Funnel analysis: The ultimate guide to unlocking insights and maximizing conversions
What is funnel analysis?
Funnel analysis definition
Funnel analysis is a method used in marketing and analytics to understand and optimize the steps that users or customers take during their journey toward a specific goal or conversion. The term "funnel" refers to the sequential stages that users go through, starting from the initial awareness stage to the final conversion or desired action.
What's the purpose of funnel analysis?
The primary purpose of funnel analysis is to identify and address bottlenecks or areas of improvement within the conversion process. By tracking and analyzing user behavior at each stage, businesses can gain insights into where users drop off, lose interest or face obstacles that prevent them from progressing further. This information helps businesses optimize their marketing strategies, user experience and conversion rates.
The benefits of funnel analysis for websites and mobile applications
All digital customer journeys can benefit from funnel analysis. Some funnels are 3-4 steps, while others are much longer. For instance it could be a simple conversion funnel to go to a website, watch a short video and fill out a contact form. Or a funnel could involve more decision points, like a purchase. See below for an example.
A visitor takes the following steps:
- Step 1: Goes to the website
- Step 2: Clicks to a product page
- Step 3: Adds that product to the shopping cart
- Step 4: Clicks to the purchase check out page
- Step 5: Fills out the purchase form
- Step 6: Completes the purchase
Here are some of the core benefits of carrying out funnel analysis:
Find drop off and friction points
Funnel analysis allows you to pinpoint specific stages where users are dropping off or experiencing difficulties. No matter if it’s signing up for a trial period, requesting a demo or putting items in a shopping cart. Knowing when and where (and why) potential customers are leaving your website is critical data. By analyzing these bottlenecks, you can identify the reasons behind the drop-offs, such as confusing navigation, lengthy forms or technical issues. This insight enables you to optimize those stages and improve overall conversion rates.
Optimize user experience
Understanding the user journey through funnel analysis helps you gain insight into how users interact with your website or mobile application. By analyzing user behavior, you can identify pain points, user preferences and areas where improvements can be made to enhance the overall user experience. This information can guide design changes, content improvements and feature enhancements.
Reveal technical errors
Drop-offs happen for many reasons, but one you may not know about until funnel analysis is technical errors in one or more steps. For example, if you’re getting a big drop-off at the last step, it could be that the link is broken or is directed to the wrong page. Or if users are backtracking in the funnel flow to the prior step, that indicates an issue.
Iterative improvement and data-led decision making
Funnel analysis provides a data-driven approach to decision making. By continuously analyzing and optimizing the user journey, you can make informed decisions based on real user data rather than assumptions. This iterative improvement process helps you make data-driven decisions to enhance user engagement, increase conversions, and achieve your business goals.
Understand visitor demographics
Another important benefit of funnel analysis is surfacing who your potential buyers and customers are. Analyzing the sales funnel through the demographics lens can elicit powerful data to segment your audience into personas or different audiences. You can learn who your highest-converting customers are, create a different decision flow for certain segments or other actions that leverage visitor insights.
Five ways to use funnel analytics
1. Increase conversion rates: Analyzing digital funnels can help find answers to get more conversions and reduce churn. It could be that there are fewer pop-ups along the way, showing pricing upfront in the shopping cart, cutting a step altogether or other refinements. They all add up to an overall better experience for the potential customer.
2. Optimize the customer journey: Conducting analysis for all of your website or app funnels can shape decision-making throughout the customer journey. Taking a holistic view, you can use this analysis to optimize each step of the user experience and make it easier for users to engage and convert at each touchpoint.
3. Measure marketing effectiveness: By analyzing how users move through your funnel, you can determine which marketing campaigns are most effective for driving conversions. This can help you optimize your marketing efforts and allocate your resources more effectively.
4. Identify trends in user behavior: Funnel analysis can help you evaluate trends in your visitors’ behavior, such as fluctuations in the conversion rate, or how much time users spend navigating through each funnel step. These insights can help you make data-driven decisions about your website or app's design and functionality.
5. Monitor performance over time: By tracking your funnel over time, you can monitor your website or app's performance and identify areas where it may be underperforming. This can help you make proactive changes to improve your conversion rate and overall user experience.
Getting started with funnel analysis
Define your strategy and goals: Clearly define the objectives you want to achieve with your website or mobile application. Identify the key actions or conversions that align with your business objectives. For example, it could be completing a purchase, signing up for a newsletter or filling out a form. Your funnel strategy will, of course, be driven by your industry, specific business goals and marketing tactics. But there are some common funnel requirements for all digital journeys that narrow the scope as you map out your funnel. Here is a sampling of questions that may be asked:
- What do you want your visitor to do at the end of the conversion funnel?
- What are the funnel metrics you’re tracking? (volume, churn, conversions, etc.)
- Is it a B2B play nurturing for the long haul or fast B2C, like a travel purchase?
- What audience segment is for this funnel? (prospect, new customer, returning customer)
- Is the funnel nurturing leads in the sales pipeline?
- Does this visitor need more education before making a purchase?
- Does the visitor need social proof as part of the conversion journey?
…and many more.
Map out your funnels: Identify the critical user journeys or flows that lead to your defined goals. Break down these journeys into stages or steps, starting from the initial interaction to the final conversion. Each stage represents a milestone in the user's journey, such as a landing page visit, product selection or checkout process.
Set up tracking: Implement a robust analytics system to track user behavior at each stage of the funnel. Use event tracking, pageview tracking or other relevant tracking methods to capture user actions and interactions. Ensure that the tracking is accurately implemented and aligned with your defined goals and funnel stages.
