How to turn funnel analysis into funnel optimization
What is funnel analysis?
Funnel analysis is a method used to map out the journey your visitors take through your website or mobile app. You can use it to understand what pages work best and where people drop off. By optimizing these areas, you can increase traffic and sales.
When looking at typical digital funnel analysis, many people are often looking to answer questions that include:
How many users completed each step and the entire journey?
Where does the biggest fallout occur?
How long does the process take?
These questions are essential, but only if they lead to even deeper questions like:
What are the primary causes of fallout?
What is unique about the users who are – or are not – completing the flow?
What would make the process easier, faster, and better for the users?
By answering this second set of questions, we can go beyond funnel analysis to funnel optimization.
The primary causes of user abandonment
For starters, let’s take a look into some of the primary causes of user abandonment: errors, struggles and missed expectations.
Identifying and eliminating errors can often be one of the easiest ways to deliver funnel optimization and prevent users from abandoning a purchase or conversion.
In our experience, users who encounter an error will often try again - either right away or at another time. But if the error persists, or if they have to invest a lot of time for each attempt, they may not be so forgiving. Depending on the nature, severity and frequency of the error(s), some users may decide that your organization just isn’t worthy of their time and attention – even if the errors aren’t “fatal.” Some of these users may still attempt one of your organization’s other channels, but even with this option, there are extra costs involved and increased potential that you may lose this opportunity.
Wouldn’t it be great to fix every error as soon as they’re identified? Unfortunately, that’s not remotely possible. In prioritizing which errors to resolve first, consider the following:
How often do they occur?
How many users are impacted?
How critical it is to the process?
What is the potential revenue that could be achieved if this error wasn’t in the way?
What resource challenges will you face getting it resolved?
It’s worthwhile to track all of these factors and prioritize accordingly when pursuing your funnel optimization program.
Even if users don’t encounter critical “show stopping” errors, they are still an abandonment risk if they are having difficulty. The more users are struggling at a specific step in the process, the more likely it is that they will abandon.
For example, if users don’t understand what the next step is supposed to be or if they are confused by the options presented, they may still make a couple of attempts, but they’re not going to be fully invested in a challenging process.
How can you look at the challenges that your users face in a new light and identify the patterns when pursuing your funnel optimization program?
One of the things we like to look at first are the different types of struggles:
Are users exhibiting signs of frustration like “rage clicking” a button which doesn’t give them the expected results?
Are they reloading pages?
Are they frequently referring back to your in-line “tips” or help pages?
Are they entering the wrong values into fields, or skipping fields altogether?
Are users losing patience with the process because it is too complex or it takes too long?
Reviewing these items will help you determine and prioritize which struggles to try and eliminate. You may even want to experiment with alternative design options in an A/B testing and optimization program.
There are also many other things that can contribute to abandonment which are more subtle than errors or struggles. Whenever a user isn’t getting the outcome they anticipated there can be “missed expectations” you should consider when pursuing your funnel optimization program.
Cost, terms, extra fees, availability, customer reviews and other preferences may all contribute to abandonment – sometimes even for the “right” reasons. For example, a customer may abandon an insurance or a credit application after being informed that this product is not available in their state. In this case, it’s important to find ways to inform the customer of this limitation as soon as possible to help them manage expectations and so that they don't waste time.
Or, it might even be possible to route them to a partner or subsidiary that is more appropriate for their needs and actually turning the abandonment into an alternative conversion event.
These are often harder to detect (and correct) than some other reasons for abandonment, but the aggregated data may provide insight and identify helpful correlations.
For example, you may observe that users from certain regions are more likely to abandon. Or perhaps you can compare the average purchase amounts for users who do convert to the average cart value of users who abandon and realize that it’s only high-end customers who are abandoning. Again, that may even be intentional given your target audience, but don’t forget there may still be ways to redirect those users to something positive.
Altering your campaigns and content to attract the target audience will help to improve conversion rates.
We have explored some of the primary causes of user abandonment: errors, struggles and missed expectations, however, pursuing a funnel optimization program should evaluate all causes of abandonment. A better understanding of these elements will help you to maximize conversions and deliver funnel optimization recommendations.