer “temperaments of different dog breeds” or “easiest dog breeds to train.”
- Once you understand searcher intent, create content that matches. Make your resource as rich and in-depth as possible.
- Create additional landing pages to satisfy other searches that match user intent.
- Focus on creating “complete guides” and other comprehensive pieces of evergreen content. Include relevant short- and long-tail keywords wherever appropriate.
- Check Google’s Knowledge Graph for an entity* on your business and products. To do this, enter your brand/product’s name into the Query field, and click Execute.
*There’s no easy solution if no entity is found, but you can try using schema markup for your business and your product, creating a Wikidata entry for your business and product, verifying your social media accounts, and creating a Wikipedia article.
Try to feed Google as much info as you can!
3. Machine Learning
Machine learning is closely related to the topic of semantic search in that it’s a way for search engines to make “educated guesses” about what ambiguous queries mean and to deliver better search results as a whole.
RankBrain and other machine learning systems examine user behavior to deliver the “best” search results possible. Unfortunately, what’s deemed best for one query might not be the best for another, which makes machine learning very difficult to optimize for.
Pro Talk Club is content sharing website, where you can Read great articles, Write amazing articles and Share the knowledge around the web!