When first launching your Zendesk, it’s important to take into account your different staffing requirements across all products. This article will discuss some practices you can implement to help plan staffing for Zendesk Suite.
For an overview of messaging specific staffing, see Planning agent staffing for messaging. For an overview of Talk specific staffing, see Determining your Zendesk Talk staffing requirements.
This article contains the following sections:Deciding on a staffing model
When initially scheduling your agents, you should consider the type of staffing model you would like to implement. There are two methodologies for staffing across multiple channels:
Dedicated staffing model
In general if your organization has more than 10 agents, it is recommended to use the dedicated model. In this format, agents focus their attention on customers from one channel. For example, Talk agents would offer phone support during the duration of their shift. This model enables agents to develop a solid understanding of one channel and find the most effective methods of helping customers. Further, a dedicated model enables your team to scale more effectively.
The downside of this model is that agents often don’t get a deeper understanding of a customer’s problems as they end up escalating complex queries.
Shared staffing model
In a shared model, agents are expected to work on channels that require the most attention and then switch over to other channels as they become busier. For example, a shared agent might start their day working on email support, but then switch over to answering phone calls as more start coming in. The advantage of this model is that agents maximize their time and are always solving customer queries. However, an agent would have to be trained more thoroughly to be able to effectively switch between multiple channels with little notice.
Planning your staffing schedule
Using a blocked schedule model
When planning scheduling and staffing across multiple channels, one option we recommend is a blocked schedule . A blocked schedule strategy acts similar to a dedicated staffing model, in which agents are assigned one channel per time slot. The agent will monitor the associated channel for their shift before switching to another channel.
The following are a few recommendations to consider when creating and staffing a blocked schedule strategy:
- Distribute your channel shifts evenly. If agents are placed on the same channel throughout the entire day, they might experience channel overload.
- Schedule your Support channel shifts after your live channels. In general, it is a good practice to schedule your agents Support shift after their Talk and messaging channel shifts, so they have the opportunity to follow-up quickly on any open tickets created from those shifts.
- Prepare for transitions. Transitions between timezones and agent shifts can be one of the most frequent opportunities for support request to be missed.
- Consider all of your channels. While this article primarily discusses your primary product channels, it is important to evaluate all of the areas customers might request your support. For example, it is a good idea to have an agent monitor your social media throughout the day.
- Track your metrics. To accurately evaluate your staffing and scheduling methods, you will need to track your request volume. See Using reports to evaluate staffing for examples of the reports you could use.
The most important recommendation is to communicate with your agents both throughout the day and after their shifts are complete. While we recommend breaking up channel blocks to prevent channel overload, sometimes agents might be focused on their channel and require more time to finish up their current tasks before switching. At the end of the day, you will want to gather feedback from your agents to evaluate how you can make adjustments on staffing and scheduling.
Making staffing adjustments
The most critical aspect of staffing is making adjustments according to your agents feedback. You should continue to communicate with your agents to evaluate how their experiences with each channel and adjust the number of agents for each shift accordingly. Your agents’ feedback and your support request volume metrics will be critical factors in determining your staffing.
While you are still collecting agent feedback, it might be good to implement an override agent. An override agent is an agent currently scheduled for the Support channel, but their primary responsibility is to transfer into another channel when extra assistance is needed. This could be when your call wait time becomes too high, your messaging requests increase unusually, or an agent cannot transition to their following channel. An override agent can provide back-up assistance whenever necessary.
You can read more about the adjustments you might need to make for each product in Planning agent staffing for messaging and Determining your Zendesk Talk staffing requirements.
Using reports to evaluate staffing
After launching your staffing, it’s important to monitor your request volumes and adjust your volumes accordingly. This section discusses some valuable reports you can use to evaluate your staffing.
Below are the following reports that can help you analyze your overall ticket volume. For more information on these reports, see Using the Reporting Overview and Analyzing your Support ticket activity and agent performance.
- Ticket Stats:The Ticket Stats report at the top of the native Reporting Overview dashboard can help you evaluate a variety of statistics such as new tickets, solved tickets, and first reply time by date. This report can help you analyze general ticket volume.
