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:
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.
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.