  It is difficult to decide upon the efficacy of an online sale simply from the
discount offered on commodities. Different features have different influence on
the price of a product which must be taken into consideration when determining
the significance of a discount. In this paper we have proposed a machine
learning based heuristic to quantify the \textit{"significance"} of the
discount offered on any commodity. Our proposed technique can quantify the
significance of the discount based on features and the original price, and
hence can guide a buyer during a sale season by predicting the efficacy of the
sale. We have applied this technique on the Flipkart Summer Sale dataset using
Support Vector Machine, which predicts the efficacy of the sale with an
accuracy of 91.11\%. Our result shows that very few mobile phones have a
significant discount during the Flipkart Summer Sale.