- Tickets by Channel: The Tickets by Channel report on the native Reporting Overview dashboard provides more granular detail about your new tickets. You can use the report to view the percentage of tickets created by each channel and determine your most popular channel to distribute your staffing.
- First reply time: The First reply time report on the native Reporting Overview dashboard can help you analyze how quickly your agents are replying to customer requests. If your first reply time is too high, then you might want to evaluate your staffing.
To analyze your Talk volume, you can use the Talk analytics dashboards (see Analyzing call activity with the Talk dashboard and Analyzing call activity with the Talk Team dashboard).
8 comments
Oscar Tobar
Any suggestions on what reports to look at in Explore to evaluate staffing? 😀
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Dave Dyson
Hey Oscar, what a great question!
Staffing of course isn't just numbers – how many agents you need can depend on many factors, including whether they have the training, tools, and information they need, if your internal policies and processes are conducive to a good agent and customer experience (while meeting the needs of the business), the quality and ease of use of your product, the quality of your documentation and self-help experience, not to mention the expectations you set for the quality of your customer service. But I think a good starting point can be to ask: "Do I have enough staff at the right times?" Here's a way to investigate that:
First, take a look at a heatmap of median first reply time – this will show you generally at what times of the week customers are having to wait the longest: Explore recipe: First reply time heatmap
This will show you right away if customers are having to wait longer at certain times than others (the examples shows much longer wait times on the weekend). The example in that article shows much longer wait times on weekends, so it would suggest that adding additional weekend staff could help get that wait time down – which should lead to those weekend customers being happier with the service they receive, unless of course they don't have an expectation of fast weekend service. But let's assume they're not happy with the weekend wait. How much additional staff do you need to add?
For that you'll want to know how many tickets you're actually receiving at any given hour, so you'll want to look at another heatmap: Explore recipe: Ticket creation heatmap
Between that and a general idea of how many tickets your agents can handle in a given hour, you should be able to make an estimate of how many additional staff you might need during the times when customers are waiting the longest.
Hopefully this helps as a starting point. Anyone else in the community have any other ideas?
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Hillary Latham
Hey Oscar - we have a staffing model that pairs customers directly with assigned agents, so the things I look at and apply to a staffing model that we have are:
Hope this helps!
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Rob Stack
Hi Oscar Tobar, in addition to the great answers above, you'll find some good tips to help you plan for staffing in this article: Using the metrics that matter to improve customer support
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Whitney Votaw
@...
Those are awesome metrics! Thank you so much for sharing. Looking at different staffing models to help ensure we're more properly staffed for Talk during busy times, but also increasing the length of time agents have to actually get to Support tickets so there is more of a balanced feel every day.
I have a lot to learn with Explore, so I apologize if this is juvenile, but would you mind specifically sharing how you're calculating these two metrics? These would help me a ton!
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Gab Guinto
Hi Whitney,
You create a query with the native Tickets metric and then slice your data by the attribute Assignee name. You can then add the default date attributes under Rows/Columns such as Ticket created - Day of week, - Week of Year, - Quarter, and Ticket created - Year.
About tracking escalations – you can create a report using the Ticket updates dataset. Here is an Explore recipe that you can use as guide: Tracking ticket assigns across groups.
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Pablo Payet
Hi,
Closed ticket is not a good metrics to assess agent performance on Zendesk at all.
Note that a ticket can only counted as solved 1 time. This means that no matter how often it reopens, it will only be counted as solved 1 time. Secondly, if agent A solve a ticket on day 1 on that agent B solves it again on day 2, it will count as solved only for agent B.
So basically, anytime you will look at the past on how many tickets were solved by X agent, you will get a different number as it depends on how often and when it will reopen, and who will then solve it for the last time.
This is also a problem when you want to define your staffing need. Usually I would see how long it take to close a ticket ( AHT), and apply to the number of tickets expected. But then you also need to know how often a ticket will reopen and require to be solved (additional AHT). This is very complicated.
Anyone can comment here or support please?
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Gab Guinto
Under the Updates history dataset, you can build reports to count the number of times a ticket was placed in solved status (Resolutions), and depending on your workflows, you can you slice the metric by Updater name (the user who submitted the status change) or Update ticket assignee (the assignee during that update).
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