Neo4j funnel analysis

This Neo4j based project does a funnel analysis for a E-Commerce website. It is designed to serve as a template for further development projects. Feel encouraged to fork and update this repo!

Data Model

Nodes with properties

• User { id: string, timestamp: timestamp, device: string, gender: string }
• Entry { page: string}

Relationships with properties

• (:User)-[:VISITED {count: string}]->(:Page)

Users and Pages

Load some fake data

If you're running the app locally, you might want to tweak without having a robust community of users. In the /datasets directory, note that there are files named users.csv, search.csv, home.csv, checkout.csv, payment_confirm.csv. These files contains some pseudo-randomly generated values.

Move users.csv into the import directory of your database either by dragging and dropping or using

Set your NEO4J_HOME variable:

export NEO4J_HOME=/path/to/neo4j-community

Copy files :

cp datasets/users.csv $NEO4J_HOME/import/users.csv

Copy every file contained in the datasets directory by the above command

Assuming your database is running, paste the following queries into the Neo4j browser:

// Assert that the USER nodes are unique by it's ID
CREATE CONSTRAINT ON (u:User) ASSERT u.user_id IS UNIQUE;

// Assert that the ENTRY nodes are unique by it's page name
CREATE CONSTRAINT ON (e:Entry) ASSERT e.page IS UNIQUE;

USING PERIODIC COMMIT
LOAD CSV WITH HEADERS 
FROM 'file:///your/location/user.csv' AS line
WITH DISTINCT line , datetime(line.`date`).epochMillis as date

CREATE (u:User { id: toInteger(line.`user_id`) })
SET u.date = toInteger(date),
    u.device = line.`device`,
    u.gender = line.`gender`

// Create page node with diffrent page properties 
CREATE (:Entry { page : 'search_page'})
CREATE (:Entry { page : 'checkout_page'})
CREATE (:Entry { page : 'home_page'})
CREATE (:Entry { page : 'payment_confirmation_page'})

// Load search page entry and create relationships 
USING PERIODIC COMMIT
LOAD CSV WITH HEADERS 
FROM 'file:///search.csv' AS line
WITH line

MATCH (u:User { id : toInteger(line.`user_id`)}), (e:Entry { page : 'search_page'})
MERGE (u)-[r:VISITED]->(e)
    ON MATCH SET r.visited_count = r.visited_count + 1
    ON CREATE SET r.visited_count = 1

// Create user and checkout page relationship
USING PERIODIC COMMIT
LOAD CSV WITH HEADERS 
FROM 'file:///checkout.csv' AS line
WITH line

MATCH (u:User { id : toInteger(line.`user_id`)}), (e:Entry { page : 'checkout_page'})
MERGE (u)-[r:VISITED]->(e)
    ON MATCH SET r.visited_count = r.visited_count + 1
    ON CREATE SET r.visited_count = 1

// Create user and home page relationship
USING PERIODIC COMMIT
LOAD CSV WITH HEADERS 
FROM 'file:///home.csv' AS line
WITH DISTINCT line

MATCH (u:User { id : toInteger(line.`user_id`)}), (e:Entry { page : 'home_page'})
MERGE (u)-[r:VISITED]->(e)
    ON MATCH SET r.visited_count = r.visited_count + 1
    ON CREATE SET r.visited_count = 1

// Create user and payment confirmation page relationship
USING PERIODIC COMMIT
LOAD CSV WITH HEADERS 
FROM 'file:///payment_confirm.csv' AS line
WITH line

MATCH (u:User { id : toInteger(line.`user_id`)}), (e:Entry { page : 'payment_confirmation_page'})
MERGE (u)-[r:VISITED]->(e)
    ON MATCH SET r.visited_count = r.visited_count + 1
    ON CREATE SET r.visited_count = 1

Finally the graph looks like this: