Boost your sales with funnel analysis! A thorough explanation using tools and practical examples [Latest 2024]

Are you struggling with having a lot of traffic to your website, yet not achieving the desired results?

Essential to visualize the actions customers take until they make a purchase or request a service is "funnel analysis." In 2024, marketing strategies based on data are becoming increasingly important.

In this article, we thoroughly explain everything from the basics to practical applications of funnel analysis. We packed practical know-how that can be utilized from tomorrow, including a comparison of 10 recommended tools (free and paid), specific analysis methods using GA4, Excel, and Python, as well as successful case studies from various industries such as e-commerce sites and BtoB SaaS companies. Master funnel analysis that leads to increased sales through this article.

9 Recommended Funnel Analysis Tools! Thorough Comparison from Free to Paid

Funnel analysis tools are offered with a variety of features and price ranges. Many people may be wondering which tool to choose. In this section, we have carefully selected four free tools and five paid tools, and by comparing their features, advantages, and disadvantages, we will support you in choosing the optimal tool.

4 Free Tools: For Those Who Want to Start Analyzing Easily

First, here are 5 recommended free tools for those who want to start funnel analysis without incurring costs. These tools come with basic functionalities and are appealing for their easy implementation. However, please be aware that there may be limitations on features or data capacity.

1. Google Analytics 4 (GA4)

GA4 is a free web analytics tool provided by Google. It allows detailed analysis of website access and user behavior and can be utilized for funnel analysis. By using event tracking features, it visualizes customer behavior within the website, making it possible to identify drop-off points and consider improvement measures.

2. Google Sheets

Google Sheets is a spreadsheet software that anyone can easily use. If you only need simple funnel analysis, spreadsheets will suffice. By importing data from GA4, for example, and creating graphs, you can visually grasp the funnel.

3. Hotjar

Hotjar is a tool that provides a heatmap feature allowing you to visually confirm user behavior. By visualizing the click locations and scrolling behavior of users on the website, it contributes to improving user experience. The free plan has limited features, but it is useful for understanding user behavior in the early stages of funnel analysis.

4. Simple Analytics

Simple Analytics is a web analytics tool that pays attention to privacy. It allows analysis while anonymizing personal data, making it possible to comply with privacy regulations such as GDPR. The free plan has restrictions on the number of website registrations and data retention periods.

5 Paid Tools: For Those Who Want to Achieve Results with Serious Analysis

If you need more advanced analysis or large-scale data processing, paid tools are recommended. Paid tools are characterized by advanced functionalities and customization not available in free tools, along with comprehensive support. Consider cost-effectiveness and choose the appropriate tool.

1. Adobe Analytics

Adobe Analytics is a tool ideally suited for large-scale data analysis. It is equipped with various features, such as advanced segmentation and real-time analysis functions. It is suitable for analyzing corporate-scale websites and applications.

2. Mixpanel

Mixpanel is a tool specialized in user behavior analysis. It can track user behaviors in apps or on websites in detail and analyze drop-off points and customer behavior patterns.

3. Kissmetrics

Kissmetrics is a tool that provides analysis to track customer behavior in detail and improve customer lifetime value (LTV). It is also helpful for customer segmentation and personalization.

4. Amplitude

Amplitude is a tool that can analyze user behavior in mobile apps and websites. By creating user segments and analyzing the actions of each segment, you can consider optimal measures tailored to your target demographic.

5. Cascade

Cascade is an AI-powered platform specialized in advertising analysis and website behavior analysis. It provides tools for optimizing advertising budgets, funnel analysis, and pathway analysis, enabling maximization of advertising effectiveness and data-driven decision-making.

Tool Comparison Table: Check Features, Prices, and Characteristics at a Glance

Here is a comparison table of the 9 tools introduced above, focusing on features, prices, and characteristics. Use this as a reference for selecting the right tool for your needs.

※Prices may vary depending on the plan. Please check each tool's official site.

Practical! Funnel Analysis Methods Using Various Tools

Funnel Analysis with GA4! Thorough Dissection of Customer Behavior Until Goal Achievement

Google Analytics 4 (GA4) is a powerful tool for analyzing website traffic and user behavior. Funnel analysis using GA4 allows you to visualize in detail the process from when customers access the website until they reach their final goal (e.g., purchase, inquiry). It lets you grasp the drop-off rates and conversion rates at each step, aiding in the identification of areas for improvement for your website and optimization of marketing measures.

Setting Up GA4

To conduct funnel analysis with GA4, you first need to set up goals. Goals define the actions you want to achieve on the website (e.g., visit specific pages, submit a specific form). Once you define the goals, you can use the funnel data exploration reports. This feature visualizes the steps users take to achieve the goals. While creating the report, it's important to accurately set the events and page views for each step.

Visualizing and Analyzing the Funnel

The funnel data exploration report in GA4 displays the number of users, conversion rates, drop-off rates, etc. at each step in graphs. This clearly identifies where users are dropping off the most, pinpointing bottlenecks. Furthermore, by utilizing segmentation features, it’s possible to analyze the behavior of specific user groups (e.g., new users, repeat users) individually, allowing you to consider improvements tailored to the target demographic.

Identifying Improvement Points

From the results of the funnel analysis, identify steps with high drop-off rates and analyze their causes. For example, in the case of an e-commerce site, if there are many additions to the cart but few conversions, the design or complexity of the payment page may be the issues. By utilizing GA4's event tracking features, you can analyze customer behavior in detail and consider specific improvement measures, such as improving the UI/UX of pages, revisiting pathways, or strengthening promotions.

Simple Funnel Analysis with Excel Templates! Download and Use Immediately

If you cannot use tools like GA4 or want to conduct simple analysis, you can leverage Excel templates for easy funnel analysis. Various funnel analysis Excel templates are published online. By using these templates, you can create visually understandable funnel charts simply by entering your data.

How to Use Templates

Many templates provide input fields for user numbers and conversion numbers for each step. Once you input the data, the funnel chart will be automatically created. You can adjust the chart’s colors and titles to make it visually clearer as needed.

Interpreting Analysis Results

From the created funnel chart, you can check the number of users, conversion rates, and drop-off rates at each step. Similar to GA4, identify steps with high drop-off rates and analyze their causes. While detailed analysis might be challenging with Excel templates, they are useful for grasping the overall picture and considering improvement directions.

Advanced Analysis

Utilizing Excel's features enables the execution of more detailed analyses. For instance, using pivot tables allows you to analyze data from various perspectives (e.g., time, device, region). Additionally, using functions can also enable automatic calculations of conversion rates and drop-off rates.

Automating Funnel Analysis with Python! Code Examples and Explanation

For more advanced analysis or automation needs, using programming languages like Python for funnel analysis is effective. Python has many libraries convenient for data analysis, allowing efficient processing of large data sets and visualization of analysis results.

Required Libraries

To conduct funnel analysis in Python, libraries like Pandas (for data manipulation), Matplotlib or Seaborn (for data visualization) are helpful. These libraries can be easily installed using the pip command.

Code Explanation

Specific code examples may vary depending on the data used and the analysis methods, but generally, you would load data using Pandas, process it, and create funnel charts using Matplotlib or Seaborn. While code examples are beyond the scope of this article, many tutorials are published online.

Execution Method and Interpreting Results

Executing a Python script will yield analysis results including funnel charts. From these results, you can check the number of users, conversion rates, and drop-off rates at each step, just like with GA4 or Excel templates, and identify points for improvement. By using Python, you can automate the processing of large data sets and complex analyses, achieving efficient funnel analysis.

Deepening Customer Understanding through Funnel Analysis Methods [Case Studies]

Marketing Funnel Analysis: Optimizing Customer Acquisition Processes

Case 1: Funnel Analysis of an E-commerce Site

At an e-commerce site, funnel analysis using Google Analytics was conducted. The analysis of drop-off rates at each step from product viewing to cart addition and purchase completion revealed that the drop-off rate after adding to the cart was very high. Accordingly, various measures were implemented, including changing the design of the cart page, adding payment methods, and executing free shipping campaigns. As a result, the conversion rate after adding to the cart improved by 15%, leading to increased sales.

This case study shows that specific challenges can be identified through funnel analysis, and effective improvement measures can be implemented, contributing to increased sales of the e-commerce site.

Case 2: Funnel Analysis of a BtoB SaaS Company

Funnel analysis in lead nurturing becomes important for BtoB SaaS companies. By analyzing drop-off rates at each step from inquiry to demo request and contract signing, challenges in lead nurturing can be identified. For example, if the conversion rate after a demo request is low, there may be issues with the content of the demo or the follow-up system.

In one BtoB SaaS company, by leveraging marketing automation tools like HubSpot for lead scoring and segmentation, they conducted personalized email marketing, leading to improved conversion rates after demo requests.

