Assuming you’ve already spent some time optimizing your retention so that you’re not wasting money converting customers with low lifetime values, it’s time to get to work on your conversions.

Now, when it comes to conversion optimization, there are countless strategies an organization can implement, begging the question: Which ones should be prioritized?

To answer this question, you need to identify the strategies that will yield the highest returns. You’re probably thinking, “how can I find the strategy that will yield the highest returns before I actually try it?”

The key is simply finding the main problem area in your conversion process, or what we’re going to call your Area of Greatest Friction (AGF). Just as a bottleneck will slow down an entire operational process, your AGF will dramatically slow and hurt your conversions.

Once you’re able to identify your AGF, even a slight improvement at this step will result in much higher returns.

Finding Your AGF

If you were to visually map out every step in your conversion process, you could see how many people make it to each step and how many people drop off at each step. This is what funnel analysis does.

In the funnel analysis above, we can see that 81.3% of people made it from step 1 to step 2, 39.7% of people made it from step 1 to step 3, and so on. We can also see the percentage of people who made it between steps. For example, we see that 48.8% of people made it from step 2 to step 3 and 3.3% of people made it from step 3 to step 4.

Mapping out our conversion process in this way makes it quite easy for us to identify our AGF, which is simply the step with the largest drop off. In this example, we can see that our AGF is at step 4, “Confirm”, where only 3.3% of people make it from the previous step.

The Cause

Next, you have to understand why there is so much friction at this step. In many cases it will be obvious to you for one reason or another, such as:

1. The step requires greater effort than the others (e.g. setting up or implementing something technical)
2. The step requires some type of commitment from the user (e.g. adding a credit card or sharing very personal information)
3. The step involves obviously confusing UX (e.g. a lack of feedback, non-obvious button)
4. The step introduces other variables that may be problematic (e.g. sending an email confirmation that can end up in spam folders, be sent to unattended email accounts, etc.)

Other times, the cause of the drop off won’t be as apparent and will require additional analysis. At this point, you will want to set up a sub-funnel to analyze just that step which is your AGF.

For example, say your AGF is your “add shipping details” step. You will want to create a funnel that looks at every minute step required for your users to add shipping details, from button clicks to fields they must complete.

This sub-funnel allows you to take a closer look at your AGF and diagnose the cause of the friction. In the “add shipping details” example, we might find that our shipping options are unclear or that customers are taken aback by high shipping costs, causing them to abandon at that point.

Another way you might find out what is causing your AGF is by comparing how different segments move through your funnel. You may discover that each segment behaves quite differently, particularly if you have customer segments with distinct characteristics.

In the above examples, we were simply looking at averages. However, in some cases, the averages will actually hide more than they will expose, making segmentation critical. For example, say we have two segments that each perform poorly at a different stage of the funnel. If we simply average the performance of both segments, we will end up with metrics indicating that there are no issues at either of these two stages.

You will need to have a good understanding of your customer base in order to know which segment characteristics might affect conversion performance. For example, a B2B company with both small and large accounts may want to segment by company size (smaller companies will likely stumble at different steps than larger enterprises), while a social network might want to segment by student age group.

Fixing Your AGF

If you’ve made it to this step, congratulations! You’ve already completed the hardest part. Now that you know what is causing your AGF, you have a clear compass directing you to your top solutions. Here are just a couple examples of organizations that successfully identified their AGFs and implemented solutions that improved their conversions.

TOPS Products

RR Donnely’s TOPS Products was experiencing an underperforming product launch, despite significant marketing investment and highly positive feedback from focus groups. With some analysis, they were able to identify their AGF: a confusing product search that was preventing customers from finding the new product. As soon as they resolved this issue, their first orders started rolling in.

Woopra, Inc.

At the company where I work, we found our AGF was at the step where customers were required to add a JavaScript tracking code to their website or application. The cause of friction was quite obvious to us – although adding the tracking code requires only 5 minutes, many users who sign up do not have the energy or the ability, to add the tracking code in that moment. The first solution we implemented was quite simple. We triggered an email to be sent to users who signed up but failed to add the code within 3 days. The email offers assistance and also directs them to documentation to help them add the tracking code. After just one week, this simple email campaign improved our conversion rates by 20%.

Ultimately what both of these organizations have in common is their ability to maximize their return on investment in conversion optimization by first identifying their AGF. By focusing their efforts, they were able to achieve maximum impact with minimal effort.