How Deezer saved 200 agent hours each week & delivered joyful CX through instant support

A smiling woman dancing, with the Ultimate connector.

High volumes of casual contacts? No problem. With Ultimate’s automation solution taking on the workload of 5 agents (and providing instant first responses) leading music streaming service Deezer can keep its close-knit support team small by design.

Deezer at a glance

The customer

Music streaming service giving customers access to 90 million tracks, curated playlists & personalized recommendations

The market

Deezer supports its global users in 7 languages: French, English, Turkish, Arabic, German, Spanish & Portuguese

The support team

Approximately 50 agents serve Deezer’s customers — and Head of Customer Care, Patrick Dunford, wants to keep it that way

The situation

High volumes of (relatively) non-urgent inquiries and unpredictable surges in support requests

The solution

With automation, Deezer implemented a scalable and cost-effective first point of contact across both chat and tickets

The CRM

Zendesk

“Carl from Ultimate really understands how Zendesk works. So when we’re bringing up ideas he knows if they’ll be possible or not and can suggest other solutions.”

Aline Giazzon
Automation Manager, Deezer

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Automation use case spotlight: providing instant support

100% of queries are initially answered by the virtual agent, providing an immediate first response to customers
The virtual agent then gathers additional information before escalating more complex questions to a human agent, driving down handle times
Automation allows Deezer to deflect 2,500 chats and 7,000 tickets each month

Automation use case spotlight: managing contact spikes

To manage costs, Patrick keeps his support team small — but this makes them vulnerable to unexpected fluctuations in request volumes
After a recent service outage, AI-powered chat and ticket automation saved agents from manually answering around 3,000 extra inquiries
Their virtual agent allows them to ride out any storms, without taking on extra staff or making their customers wait

“We deliberately decided we don’t want hundreds of agents, so we needed to find a scalable model that could deal with a large number of users in a cost-efficient way.”