Analyze user behavior: Collect and analyze data from your tracking system to gain insights into user behavior within the funnel. Examine the conversion rates at each stage, identify drop-off points and understand user flow throughout the journey. Look for patterns, trends and areas of improvement.
Identify bottlenecks and optimization opportunities: Based on your analysis, identify stages in the funnel where users are dropping off or experiencing difficulties. Investigate the potential causes, such as usability issues, confusing navigation or technical errors. Use this information to optimize those stages and improve overall conversion rates.
Iterate and test: Continuously monitor and analyze the performance of your funnels. Implement A/B testing, user feedback or usability testing to validate improvements and iterate on your optimization efforts. Make data-driven decisions to enhance the user experience and maximize conversions.
Measure and refine: Regularly track and measure the performance of your funnels. Use key metrics such as conversion rates, drop-off rates and average time spent to evaluate the effectiveness of your optimizations. Refine your funnels based on the data and insights gathered, aiming for continuous improvement.
💡Pro tip: Use funnel alerts to stay informed about conversion rate changes. Act swiftly during issues and learn from positive improvements.
Choosing the right tool for funnel analysis
The real power of funnel analytics lies beyond displaying the number of users progressing through a predefined flow. Google Analytics for instance can show the drop-off count at each step, but it doesn't provide the underlying reasons. Advanced tools, such as digital experience intelligence, provide the insights required to identify the root causes of problems and the additional context required to prioritize based on impact. Access to this level of insight enables faster issue resolution.
Here are some key features to look for:
Session replay captures the entire interaction the visitor went through on your website. Session replay is critical in identifying bugs, user struggles and UX design flaws. You can pinpoint sections to see clicks, keyboard entries, mouse movements and other actions. For mobile users, you can review their every tap, scroll, pinch and more.
🔎Keep a look out for advanced functions where funnel creation is possible from within the session replay window itself.
Heatmaps are a well-established and popular web analytics tool. It uses a visual representation to show the visitor’s activity and engagement on a website. There are many types of heatmaps. The most common ones are scroll maps, click maps and move maps. There are also mobile heatmaps to get a drill-down visual view of app activity.
Other advanced capabilities that enhance digital analytics insights:
- Tagless data capture automatically tags every digital interaction, saving time and resources
- Retrospective analysis: By utilizing a tool with retrospective analysis, users can effectively explore and analyze data to gain valuable insights into past occurrences. No more waiting for your funnel to gather data--view the data from that specific funnel the second you hit publish
- Revenue impact analysis provides a view as to the impact abandonment is having on your business
- Browser and device analysis provides the context you need when investigating the cause of issues leading to funnel abandonment
- Integration with third-party solutions boosts insights and relevance from your analytics
- Privacy and compliance features to protect sensitive data and increase security
How to extract actionable insights from funnel analysis
You’ve set up your funnels, they’ve been live for a certain amount of time and it’s time to evaluate how they perform for engagement and conversion. Funnel analysis will give you the insights to start making improvements. You’ll be asking questions like:
- How many users completed each step of the funnel and did they finish?
- Was there a pattern in visitor drop-off behavior?
- How long does the funnel take to get through?
- Is this data that would benefit from A/B testing to further evaluate results?
This is where advanced digital analytics show their strength, saving time and effort while delivering actionable insights. Beyond drilling down into the data, you can quickly interpret user behavior, identify the root cause of struggles and errors, prioritize improvements by their business impact or segment specific audiences to learn more about their behaviors. Altogether, these features help you come to data-driven decisions for a better user experience–redefining what success looks like.
Here are some common examples of how using heatmaps or interaction maps, session replays and other digital analytics insights can lead to decreased abandonment and increased engagement and conversion:
- Removing steps in the funnel
- Change the order and location of key messages and CTAs
- Swap large amounts of text with a shorter copy
- Add pop-up windows or hovers for explanatory text
- Change a form field from required to optional
- Expand ad campaigns to increase funnel entry points
Funnel analytics: An example of extracting actionable insights
Funnel analysis paired with advanced digital analytics can provide the most powerful, detailed and actionable insights. Here are some in-depth, advanced use cases where the results show a clear correlation to dramatically improved funnels.
Console error detection and impact analysis for leading financial services website
Summary: With funnel alerts in place, the team at a leading financial services company was alerted to an issue where users were unable to 'add to cart.' Jumping into the console and analyzing the funnel for this particular flow, the team was able to identify the issue and quickly rectify it, mitigating any additional losses.
Funnel analysis results
- Over 15k sessions were impacted by the error and over 80% of those sessions went on to abandon their journey without placing an order
- The error was specific to a certain subset of products on their website
- The team was able to quickly find the root cause and rectify it to prevent further losses
📉The potential impact of this issue was quantified as over $1.5 million in at-risk revenue per month.
What is funnel analysis?
Funnel analysis maps out and analyzes the journey your visitors go through on your website or app to understand which parts of the funnel are working well or need improvements. These insights can be used to optimize the funnel to increase traffic, convert visitors and retain customers.
What are the benefits of funnel analysis?
There are many benefits to conducting funnel analysis. Some major ones include:
- Finding areas of friction and abandonment in the funnel to correct them
- Uncovering hidden technical issues that you were unaware of
- Understanding your audience personas and segments so you can better address their needs.
How can funnel analysis be used as part of your digital strategy?
Funnel analysis can be used to:
- Help increase conversion rates and reduce churn
- Optimize the customer journey to make it easier to engage each step of the way
- Measure marketing effectiveness to see which campaigns drive conversions
- Identify behavior trends such as conversion rate fluctuations, time spent on pages, etc.
- Monitor performance over time to track areas that are underperforming or working well