Put the turbo to your Conversion Rate with a better UX – Part 1

How many possible leads are lost due to a too long or poorly structured funnel? How many users leave your site or app for a poor user experience? And what can you do to get them to accomplish their (and your) goals? The magic word is conversion, but it is not so simple to design a UX that allows transforming the simple visitor into a user or a consumer.

A virtuous conversion rate optimization approach is based on 6 key moments:

• Define the conversion goals and metrics
• Analyze the user experience to formulate hypotheses on critical issues
• Plan the changes that can improve the design and performance
• Test the alternative design to measure its effectiveness and compare it with the original layout
• Analyze the results to understand whether to permanently implement the changes
• Repeat the process over and over again, with a view of constant improvement

In this article, we will focus on the first three steps of this process.

The conversion rate is a simple but fundamental concept: it is the “queen” metric for any service that has a business goal: generating leads, selling, downloading an application, spreading its contents, expanding the audience of users. The best method for measuring the performance of a digital product is to evaluate the ability of a system to transform occasional visitors into users and consumers.

This is the purpose of the conversion rate, which is the indicator that expresses the percentage of conversions generated with respect to the total number of visits (or unique visitors).

Given the flexibility of the conversion idea, being applicable to multiple event categories (for example, the purchase on e-commerce, the subscription to a newsletter, the registration to a site just to name the most common), the conversion rate can be used to measure the performance of any purpose.

It is therefore essential to clearly define the objectives of the product or service whose performance is to be monitored. And the objectives can obviously vary based on the type of product and the reference market: if for e-commerce, the number of sales and the average value of purchases represent the key metrics, the reference indicator for a blog or a magazine is the number of subscribers.

Next to the conversion rate, it is appropriate to consider other KPIs, to keep an eye on and to measure during the optimization process: for example, the average time spent on the site or the bounce rate are other useful variables to evaluate the results of the changes made to the user experience of a product.

An optimized conversion strategy does not arise from chance or intuition. The analysis phase of the initial situation plays a crucial role: to improve the conversion rate we need insights that allow us to formulate hypotheses to be tested.

The starting point is the search for critical issues to be solved: only by correctly identifying the problems that negatively impact the conversion process, it is possible to find the most suitable solutions to experiment.

As we shall see later, in a virtuous process of continuous optimization, the analysis can be conducted at different levels of depth in the different phases and can concern many aspects of the conversion process. The iterative approach, based on continuous cycles of research and testing, allows for rapid feedback for detailed problems. Both the frictions between the various steps of the funnel and those detectable within each screen can end up under the magnifying glass. Depending on the problems identified, then, it can be decided to test a funnel structured differently or two different versions of the same page.

The tools and techniques to identify the aspects to intervene are the most various: from the expert analysis to the visual analytics that track the behavior of the users (heatmap, scrollmap, session recording), passing through the online surveys to directly collect the opinion of the users and for the funnel and the form analysis.

Once the possible areas of intervention have been identified to improve the interface and the UX, it is necessary to design the alternative. It is a good practice to structure an optimization plan to keep track of the results of all experiments done to improve the product design.

This plan should take into account the critical issues identified during the analysis phase and contain, at the page level and the entire flow, the list of hypotheses formulated on the problems of the system and the changes that can be made.

Changes should point to:

• maximize the relevance of the important content for users and make texts clear and simple, effectively communicating what is offered to the user;
• remove the frictions that cause doubts and uncertainties and eliminate the distractions that can divert the user from the final goal.

Through A / B testing, it is possible to evaluate empirically the positive and negative impact of a redesign of a page. What to do? Testing different variants helps to experiment and optimize text and graphics to find the best solution.

Specifically, it is possible to create alternative layouts to identify:

• Which labels and texts are more effective?
• What is the graphic aspect of each element (buttons, text blocks, etc.) that captures users’ attention?
• What is the correct positioning of the content and other elements within the page?
• What is the optimal number of fields that make up a form?

But is it better to change one thing at a time or proceed with the overall redesign? It depends.

The approach based on small progressive changes is certainly preferable because it allows each change to be evaluated punctually. Making radical changes to the appearance of a page does not make it possible to measure the effects of a single change: by changing several elements at once, it is not possible to understand who to attribute the positive or negative result of the change to.

The individual evidence emerged from the tests can however be useful to support a complete redesign of the user interface.

In the next article, we will look closely at the other steps in the conversion rate optimization process.