It seems the question on everyone’s mind these days is what’s the future of SEO? And how does Google’s announcement of RankBrain change the game? We'll explore that answer in this video.
- It seems the question on everyone's mind these days is what's the future of SEO and how does Google's announcement of RankBrain change the game? So if you're just hearing about this for the first time, I'll catch you up. A while ago, Google updated a portion of their algorithm, dubbing it RankBrain. Simplistically, it's a machine-learning artificial intelligence system. It provides a modern approach to how Google understands search queries and searcher intent.
RankBrain's primary purpose is to evaluate queries and then identify the best content. Google wants to return results that are incredibly relevant, even if in some situations, the content doesn't contain any of the words from the original search query. It's all about evaluating the intent of the search, and finding content that meets this goal. The major idea behind RankBrain is that we can get away from specific keyword matching and move to mapping content to concepts.
In the past, a query for laptop may not have listed content referencing its plural, laptops. Let's think about this another way. Say we've got a blog article that lists the best hamburgers in Santa Barbara. So the old method of SEO would look to see what keywords were most frequently used. Does a user search for best burgers in Santa Barbara, or maybe where's the best hamburger in Santa Barbara. We'd then fiddle with our content to make sure we use burger versus hamburger, and included any necessary modifiers, such as where or what, and so on.
But, when you really think about it, a search for best burgers Santa Barbara versus what are the best burgers in Santa Barbara versus top 10 hamburgers in Santa Barbara are all really asking the same question. RankBrain connects the dots and decides that regardless of the difference in word pairs and ordering of the search query, the same content will work. RankBrain is reducing the importance of keyword matching and improving the importance of matching your content to fit a user's intent.
So what does this mean for the future of search? Well, it's hard to say. But as you know from my other courses, I'm a big fan of Moz founder, Rand Fishkin, and he has three suggestions. First, mapping single keywords to single pages is an outdated idea. Gone are the days that we need to build a page for best burgers, and another page for best hamburgers. We instead should optimize our content by condensing it and choosing the group of keywords that map back to it.
Second, the same input can yield a different output because Google factors in context. If I do a search for coffee shop while I'm in Los Angeles, I'm going to get different results than the same search while in New York. You need to understand that certain queries will require different content. For coffee shop, you're going to want to invest in lots of local SEO and validate your content as having this local context. Gone again are the days of needing to shove the city after every instance of the word coffee shop.
You also need to evaluate that some search queries will demand fresh content while others, indepth thoroughly-linked content. You may have queries that should be formatted as a list over a table, and so on and so forth. The new model requires careful planning, and a deep analysis to determine what signals you need to give to Google to clarify which users will find your material, in line with their specific intent. And finally, you need to stay focused.
If you're always producing content that's fresh then work to capture search queries that demand this fresh content. If you serve up short answers to niche questions, then maintain that focus because Google will measure the reputation you earn when serving up content to these particular query types. A great approach to RankBrain is really just to stay on top of articles, news and data being shared by the industry. Start to experiment with your content, and begin to look at search queries through the intent-based approach we outlined earlier.
In a later video, we'll be looking at specific examples of RankBrain at work, and taking a closer look at machine learning.
- Evaluate the difference between Google and Bing search engines. Recognize the characteristics of three categories of search queries. Identify the purpose of clustering tools. Explain what kinds of content would improve a website’s snippet positioning. Define the function of a sitelink. Describe how to use operators to filter advanced search results.