Abstract:
Recognising innovation opportunities based on customer needs online is labor intensive, as user-generated content grows exponentially. Machine learning takes the insight process to a new level by utilising machine's and human's individual strengths. In the following, we are sharing our leanings from a project that allowed a direct comparison between human-driven and machine-driven approaches in qualitative research: classic Netnography conducted by researchers versus machine-enabled research supported by algorithms.
Research Papers
AI meets CX
Catalogue: Fusion 2018 (Big Data World + Global Qualitative)
Authors: Christopher Harms, Luis Freile, Marc Zörnig
Company: SKOPOS
November 11, 2018
Videos
Standing on the shoulders of giants
Catalogue: Fusion 2018 (Big Data World + Global Qualitative)
Authors: Anna Marchuk, Stefan Biel
 
November 11, 2018
Research Papers
How we used a robot to solve a very human problem
Catalogue: Congress 2018
Authors: Elaine Rodrigo, Nina Rahmatallah
Company: Kantar
September 23, 2018
