Author: Adam Bunker
Subject Matter Expert: Sam Scott
What is website funnel analysis?
Website funnel analysis is the act of understanding – and optimizing – the journey users take to complete a task or goal on a website, such as making a purchase or applying for a new credit card. This process is commonly referred to as the conversion path, and funnel analysis examines both the successes and failures encountered along the way.
We refer to this journey as a funnel because it visually represents the narrowing path, with fewer customers progressing at each step (or ‘down the funnel’) toward conversion.
So, if your ultimate goal is for a customer to complete a purchase from your online store, the top of funnel would be the customer arriving at your website’s homepage, while the check out process would be the funnel’s final (bottom-most) point. There will be some user attrition in between as people move through each step.
When analyzing this funnel, you’re examining each step of the customer’s path to understand what’s working, and what’s not. A noticeable drop-off between steps can signify points of friction in the customer’s experience, causing them to abandon their task. The more optimized your funnel, the higher your conversion rate will be.
Website funnel analysis vs the sales funnel
A website conversion funnel differs from the traditional sales or conversion funnel in that it focuses on a single channel and often a specific task, such as successfully signing up for a new account through the website. In contrast, the traditional sales funnel (awareness, interest, consideration, and purchase) represents a buyer’s holistic journey and interactions with a brand across multiple channels, starting from their initial awareness of that brand.
Website funnel analysis allows teams to examine the specific journeys people take across a single channel. What you learn will reveal UI, UX, and user behavior insights that can be directly acted upon to maximize conversions.
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The benefits of funnel analysis
Website funnel analytics show channel owners how well their efforts to streamline the customer journey are working. Honing in on website visitors’ behavior can help in a few key areas:
Identify drop-off points
If you know where people tend to drop out of the funnel, you can pinpoint which areas of your site are not performing as they should. Overly large attrition on a given page or at a certain point of the conversion funnel may indicate a poor user experience, a broken link, or a lack of a compelling next step. For example, if a handful of people abandon their carts when asked to enter their delivery information, it could suggest issues with either the form design or delivery costs.
Optimize marketing
If one marketing campaign or traffic source leads to more completed sales than others, you’ll know to focus more of your efforts and resources on that kind of marketing. You might find that some channels or approaches attract many visitors but relatively few sales, while others bring fewer visitors to your site but achieve higher conversion rates.
Test and validate changes
If you’re using A/B testing to deploy website changes to groups of users, funnel analysis will reveal whether those changes are effective. A/B testing becomes more of a science when you can see how your design or process changes impact the entire funnel, instead of just individual metrics like sales.
Website funnel stages
As people move through your website, they’re moving down the funnel toward your end goal.
Every business will have its own version of what that goal is and what success looks like, but there are a few common archetypes:
- Make a purchase: This is the main goal – and funnel endpoint – for the vast majority of businesses. For eCommerce website retailers and online stores, the website’s primary function is to direct users toward completing a purchase.
- Capture leads: If your business has a more complicated product or service offering that can’t be purchased within a few clicks, the endpoint in the funnel is usually to capture users’ contact information – this allows them to become leads for sales teams to follow up on. This might be achieved by gating a piece of useful content behind a contact details form or asking people to sign up for a newsletter.
- Engage with content: Sometimes a site’s business model doesn’t need a sale to drive revenue. YouTube, for example, delivers ads to users watching videos. In this case, the end of the funnel would be to get a user to find a video they like and watch it through to the end.
Because these goals are different, they will require different funnel phases – and conversion funnel analysis will look different for each. But if we use ‘make a purchase’ as an example, then the web page’s desired funnel might look something like this:
1. Arrive on a landing page
This might be the homepage for an online business or a targeted landing page for a specific campaign.
2. Browse products
You’ll want to make moving from product to product seamless – ideally in a way that can anticipate what each user is looking for.
3. Add a product to the basket
There’s a science to enticing users to add products to their carts, but doing so is only half the battle.
