Boost Click-Through Rate for Zendesk Article Recommendations
What steps can I take to increase the click-through rate for article recommendations?
To increase the click-through rate for article recommendations, focus on crafting engaging emails. The click-through rate is the percentage of users who click on suggested articles from the total number of articles recommended.
Enhance your email's subject line to make it appealing and informative, indicating that the email contains valuable content. Additionally, ensure the body of your email is well-structured, with the{{answer_bot.article_list}}or{{answer_bot.article_body}}placeholders positioned effectively to encourage clicks. This approach can help improve user engagement with your article recommendations.
More related questions
How can I improve the suggestion rate for article recommendations in Zendesk?
Improving the suggestion rate for article recommendations involves ensuring proper configuration and labeling. If your suggestion rate is lower than expected, it might be due to misconfigured article labels or unsupported languages. To enhance your…
How can I improve the resolution rate for article recommendations?
Improving the resolution rate for article recommendations involves focusing on content relevance and clarity. The resolution rate measures how often suggested articles successfully resolve user queries. To boost this rate, ensure your articles…
What can I do to decrease the rejection rate for article recommendations?
To decrease the rejection rate for article recommendations, optimize your help center content for clarity and focus. A high rejection rate indicates that users are not finding the suggested articles helpful. Ensure your articles have clear titles,…
How do article titles affect the performance of Zendesk's Answer Bot?
Article titles play a significant role in the performance of Zendesk's Answer Bot. Titles that closely match the text of a support request are more likely to be suggested by the bot. While formatting titles as questions can be effective, overuse of…
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“It now resolves 71% of queries (over 35,000 every month), meaning more time solving complex issues and improving UX.”
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