In 6 weeks to a modern call center with deepassist

Stadtwerke Hamm has remained a reliable gas and energy supplier for its customers even in turbulent times. Thanks to solid and foresighted purchasing management, the price increases were significantly lower than those of many other suppliers – but they could not be avoided.

While the contact centre’s contact volume had already increased dramatically since the start of the pandemic, it would multiply again when the new price regulations came into force. It was therefore necessary to develop a solution within a few weeks in order to continue to provide good, if not better, customer service.

Optimization by deepassist

First Contact Resolution Rate

↑

Process acceleration

Customer

Stadtwerke Hamm GmbH

Industry

Energy

Company size

500 - 1000

The Challenge

Stadtwerke Hamm’s Shared Service Center had reached the limits of its optimization possibilities due to the static telephone system. In order to ensure better availability and to be able to answer incoming customer inquiries more quickly, there were two options:

Outsourcing customer service or a fundamental technical modernization of the contact channels, whereby in-house operation of customer service was clearly preferred.

The greatest immediate added value was hoped for by redesigning the telephone routing. Instead of a static voice menu, where the caller selects their request from a predefined group by pressing a button, the spoken language was to be automatically understood and assigned to the correct internal specialist hotline.

deepassist is...

Industry specific

The deepassist AI already has the relevant knowledge of the energy sector and thus reduced the training effort many times over.

Strategic

The use of deepassist as an NLU solution can be used by all departments within Stadtwerke Hamm.

The Solution

The technological partnership between deepassist and babelforce impressed with its agile approach to the solution.

With babelforce, there is no need to replace the telephone system, as incoming calls can be redirected to the software-based call center platform. On the other hand, deepassist provides a pre-trained, industry-specific semantic AI that understands the caller’s colloquial language and initiates appropriate solution steps.

Babelforce and deepassist are both no-code platforms, which means that they can be implemented without programming. This means that call center automation can also be implemented quickly and cost-effectively in medium-sized companies.

The use of deepassist’s semantic AI has enabled us to implement request-based routing, which offers everything from targeted call routing to partially and fully automated request processing, taking future-oriented customer service to the next level. We are already looking forward to the next expansion stages!

The Result

Within just six weeks, the intelligent routing for two different service went live, noticeably reducing the workload in the call center.

Thanks to deepassist’s strategic technological approach, the semantic AI can be quickly rolled out to other hotlines and communication channels. Stadtwerke Hamm’s automation plans also include other customer service contact channels such as email. The language models already developed and the NLU engine from deepassist can be used and further developed for this in the future – regardless of the platform.

Automate Your Customer Service

During a short demo appointment, we will show you how we automate routine inquiries via telephone, e-mail and chat.

Cronos compactSession: Insights into the successful project of Stadtwerke Hamm with Niklas Ostrowski and Joseph Hotter.

In the Cronos compact session on “SOS in customer service – AI meets RPA”, Niklas Ostrowski, team leader of external customer service at Stadtwerke Hamm, and Joseph Hotter, CSO at deepsearch, meet.

Among other things, they talk about:

Difficulties in customer service before automation
the technological partnership with babelforce
the approach during the project
the relief of customer service and the improved accessibility through deepassist