What Is Vertical Search and How Does It Work

Vertical search is a way to find information that's tailored to a specific need or interest. It's like having a super-smart librarian who knows exactly where to find what you're looking for.

Vertical search engines focus on a specific area of information, such as recipes, travel plans, or product reviews. For example, a vertical search engine for recipes might allow you to search by ingredient, cooking time, or dietary restriction.

This approach is different from traditional search engines, which try to be all things to all people. By specializing in one area, vertical search engines can provide more accurate and relevant results.

For another approach, see: Website in Search Engines

Vertical search is a type of search engine that focuses on a specific industry, sector, or type of content. This approach is particularly prevalent in industries where depth and expertise are valued over breadth.

Vertical search engines emerged as a response to the challenge of sifting through the ever-growing amount of information on the internet. They provide users with a curated experience that aligns closely with their specific needs or interests.

Unlike general search engines, which index the vast expanses of the web, vertical search engines hone in on a targeted slice, delivering more refined and relevant results. This is because vertical search engines only search a specific part of the web.

Some examples of vertical search engines include in-platform eCommerce product search engines like Amazon, eBay, and Etsy, as well as vacation rental engines like Airbnb and HomeAway. These search engines are tailored to the expectations and requirements of users interested in a specific domain.

Key components of vertical search platforms include niche content indexing, advanced filtering, and user experience. Niche content indexing involves indexing content that is deeply relevant to a particular sector. Advanced filtering offers sophisticated filters that help users drill down to the information they need.

Here are some examples of vertical searches incorporated in Google:

Vertical search offers several benefits that make it a valuable tool for both users and businesses.

One of the main benefits of vertical search is its ability to provide greater precision due to its limited scope. This means that users can expect more targeted search results that are directly relevant to their query.

Vertical search engines also leverage domain knowledge, including taxonomies and ontologies, to provide more accurate results. This is especially useful for users who are searching for a niche topic.

Vertical search engines support specific unique user tasks, making them a valuable resource for users who need to find specific information quickly.

Here are some of the key benefits of vertical search:

You can add search verticals at an organization or site level to search for content from specific sources, such as Microsoft 365 Copilot connectors or SharePoint.

Custom verticals for SharePoint content show results from the respective scope, similar to other verticals at that scope. For example, a custom vertical at the organization scope shows all results, while a custom vertical with SharePoint content in the Marketing site shows data from that site.

Discover more: Search Engine Results Page

Customization allows you to add search verticals at an organization or site level, enabling you to search for content from Microsoft 365 Copilot connectors or SharePoint.

You can create custom verticals for SharePoint content, which will show results from the respective scope. For example, a custom vertical at the organization scope will show all results.

A custom vertical with SharePoint content in a specific site will only show data from that site, giving you more targeted results. Hub sites also apply the same hub scope to custom verticals.

You can create or modify search verticals, which is a wizard-driven process that guides you through defining the vertical's name, content source, and scope of the content to search.

The scope of the vertical search can be defined using a limited set of Keyword Query Language (KQL).

Filters can also be added to out-of-box and custom verticals at the organization and site level.

For more information about filters, see Manage filters.

In a custom search setup, you have the flexibility to add multiple connections as content sources under a single vertical. This allows you to design your search result page in a way that suits your needs.

You can't use connections under multiple verticals, so it's essential to plan your setup carefully.

To set up a query for a search vertical where multiple connection sources have been added, you'll want to use common source properties to create the query.

Here are some key points to keep in mind when working with multiple connections:

Vertical search engines like Google's specialized search results can display a significant amount of information at once.

You can use the "View all results" link to expand the search results and see more information, such as the snippet, URL, and date.

The search results are organized by relevance, with the most relevant results appearing at the top.

The search engine also provides a "Filter" option to narrow down the results by specific criteria, such as date, location, or file type.

You can also use the "Sort by" option to arrange the results in a specific order, such as by date or relevance.

The search engine also provides a "Refine" option to further narrow down the results by specific criteria, such as content type or language.

On a similar theme: Search by Criteria

Language localization doesn't apply to names of out-of-box verticals once modified. This means that even if you customize an existing vertical, its name won't change to reflect the new language.

Custom verticals don't appear on the mobile view of Microsoft Search. So, if you create a custom vertical, users on mobile devices won't see it.

Adding a query isn't supported on the People vertical. This limits the types of searches you can perform on this vertical.

Query string variables can only be used in SharePoint sites. This means that if you want to use query variables, you need to be in a SharePoint site.

Here are some limitations to keep in mind:

KQL allows you to narrow down search results by adding a query to a vertical. This can be done using free-text keywords and property restrictions with boolean operators.

You can use KQL to exclude results from archive sites by using the NOT operator with specific paths. For example, the query NOT (path:http://contoso.sharepoint.com/archive OR path:http://contoso.sharepoint.com/CompanyArchive) will do just that.

Dynamic ranking operators, proximity operators, and words aren't supported in KQL. It's recommended to use free-text keywords and property restrictions with boolean operators instead.

You can also use variables in the KQL query section of a vertical to provide dynamic data as input to the query. This can be done using "Profile" and "query string" types of query variables.

