# 2021_191

CRetention:
     Web application to support Customer Churn Management for Grocery Stores
  
 ** Main objective**
 The objective behind the problem statement is to create a machine learning 
 model that predicts churn value for a retail grocery store and compute the 
 overall churn rate for a given period. To assist businesses presenting 
 personalized customer retention plans to reduce the churn rate of
 business deliverables.
 
  ** Main Research questions**
* What features can be used in order to build a predictive web-based solution to
achieve effective customer retention?
* What methods/solutions can be recognized in order to increase the customer 
service?
* Identifying customer purchasing behavior with market basket analysis. 
* Why most products get no profit through the grocery stores?
* What are the types can be profitable from customer service?

**Individual research question(IT18185126)**
mostly product get expired and wastage sometime because those items can’t be
stock long time or those products are not demanded. 

People visiting to the grocery shop weekly and they are going to choose the 
products with look on the quality of the product, price of the product and
brand name of the products but they can not find products on store

In the marketer day to day there will be introducing a new product or new brand
there will be stock in inventory stuck customer are refused to buy those items. 

In unexpected time products get demand, products will not available to buy or
sale. 

The overall country economy will be an issue to get unprofitable products on 
some time periods. 

**Individual research question(IT18112474)**
One-to-one personalized marketing system through social media and email systems
to recognized customers using transactional data analysis results. 

Customized offers promoting according to purchase habits and interest of the
loyal customers. (Combo packs, discount offer, promotions)  

Gathering data on customer behaviors and habits separately to form beneficial 
customer attraction strategies.  

Understanding customer to suggest ideas to improve the store in more convenient
and effective shopping service.

**Individual research question(IT18156898)**
Using an existing dataset to find the current churn rate, already and to be 
churned customer list with reasons to churn. 

Using the obtained data suggest more effective churn prevention strategies. 

Connecting to the market basket analysis to get promoting item set details and 
use forecasting to obtain selling rate according to different price ranges. 

Identifying limitations and future research area.

**Individual research question(IT18183450)**
What are the customer habits? 

What are the customer behaviors? 

Is there any relationship between the items that customer buys? 


** Individual Objectives(IT18185126)**
Analyze the historical patterns of sales of the customers and suggest the 
Stock-In items/item quantities for specific time periods.

 **Individual Objectives(IT18112474)**
 Analyzing individual customer profiles and providing customer personalized
 marketing offers for the customer.
 
** Individual Objectives(IT18156898)**
Analyzing number of visits of customers and predicting customers to be dropped
out so that necessary actions can be taken and pricing suggestions to attract 
more customers.

** Individual Objectives(IT18183450)**
Analyzing customer purchasing behavior and identifying item sets that occur 
frequently to suggest discount item sets to make personalized offers.

