  Sellers and executives who maintain a bidding pipeline of sales engagements
with multiple clients for many opportunities significantly benefit from
data-driven insight into the health of each of their bids. There are many
predictive models that offer likelihood insights and win prediction modeling
for these opportunities. Currently, these win prediction models are in the form
of binary classification and only make a prediction for the likelihood of a win
or loss. The binary formulation is unable to offer any insight as to why a
particular deal might be predicted as a loss. This paper offers a multi-class
classification model to predict win probability, with the three loss classes
offering specific reasons as to why a loss is predicted, including no bid,
customer did not pursue, and lost to competition. These classes offer an
indicator of how that opportunity might be handled given the nature of the
prediction. Besides offering baseline results on the multi-class
classification, this paper also offers results on the model after class
imbalance handling, with the results achieving a high accuracy of 85% and an
average AUC score of 0.94.
