Project Details
Projekt
Needmining - Analyzing Social Networks to Guide New Product Development Activities; first funding period: Analyzing Networks to Guide Targeted Marketing Communication
Subject Area
Accounting and Finance
Term
from 2014 to 2023
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 163849297
In the first funding period, project A1 analyzed the various ways in which social networks can be used for targeted marketing communication in the early phases after product launch. Initially, the focus was on network structures and the derivation of criteria that describe their suitability for targeted advertising. Formal criteria for network classification were developed and successfully tested within the scope of simulations. In addition, aspects of reciprocity in communication networks were analyzed that have not been adequately considered in empirical research up to now. Finally, in the last step, first complex simulation models were developed, which help to significantly improve concrete marketing decisions (e.g. the award of advertising premiums or stop / go decisions for new products).Whereas the focus in the first funding period was to use social networks after a product launch, the upcoming project will investigate the time before the product launch. It is to be investigated how information obtained in social networks can be used even before product launch for ideation and product development. To this end, existing methods of text mining approaches are to be extended and refined to enable an automated needmining, i.e., a quantitative, objective representation of potential customer needs. This automated needmining is based on user-generated content that with the rise of the participative web and social networks is nowadays widely available for evaluation. Through this approach a "datafication" of the ideation- and product development phase is to be established, so that quantitatively collected, qualitatively edited wishes, filtered out of the communication of the potential customers can be used as decision support instead of biased instinct and creativity.Thus in the context of the second funding phase the following research questions will be examined: (1) Which methodical approaches of text mining are appropriate for the needmining concept? (2) On which level of detail is needmining useful - on the macro level for the collection of general trends and / or on the micro level for the derivation of specific product characteristics and functionalities? (3) At which stage of product development is the application of needmining useful? (4) How can a feedback loop be designed for the needmining to test whether the implementation of the collected needs also meets the expectations of the potential users?
DFG Programme
Research Units
Co-Investigators
Professor Dr. Mark Heitmann; Professor Dr. Thorsten Hennig-Thurau
