A funnel is an arbitrarily defined user flow that measures the drop off from step to step. Arbitrary because you can create a funnel out of any sequences of events you would like to analyze. For example, a signup funnel would include all the steps between the landing page and signup complete; a checkout funnel would represent all steps between product view and purchase complete.
Those are well known but there are many others that a company can create. An engagement funnel perhaps or [another type of funnel]. The important point is that the funnel be representative of a known or rationally-hypothesized sequential user flow.
As mentioned earlier, the core of funnel analysis is actionable conversion measurement. Actionable meaning that you can readily identify the most basic steps contributing to drop off. Measuring a single conversion rate between distance steps is neither informative nor immediately actionable.
This is an important endeavor for any business seeking to optimize. You may have a great product, with revenue flowing in but a design flaw in your signup process is deterring would-be customers from joining and purchasing. Engaging in funnel analysis would quickly identify this bottleneck and allow a company to fix the issue.
There are two types of funnels: one in which a user progresses through a closed-flow path and the other an open-flow. A closed-flow path is where a user has no option but to follow the steps sequentially. Signing up is a good example: users start at the landing page and have no choice but to proceed to Page 1 then Page 2 and so forth until they finish. In this example, the funnel would be simple and linear:
An open-flow path exists when there are many parallel steps between the beginning and end of the funnel that users can take. Take an engagement funnel. In this case, signing up would be the first step and making a purchase the last. In between, a user can embark on a multitude of paths: some users might view the product page, read some testimonials and then make a purchase. Some may simply view the product page before purchasing. While yet others may view the product page, read testimonials, view a coupon and only then decide to purchase. How would you create the funnel?
This is where multi-dimensional funnels come in handy. A powerful but seldom offered tool, they allow for the visualization of parallel user paths while retaining the simplicity characteristic of their linear counterparts. Using them would allow you to see all the paths users take to reach a goal, in this case a purchase. In one fell swoop, you’d be able to identify, for example, that users who viewed testimonials were more likely to purchase than those who didn’t. And those who viewed a testimonial and then a coupon had the highest purchase conversion rate. Granted, it’s possible to perform this analysis using simple linear funnels but the process would be very time-consuming, especially with alot of parallel paths.
When creating your funnel, the most important thing to do is identify the basic intermediary steps. Missing one out may mask a poor (well) performing conversion or assign blame (or praise) to the wrong element. For closed paths, the steps should be relatively easy to ascertain. Open paths, however, require a bit more investigation. The key point is to hypothesize steps that are causally relevant to users reaching the goal.
Once you have created your funnel and are able to see the conversions, it is time to begin optimizing. The best place to focus your efforts are usually at the top of the funnel; improving the conversion upstream will usually increase the volume subsequent events.
To get started, you'll need an analytics tool that has robust funnel capabilities like Indicative.
Once you have created your funnel and are able to see the conversions, it is time to begin optimizing. The best place to focus your efforts are usually at the top of the funnel; improving the conversion upstream will usually increase the volume subsequent events.
Get Started With Funnels