Develop a SQL script to create a database with tables, views, roles, and functions. Form personalized offers to increase average check, frequency of visits, and cross-selling.
This repository contains scripts and functions for creating a database, creating views, managing user roles, and forming personal offers aimed at the growth of the average check, increasing the frequency of visits, and cross-selling.
To create the database and tables described in the Input data, follow the steps below:
Execute the part1.sql script provided in the repository.
This script will create the necessary tables and also include procedures for importing and exporting data for each table from/to CSV and TSV files.
Make sure to upload the required CSV and TSV files from the datasets folder to the repository.
Views Creation
To create the views described in the Output data, follow the steps below:
Execute the part2.sql script provided in the repository.
This script will create the views and include test queries for each view.
User Roles
To set up user roles and their permissions, follow the steps below:
Execute the part3.sql script provided in the repository.
This script will create the roles and assign the following permissions:
Administrator: This role has full permissions to edit and view any information, as well as start and stop the processing.
Visitor: This role only has permission to view information of all tables.
Forming Personal Offers for Average Check Growth
To form personal offers aimed at the growth of the average check, follow the steps below:
Execute the part4.sql script provided in the repository.
This script contains a function that determines offers based on the average check calculation method, first and last dates of the period, number of transactions, coefficient of average check increase, maximum churn index, maximum share of transactions with a discount, and allowable share of margin.
The function will output the customer ID, average check target value, offer group, and maximum discount depth for each offer.
Forming Personal Offers for Increasing Frequency of Visits
To form personal offers aimed at increasing the frequency of visits, follow the steps below:
Execute the part5.sql script provided in the repository.
This script contains a function that determines offers based on the first and last dates of the period, added number of transactions, maximum churn index, maximum share of transactions with a discount, and allowable margin share.
The function will output the customer ID, period start date, period end date, target number of transactions, offer group, and maximum discount depth for each offer.
Forming Personal Offers for Cross-Selling
To form personal offers aimed at cross-selling, follow the steps below:
Execute the part6.sql script provided in the repository.
This script contains a function that determines offers based on the number of groups, maximum churn index, maximum consumption stability index, maximum SKU share, and allowable margin share.
The function will output the customer ID, SKU offers, and maximum discount depth for each offer.
Input Data
Personal information Table
Field
System field name
Format / possible values
Description
Customer ID
Customer_ID
---
---
Name
Customer_Name
Cyrillic, the first letter is capitalized, the rest are upper case, dashes and spaces are allowed
---
Surname
Customer_Surname
Cyrillic, the first letter is capitalized, the rest are upper case, dashes and spaces are allowed
---
Customer E-mail
Customer_Primary_Email
E-mail format
---
Customer phone number
Customer_Primary_Phone
+7 and 10 Arabic numerals
---
Cards Table
Field
System field name
Format / possible values
Description
Card ID
Customer_Card_ID
---
---
Customer ID
Customer_ID
---
One customer can own several cards
Transactions Table
Field
System field name
Format / possible values
Description
Transaction ID
Transaction_ID
---
Unique value
Card ID
Customer_Card_ID
---
---
Transaction sum
Transaction_Summ
Arabic numeral
Transaction sum in rubles(full purchase price excluding discounts)
Transaction date
Transaction_DateTime
dd.mm.yyyy hh:mm:ss
Date and time when the transaction was made
Store
Transaction_Store_ID
Store ID
The store where the transaction was made
Checks Table
Field
System field name
Format / possible values
Description
Transaction ID
Transaction_ID
---
Transaction ID is specified for all products in the check
Product in the check
SKU_ID
---
---
Number of pieces or kilograms
SKU_Amount
Arabic numeral
The quantity of the purchased product
Total amount for which the product was purchased
SKU_Summ
Arabic numeral
The purchase amount of the actual volume of this product in rubles (full price without discounts and bonuses)
The paid price of the product
SKU_Summ_Paid
Arabic numeral
The amount actually paid for the product not including the discount
Discount granted
SKU_Discount
Arabic numeral
The size of the discount granted for the product in rubles
Product grid Table
Field
System field name
Format / possible values
Description
Product ID
SKU_ID
---
---
Product name
SKU_Name
Cyrillic, Arabic numerals, special characters
