User Funnel Analysis using Python

User Funnel Analysis is a way to analyze the flow of users on a website or an application. It helps analyze the conversion rate on each page visited by the users. So, if you want to know how to analyze the user funnel, this article is for you. In this article, I will take you through the task of User Funnel Analysis using Python.

User Funnel Analysis

User funnel analysis is a way to understand how users interact with a website or an application. It helps businesses analyze the conversion rate from the page the user visited the website or the app to the page user left the website or the app.

By tracking user flow as they move through the various stages of the funnel, companies can identify areas where users are giving up or getting stuck, then take action to improve user experience and increase conversions.

For example, if a lot of users leave the website after adding items to the cart, the company may look for ways to make the checkout process faster and easier.

User Funnel Analysis using Python

Now let’s see how to analyze the user funnel by using the Python programming language. I’ll start this task by importing the necessary Python libraries and the dataset (you can download the dataset from here):

import pandas as pd
data = pd.read_csv("user_data.csv")
print(data.head())

  user_id     stage  conversion
0  user_0  homepage        True
1  user_1  homepage        True
2  user_2  homepage        True
3  user_3  homepage        True
4  user_4  homepage        True

The stage column contains the stages of the flow of the users. For example, when you visit Amazon, the first stage will be the homepage of Amazon, and the last page will be the page where you proceed with the payment. So, let’s have a look at the stages in this dataset:

print(data["stage"].value_counts())

homepage        10000
product_page     5000
cart             1500
checkout          450
purchase          225
Name: stage, dtype: int64

So the user funnel stages of the website are homepage >> product_page >> cart >> checkout >> purchase. Now below is how we can analyze user funnels:

import plotly.graph_objects as go
import plotly.io as pio
pio.templates.default = "plotly_white"

#define the funnel stages
funnel_stages = ['homepage', 'product_page', 'cart', 'checkout', 'purchase']

#calculate the number of users and conversions for each stage
num_users = []
num_conversions = []

for stage in funnel_stages:
    stage_users = data[data['stage'] == stage]
    num_users.append(len(stage_users))
    num_conversions.append(stage_users['conversion'].sum())

#create a funnel chart
fig = go.Figure(go.Funnel(
    y=funnel_stages,
    x=num_users,
    textposition='inside',
    textinfo='value',
    name='Users'
))

fig.add_trace(go.Funnel(
    y=funnel_stages,
    x=num_conversions,
    textposition='inside',
    textinfo='value',
    name='Conversions'
))

fig.update_layout(
    title='Funnel Analysis',
    funnelmode='stack'
)

fig.show()

So this is how you can analyze user funnels using the Python programming language.

Summary

Funnel analysis is a way to understand how users interact with a website or app. It helps businesses analyze the conversion rate from the page the user visited the website or the app to the page user left the website or the app. I hope you liked this article on User Funnel Analysis using Python. Feel free to ask valuable questions in the comments section below.