Since the beginning, Google algorithm has been programmed to tie results to queries with little context except for demographics or technology details. Nonetheless, it often succeeds in giving users the answers they want.
In September 2018, Google evolved again:
We’ve spent the last 20 years optimizing Search so it works well for getting quick information. But in life, we often take longer journeys, and people turn to Search for help in these moments too. - Someone at Google
Nowadays, with the current mobile technology context, and the popularity of smartphones, netizens are researching mostly online, with little or no offline research.
Therefore, many searches are related to longer sessions that span multiple days, with people coming back and forth to the search engine result page with the hope to find the latest updates on a topic or explore the range of content available.
For example, some might be planning a trip and searching for information about a destination for a whole month. Or perhaps others regularly search for “easy dinner recipes” to help plan their meals for the week.
In this context, Google aims to help searchers to :
- resume tasks where they left them off,
- keep track of ideas and content that they deemed useful,
- obtain relevant suggestions of things to explore next.
Enter Search Journey, a concept that extends Search Intent, and that is becoming crucial in how Google algorithm understands what searchers are expecting, implicitly, when they type in a query.
The issue with “history-blind” answers search results?
When people are searching for something online, first they go to their favorite search engine, then type in what they want to know, in the form of a search query such as:
- “painting tips for beginners”
- “family lawyer in Jakarta”
- “how to make a wooden chair”
In the past, Google was history-blind and focused on giving people the best results based on queries. It was determined mathematically by a variety of factors (keyword match, relevancy, proximity, and numerous others).
The weakness with this approach is that it simply tried to find the best fit for what visitors explicitly searched for, and did not account for what a user “implicitly” meant to find.
In that sense, Google was neither predictive in what results to show searchers next, based on previous searches, nor it considered what stage they were at in the search journey.
Why evolving to Search Journey?
Instead of personas and answering questions, Google now focuses on the full experience.
This evolution challenges the way web searches previously worked but also reveals how Google uses prior search history in an entirely new way to present users with potentially more relevant and highly-tailored results.
Over time, Google learned that there can be a variety of things that users are looking for when they type in the same query, and consequently, that there can be many different stages to that process.
With Search Journeys, Google relies on machine learning to understand better the context when people search for things. It considers where they have been, what they have searched for in the past, and what they are likely to look for or do next.
Below is an example of a user’s Search Journey in action:
- A user starts searching for a family law attorney in Zurich.
- They Google a few terms, like “family lawyer near me” and “best family lawyer in Zurich.
- After visiting a few websites of law firms, and learning about them, they made a mental note of who they would hit back later. Suppose they decide to think about it for a while.
- About a week later, they search for the same terms again.
- This time, Google knows the websites they already visited the last time, and for how long. The algorithm knows that they aren’t looking to explore new options, but are wanting to decide between the options they found in their first search. Google may show the user reviews of the law firms they checked out already, or present them with content focused on how to hire a lawyer.
Already, we can see how this lines up with what we already understand about the buyer’s journey.
Users often start by looking for a solution to a problem, then they weigh their options, and then they are ready to buy.
With Search Journeys, Google’s algorithm uses user history to figure out where a user is at in their journey and then present them with content that fits, and this change should redefine how you structure your content strategy to better serve your prospective customers.
What do context-based and intent-based results mean for your SEO strategy?
What that means for SEO is that it’s no longer good enough only to rank for certain keywords.
You may have been in the top spot in Google for a solid six months, but now you may not show up if your content doesn’t match with the stage Google deemed the user to be in. Your content may have been in the decision stage when most searchers are looking for awareness stage and you’ve missed the mark.
How to fix your SEO strategy
You will need a “content re-think”. Many businesses have content that is only about the decision stage (contact us now, buy now) and ignores the other stages in the buyer’s journey. It’s problematic.
Before your traffic plummets, start by understanding which stage of the buyer’s journey your content does cover. Are there any gaps? What topics do you need to write about to create a full journey? How many pieces do you need?
Additionally, you’ll want to categorize your keywords by type: informational, navigational, transactional. Again, create more content around these keyword categories to capture more stages of the buyer’s journey.
Again, make sure that:
- You aren’t all commercial or all informational, for example. More about this here.
- You capture all the stages of the journey to ensure that your website answers user’s intent, no matter their buying stage.