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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:
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.
The front-end bundle for Algolia’s Help Center search experience consists of:
In the current site, searches happen on 4 indices across 4 apps:
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:
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.
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