Summary
Service oriented platforms frequently utilize coupons to entice customers and increase the likeness of a purchase. According to Juniper Research, mobile coupon users will pass 1 billion by the year of 2019, driven by increased consumer engagement as retailers reach out through more mobile channels. However, rather than sending promotions collectively, machine learning can assist in tailoring coupon suggestions based on customer wants and profiles. To accomplish this goal, we will use classification to build and find the best model that most accurately predicts the set of factors which will lead to a consumer using a coupon for a low-cost restaurant (less than $20 per person).
Big Data has allowed the growth of leveraging machine learning techniques and data science to enhance marketing across all industries. It is no secret that coupons bring streams of business to a company, but by targeting individuals who are more likely to accept the coupons based on their actions or preferences, businesses can save time and money by pushing out coupons straight to consumers with preferences which match the company’s product. This data is crucial to a company’s success because it helps it identify their target audience and allows them to gain insight into the purchasing behavior of their customers.
Big Data has allowed the growth of leveraging machine learning techniques and data science to enhance marketing across all industries. It is no secret that coupons bring streams of business to a company, but by targeting individuals who are more likely to accept the coupons based on their actions or preferences, businesses can save time and money by pushing out coupons straight to consumers with preferences which match the company’s product. This data is crucial to a company’s success because it helps it identify their target audience and allows them to gain insight into the purchasing behavior of their customers.
