From c60684efb73d5de5994326612766e0b42275d625 Mon Sep 17 00:00:00 2001 From: Nadiia Date: Mon, 12 Nov 2018 21:55:47 +0100 Subject: [PATCH] added draft for a project background --- Project Proposal.Rmd | 27 +++++++++++++++++++++++---- 1 file changed, 23 insertions(+), 4 deletions(-) diff --git a/Project Proposal.Rmd b/Project Proposal.Rmd index 4edaede..f3b6133 100644 --- a/Project Proposal.Rmd +++ b/Project Proposal.Rmd @@ -17,7 +17,7 @@ __Project title:__ "Customer Behavioural Analytics in the __Names of team members:__
-1. Nadiia Honcharenko (220681)
+1. Nadiia Honcharenko (220681, nadiia.honcharenko@st.ovgu.de)
2. Rutuja Shivraj Pawar (220051, rutuja.pawar@ovgu.de)
3. Shivani Jadhav ()
4. Sumit Kundu () @@ -27,9 +27,28 @@ __Under the Guidance of:__ M.Sc. Uli Niemann __Date:__ ```r format(Sys.Date(), "%B %e, %Y")``` -__Background and motivation:__ - -__Project objectives:__ +__Background and motivation:__ +

Consumer behavior is the series of behaviors or patterns that consumers follow before making a purchase. +Understanding, analyzing and keeping track of customer decisions +helps to increase an annual revenue of companies and satisfy the needs of clients.

+

In this project we are trying to research a customer behaviour during shopping, +how consumers make buying decisions and what influences those decisions. +This study shows that products have a "range" effect: +for some products, customers travel long distances, while +for other products they settle down with the closest shop. +We want to check the existence of dependencies between product prices, +their uniqueness and location of a store, then compare and explain them.

+ + +__Project objectives:__ +
    +
  • Find and investigate the dependencies between product prices, +their uniqueness and distance to a shop
    • +
  • Show when customers overcome long distances to stores
    • +
  • Predict a customer behaviour to +improve marketing strategy of the shop
    • +
+ __Name of the dataset to be used:__ Supermarket aggr.Customer^[https://bigml.com/user/czuriaga/gallery/dataset/5559c2c6200d5a6570000084]
The dataset to be used is the retail market data of one of the largest Italian retail distribution company called _Coop_ for a single Italian city [@pennacchioli2013explaining].