---
SKU group
Group_ID
---
The ID of the group of related products to which the product belongs (for example, same type of yogurt of the same manufacturer and volume, but different flavors). One identifier is specified for all products in the group
Product purchase price
SKU_Purchase_Price
Arabic numeral
The purchase price of the product for this store
Product retail price
SKU_Retail_Price
Arabic numeral
The sale price of the product excluding discounts for this store
Stores Table
Field
System field name
Format / possible values
Description
Store
Transaction_Store_ID
---
---
Product ID
SKU_ID
---
---
Product purchase price
SKU_Purchase_Price
Arabic numeral
Purchasing price of products for this store
Product retail price
SKU_Retail_Price
Arabic numeral
The sale price of the product excluding discounts for this store
SKU group Table
Field
System field name
Format / possible values
Description
SKU group
Group_ID
---
---
Group name
Group_Name
Cyrillic, Arabic numerals, special characters
---
Date of analysis formation Table
Field
System field name
Format / possible values
Description
Date of analysis
Analysis_Formation
dd.mm.yyyy hh:mm:ss
---
Output data
Customers View
Field
System field name
Format / possible values
Description
Customer ID
Customer_ID
---
Unique value
Value of the average check
Customer_Average_Check
Arabic numeral, decimal
Value of the average check in rubles for the analyzed period
Average check segment
Customer_Average_Check_Segment
High; Middle; Low
Segment description
Transaction frequency value
Customer_Frequency
Arabic numeral, decimal
Value of customer visit frequency in the average number of days between transactions
Transaction frequency segment
Customer_Frequency_Segment
Often; Occasionally; Rarely
Segment description
Number of days since the previous transaction
Customer_Inactive_Period
Arabic numeral, decimal
Number of days passed since the previous transaction date
Churn rate
Customer_Churn_Rate
Arabic numeral, decimal
Value of the customer churn rate
Churn rate segment
Customer_Churn_Segment
High; Middle; Low
Segment description
Segment number
Customer_Segment
Arabic numeral
The number of the segment to which the customer belongs
Main store ID
Customer_Primary_Store
---
---
Purchase history View
Field
System field name
Format / possible values
Description
Customer ID
Customer_ID
---
---
Transaction ID
Transaction_ID
---
---
Transaction date
Transaction_DateTime
dd.mm.yyyyy hh:mm:ss.0000000
The date when the transaction was made
SKU group
Group_ID
---
The ID of the group of related products to which the product belongs (for example, same type of yogurt of the same manufacturer and volume, but different flavors). One identifier is specified for all products in the group
Prime cost
Group_Cost
Arabic numeral, decimal
---
Base retail price
Group_Summ
Arabic numeral, decimal
---
Actual cost paid
Group_Summ_Paid
Arabic numeral, decimal
---
Periods View
Field
System field name
Format / possible values
Description
Customer ID
Customer_ID
---
---
SKU group
Group_ID
---
The ID of the group of related products to which the product belongs (for example, same type of yogurt of the same manufacturer and volume, but different flavors). One identifier is specified for all products in the group
Date of first purchase of the group
First_Group_Purchase_Date
yyyy-mm-dd hh:mm:ss.0000000
---
Date of last purchase of the group
Last_Group_Purchase_Date
yyyy-mm-dd hh:mm:ss.0000000
---
Number of transactions with the group
Group_Purchase
Arabic numeral, decimal
---
Intensity of group purchases
Group_Frequency
Arabic numeral, decimal
---
Minimum group discount
Group_Min_Discount
Arabic numeral, decimal
---
Groups View
Field
System field name
Format / possible values
Description
Customer ID
Customer_ID
---
---
Group ID
Group_ID
---
---
Affinity index
Group_Affinity_Index
Arabic numeral, decimal
Customer affinity index for this group
Churn index
Group_Churn_Rate
Arabic numeral, decimal
Customer churn index for a specific group
Stability index
Group_Stability_Index
Arabic numeral, decimal
Indicator demonstrating the stability of the customer consumption of the group
Actual margin for the group
Group_Margin
Arabic numeral, decimal
Indicator of the actual margin for the group for a particular customer
Share of transactions with a discount
Group_Discount_Share
Arabic numeral, decimal
Share of purchasing transactions of the group by a customer, within which the discount was applied (excluding the loyalty program bonuses)
Minimum size of the discount
Group_Minimum_Discount
Arabic numeral, decimal
Minimum size of the group discount for the customer
Average discount
Group_Average_Discount
Arabic numeral, decimal
Average size of the group discount for the customer
License
This project is licensed under the MIT License. Feel free to use and modify the code according to your needs.
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Develop a SQL script to create a database with tables, views, roles, and functions. Form personalized offers to increase average check, frequency of visits, and cross-selling.