As a Conversion Optimizer, your biggest responsibility is finding where the highest optimization potential lies on your website. You cannot do this by just having personal opinions. You cannot just say, ‘I think if we make this element bigger, we will have more conversions’. That’s not how it works. The decision-makers won’t agree. Unless you have trustworthy insights to prove your point, the conversation will ultimately result in an argument. So, how do you get those unbiased and reliable insights? The only answer is Research! Even for new businesses, focusing on research at the customer development stage can help you minimize the risk. In a lean startup methodology, it’s called ‘Pivot’.
In this post, I will share a few Conversion Research Frameworks and Techniques which I’ve learned in the CXL Institute’s Conversion Optimization Mini-degree. This can definitely help you to start off your career as an Optimizer, especially, when you are not sure where to begin your Optimization journey.
The ResearchXL Model
When you start analyzing a website, you will probably wonder which areas to focus on and which data is important. This Framework helps you get started using 6 steps.
Step 1: Start with an Experience-based heuristic analysis. The factors to examine are Clarity, Friction, Anxiety, and Distraction. On a scale of 1 to 5, rate your website on these factors, and note down the positive and negative impacts.
Step 2: Do a technical analysis. Things to check here are the Page speed, Responsiveness, Browser compatibility, Device compatibility, Broken pages, and Cross-browser bugs.
Step 3: Dig into Digital Analytics. This will help you understand where is the flow stuck and in which part of your website the money is leaking.
Step 4: Conduct a Qualitative analysis. Try to understand your customer’s attitude towards your product by using methods like Surveys & Polls. We will discuss Surveys further in this post.
Step 5: Conduct User testing. Recruit people who reflect your target audience and see how they use your website and complete a given set of tasks.
Step 6: Use analytics tools to create tests like Heatmap, Scroll map, and Session replay. Remember this can give you the right insights only if there is a significant amount of audience traffic.
Rank the issues based on priority and the impact it has on your conversion rate. Most optimizers skip this initial research and jump immediately into A/B Testing and Personalization tests. It’s not always a great idea to start tests based on your assumptions. Without proper research, your optimization strategies can backfire very badly.
The Survey is qualitative research that allows us to understand our customer’s attitudes towards our brand. Designing the right survey won’t take a lot of time and effort if you follow the correct principles.
Any survey should have a purpose. The questions should be open-ended and not too long. The product knowledge of you, who is creating the survey will be different than your customer. Do not over assume that the customer might know certain things. Hence it is best to avoid jargon and short forms in survey questions. Most importantly, do not mix behavior and attitude questions on your survey.
Let’s take a common survey for example and analyze it:
‘On a scale of 1 to 9, how happy are you with this page?’.
Mistake 1: Firstly, as a customer, how will I know which one is the most positive response? Is it 1 or 9? Avoid this scaling error and have the responses in words. (For example, Agree or Disagree)
Mistake 2: You are asking your customer to respond with a number between 1 to 9 indicating their level of happiness with your website. What insights will you get if the customer responds with a rating of 5?
Mistake 3: If there is an answer that you are hoping to get, you are most likely to bias the customer. On the above survey question, you are already telling that the customer is happy and just asking how happy he is. A better approach would be first to ask about the experience whether good or bad and then a rating with an optional explanation field.
There are 3 types of Survey scales. Dichotomous scale (Yes or No), Rating scale (1 to 10), and Semantic differential scale (Strongly Agree, Agree….Disagree, Strongly Disagree). Choosing one among them really depends on your type of research and the data you are looking for. Also, conducting a survey on the right sample audience can help you get a lot of optimization insights.
Conducting User Research
What users think is not always the same as what they do. The goal of doing User research is to understand the user’s needs and beliefs so you can create better experiences. We often think it is the same as Market research or something that needs to be taken care of by the Designers, but it’s not. Even Optimizers should focus on User Research to develop a better product.
Create simple goals from which you can see changes. Let’s say you have a goal to reduce the number of support tickets on a particular integration feature on your product by 50%. You will do the User research on who, what, when, why, and how to solve it. Based on the answers, the page containing the particular feature can be simplified or made intuitive. But keep in mind that false assumptions can result in faulty design. You will get the best results when you research the users who have interests that are directly relevant to your goals. For example, you need to do research on new users when you want to investigate the onboarding experience.
When you have your initial research findings, simplify them so that the stakeholders can understand the meaning of it. Creating a checklist and ranking the items can help you during the audits. It is also better to benchmark your insights with your competitors while doing a presentation.
Thanks for reading and share your thoughts on Conversion research with me in the comments!