How we increased website registration by 118% & CTR by 68% for OneFamily Adviser.

The Brief

OneFamily is an award-winning financial services company, providing products and services to empower modern families through their financial lives.

OneFamily Adviser provides information to Financial Advisers on Lifetime Mortgage (LTM) and Over 50s Life Cover. The website is a critical business channel as each new adviser registration creates high potential revenue.

The core KPI for the business is registration of Financial Advisers working alone or in small businesses. Our challenge was to find opportunities on the website to increase registration of this cohort.

The Approach

Google Analytics page navigation reports, customer call to action buttons and scroll tracking events were configured in Google Tag Manager, to build a comprehensive picture of how users navigate the website using data.

Early analysis of this new data demonstrated the following:

• 97% of users were using desktop devices.
• Only a small % of desktop users saw the call to action button at the bottom. 

• The website menu navigation did not include a ‘Register’ link unless users scrolled down a certain percentage of the page.
• The Lifetime Mortgage page contained a hero banner which took up a high percentage of visible content above the fold.  

The data helped us to identify that users did not see the register button, impairing new adviser registrations. We hypothesised that by including a ‘Register’ button within the banner we would increase click-through rate to get more users into the start of the registration funnel journey.

The process

Google Analytics data had not been used extensively to inform UX design. Qualitative research had helped to create the site structure and the business wanted an easy to use site for advisers. 

Using the process below, we were able to show how Google Analytics data could help inform UX changes resulting in a positive impact on the key business KPI.

1. Google Analytics data was analysed to paint a picture of site usage and find opportunities for improvement.
2. We created the challenge hypothesis and testing plan based on the Google Analytics data.
3. Provide a wireframe of proposed changes for development.
4. As traffic was low, it was agreed the change would be implemented on the live website.
5. Configured Custom Reports in Google Analytics to allow performance monitoring of our hypothesis.
6. Annotate in Google Analytics as change goes live.
7. Review Custom Reports and share performance with teams.
8. Learnings and iteration – where else in the business the learning can be implemented to improve KPI performance.