Right knowledge for the right user at the right time
Hannila, Jaana (2021)
2021
All rights reserved. This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2021120924760
https://urn.fi/URN:NBN:fi:amk-2021120924760
Tiivistelmä
A globally operating software product company provides online support services such as user assistance and discussion forum for its B2B customers in the building construction industry. Its vision for 2025 states that online services provided to users will reduce mental stress and help customers in digitalization. Backbone of this research was an intelligent user assistance that would shorten the learning curve, expand the knowledge of users, and improve user performance. In this way, the customer's value in use could be realized faster affecting the intention to buy after the trial or renew order and thus reduce churn.
In this thesis we deal with two practical topics. The first topic is how the results of the user assistance knowledge search should be ranked to best help the end user. This was explored by innovating and developing a proof of concept of an intelligent search. Another topic was to identify the concrete steps needed to implement intelligent user assistance. The tangible result of this was a roadmap stating the intention and direction using themes and more detailed features.
The constructive research and development of the proof of concept was based on data collection among the company’s experts. The proof of concept was built in collaboration with an AI partner and evaluated in interviews. The applicability of the proof of concept was considered when roadmap towards intelligent user assistance was created. For the evaluation of the roadmap, it was presented to the steering group of the company.An analysis of the primary data collected clearly showed how search results should be ranked and what types of users the new service should focus on. The abstract concept of "advancedness" developed proved essential to ensure the relevance of the assistance provided. The new intelligent assistance would bring together the target company, customer organization as well as community of practice for co-creation of knowledge. Finally, the roadmap was evaluated and accepted by the target company's steering group.
In the thesis, intelligent user assistance was combined with knowledge management theories which created a new perspective and solution that would make it possible to reduce the deep learning curve of the target company’s professional software. The approach presented could be extended in the future allowing a customer using multiple products from the portfolio to share and re-use valuable construction domain knowledge that help to successfully complete the various phases of a building construction project.
In this thesis we deal with two practical topics. The first topic is how the results of the user assistance knowledge search should be ranked to best help the end user. This was explored by innovating and developing a proof of concept of an intelligent search. Another topic was to identify the concrete steps needed to implement intelligent user assistance. The tangible result of this was a roadmap stating the intention and direction using themes and more detailed features.
The constructive research and development of the proof of concept was based on data collection among the company’s experts. The proof of concept was built in collaboration with an AI partner and evaluated in interviews. The applicability of the proof of concept was considered when roadmap towards intelligent user assistance was created. For the evaluation of the roadmap, it was presented to the steering group of the company.An analysis of the primary data collected clearly showed how search results should be ranked and what types of users the new service should focus on. The abstract concept of "advancedness" developed proved essential to ensure the relevance of the assistance provided. The new intelligent assistance would bring together the target company, customer organization as well as community of practice for co-creation of knowledge. Finally, the roadmap was evaluated and accepted by the target company's steering group.
In the thesis, intelligent user assistance was combined with knowledge management theories which created a new perspective and solution that would make it possible to reduce the deep learning curve of the target company’s professional software. The approach presented could be extended in the future allowing a customer using multiple products from the portfolio to share and re-use valuable construction domain knowledge that help to successfully complete the various phases of a building construction project.