As a consumer, our loyalty towards a brand, products or services is determined by the quality and customer services that they provide. Having said that deals and discounts also plays an important and an encouraging role in maintaining customer loyalty. We as consumers tend to get attracted towards a product or business entity that offers better deals and discounts as compared to their competitors, this is human nature. This does not mean that these business entities are going to make a loss, but instead, they are much more benefited from these strategies and eventually make more sales and make a profit. For Example, we are all inclined towards making purchased on Amazon and BestBuy which are e-commerce websites over retail stores. All of these purchases are done without even looking and inspecting the product before making the purchase.
Although some might say that the reason behind this to deal with the convenience of purchase, but in reality it the price and discounts that these e-commerce websites offer that actually drive the huge customer traffic and increase the sales figures for them. An Empirical Analysis of the Impact of Promotional Discounts on Store PerformanceĀ shows that these sales numbers are even more amplified when these websites announce their seasonal sales, which drive the customers crazy to buy even more products and sometimes they end up buying more than what they need.Ā For instance, an industry survey estimated that e-commerce sales in India soared by 350 percent during a seasonal sale during the month of October as the occasion of an Indian festival called Diwali.
At Neighborhood we employ a similar strategy by providing allowing the business entities that are associated with us to use our platform to market their deals and discounts, which helps them in increasing their business sales and on the other hand their customers who are neighborhood members are also happy and delighted to use our services to get lower priced products or special deals. These deals and discounts would be sent as push notifications to the userās mobile application notifying them of the offers that are posted by their favorite business entities. To make these interactions more pleasant and enthusiastic, we employ machine learning techniques to identify and understand the taste and trends of each and every individual and provide customized notification that is tailored made to each and every one. These sorts of techniques provide better efficiency and a personalized user experience, which would not only encourage the user to revisit their favorite places but would also expand their horizon by suggesting some new similar places and interests based on the homophilic study of other users which are worth exploring.
Having said the positives of machine learning to track and monitor the users to provide them with a better-personalized user experience might sound interesting and fascinating, these sorts of technical implementations might raise some red flags with respect to privacy and data tracking. For which we suggest a user setting option which ensures that each and every user has control over their personal data and could deny these added feature tracking based on their will and wish.