4. Fill in shipping and billing information
Any points of friction here will result in an abandoned cart and the loss of potential customers.
5. Complete checkout
If completing the buying process is the goal of your site, then this is when the customer reaches the bottom of the funnel. Bonus points if they also sign up for a newsletter for future promotion.
Website funnel analysis metrics
We’ll talk about website funnel analysis tools shortly, but first, it’s important to consider what we aim to track when collecting this information. As with any kind of digital analytics, data can be a blunt instrument if not utilized effectively. The key to making data actionable is to monitor how specific metrics change over time.
In website funnel analysis, you’ll want to focus on a couple of core metrics that you can use as stage-specific or site-wide KPIs:
- Task completion: As stated, the task at hand might change from business to business, but what’s important is the percentage of customers or users who successfully completed it. So this could specifically be conversion/sales, signups, or engagements.
- Churn/drop-offs: This metric is essentially the inverse of the above. It tracks the percentage of people at any given stage of the funnel who don’t make it to the next step. High drop-off rates indicate issues at a specific part of the customer journey.
How to use funnel analysis
1. Understand your goals
While your ultimate goal will probably be something like ‘increase sales’, you’ll only be able to increase the number of paying customers if you hone in on a more specific goal with your funnel analysis. For example, you might outline three goals:
- Understand which part of the conversion path loses the most users
- Test iterations that seek to reduce churn at that stage
- Monitor and analyze the results of those changes
2. Take stock of your current conversion funnel
What do things look like now? Where are people leaving? Can you guess why? The current state of your website’s funnel is your benchmark – it’s what you’ll compare future changes against.
3. Analyze drop-off points
Each big drop-off is a red flag and a sign that things on the page or within the customer journey could be improved. Analyzing data over a long period of time can help here. For instance, if a particular page previously directed more users to the next step than it does now, you may be able to trace the decline back to a UX change that has increased user friction.
4. Iterate and test
Using funnel analysis alongside other operational and experience analytics tools, you should be able to pinpoint specific strategies and website tweaks that might help improve conversions.
Whether you use A/B testing or dive in with both feet, you’ll want to monitor and assess the effect of these changes. Improving website experiences, optimizing landing pages, and improving the customer journey is an ongoing process of iterative change and analysis.
Funnel analysis example
An online store wants to use conversion funnel analysis to understand how it can turn more users into customers. The data shows a clear trend: there’s an unusually big drop-off in users as people move from the first page of the online checkout tool to the second.
The business posits that the billing information form is overly complicated, so it A/B tests a solution that merges these two pages into one. A month later, follow-up funnel analysis shows that conversions improve and drop-off rates decrease.
Funnel analysis tools
Website funnel analysis tools can be cost-effective and fairly simple, or deeper and insight-rich. For example, Google Analytics is a free suite that can help give website owners a good idea of key performance drivers. Its website funnel view tool will show you the number of people moving from page to page and completing specific journeys.
The downside here is that you’ll need to draw your own conclusions – Google Analytics can only show you what’s happening, without any real insight into why. This means you’ll need people skilled in data analysis to understand what’s making website visitors or users drop off.
On the other end of the spectrum? Feature-rich, intelligent tools like Qualtrics® Digital Experience Analytics Software.
How Qualtrics can help
Qualtrics enables teams to access a comprehensive view of customers’ interactions across digital properties and touchpoints – allowing you to identify the root cause of what’s driving high funnel drop-off rates, and dramatically increase conversions.
While funnel analysis is a huge part of website journey optimization, it’s just one part of the wider customer experience. It’s only when you combine insights from multiple channels and sources that you can truly understand what’s influencing your customers – and what’s stopping each user from reaching their desired outcome.
That’s why we combine funnel analysis with advanced conversational analytics and behavioral insights like session replays and context-driven customer histories. Bringing all this data together – and turning it into actionable insight – helps businesses close digital experience gaps and deliver personalized, omnichannel journeys for every customer.
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