Here are some example KQL queries:

Remember to use variables in the KQL query section to provide dynamic data as input to the query.

Limitations are a crucial part of any system, and Microsoft Search is no exception. Custom verticals don't appear on the mobile view of Microsoft Search.

Recommended read: Microsoft Bing

You might be surprised to know that language localization doesn't apply to names of out-of-box verticals once modified. This can be a bit of a challenge if you're working with a multilingual team.

Adding query isn't supported on the People vertical, which can be a limitation if you're trying to use this feature to search for people within your organization. This might require you to use a different method to search for people.

Vertical modification and new verticals aren't visible to guest users in an organization, which can be a security feature but also a limitation. This means that guest users won't be able to see the custom verticals you've created.

Here are some specific limitations to keep in mind:

When troubleshooting issues with your setup, it's essential to know where to look for solutions. Here are a few common problems you might encounter and how to fix them.

If you see a "Something went wrong" error message on the vertical, it's likely because both the vertical and result types are needed to complete the setup. Make sure both are set up for the content source.

If you don't see any content sources on the vertical page, it's probably because you haven't configured connectors and indexed data.

Sometimes, a simple fix can resolve the issue. For example, if you're experiencing issues with your setup, try checking that both the vertical and result types are properly set up for the content source.

Here are a few common problems and their solutions:

Vertical search is a specialized type of search that targets a specific media type or content. It's a great way to connect with a more relevant audience and establish authority in a particular domain.

To optimize for vertical search, you need to focus on industry-specific keywords and provide in-depth, authoritative content that addresses the unique needs of your sector. Utilizing structured data can also help vertical search engines easily categorize and display your content.

Here's a comparison of vertical and horizontal search:

Note that vertical search has a narrower scope, making it easier to appear on if SEO is implemented appropriately. Having extra media like graphics, photos, and videos can also help you rank higher in vertical searches.

DARPA's Memex program is a research initiative that aims to develop new search technologies to overcome the limitations of text-based search. The program's goal is to create a new domain-specific indexing and search paradigm that will provide mechanisms for improved content discovery, information extraction, information retrieval, user collaboration, and extension of current search capabilities to the deep web, the dark web, and nontraditional content.

The Memex program was inspired by Bush's original Memex invention, which served as a precursor to modern search engines. As part of the program, DARPA wants to develop search engines that can search for information on the Deep Web, which is largely unreachable by commercial search engines like Google or Yahoo.

In 2014, DARPA released a statement outlining the preliminary details of the Memex program, with the aim of inventing better methods for interacting with and sharing information. The program's technology is expected to be usable for search engines that can search for information on the Deep Web.

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The Memex program has the potential to replace the centralized procedures used by commercial search engines, providing a more decentralized and user-centric approach to search. This could lead to improved content discovery and information retrieval for users.

Some of the key areas that the Memex program aims to address include:

In April 2015, it was announced that parts of the Memex program would be open sourced, with modules available for download. This move is expected to accelerate the development of the program and its potential applications.

Horizontal searching is a general type of searching that doesn't refer to specific media type or content. It searches the whole internet, covering a wide range of media topics and subjects.

The outcome of horizontal searching is a mixed result of various contents, including news, videos, and images, all in one place. This is in contrast to vertical searching, which gives specific results based on the media type or content.

To rank for horizontal searches, you need unique and regularly updated pages and content. This is because horizontal searching has a very high volume, making it more competitive than vertical searching.

Here's a comparison of vertical and horizontal searching:

To maximize your visibility in vertical search engines, focus on industry-specific keywords that your audience is likely to use in their searches. This is especially true for niche businesses.

Providing in-depth, authoritative content that addresses the unique needs of your sector is crucial for vertical search optimization. This can help establish your authority in a particular domain.

Utilizing structured data is another key aspect of vertical search optimization. This helps vertical search engines easily categorize and display your content.

Here are the three key areas to focus on for vertical search optimization:

By focusing on these areas, you can connect with a more relevant audience and establish your authority in your industry.

Domain-specific search engines focus on a specific topic, creating customized search experiences that provide extremely relevant results for searchers.

General search engines, on the other hand, index all pages and searches in a breadth-first manner, which can be inefficient and less effective.

Domain-specific search engines, like those using a reinforcement-learning framework, can be three times more efficient in spidering and collecting documents than general search engines.

Discover more: Comparison of Search Engines

Default verticals are present at the organization level in experiences like SharePoint, Microsoft Office, or at the SharePoint site level in each site's search result page.

At the organization level, you can rename default verticals, which is a great way to give them a more personalized touch.

You can also disable default verticals at the organization level, but be aware that this option is only partially available.

Disabling a vertical is a good idea if you don't need it, but you can't completely disable it at the organization level.

At the site level, you have more control over default verticals, and you can rename, disable, or add a query to them.

Here's a summary of the customization options for default verticals:

Domain-specific search engines are incredibly efficient, focusing on a particular area of knowledge and indexing a small subset of documents. This approach provides extremely relevant results for searchers.

Domain-specific verticals focus on a specific topic, creating customized search experiences that are three times more efficient than breadth-first search.

By focusing on a particular set of documents, these engines can spider more efficiently, saving time and resources.

For more insights, see: List of Search Engines