Federated Search: All One Needs In A Search


What is federated search?  🔎 💙

-Examples of federated search 🧐 🧐

-Types of federated, unified search 🧠 ℹ️

-Benefits of implementing federated search 🤩 🚀

The amount of content and data keeps growing, year after year, and the fragmentation of content has become a real issue. Companies have content everywhere, on numerous platforms. How do you ensure that people find the information they want when there are so many search options?

Discover in this article how business leaders – in customer service, marketing, or operations – can centralize their search to reduce search efforts on the part of their customers and teams and simplify findability among their content sources.

Simply put, Federated Search is a technique that allows a user with a single search query to receive aggregated results from multiple information resources.

The main benefit to your clients (website search) or collaborators (internal search) is to have all content in a single place. This way, they do not have to go through multiple platforms to get an answer.

What do we mean by “sources”?

These can be any anything (databases and more) that includes information. For instance:

  • Websites linked to a company
  • Intranet assets: websites, applications, knowledge management systems, and/or project management software.
  • Blogs and other Content Management Systems

At this point, you might be thinking, okay, but what are good examples of federated search? Well, there are many, many examples of federated search online. Some of them are used in highly well-known websites. So let’s take a look at them:

1. Federated Search in Travel

As we’ve seen, in federated search the same query is sent to multiple databases simultaneously, and the to present the results together. This is quite common in the travel and airline industry, where we find examples of federated search in sites such as Skyscanner, Kayak, Expedia, or Priceline. These sites look for flight and accommodation availabilities through hundreds of other websites to return the results in a single page.

2. Federated Search in Retail

Another good example of Federated Search is Google Shopping or retail aggregator websites like Lyst. This last example, for instance, has a user interface that looks like any fashion marketplace out there.

However, if we look closely, we realize the site itself doesn’t have a checkout option, but rather indexes products from different websites.

We made the test and searched for ‘flowery summer dress’, which returned several items from different brands. Upon clicking on one item, we get redirected to the original retail site.

3. Federated Search in Customer Support

Quite often we think about federated search as a means of facilitating search of products or services, but what about answers to customer requests?

Adding federated search to your support site or even creating a federated chatbot that pulls information from FAQs, Knowledge Bases, technical documentation and more.

There are two basic components to Federated Search. First, the “index” is an aggregation of the data to search. This index is structured to facilitate efficient searches. Second, the “search function” is the element that looks for relevant information among the index in response to a specific query. The index and the search function interact together to make Federated Search possible.

1. Search-Time Merging (or “Query-Time Merging”)

In this type of Federated Search, a query is issued to each data source separately. It requires that a separate index for each data location be included in the search. Results are presented in an unstructured format and according to the priority order of each data source. Adjustments are restricted but no additional indexing of the content is required.

This is the simplest solution, but there is a risk of slow response times – which may undercut the need for fast, real-time responses for users.

2. Index-Time Merging

For this type of search, all content must be in the same index. This allows the search to manage the data and obtain better results. In this case, search results are sorted by relevance. This is a more complicated and expensive solution to set up as it requires building a whole indexing system. However, it is well worth the effort as it will ensure a best-in-class search experience and faster response times. Federated search tools make it easy to implement such a solution.

3. Hybrid Federated Search

The hybrid approach mixes query-time merging and index time merging. As much as possible, you should create a central index for each data source (as in index-time merging). In some cases, data sources cannot be represented in the central index and must be kept separately. When searching, you must then search all indexes, the central index, and the others. The results are aggregated to create a final list (as in query-time merging). Hybrid federated search offers better performance than merging at query time because it reduces the number of indexes that need to be searched. However, since there is more than one index, the search is slower than when there is only one index.

– Higher reliability and security 🛡️

Federated Search not only sends search queries to all the different data sources but can also consider a user’s credentials. This allows for results that would not appear in a simple web search, removing the need to log into each credentialing system and search.

– More accurate results 💯

In a traditional search, results do not always appear prioritized the way you want them to. Some information may be ranked below the stack when it is more valuable to the searcher. With Federated Search, sources can be weighted according to the visibility a user wants to give them in their search. This way, the adjusted results allow better prioritization of the searched data according to the needs of the person or the company.

– Faster responses ⏰

Software as a Service (SaaS) adoption has grown significantly over the past decade and some studies have shown that companies are using from 100 to nearly 300 apps, depending on their size. Each platform contains data and information important to business operations. It can be time-consuming and frustrating to spend much of the day going back and forth from one source to another to consolidate information or, even worse, not being able to find the information. Having all the search results gathered into one single search solution saves people time.

– Improved user experience 💻 💙

Federated Search makes it possible for people to search all existing content simultaneously. It allows users to find exactly what they are looking for, without even thinking about where it might be. This improves the user experience, increasing engagement and loyalty.

Mindbody, a California-based wellness company, implemented Inbenta’s federated search to optimize the performance of its Zendesk knowledge base and thus improve the satisfaction of its online community. One week after implementation, the number of visits and users increased by 100%.

Beyond just the Federated Search solution, Inbenta is an AI-powered intelligent search that uses natural language processing. Natural language processing helps computers clearly understand what people are typing online, whether there is a typo or not. That’s why Mindbody chose to work with Inbenta, and it appears they were right: after one month, they saw a more than 500% increase in visits to their community.

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