Answer passages are collections of text that provide greater informational value to readers, in the form of rich data extract from a site. Interestingly, this doesn’t require structured data markup, but is instead extracted directly from the text.
In a natural language processing patent by Google, they explained that when users are searching for answers to specific questions, they often expect more than a definition, or single line response.
What users are really looking for, is a general explanation of the principle, or as the patent refers to it, an “Entity,” which provides more value than a single definition. For example the inclusion of history, growth projection, origin, authors, commissioners, nations, or anything that’s relevant to the Entity, categorised as an “Attribute.”
Users of search systems are often searching for an answer to a specific question, rather than a listing of resources. For example, users may want to know what the weather is in a particular location, a current quote for a stock, the capital of a state, etc. When queries that are in the form of a question are received, some search engines may perform specialized search operations in response to the question format of the query. For example, some search engines may provide information responsive to such queries in the form of an “answer,” such as information provided in the form of a “one box” to a question.
This grouped text that provides a more developed response to a user-query is referred to as an “answer passage.” Thereby, providing detailed information when dealing with definitions in the form of “prose-type-explanations,” can significantly improve your ability of being extracted for rich data snippets.
In fact, groups of text on every page are actually scored for relevance and value. So instead of having entire websites scored to form a SERP, text within the page is simultaneously scored and weighed in order to determine whether or not a data extract will provide additional value. This introduces a new algorithm, per se, which requires specific optimisation.
Some question queries are better served by explanatory answers, which are also referred to as “long answers” or “answer passages.” For example, for the question query [why is the sky blue], an answer explaining Rayleigh scatter is helpful. Such answer passages can be selected from resources that include text, such as paragraphs, that are relevant to the question and the answer. Sections of the text are scored, and the section with the best score is selected as an answer.
How are “Answer Passages” scored?
Step 1, Google receives a query which requires processing. Does this query benefit from having rich data extract? Maybe Google has repository information which can be displayed above ranking websites? Maybe this should be an image-driven SERP and therefore there isn’t need for rich data extract?
Once Google decides that this SERP requires rich data extract, it ranks passages based on two selection criteria:
- Query dependant signals
- Query independent signals
Query dependent signals are ones that are based upon the relevance of the answer passage of a site in regard to the query. For example a query about the quality of SEO in Madrid is entered into Google; answer passages that address SEO, Madrid, and the relationship between them will have a far better relevance score than non-Madrid based SEO answer passages. Makes sense, doesn’t’ it?
Query independent signals are signals that are “inorganic” to the page, such as number of links pointing to that page, the freshness of the article, anchor text, or infrastructure (such as DA and PA). For example, two answer passages of competing sites that have the same query dependent signals, will be finalised based on the independant signals, such as DA and freshness. This allows you, as an SEO, to have power over the ranking of your answer passages in particular.
The query dependent signals may be weighted based on the set of most relevant resources, which tends to surface answer passages that are more relevant than passage scored on a larger corpus of resources. This, in turn, reduces processing requirements and readily facilitates a scoring analysis at query time.
Google does not necessarily want structured data markup. Which is great news for us non-Microdata SEOs. JSON-LD would not be applicable in this sense due to it’s broad scope, whereas Microdata is perfectly suited to the providing attributes to a standard <p> tag. Luckily, Google is capable of extracting the answer passage based on contextual material and through query matching.
Read more: Easy JSON-LD templates for eCommerce sites.
How do you optimise your Answer Passages?
As a result of the above patent, it’s crucial that technical information and definition driven text is well elaborated. After some testing, we have found that the two sentences before, and two sentences after a definition plays a crucial role in the ranking of an Answer Passage in terms of having it registered.
Ensure that you elaborate on the specificity of details in your Answer Passage. If you’re discussing a technical programming language, ensure you discuss its applications in the following sentence as briefly and efficiently as possible. This allows Google to extract the maximum amount of value out of your copy.
Employ structured data markup if possible. Google will always lean towards structured data markup, because it reduces the workload of their bots. It also allows them to better identify content, and connect it with search queries. There is no doubt that answer passages as dignified by structured data markup will rank better than non-marked data.
Develop as much query matching in your definition as possible. If you know your users search “What is SEO?” ensure you have something very similar to that to meet Augmented Search Query demands. Google knows when Answer Passages exist particularly when they are directly matched with text from a site.
Work on your general SEO. This is common advice that any SEO would tell you, but it does matter. When it comes to rankings, you will lose to sites of better Domain Authority, digital presence, recognition, retention, CTR, and such. Make sure you squeeze the optimisation out of your site to get your Answer Passages ranking in rich data snippets above your competitors, especially if you believe it meets the query dependent signals better than your competitor.
Read more: 10 Quick on-page SEO SEO tips for 2019