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Organization Name: Insta-Buy

Insta-Buy is an E-Commerce Multinational American company. It was founded in 2010 and is based in Atlanta, Georgia. It mainly operates with grocery delivery and pick up and it offers services through web application and mobile application to various states in United States. It is one of the major online marketplaces for grocery delivery. The company is valued at $1 billion worth and has partnership with over 150 retailers. It is known for its fresh produce and timely delivery and pickup.

Predictive Analysis at Insta-Buy:

The predictive analytics is termed as what is likely to happen in the future. The predictive analytics is based on statistical and data mining technique. The aim of this technique is to predict the future of the project such as what would be the customer reaction on project, financial need, etc. In developing predictive analytical application, a number of techniques are used such as classification algorithms. The classification techniques are logistic regression, decision tree models and neural network. Clustering algorithms are used to segment customers in different groups which helps to target specific promotions to them. To estimate the relationship between different purchasing behavior, association mining technique is used (Mehra, 2014). As an example, for any product on Amazon.com results in the retailer also suggesting similar products that a customer might be interested in. Predictive analytics can be used in E-commerce to solve the following problems

1. Improve customer engagement and increase revenue

1. Launch promotions that target specific customer group

1. Optimizing prices to generate maximum profits

1. Keep proper inventory and reduce over stalking

1. Minimizing fraud happenings and protecting privacy

1. Provide batter customer service at low cost

1. Analyze data and make decision in real time

TOPICS:

Student: Ahmed

Topic: Bayesian Networks (Predicting Sales In E-commerce Using Bayesian Network Model)

Student: Meet

Topic: Predictive Analysis

Student: Peter

Topic: Privacy and Confidentiality in an e-Commerce World: Data Mining, Data Warehousing, Matching and Disclosure Limitation

Student: Nayeem

Topic: Ensemble Modeling

Student: Shek

Topic: L.Jack & Y.D. Tsai, Using Text Mining of Amazon Reviews to Explore User-Defined Product Highlights and Issues.

Student: Suma

Topic: Deep Neural Networks

REFERENCES:

Olufunke Rebecca Vincent, A. S. (2017). A Cognitive Buying Decision-Making Process in B2B E-Commerce Using Analytic-MLP. Elsevier.

https://www.researchgate.net/publication/319278239_A_Cognitive_Buying_Decision-Making_Process_in_B2B_E-Commerce_Using_Analytic-MLP

Wan, C. C. (2017). Forcasting E-commerce Key Performance Indicators

https://beta.vu.nl/nl/Images/stageverslag-wan_tcm235-867619.pdf

Fienberg, S. (2006). Privacy and Confidentiality in an e-Commerce World: Data Mining, Data Warehousing, Matching and Disclosure Limitation. Statistical Science, 21(2), 143-154. Retrieved June 13, 2020, from www.jstor.org/stable/27645745

https://www.researchgate.net/profile/Yi_Fang_Tsai2/publication/284188657_Using_Text_Mining_of_Amazon_Reviews_to_Explore_User-Defined_Product_Highlights_and_Issues/links/564f69eb08aefe619b11de8b/Using-Text-Mining-of-Amazon-Reviews-to-Explore-User-Defined-Product-Highlights-and-Issues.pdf