May 21, 2020

How to build a forecast for customer support

Ryan Wang


Great customer support requires that you solve customer problems promptly and with empathy. As with many things, preparation is key. Accurate forecasts of contact volume put the team in a position to succeed, helping ensure that customers can connect with the right person at the right time. This article will walk you through the basics of forecasting your volume.

Why forecast at all?

In many cases, those who have been working in support for a long time have developed a "spider sense" for what will happen on any given day, whether through hard-earned experience or spooky omniscience. For the rest of the team, though, good forecasts can help enable:

  • Predictable response times: An understanding of when customers tend to call or write in allows the team to staff accordingly.
  • Well-informed hiring plans: Support leaders increasingly seek data to inform their decision making, and accurate forecasts can bring clarity and show that you've done your homework.
  • Team visibility: If things feel unexpectedly busy on a given day, why is that and what can be done? Forecasts help a team supplement their intuition.
  • Efficiency and fairness: It’s always a tricky balance between understaffing and overstaffing. Accurate forecasts support a distribution of workload that is both efficient and fair.

How to build a forecast

Good forecasts start with an understanding of what you’re trying to achieve and the fundamental dynamics of your support volume.

Choose the right interval

Start by deciding on the interval and timespan that are most relevant to your goals. It’s best to match up your interval with what you’re trying to achieve:

  • Headcount planning (long term): If you’re planning headcount or thinking about what your team will look like months or years down the line, you should try forecasting volume for weeks or months at a time.
  • Email or non-urgent support (medium term): When forecasting for non-urgent support channels, such as email or help desk tickets, consider segmenting volume by day.
  • Chat, phone, or real-time support (short term): For real-time support over the phone or live chat, consider forecasting at an hourly or even 15-minute granularity. Though keep in mind that you’ll need large amounts of volume and data for this to be informative.

Retrieve the right data

Most contact platforms allow you to export historical data. To enumerate a few of the most popular platforms:

  • For Zendesk, you can use Zendesk Explore to export a count of tickets.
  • For Intercom, you can inspect the New conversations report, though there’s no way to export the contents in a structured form.
  • For Kustomer, you can use the CSV Export Feature, though data goes back only as far as one month.
  • For Salesforce, you can use a Custom Report Type on Cases.

In cases where data is incomplete or difficult to export, you can always use Assembled’s out-of-the-box integrations.

The simplest approach: average the past

At its core, most forecasts use knowledge about the past to inform the future.The simplest forecasting approach is to calculate the average number of contacts over a set interval. For example, in order to forecast how many tickets you will receive at 9am on Monday, take the average of 9am’s for the past several weeks. If your volume varies based on the day of the week—often weekends are lighter than weekdays— average together only 9am’s for the past several Mondays or weekdays.

We put together and excel template to walk you through this process from beginning to end. Preview it below or click here to make a copy of the template:

Next steps

We hope this article has given you a framework to get started with forecasting. Don't be discouraged if all this sounds like a lot of work, forecasting is definitely no walk in the park—after all, we're trying to predict the future! If you’d like to discuss tactics or to explore Assembled’s out-of-the-box forecasts, please drop us a line at

Photo by Julie Molliver on Unsplash

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