From fragmented knowledge to automated customer service

Want to experience the ImmoScout24 case study for yourself? In a joint webinar, Felix Lessing and Sandra Schütt from ImmoScout24 will show you how the chatbot was developed in practice. Click here to watch the recording!

From query chaos to AI support

Around 18.6 million people use ImmoScout24 every month. As a digital ecosystem for the property sector, the platform connects estate agents, investors, property owners and those looking for a home. Users have a wide variety of queries regarding listings, memberships, application portfolios, technical issues and much more. This poses a major challenge for the support team, as everyone expects fast, reliable answers around the clock.

The problem with ImmoScout24 was that, although much of the company’s support knowledge was available, it was scattered across external FAQs, Confluence and Salesforce. There was no consistent structure and no clear lines of responsibility.

Autonomy rather than dependence

This case study shows how ImmoScout24 tackled this initial challenge by setting up a central knowledge base and a new enquiry categorisation system. The key to success was a ‘learning by doing’ approach rather than lengthy planning phases.

Discover this and more in the case study:

• Why fragmented knowledge was the real driving force behind the AI chatbot project – and not the chatbot itself!
• How ImmoScout24 used the enquiry categorisation system to make recurring queries visible and automatable
• How ImmoScout24 plans to increase the automation rate to around 90%
• What companies in a similar situation can learn from this project!