Funnel Analysis involves using a series of events that lead towards a defined goal. This goal could be anything –
- Finding answer to a specific problem
- User engagement
- Number of conversions
- Number of visitors, etc.
This term originated from the name of a tool called the Funnel, which is used in the kitchen or in mechanics, which gets narrower along its length, allowing less volume to pass through it. A funnel in analytics represent the same behavior where –
- A funnel is identified
- Set of users in the beginning (or top of the funnel) are identified
- These users are allowed to pass through a funnel
- Some users drop on the way
- And, some make their way out of the funnel
Funnel Analytics is the study of one or more of such events.
Let us consider a common e-commerce scenario and understand how this process works and what all is needed to be considered before starting the actual process.
Let us assume that we need to perform funnel analysis for the event where we want to measure how many users who actually visited the website bought something or not.
To begin with, we should be clear about our goal. Our goal is to see how many users who visit the website, buy something or not.
Who to include in the Funnel Analysis? Or rather, which users to include?
In an ideal scenario, all users who either visit the website, either buy or don’t buy something. But, this is too ideal. In the real world, it is difficult to identify users who actually came to buy something and din’t buy for some reason or users who actually bought something while they were here for something else. For example, it could be possible that the user is on the website to track his order, or change his account settings, or to return a product, or maybe for refund queries. We don’t want to include such users. Hence, it is very important to be able to identify users who are here to buy something.
Which funnel to include the user on?
There could be multiple funnels on a website. For the reasons mentioned above, a user who is here to buy something should be included on the funnel to measure user conversions. While, a user who is here to report an issue, should be on the funnel to measure user issues/concerns. It is extremely important that the user intentions are distinguished clearly and the users are put through the right funnel to get accurate results.
What can a funnel analysis be used for?
The aim of a funnel analysis is to draw actionable insights from the study. It can be used to –
- determine conversion
- user fallout rates
- identify users who actually make it till the end
- or who fail to make it till the end
This kind of analysis helps to further improve the marketing strategies of the company. By understanding the user response and reactions, it can be identified if the existing marketing campaign was effective or not. Changes can be made to make the campaign more effective so that it reaches the right people and the user conversion rate is high. Funnel Analysis also helps to determining which users dropped out and understanding why that happened. This way the marketers can understand the reasons behind the drop-offs and work towards reducing the drop off rates and in turn to increase overall conversion.