Search tools basically think for us, finish our sentences, and sometimes push ads for things we’re fairly certain we’ve only thought about.
Modern search tools are sophisticated and useful. They also tend to follow one of two examples.
Google and Amazon.
When it comes to your content management, Google might be known for its auto-fill search bar and cute google-doodle, but we believe that Amazon is the better model.
We know, it’s a strong claim to make between two titans of tech. Stay with us because a lot of what we discuss here has to do with how you interact with search, both voluntarily and involuntarily.
Search Your Feelings, You Know It To Be True
As search algorithms have evolved and become unnervingly advanced, we’ve become spoiled. Finding something becomes easier every second and our patience for a poor search experience is lower than ever.
Once upon a time, we mostly thought about search as an empty box with the little magnifying glass icon. You start typing what you want, hit Enter, and hope the engine works its magic. In most cases, it does its job beautifully with nary a hiccup.
This may be the case if you’re looking for the best pizza shop nearby or a quick oil change, but when searches become entangled in complex webs of data, the process becomes more involved.
Successfully completing a complex query requires your search to be broken down into smaller pieces than a general query. This is what search filters are built for. Also known as faceted search, search filters are renowned for making the life of a content manager much easier.
Faceted Search: Your Old-But-New BFF
The most common example of faceted search is on Amazon. As a store for almost everything, a good faceted search tool is essential for Amazon’s success. We, as consumers, can find the exact product we need among thousands of options. It works so well that we hardly notice.
When you’re looking for an espresso machine on Amazon, the search tool will populate a list of ideas to help guide your search. The first instance of faceted search you see is the drop-down menu that helps define the product’s category.
Searching for an espresso machine in the Home and Kitchen department, Amazon will use that filter to determine that you’re probably not looking for a commercial-grade piece of equipment.
Instead, it’ll guide you toward espresso machines meant for enjoying a leisurely cappuccino at home. Faceted search plays an important role in narrowing the espresso search even further.
Each selection you make narrows your choices from thousands of results until you have a page of machines that best fit your requirements.
That’s faceted search.
Faceted Search In easyDITA
When you create content in easyDITA, it’s tagged with metadata based on categories like:
- Product Model
- Release Version
- Any custom tag you establish
This metadata enables the Component Content Management System (CCMS) to create a faceted search with each metadata tag acting as a filter.
Content managers can easily find all the content in the system that fits the filters they’ve selected. This makes use and reuse of that content faster and easier. Because metadata is information about content, when metadata is thoughtfully developed, finding pieces of content through faceted search is a smooth process.
Just like Amazon’s metadata ensures a seamless search process, content managers who put effort into tagging their content thoughtfully will also reap the benefits of a smooth faceted search experience.
Faceted Search and Component-Based Organization
A Component Content Management System (CCMS) manages contents in little chunks (components) that give more granular control. Basically, each component can exist by itself as a standalone piece of information.
This makes the components in a CCMS ideal for rearranging, resuing, editing, and repurposing. Because each component is its own thing, the changes made only affect the component being changed.
The key to finding and managing the organization of these components in a CCMS packed with content? Faceted search.
But, Why Not Use a Google-esque Search Bar?
We don’t have anything against Google search. It is perfectly designed for users looking for approximate answers to general questions. You could use a search bar like Google’s to search through your documentation to find all the instances of keywords you’ve entered.
The trouble is, you’ll end up getting pages and pages of irrelevant results to slog through to find the specific content you need. This is especially troubling (and time-consuming) when your content library is massive. A recent Mckinsey study showed that interaction workers spend nearly 20% of their day looking for internal information.
The focus on speed is why Amazon brings you to a faceted search as soon as you’ve identified a broad product category. Amazon requires defined metadata when a product is added to their database. It makes sense because you don’t want to look through thousands of espresso machines. Similarly, easyDITA guides content identification by providing both pre-configured metadata and custom metadata that you can define. Your faceted search in easyDITA is a tool designed to make your content much more searchable, findable, and easily available for reuse, updates, edits, and more.
Good Structure Simplifies Search
Faceted search is a key capability that makes structured content such an advanced way to work. Compared to dealing with unstructured content like MS Word Docs, faceted search in structured content is much preferred to the nightmarish thought of using a text search tool to sift through hundreds of Word Docs.
With faceted search in a CCMS, you’re not only able to find content quickly, you can navigate to it directly and take whatever actions you need. Search should be simple, root to tip, and it all starts with good structure.
Hungry for more on good structure and faceted search? Just ask us. easyDITA wrote the book on it.
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