What is Funnel Analysis
Funnel analysis helps product managers and marketing teams understand the user flow across a website. The goal of funnel analysis is to observe the steps a user takes to get to a desired outcome. For example how many steps does it take for an end-user to complete a purchase, a registration, or a lead form.
Each of the steps required to complete an outcome are a part of the buying journey. Conducting funnel analysis helps visualize how a buyer progresses through the funnel, and if there are opportunities to increase conversions, decrease drop-offs, and improve the customer experience along the way.
Benefits of Funnel Analysis
To get to the ultimate goal (a conversion), your end-users will go through a series of micro conversions. For example, a customer of an eCommerce business might go through the following buying journey:
- Visiting a site
- Adding a product to the shopping cart
- Clicking to check out
- Completing the purchase
- Visiting a thank you page
Visualizing the funnel helps you recognize the points of the customers' journey where they usually drop off and note which part presents the highest opportunity for improvements.
For instance, if we use this funnel as an example:
We can see that 50% of users drop off between the homepage and the registration page, indicating there may be an issue with how a user finds the registration page, or the overall UX of the registration page.
By making product experience improvements, not only are you improving the customer experience, but you’re earning the opportunity for higher conversions as well.
Analyzing the funnel
When analyzing the funnel, it’s important to:
- Set goals and monitor KPIs for your business: For example, is there a total number of conversions you’re aiming to reach? Are you looking to reduce churn, and by how much? And by making product improvements, are you moving closer to your goal?
- Visualize the funnel: When comparing vast amounts of data, a bird’s eye view of the funnel can help you quickly understand where your problem areas are.
- Create subsets to understand different types of users: Seeing how different users navigate your website can help inform UX changes. For example, do first time visitors behave differently than returning visitors? How can you improve the customer journey so both subsets act similarly?
- Pick the right tool: Finding a solution with robust analytics and visualization features will act as a one-stop shop for data collection, storage, analysis, visualization, and allow you to quickly make data-informed decisions.
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