Scipediacontent: Scipediacontent moved page Draft Content 238473339 to Chu et al 2015a

2021-02-02T04:02:31Z

Scipediacontent moved page Draft Content 238473339 to Chu et al 2015a

Scipediacontent: Created page with " == Abstract == Sales pipeline analysis is fundamental to proactive management of an enterprize's sales pipeline and critical for business success. In particular, win propens..."

2021-02-02T04:02:22Z

Created page with " == Abstract == Sales pipeline analysis is fundamental to proactive management of an enterprize's sales pipeline and critical for business success. In particular, win propens..."

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== Abstract ==

Sales pipeline analysis is fundamental to proactive management of an enterprize's sales pipeline and critical for business success. In particular, win propensity prediction, which involves quantitatively estimating the likelihood that on-going sales opportunities will be won within a specified time window, is a fundamental building block for sales management and lays the foundation for many applications such as resource optimization and sales gap analysis. With the proliferation of big data, the use of data-driven predictive models as a means to drive better sales performance is increasingly widespread, both in business-to-client (B2C) and business-to-business (B2B) markets. However, the relatively small number of B2B transactions (compared with the volume of B2C transactions), noisy data, and the fast-changing market environment pose challenges to effective predictive modeling. This paper proposes a machine learning-based unified framework for sales opportunity win propensity prediction, aimed at addressing these challenges. We demonstrate the efficacy of our proposed system using data from a top-500 enterprize in the business-to-business market.

Comment: accepted by IM2015 as short paper

== Original document ==

The different versions of the original document can be found in:

* [http://arxiv.org/abs/1502.06229 http://arxiv.org/abs/1502.06229]

* [http://arxiv.org/pdf/1502.06229 http://arxiv.org/pdf/1502.06229]

* [http://xplorestaging.ieee.org/ielx7/7121095/7140257/07140393.pdf?arnumber=7140393 http://xplorestaging.ieee.org/ielx7/7121095/7140257/07140393.pdf?arnumber=7140393],
: [http://dx.doi.org/10.1109/inm.2015.7140393 http://dx.doi.org/10.1109/inm.2015.7140393]

* [https://arxiv.org/pdf/1502.06229 https://arxiv.org/pdf/1502.06229],
: [https://dblp.uni-trier.de/db/journals/corr/corr1502.html#YanGSHC15 https://dblp.uni-trier.de/db/journals/corr/corr1502.html#YanGSHC15],
: [https://ieeexplore.ieee.org/document/7140393 https://ieeexplore.ieee.org/document/7140393],
: [http://ui.adsabs.harvard.edu/abs/2015arXiv150206229Y/abstract http://ui.adsabs.harvard.edu/abs/2015arXiv150206229Y/abstract],
: [https://arxiv.org/abs/1502.06229 https://arxiv.org/abs/1502.06229],
: [http://ieeexplore.ieee.org/document/7140393 http://ieeexplore.ieee.org/document/7140393],
: [https://doi.org/10.1109/INM.2015.7140393 https://doi.org/10.1109/INM.2015.7140393],
: [https://academic.microsoft.com/#/detail/1916889544 https://academic.microsoft.com/#/detail/1916889544]

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Scipediacontent: Scipediacontent moved page Draft Content 238473339 to Chu et al 2015a

Scipediacontent: Created page with " == Abstract == Sales pipeline analysis is fundamental to proactive management of an enterprize's sales pipeline and critical for business success. In particular, win propens..."