Carrying Out Conversion Research for Startups: A Guide
Conversion Research is an essential activity for startups to embark on continuously to help them figure what process users are taking to convert, to trim what may not be working, and optimize what is working to maximize growth.
For week 7 of my CXL growth marketing scholarship course, I delve into the best practices for startups to have in place and go through to carry out conversion research successfully. This is not an article set in stone, rather it is a guide to help you figure out why you should consider conversion research as an important strategy for your startup.
This part of the course was taught by Peep Laja founder of the CXL institute.
Conversion Research: Definition
Conversion research is simply a systematic search for new and useful information about user or customer behavior. It uses quantitative and qualitative methodologies to build hypotheses that can be tested within an applied framework, such as A/B testing.
To be successful at conversion research, you don’t just need more data, you need better data, data that can be acted upon. For every piece of data that you gather, you need to know exactly how you’re going to use it.
What to do as a new startup to be able to carry out conversion research?
What you need to focus on is customer development — understanding which product to build and for whom. Most businesses fail because they build something that no one wants. Customer development is what helps you minimize risk and improve the chances that this new business will make it.
Next Step: Figure out which data is important
Data is only useful if it can lead to insights. Insight is something we can turn into a test hypothesis which is the core of carrying conversion research.
With conversion optimization. We need to gather data that we can read, analyze, and get meaningful information on to be able to then say, okay, I think I know what to do. For any data that you gather, you should be able to answer this question: What will I do differently based on this data? Or what could I possibly be doing differently based on this data? If the answer is nothing, then you don’t need it.
The Research XL Model
ResearchXL is a framework that is focused on helping you discover what really matters, so you can increase the number of winning tests, and increase the impact per successful experiment.
Testing is a critical part of conversion optimization which is an essential aspect of the conversion research process, which helps to make sure we actually made things better and by how much. The success of your testing program is a sum of these two things: the number of tests you run (volume) and percentage of tests that provide a win.
The testing process to ensure success entails the following process:
- Run as many tests as possible at all times (every day without a test running on a page/layout is regret by default),
- Win as many tests as possible,
- Have as high impact (uplift) per successful test as possible.
Executing point #1 is obvious, but how to do well for points #2 and #3? This comes down to the most important thing — the discovery of what matters and this is what the Research XL framework is focused on helping to optimize.
You might spend precious testing time experimenting with different headlines, only to find that there’s no or very little difference between them (no impact on the final conversion). You might also be optimizing the wrong things such as making changes to forms, maybe it’s the pages they were on before they got to the quote request page, maybe something else. Or you might spend tons of effort on your e-commerce product pages only to find that even if you get wins, the financial impact on your business is negligible.
The discovery of what matters is important. If you figure it out, you would know WHAT to optimize, and WHERE which gets you closer to winning tests with bigger impact(Uplift).
It is important to note that following global marketing trends, copying your competitors, and implementing best case practices don’t work for these reasons. What works for your competitor, doesn’t work for another. If copying Amazon would be all that it takes to grow your e-commerce business, there would be many more Amazons around. It doesn’t work like that.
“You can learn what matters through testing and research. But testing without research will result in tons of wasted tests.”
Steps in the Research XL model
There are 6 essential steps of data gathering and analysis in the Research XL framework, followed by creating a master sheet of all found issues that we then turn into action items. You can use the Research XL Framework for each and every optimization project. It’s industry-agnostic — doesn’t matter if the site you’re working on is a B2B lead gen, SaaS, eCommerce or non-profit site. The process you use to get higher conversions is exactly the same across all websites.
The six steps in the Research XL model include the following:
Step 1: Technical analysis
Step 2: Heuristic analysis
Step 3: Web analytics analysis
Step 4: Mouse tracking analysis
Step 5: Qualitative research/surveys
Step 6: User testing
Step 7: Copy testing
This is an intro into the world of carrying our conversion research. To be successful at conversion research going by gut feelings, opinions, and best case practices is not an ideal strategy to use. It is equally important to note that that conversion research is not carried out once, rather it is a continuous process. I will delve into each part of the Research XL Framework in more details in my next article.
To conclude
It is important to continually carry out enough research that gets you the insights you need to find opportunities for growth without the high cost.
Thank you for taking the time to read through. Don’t forget to 👏 and leave me your thoughts and questions.
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