Landing Page Funnel
A landing page funnel is the journey that a user takes from the referring source (before they get to your website) to the landing page and onwards as they navigate your site (hopefully finally converting to a sale).
Visualising your funnel is another way to understand how your landing page is performing. This is a deeper form of landing page analysis.
Understanding funnels is an intuitive way to track how people move through your site and analyse visitors’ behaviour. A funnel might look something like this:
Funnel visualisation of the path to purchase from landing page to purchase page
Funnel visualisation of the path to email capture from the landing page to ‘Thank You’ pager
The above images are just two funnel examples. In these examples, I have extracted data out of Google Analytics and visualised them using Google Data Studio.
Enhanced Ecommerce Funnels
Insightful funnels that are native to Google Analytics include:
- Enhanced Ecommerce “Shopping Behaviour Analysis” Funnel
- Enhanced Ecommerce “Checkout Behaviour Analysis” Funnel
The Shopping Behaviour Analysis funnel is a macro funnel. It shows the “10,000 foot view” of all site visitors and purchases.
“Shopping Behaviour Analysis” funnel showing abandonment rates for an ecommerce website.
In the above example, you can see that 15% of sessions click the ‘add to cart’ button when they’re on the Product Page.
Typically, the Shopping Behavior Funnel is useful as an executive-level overview. But it’s not generally actionable without deeper analysis and segmentation. For example, if the progress rate from the Product Page is 15%, it would be helpful to compare mobile versus desktop, traffic sources, and so on. I recommend segmenting all your funnels when running your analyses (which you can do in Google Analytics).
The Checkout Behaviour Funnel focuses on the checkout. It’s more ‘zoomed in’ than the Shopping Behaviour Funnel. Typical checkout experiences consist of the shopping cart, the checkout pages and the Thank You page.
A typical checkout behaviour funnel. In this example, the largest drop-off is between the ‘Payment’ and ‘Review’ steps.
Two important notes about these Enhanced Ecommerce funnels:
- They count ‘sessions’ rather than ‘users’. This matters because one user can generate multiple sessions (if they visit the website multiple times). Therefore, counting ‘sessions’ is actually less accurate than counting ‘users’. For this reason, I always compare these funnels against user-based funnels. Unfortunately, in Google Analytics there is no native way to build funnels that count a ‘user’ metric – you have to extract the data and visualise it somewhere else – like in Google Data Studio.
Another way to measure your landing page funnels in Google Analytics is using a Goal Funnel.
Example of a Goal Funnel
However, I don’t recommend using Goal Funnels to build ecommerce-type funnels. You’re better off using Enhanced Ecommerce funnels as described in the above section. You get a lot more granularity of data in Enhanced Ecommerce reports, such as Product Performance and Sales Performance – all in one place. Most importantly, you can segment Enhanced Ecommerce funnels (not the case with Goal Funnels).
However, the Goal Funnel report is useful for tracking micro funnels. Such as newsletter signups. To set up a goal funnel, navigate to your Google Analytics admin area. Under your View, click on Goals.
Limitations of goal funnels
1.Goals aren’t retroactive
The Funnel Visualization report only reflects data going forward and doesn’t show retroactive data. This means that you’ll only be able to view data from the date that the goals were set up.
2. You can’t segment goals
You cannot apply custom segments to goals e.g. understand how organic search traffic or Facebook traffic or mobile traffic move through the funnel. Needless to say, this is extremely limiting.
3. Goal Funnels can’t be triggered twice in a session
Since goal funnels measure unique pageviews, you’re likely to find less recorded goals (in your goal reports) than transactions (in your ecommerce reports). This is because a goal can only be triggered once per session whilst transactions can be triggered multiple times.
4. Goal Funnels register unique pageviews NOT users
A unique pageview is the number of sessions during which a page was viewed one or more times. So a user who visited a page in a funnel step multiple times across multiple sessions would be incremented in the goal funnel.
5. Goal Funnel Conversion Rate and the Goal Completion Rate are not the same thing
The funnel conversion rate relates to people who entered the funnel (and completed the goal). The goal conversion rate relates to people who entered the site (and completed the goal).
If you’ve already set up Enhanced Ecommerce funnels, then goal funnels are an OK option to track additional micro funnels (such as newsletter signups). However, your analysis should take into account the limitations listed above.
As a general rule, I recommend creating your funnels in Google Data Studio so that they do not suffer from these limitations.
Behaviour flow report
You might also want to use Google Analytics to help you to understand what funnels to build. The reality is that your visitors take many different paths through your website, and it can be difficult to predict all the different paths.
Whilst it’s unnecessary to build a funnel for EVERY user journey, you can identify the most common ones with the Behavior Flow report. This will help you to answer the question: what is the onward journey that people take AFTER visiting the landing page?
This report shows the path that users take from one page or event to the next.
Tips for using the Behaviour Flow Report:
1. Select dimension e.g. landing page content group
2. Apply and compare segments like Mobile vs Desktop, Google vs Facebook traffic, New vs Returning visitors, etc.
3. Pan and zoom to explore the report
4. Hover over nodes and connections to show the number of pages or events, progress rates, exit rates, etc.
5. Highlight specific user journeys by clicking on a node and selecting “Highlight traffic through here”
Based on your analysis of common user journeys, you might then create additional custom funnels to track these journeys in more detail.
Landing Page Campaign Best Practices
A best practice for running landing page campaigns is tailoring the landing page experience based on traffic source. This is a powerful way of ’managing continuity’ throughout the user journey.
‘Maintaining the scent’, ‘conversion coupling’, ‘message continuity’, ‘message matching’ – whatever you call it, it’s crucial to ensure that ad and the landing page message are consistent
In practice, this means:
✔ SEO: your landing pages are based on different groups of keyword themes;
✔ PPC: your landing pages are consistent with your ad groups;
✔ Facebook Ads: your landing pages are consistent with your ad sets and creative;
✔ Email: your landing pages are based on the campaign and user segment
As an example, we optimised landing pages for our travel client, Ski-Lifts, based on holiday destination:
Example Google search engine result for our client, Ski-Lifts
Ski-Lifts serves hundreds of destinations. We adopted a phased rollout that prioritised the most popular landing pages.
The result was a 91.6% uplift on the progress rate to the checkout pages.
In this instance, the whole page was customised. However, just customising a few key elements on the page (such as the headline and image) might also have yielded positive results.
How can you analyse the traffic sources for different landing pages? In the landing page report, add “source/medium” as a secondary dimension:
This will reveal the traffic channel alongside individual landing pages: