Understanding Marketing Funnel Analysis Simplified

on Marketing Analytics • March 16th, 2021 • Write for Hevo

Funnel Analysis - Featured Image

The reliance of businesses on Digital Marketing techniques/strategies to market their products or services has grown exponentially over the past few years. This is due to the fact that most Digital Marketing techniques can help businesses reach a wider audience and also track various metrics easily that can help them analyze the performance of their Marketing efforts. This analysis can help businesses and marketing teams make data-driven decisions and plan future strategies accordingly. 

One of the most well-known techniques that can help businesses understand a user’s journey on their website is Funnel Analysis. This article will help you understand what Funnel Analysis is, why it’s important, and how you can perform this analysis to understand the various stages your visitors go through until they become customers.

Table of Contents

Introduction to Marketing Funnel Analysis

A Marketing Funnel can be seen as a powerful analytics technique that can help businesses understand the customer journey all the way from the first time they visit the website to the last stage until they’re ready to make the purchase. Marketing Funnel Analysis can be used to understand the steps required to reach a particular outcome on a website and how the number of users varies as they go through these steps. 

This is referred to as a Funnel because a visualization displaying the number of users as they go through different stages until they’re ready to make a purchase is in the shape of a Funnel.

For example, suppose you run an E-Commerce website. The end goal for your business will be to sell products through your platform. Now for any sale on an E-Commerce website, the user will go through the following steps:

  • Visit Website
  • Add Product to Cart
  • Check-Out
  • Complete Purchase

These steps are usually referred to as Goals or Micro-Conversions.

Now, it is a fair assumption that not everyone visiting your website will add products to their carts. Similarly, not everyone adding products to their cart will check-out their products and make a payment. Hence, it can be observed that the number of people making it through each goal is decreasing. Suppose there are approximately 1000 people that visit your website in a given time period, 500 people add products to their carts, 300 people click on check-out and 200 finally make a purchase. A typical funnel chart for this scenario will be as follows:

Funnel Analysis - E-Commerce Funnel Analysis
Image Source: https://chartio.com/learn/product-analytics/what-is-a-funnel-analysis/

A quick Funnel Analysis on the above visualization shows that only 50% of the visitors add products to their carts. Considering that the drop in the number of users in these stages is so high, it means that these stages have the highest room for improvement. Further Funnel Analysis can be performed to determine the reason for this high dropout rate.

Now in the E-Commerce example, it can be observed that there might be some more steps that are performed after the users visit the website and before they add products to their carts. This could include searching for products, clicking on search results, etc. The Funnel chart for the additional steps will be as follows:

Funnel Analysis - E-Commerce Funnel Analysis Additional Steps
Image Source: https://chartio.com/learn/product-analytics/what-is-a-funnel-analysis/

A quick Funnel Analysis of the above visualization shows that 30% of the website visitors don’t even make a search. This could indicate a problem with the user experience on the website. Hence, changes can be made accordingly to improve the user experience so that more users make it to the next steps. For Funnel Analysis to be of any benefit, all key steps should be included in the Funnel Chart visualization.

The Funnel can be further divided into 2 different sets to signify the performance of first-time users and returning users. This visualization for the 2 different groups is as follows:

Funnel Analysis - Funnel Analysis for User Segments
Image Source: https://chartio.com/learn/product-analytics/what-is-a-funnel-analysis/

A simple Funnel Analysis of the above visualization indicates that there might be some issue with the user sign-up process since 60% of first-time visitors do not execute a search. Similarly, for returning users, it can be observed that the highest drop-off is after the search has been executed and before any of the results are viewed. This could indicate an issue with the quality of the product, pricing, or the user experience of the website. These funnels can be analyzed further by examining more steps to understand what improvements can be made to your website and products.

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Benefits of Performing Funnel Analysis

The benefits of performing Funnel Analysis is as follows:

1) Find Pages with High Dropout Rates

Funnel Analysis can help you visualize the Dropout Rates for each page and the final Conversion Rate.

Funnel Analysis - Dropout Rates
Image Source: https://www.hotjar.com/blog/funnel-analysis/#3-benefits-of-using-funnel-analysis-on-your-website

Having an understanding of where your visitors are dropping out can help you plan your future optimization goals accordingly.

