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Chat support models: shared vs dedicated

Von Andrew Gori

Zuletzt aktualisiert: September 21, 2021

Offering omnichannel customer service is the core of any organization’s support strategy. But, in some cases it’s not possible for agents to do everything, and it’s critical that there is a plan in place for assigning agents to channels. There are two methodologies for channel assignment: a shared agent model and a dedicated one. In a shared model, agents handle some or all channels simultaneously. In a dedicated model, agents are focused on a single channel.

Dedicated model

There are pros and cons to either method, but 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, chat agents would only service chat customers for the duration of their shift. This model allows agents to develop a solid understanding of one channel and find the most effective methods of helping customers. Further, a dedicated model allows the support team to scale more effectively. However, 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. This results in them (potentially) developing a shallower skillset.

Shared model

In a shared model, agents are expected to work on the 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 serving chats 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 highly trained to be able to effectively switch between multiple channels with little notice.

There is no single factor that will determine which is right for you. Ultimately, the specific realities of your business, support organization, and goals will all play a role in determining which model is best.

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