At Algolia, we obsess over the developer experience and pride ourselves on the speed and flexibility of our engine. Building is a craft, and our job is to make it easier for these builders to bring new experiences to life. At times though, using a painting analogy, teams want a paint-by-number solution, and more prescriptive guidance on how to make a client experience better efficiently. Today we’ll share more about improving search on your help center and how Algolia can help Zendesk clients. 

When we moved our support help center to Zendesk, we were keen to build an Algolia powered search experience for our customers that makes it easy for them to find the right solution for their request as fast as possible  We wanted to enable our users to search across our help articles, developer documentation, community content, and our client enablement site (academy.algolia.com), all from within one location. This is what we built:

Auto-Complete Experience

At Algolia, we obsess over the developer experience and pride ourselves on the speed and flexibility of our engine. Building is a craft, and our job is to make it easier for these builders to bring new experiences to life. At times though, using a painting analogy, teams want a paint-by-number solution, and more prescriptive guidance on how to make a client experience better efficiently. Today we’ll share more about improving search on your help center and how Algolia can help Zendesk clients.

When we moved our support help center to Zendesk, we were keen to build an Algolia powered search experience for our customers that makes it easy for them to find the right solution for their request as fast as possible  We wanted to enable our users to search across our help articles, developer documentation, community content, and our client enablement site (academy.algolia.com), all from within one location. This is what we built:

Auto-Complete Experience

Ticket Form Experience

Public Repo on Github, which is a public version of how we integrated Algolia search into our Zendesk frontend: https://github.com/algolia/public-custom-zendesk-search

Here is how we improved this search experience and improved search relevance.

• We crawled and indexed multiple sources using the Algolia Crawler
• Created a behavioral workflow that added content to the sources (adding articles regularly)
• Out-of-the-box, as-you-type search results made finding the correct article more frictionless
• Typo-tolerance provides relevant results even in the case of misspellings
• Search applies heavier ranking priority to articles found to be more useful to end-users
• Making support articles, documentation, community, and Algolia Academy searchable from a single location allows users to find answers without bouncing back and forth between platforms

The front-end bundle for Algolia’s Help Center search experience consists of:

• The Autocomplete search on the homepage

• This is accompanied by the smaller search bar on the top right of each page, which is leveraging classic InstantSearch.

• The ticket form request  search: when typing in the “Subject” field, search results will display right underneath the input.

In the current site, searches happen on 4 indices across 4 apps:

• Help Center articles
• Documentation
• Discourse posts
• Algolia Academy

The front end bundle is available via npm packages that is available through jsdelivr.

We then add the files to our Zendesk Help Center theme through simple link and script tags in the theme code editor.

In Zendesk’s HC document_head.hbs template we added the styles.

In the footer.hbs template, we added the javascript:

In our workflow, this package does not expose any kind of module or global function in the browser. This means any configuration change must happen through a commit on the package’s repository and then a release.

We organized the following constants:

• Sources (this is where the Indices and apps are defined)
• CSS Selectors (for autocomplete and ticket form search initialization, default selectors are the one from the default Help Center theme)
• Placeholder for the autocomplete
• Base URLs for the search redirections.

We used Algolia to develop our autocomplete and leveraged some styles from Docsearch.

My experience is clients care about time to value and client experience the most, but price matters. So here is some simple math to help you determine if a help center optimization project with Algolia could make sense for your organization. If the cost per ticket is $10, you need to be confident you can deflect at least 2K tickets via optimizations to justify the expense of Algolia.

Help center articles are a relatively straightforward implementation, and adding developer docs, blog, learn, community, and additional sources adds some complexity but also increases the impact. More records generally equal more API requests, and incremental cost to scale is low with Algolia. You can try it for free, and I hope the above help show how we can help move the needle for your team by improving your support experience. My experience is that if you can offer time to value & client experience enhancement, people will be happy & recommend your service to others.

If you need help implementing this solution, check out our support center or contact us.

Ticket Form Experience

Public Repo on Github, which is a public version of how we integrated Algolia search into our Zendesk frontend: https://github.com/algolia/public-custom-zendesk-search

Here is how we improved this search experience and improved search relevance. 

• We crawled and indexed multiple sources using the Algolia Crawler
• Created a behavioral workflow that added content to the sources (adding articles regularly)
• Out-of-the-box, as-you-type search results made finding the correct article more frictionless
• Typo-tolerance provides relevant results even in the case of misspellings
• Search applies heavier ranking priority to articles found to be more useful to end-users
• Making support articles, documentation, community, and Algolia Academy searchable from a single location allows users to find answers without bouncing back and forth between platforms

The front-end bundle for Algolia’s Help Center search experience consists of:

• The Autocomplete search on the homepage
  

• This is accompanied by the smaller search bar on the top right of each page, which is leveraging classic InstantSearch.

• The ticket form request  search: when typing in the “Subject” field, search results will display right underneath the input. 

In the current site, searches happen on 4 indices across 4 apps:

• Help Center articles
• Documentation
• Discourse posts
• Algolia Academy

The front end bundle is available via npm packages that is available through jsdelivr.

We then add the files to our Zendesk Help Center theme through simple link and script tags in the theme code editor.

In Zendesk’s HC document_head.hbs template we added the styles. 

In the footer.hbs template, we added the javascript:

In our workflow, this package does not expose any kind of module or global function in the browser. This means any configuration change must happen through a commit on the package’s repository and then a release.

We organized the following constants:

• Sources (this is where the Indices and apps are defined)
• CSS Selectors (for autocomplete and ticket form search initialization, default selectors are the one from the default Help Center theme)
• Placeholder for the autocomplete
• Base URLs for the search redirections.

We used Algolia to develop our autocomplete and leveraged some styles from Docsearch.

My experience is clients care about time to value and client experience the most, but price matters. So here is some simple math to help you determine if a help center optimization project with Algolia could make sense for your organization. If the cost per ticket is $10, you need to be confident you can deflect at least 2K tickets via optimizations to justify the expense of Algolia. 

Help center articles are a relatively straightforward implementation, and adding developer docs, blog, learn, community, and additional sources adds some complexity but also increases the impact. More records generally equal more API requests, and incremental cost to scale is low with Algolia. You can try it for free, and I hope the above help show how we can help move the needle for your team by improving your support experience. My experience is that if you can offer time to value & client experience enhancement, people will be happy & recommend your service to others. 

If you need help implementing this solution, check out our support center or contact us.