2) Determine Source of High-Quality Visitors

Advanced Analytics tools such as Google Analytics will allow you to gain deeper insights by performing advanced Funnel Analysis. This analysis can be used to determine the source of high-quality traffic coming to your website.

Funnel Analysis - Visitor Source
Image Source: https://www.hotjar.com/blog/funnel-analysis/#3-benefits-of-using-funnel-analysis-on-your-website

This information can be used to plan campaigns to increase the volume of traffic from these high-quality sources further.

3) Easy Communication with Team Members

Funnel Analysis is a simple to understand analytics technique that can be used to communicate observations to the team members and all stakeholders involved allowing them to make data-driven decisions quickly.

Steps to Perform Funnel Analysis

The various steps to build and perform your own Funnel Analysis is as follows:

Step 1: Define Metrics

Funnel Analysis - KPI Metrics
Image Source: https://www.klipfolio.com/blog/kpi-metric-measure

For any useful analysis to be performed, the metrics that will be tracked have to be defined first. These metrics can then be tracked which will result in the collection of relevant data for analysis. Since the entire analysis will be based on these metrics, they have to be defined very carefully.

For example, for E-Commerce websites, the metrics should include the number of visitors, sign-ups, number of products sold, transaction data, etc., for Social Media websites, it would be the number of daily active users, sign-ups, etc.

Step 2: Identify Key Touchpoints

The idea behind this step is to identify the key touchpoints that lead to conversion. To identify the touchpoints, you need to understand what goals users have in mind when they visit your website and how they can achieve those goals. Another thing that has to be considered is that there are multiple paths that different users might take before conversion. So all touchpoints have to be taken into consideration in that case. 

For example, on an E-Commerce website, a user might browse the new products page first, and then make a search query to look for something specific and make a purchase. So in this case, the user didn’t search for the product directly. To identify the right touchpoints, all possible paths that lead to conversion should be identified.

Funnel Analysis - Customer Journey Mapping
Image Source: https://www.revechat.com/blog/customer-touchpoints/

Step 3: Perform In-depth Analysis by Segmenting Users

Funnel Analysis - Segment Funnel Analysis
Image Source: https://analyticsdemystified.com/adobe-analytics/creating-conversion-funnels-via-segmentation/

Various segments can be made based on factors such as geographic location, gender, age-group, time period, etc., and further Funnel Analysis can be performed on these groups to get deeper insights, allowing you to plan future strategies accordingly.

For example, there might be situations in which more users from the USA might convert faster than users in India. The reason for that has to be investigated to ensure that the conversion in the USA continues to grow and modifications can be made to improve the Conversion Rate in India. 

Common Funnel Analysis Assumptions

Some of the most common Funnel Analysis assumptions that might lead to poor decision making are as follows:

  • High Dropout Rates Mean Issues with User Experience: Although high Dropout Rates on a particular page might be an indication of issues with user experience, it is not the only possible issue. For example, the first thing that you have to understand is whether the traffic that is dropping out was even relevant to your webpage or not. The best user experience could lead to a high Dropout Rate if the traffic coming to your page wasn’t interested in your product/service to begin with. Efforts have to be made to ensure that your website is marketed to the right audience.
  • Funnels End at Conversion: The key to the growth for any business along with the Conversion Rate is its Customer Retention Rate. The business will not experience much growth if it is not able to retain customers. Hence, efforts have to be made to ensure a high Conversion and Retention Rate.
  • All Users Follow the Same Path: Different users might take different paths until they convert to leads. Each path has to be analyzed and optimized differently to ensure high relevant traffic from all possible paths.

Conclusion

This article provided you with an in-depth understanding of what Marketing Funnel Analysis is, why it’s important along with a guide on how you can identify metrics and touchpoints for performing Funnel Analysis for your website.

For a comprehensive guide on related techniques that can be utilized for analyzing your data, click on the jump links for Cohort Analysis and Customer Churn Analysis.

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Most businesses now use multiple platforms to sell their products and services. In order to perform a proper and in-depth Funnel Analysis, data from all these platforms have to be integrated and stored in a centralized location. Making an in-house solution for this would require a high amount of resources. Businesses can instead use existing data integration platforms like Hevo Data.

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