Customer Purchase Intention Prediction Using Text Analytical Models

Identifying the potential users matters a lot for the growth of any company. This can be estimated well in advance based on several factors like the user’s opinion regarding a product before its sale is announced. Considering this, an application will be developed which will be easy to use, accurate intention prediction Website.The website is built using HTML, CSS, Javascript and Django. A text analytical model is built using an ensemble model, made by collecting tweets from users. The model will find out potential buyers who have tweeted about the product but are yet to purchase. The model would estimate the most likelihood of a customer’s purchase. Various Parameters like Accuracy, Precision, Recall and F1 score are calculated for getting the best result. Presently there are not any notable applications available that use multiple algorithms and are used for purchase intention prediction with this sophisticated architecture, which makes the application unique.