Conversion Rate Optimization is all the rage in digital today, and for good reason: traffic costs more than ever, so making more from that traffic is vital. Currently, there are two primary approaches to conversion optimization:
- Radical Redesign
- Hypothesis-Based Iterative Testing
The right approach for you depends on a number of factors. Let’s take a look at your options:
This is a complete overhaul of the site, page, or funnel. With radical redesigns we are typically not looking to optimize or make incremental changes. We are not isolating one variable and testing on it; we’re changing multiple variables at once. Something major is not working or is broken and it needs to be fixed. There are some very specific reasons a radical redesign is necessary:
- The site functionality is so broken that simply testing page elements will make it too difficult to dramatically improve results;
- Traffic levels are too low to reach statistical significance with A/B testing in a timely manner
The brutally honest truth is that many teams will choose this approach for the wrong reasons. Some of the common (mistaken) reasons are:
- The desire to create an aesthetically pleasing page someone has always dreamed of
- New VP or Director wants to own a big project to gain visibility
- The excitement of building a new page from scratch and focusing on being creative
- Motivation by a HiPPO (highest paid person’s opinion) instead of focus on a data-driven process and customer insights
The key to conversion rate optimization is testing and measurement. Radical redesigns can be resource and time-intensive, and your results will be based on any number of changing variables. If you cannot back up your hypothesis with numbers, you will likely be chasing false conclusions. If you go the radical redesign route, you need to make sure you have a good foundation of evidence to back up that decision and a solid understanding of how to interpret the analytics and results you receive.
With radical redesigns, the underlying hope is to dramatically move the needle. This does come with a price of high risk and high reward. In these situations, you are bringing a high probability of failure, and the conclusions from these tests are also tougher to decipher.
Hypothesis-Based Iterative Testing
The other option is hypothesis-based iterative testing, which uses data-driven insights from quantitative and qualitative research to isolate specific test hypotheses. With one specific hypothesis being tested in isolation, we can definitively prove or disprove whether the variation is improving performance.
Typically, the level of effort and total resources required for this type of testing is dramatically lower than for radical redesigns, which:
- Increases the velocity of testing
- Reduces the amount of time and effort required to launch the test
- Reduces the costs associated with getting a test launched
- Provides more scalability
- Accelerates the results and ROI you achieve in a given quarter
If your site is functional and usable but you want to optimize performance, then hypothesis-based iterative testing is a better option than a radical redesign. We want to look at individual variables and improve upon each one over time with a series of tests. This type of testing is less resource-intensive, but the need to support hypotheses with numbers and to have the expertise to properly interpret the results is no less pivotal.
Here’s a quick breakdown of the two testing methods:
If you know you need to get started but struggle on where to start, it is probably due to one or more of the following reasons:
- Lack of development resources or expertise dedicated to testing
- Internal focus on what’s aesthetically pleasing rather than what maximizes conversion and performance
- Cross-departmental inconsistency on what approach to take
- Difficulty getting management buy-in
Our 3Q CRO team specializes in helping you overcome these pain points. Contact us to see how we can help get your conversion rate optimization strategy off the ground today.