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Chatbots for Loyalty

Innovation project on chatbots in customer service and education

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Chatbots allows us to rethink how to design digital services. Chatbots for customer service allows for 24/7 access to automated information and support. Chatbots in education may facilitate dialogue and learning on digital platforms.

The chatbots that are available today, have been made possible through advances in artificial intelligence and machine learning. Chatbots can learn through dialogue with their users. They may also utilize other data sources to predict what users need.

In Chatbots for Loyalty, our goal is to strenghten the role chatbots may take as point of contact between customers, users, and companies. We in particular work within three areas:

User-centred design of chatbots

Chatbot concepts based on knowledge about users needs and experiences when encountering chatbots. For example, which tasks users need help with, how they want the chatbot to appear, and how chatbots interact with other channels such as webpages and manual support.

Machine learning for prediction of next best actions

How dialogue data, possibly together with other data sources, maybe used as basis for machine learning, thereby enabling chatbots to better understand the users, their context, and make adequate recommendations.

Service design where chatbots becomes an important part of a service provider's key customer journeys

How chatbots may take on a more substantial role in the key customer journeys of a service provider, becoming a preferred point of contact. What we need to take into account when chatbots take on such an extended role.

We believe chatbots will be an increasingly important part of digital service providion. Please consult the project website for updates.

Project partners:

Anzyz Technologies (owner),, EdTech Foundry, NKI Kompetanse, SpareBank 1 SR-bank, Nordea Liv, SINTEF, Universitetet i Agder – Center for AI Reseach.

The project is supported by the Research Council of Norway BIA programme

Key Factors

Project duration

2018 - 2022