by Wayne Smith
What are Listicles?
A listicle is a structure for a webpage that presents information in a concise and structured format for headlines. Often they have or can have a table of contents and are numbered; But, there is a lot of flexibility in the structure.
Merriam Webster simply defines a listicle as:
"an article consisting of a series of items presented as a list." It is commonly used in articles such as "The 10 best ... of 2023."
On-page content optimization used by Content Creators for listicles:
- Each section or list element has text that explains the headline topic.
- Visitors can go straight to the topic of interest and read that section of the page, without needing to read the entire document.
- Content editors can edit individual sections, and typically list elements can be moved up or down on the list without interfering with the understanding.
- Unlike a book with chapters, listicals can be understood without the context of other chapters, and readers can read material in any order.
For user interaction the page should be easy to scan.
Listicle Topic Structure
The primary contextual design structure of a listical for SEO purposes is a topical tree. Google and other search engines use entities which is their word for topics.
The Listicle Headlines are the sub-topics
The reason listicles do so well in search includes the gain of knowledge that is provided by the topical structure.
- It is easy for the search engine to know what topics are explained
- What new information (gain of knowledge) or view point is being presented,
- It is presented in a helpful manner to visitors to the page.
Their is a disadvantage of using numbers, for search purposes, these numbers may become part of the description, as a snippet, for the page in search; Adding a list element and renumbering interferes with the feature snippet provided in search.
Graphical web design - SEO design Considerations
The listical topics should be treated as headlines larger than the text with the verbage on the listical topic, and smaller than the page headline. All other elements can be designed as needed.
Page headline, topic headlines, and text should be visible when the page is loaded. Scroll effects still work as the effect begins at the point the element would become visible.
For supplemental content such as citations and quotes used within the subtopic (which can help people scanning through the content to find the information they want quickly):
- The text can be emphasized or the size competitive with the subtopics as long as it is styled as using an HTML element which is not a headline tag.
- The supplemental content aids in SEO when its content supports the topic.
- Supplemental content can be considered as needed or wanted; Needed content supports the topic, and wanted content such as advertising can be wrapped in an aside tag.
- The design using aside tags can be created using grids such that when the page is displayed on desktop aside goes into a side panel and on mobile it enters the content flow where it is placed.
Coding considerations used by web developers for listicles
As noted for SEO design Considerations the size relationships of headline elements: page topic, listicle topic, and supporting text matter for SEO. Proper usage of headline tags are used for listicles, and the only headline tags used are for the listicle elements, (this creates the table of content in search). The table of contents is a learned structure of Google for the site, structures not listed here are possible but keeping it simple tends to work best.
The structure of the coding becomes known to Google and other pages that do not specifically have a table of contents may receive the rich search results description because of coding.
Data Highlighter is a webmaster tool for teaching Google about the pattern of structured data on your website. You simply use Data Highlighter to tag the data fields on your site with a mouse. Then Google can present your data more attractively -- and in new ways -- in search results and in other products such as the Google Knowledge Graph.
While the data highligher does not have support to inform Google of when to use jump to links in the search description, it gives insights into how google learns the coding of ones site.
All other content is styled using a tag other than a headline tag. Semantic HTML can be used for listicle sections while using asides for wanted content that does not support SEO considerations.
Minimum viable coding (HTML5 and CSS3) example:
Listicles and Table of Contents
For the table of contents to be listed in search, headlines must be used correctly. A graphic can be used but is not a requirement, a graphic is solely a site design style choice.
The headline tags were designed to allow a TOC to be automatically generated from a web page, but the headline tags are often misused as a style tag. When headline the tags are correctly used and linked: A TOC can become a snippet appearing in Google Search Results.
Content creator considerations ... topical (entity) relevance
Google has moved over to using entities in search, the evolution started before knowledge panels showed up on Google search results. Google's usage of entities can be clearly shown when Google applies natural language processing to determine search intent.
User Query Intent + SEO insights into entities
A query for "how to make pizza," could be interpreted fairly as asking for a recipe. With the Natural Language Processing algorithm using entities: Pizza is an entity under the entity of food and related to food is the word recipe, which is closely related to the concept (entity) of "how to make." A search for "how to make pizza," pulls up "pizza recipes," even when the term "how to make," does not exist on the page.
For Natural Language Processing algorithm purposes -- the listicle items are topics related to the page headline topic. The verbage in each list element includes words and entities that are related to the listed topic, and by extension relate to the headline of the page.
On topics where the author is very knowledgeable, they may be able to do a very good job in building a listicle. However, natural language processing is very good at spotting gaps. For competitive terms, research may be required to ensure there are no gaps. The topical research can require a lot of time. It is like old-school SEO for keyword research.
SEO: The evolution from Search Keywords to Search Entities
Nothing new under the sun. Old School SEO used keywords. Entities are like keywords but with a lot of information added. For document retrieval in scale, keywords can be indexed and each keyword index would have a record pointing to the resource or web page. The document retrieval system then looks for a record in the index that points to the same resource for all of the keywords. The natural order of the indexed data can be based on a page rank, (or using Search Entities Authority/Trust), which presorts the data. The smaller data set with all of the keywords can then be sorted for an exact, better match, and on expertise and experience.
Human vs AI: Humans can win because of the Gain of Knowledge Algorithm
AI is based on natural language processing and reports on what it understands about a topic. It learns as search learns what topics are related by reading documents. AI is always one step behind the humans that create the content, which both AI and search use to discover the relationship between entities or topical words. AI does not know anything until it reads a document created by a human.
AI is limited to a common understanding of a topic; Human experts and those with experience have a greater understanding of a topic than the common understanding. And, People with different backgrounds have unique insights into a topic. In other words, they can provide additional knowledge on the topic, which is why people search for information on the internet. There are also audience considerations where a human has a better understanding of other people than an AI does. Humans know how to persuade each other because of their understanding of other people, or because humans have empathy. A human can write a document with far more depth because of their understanding of the topic, unique point of view, and understanding of other people.
Gain of Knowledge Algorithm: The gain of knowledge algorithm is an algorithm that is applied after a search. Google learns from prior user searches and applies what it learned to future searches. The gain of knowledge factor is simply was the user happy with the search results or did they return to search and try another site or add another keyword? Google then re-evaluates the search for that topic to promote better results to the top and unsatisfactory results down.