Second Generation Recommendation Engines in a SME B2B Context : A Case Study
ISBN
978-3-938137-57-4
Type
conference paper
Date Issued
2014-06-02
Author(s)
Eggel, Thomas
Abstract
Recommendations systems are artificial intelligence systems that have found a wide range of applications notably in e-business contexts, providing benefits such as automated cross- and upselling in addition to a reduction of transactional costs on both the demand and the supply side. They have been widely accepted by large enterprises but SMEs trying to adopt and implement similar technologies must face the problem of scarcity of transactional data. As a case in point we present the obstacles that a recent SME venture ran into and needed to overcome in order to provide the customers with a satisfying sales experience We will touch upon both the marketing and machine learning aspects of the platform and discuss several techniques that have been key in the successful implementation of expert knowledge extracted from the experience of the company's founders.
Language
English
Keywords
recommendation engines
B2B marketing
technology transfer
machine learning
expert systems
HSG Classification
contribution to practical use / society
Refereed
Yes
Book title
Conference Proceedings of the 13th International Science-to-Business Marketing Conference on Cross Organizational Value Creation
Publisher
Fachhochschule Münster
Start page
388
End page
345
Event Title
13th International Science-to-Business Marketing Conference
Event Location
Winterthur
Event Date
02.-04.06.2014
Subject(s)
Division(s)
Eprints ID
232207