@article{8553062,
  abstract     = {{Business-to-business organizations and scholars are becoming increasingly aware of the possibilities social media and predictive analytics offer. Despite the interest in social media, only few have analyzed the impact of social media on the sales process. This paper takes a quantitative view to examine the added value of Facebook data in the customer acquisition process. In order to do so, we devise a customer acquisition decision support system to qualify prospects as potential customers, and incorporate commercially purchased prospecting data, website data and Facebook data. Our system is subsequently used by Coca Cola Refreshments Inc. (CCR) to generate calling lists of beverage serving outlets, ranked by their likelihood of becoming a customer. In this paper we report the results, in terms of prospect-to-customer conversion, of a real-life experiment encompassing nearly 9000 prospects. The results show that Facebook is the most informative. data source to qualify prospects, and is complementary with the other data sources in that it further improves predictive performance. We contribute to literature in that we are the first to investigate the effectiveness of social media information in acquiring B2B-customers. Our results imply that Facebook data challenge current best practices in customer acquisition. (C) 2017 Elsevier B.V. All rights reserved.}},
  author       = {{Meire, Matthijs and Ballings, Michel and Van den Poel, Dirk}},
  issn         = {{0167-9236}},
  journal      = {{DECISION SUPPORT SYSTEMS}},
  keywords     = {{SALES PERFORMANCE,TECHNOLOGY USAGE,RANDOM FORESTS,PROFITABILITY,BUSINESS,BEHAVIOR,IMPACT,MODEL,PREDICTION,ANALYTICS,Social media,Business-to-business,Customer acquisition,Experiment,Predictive analytics}},
  language     = {{eng}},
  pages        = {{26--37}},
  publisher    = {{Elsevier Science Bv}},
  title        = {{The added value of social media data in B2B customer acquisition systems : a real-life experiment}},
  url          = {{http://doi.org/10.1016/j.dss.2017.09.010}},
  volume       = {{104}},
  year         = {{2017}},
}

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