Sales Funnel Analysis: Discovering and Improving Bottlenecks to Increase Closing Rates

Case 3: Sales Funnel Analysis of a Real Estate Company

Real estate companies can analyze the sales process from the first contact with customers to contract signing to consider measures that enhance closing rates. For instance, if the drop-off rate from property viewing to contract is high, there may be room for improvement in property explanations or proposals. Additionally, lack of communication with customers could also lead to a drop in closing rates.

By effectively analyzing the sales funnel, you can accurately grasp customers' needs and propose optimal solutions, aiming to improve closing rates. By utilizing CRM systems and appropriately managing customer touchpoints, more effective sales activities can be conducted.

Case 4: Sales Funnel Analysis of a Recruitment Agency

Recruitment agencies can analyze the process from the first interview with candidates to offer acceptance to consider improvements that lead to enhanced closing rates. For example, if there are delays in contact after interviews, or if proposals do not sufficiently consider candidates' desired conditions, it may lead to a decline in acceptance rates.

Through regular funnel analysis, identifying and improving bottlenecks in the sales process can contribute to enhancing the recruitment agency's closing rates. It can also enhance candidate satisfaction, thereby improving the company's reliability.

Common Questions about Funnel Analysis

What is Funnel Analysis?

Funnel analysis is a method of visualizing the behavioral processes of customers until they reach their ultimate goals (conversions) such as purchasing products or utilizing services, in the shape of a funnel. By sequentially tracking customer behavior, it helps identify where many people are dropping off (bottlenecks), thereby aiming to improve conversion rates through implementing improvement measures. For example, on a website, you analyze drop-off rates at each stage from traffic to inquiries, applications, and purchases.

What Businesses Is It Effective For?

Funnel analysis is effective for various businesses, whether BtoB or BtoC. Particularly for companies utilizing websites, online services, and e-commerce sites, it's a very effective tool for analyzing customer online behavior and translating that into improvements. It is also useful for enhancing conversion rates among potential customers in sales activities. For instance, by analyzing each step from acquiring potential customers to negotiations and contracts, challenges in the sales process can be identified and improved. Moreover, it can be utilized to measure the effectiveness of marketing initiatives. For example, by analyzing the effectiveness of advertising campaigns, you can clarify which channels are leading to conversions, thus devising more effective marketing strategies.

Which Tools Are Recommended?

There are a wide range of tools available for funnel analysis, from free tools to those with advanced features. This article includes a comparison table of four free tools and five paid tools, allowing for examination of their functions, prices, and characteristics. The optimal tool varies based on the scale of the business, the analysis purpose, and budget. Free tools are recommended for those wanting to start analyzing easily, while paid tools are for those seeking serious analysis with results. Our developed tool Cascade features a UI that is easy for anyone to use, and it's a service that can be sufficiently utilized in terms of functionality.

How Should Analysis Results Be Utilized?

The results of funnel analysis are an essential source of information that should be leveraged for business improvement. Improvements must be based on the identified bottlenecks from the analysis results. For example, on a website, changes to the design of high drop-off rate pages, content improvements, or revising pathways could be considered. In sales activities, improvements might include refining communication methods with potential customers, revising proposal content, or streamlining sales processes. The key is to hypothesize based on data, conduct verifications like A/B testing, and continuously improve. Funnel analysis serves not just as mere data analysis but as a critical step toward deepening customer understanding and facilitating business growth.

Conclusion: Making Data-Driven Decisions with Funnel Analysis

This article comprehensively explained funnel analysis, a powerful method leading to increased sales, covering everything from tool selection to practical analysis methods and specific case studies. By presenting various approaches, including free tools, paid tools, GA4, Excel, and Python analysis methods, we aimed to help readers choose the most suitable analysis method according to their business scale and skill level.

Funnel analysis enables the visualization of customer behavior and clarification of issues, allowing for effective implementation of marketing measures. By utilizing the tools and analysis techniques introduced in this article, you can discover and improve bottlenecks in your business, leading to increased conversion rates and ultimately higher sales. In particular, using GA4 for analysis provides precise improvements based on the latest data.

Data-driven decision-making is essential in modern business. Funnel analysis becomes a powerful weapon supporting that decision-making. Utilize the knowledge gained from this article to achieve strategic business development based on data analysis.

For more advanced funnel analysis and the establishment and execution of efficient marketing strategies based on data, consider pre-registering for Cascade. Cascade is a platform that integrates advertising analysis and website behavior analysis, providing AI-powered advertising cost optimization, funnel analysis, and automated reporting.