Bridging the gap between Analytics and UX Research at Sibelga

Analytics & Optimisation

User Experience

The client

Sibelga is responsible for the distribution of energy and gas for the 19 municipalities of the Brussels Capital Region. In need to replace your old energy meter with a smart one? Want to signal an outage in the street you live? Or time to report your annual meter readings? Sibelga’s website provides a central hub to request works or information to the residents of Brussels. Besides work requests, visitors can find contact details, updates about maintenance of the city’s network and news about the fast-changing energy industry.

The goal

After completing the website’s redesign in a previous project phase, the next chapter in the collaboration with Sibelga focused on optimization. The aim was to let visitors complete their tasks or find information as quick and frictionless as possible. To keep track of this process, Sibelga expressed a need for more clear and centralized user insights. These became the foundation to discover pain points and opportunities to further optimize their website based on user data.

What we did

Analytics tool migration and configuration

Measurement framework

Web surveys

Dashboard with centralized analytics and UX metrics

Our approach

Connect business objectives with UX metrics

Before we configured any optimization actions, it’s important to establish a clear overview on the KPIs and objectives for the website. Tracking possibilities are plenty, yet they become less valuable if they don’t serve your company goals. Together with Sibelga we mapped business objectives, translated them to human questions and ranked them by importance. We then attached the matching analytics and UX metrics to those objectives. This measurement framework provided direction on:

How we were able to measure its performance.
What parts of the website required most attention.
When the optimizations can be considered a success.

GDPR compliant analytics tool

Most of the web analytics metrics are captured with an analytics tool. To be compliant with the European GDPR legislation, a migration was planned from the previous tracking tool to one where data was only captured and processed within the EU. In this case, Matomo Analytics was set up and all tags were configured in order to capture the necessary metrics as determined in the measurement framework.

Bring UX research into analytics

Web analytics provides data such as the number of users visited the pages, how much time they spent or how many clicks certain elements received. This laid a solid foundation to analyze user behavior. However, a lot of opportunities to learn more about Sibelga’s visitors were still untapped. To get a more detailed view on why users left a page or what their experience was completing a task, web and CSAT surveys were conducted on specific sections of the site. The surveys featured a set of questions that can be repeated and measured to track progress over time. In addition, session recordings and heatmaps helped to visualize the interactions. This input from UX research methods formed a crucial part alongside web analytics to better understand the behavior of Sibelga’s visitors.

GDPR compliant analytics tool

Bring UX research into analytics

A centralized UX dashboard for future optimizations

With the web surveys and analytics tracking in place, a continuous stream of user feedback was established. Time to centralize the data and make it actionable. To do this, a UX dashboard was built. Different from a standard analytics data dashboard, we started from the most important tasks the Sibegla users have to perform on the site. Each task was split into a separate dashboard tab to keep its focus. This allows to analyze the data from the user’s perspective and keep a clear overview of the most important objectives of the website.

From a data perspective, UX research insights can be displayed next to web analytics results in the dashboard. It brings quantitative data together with qualitative insights. This way the dashboard covers what actions users perform and how many users complete or abandon the task. Next to direct user feedback on why they experienced the website the way they did, coming from tools like Hotjar. Combining data makes analysis more actionable and easier to discover substantiated pain points and next optimization areas.