Customize Ticket Volume Forecast in Zendesk Explore
How can I customize my ticket volume forecast in Zendesk Explore?
To customize your ticket volume forecast in Zendesk Explore, you can adjust the forecasting path, method, and values to predict. For instance, you can switch the path to 'On rows' for a table view, choose between additive or multiplicative models, and set custom values to predict up to five years ahead. These options allow you to tailor the forecast to your specific needs.
More related questions
How can I forecast ticket volumes by year using Zendesk Explore?
To forecast ticket volumes by year in Zendesk Explore, you'll need at least two years of ticket data. This allows Explore to generate a forecast using your existing data. Start by creating a report with the Support: Tickets dataset, then add the…
What are the requirements for forecasting ticket volumes in Zendesk Explore?
To forecast ticket volumes in Zendesk Explore, you need at least two cycles of data, which typically means two years if you're forecasting by year. You'll also need Zendesk Explore Professional or Enterprise, Editor or Admin permissions, and a…
How do I create a ticket volume forecast report in Zendesk Explore?
Creating a ticket volume forecast report in Zendesk Explore involves adding the 'Tickets' metric and 'Ticket created - Year' attribute to your report. Change the visualization to a Line chart and use the Forecast option to predict future ticket…
What forecasting options are available in Zendesk Explore?
Zendesk Explore offers several forecasting options, including the ability to calculate forecasts based on columns or rows, choose between different forecasting methods like the Holt Winters model, and specify the number of values to predict. You…
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“At the end of last year I was given the challenge - how can we provide the same or better service, without hiring anyone?”
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“My AskAI blew everybody else out of the water. It made the selection process very easy for us.”
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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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