Launching a large volume of experiments often seems like a lengthy, complex process that depends heavily on technical teams. But when your growth strategy is built on optimization and data analysis, speeding up operations without compromising quality and performance becomes essential.
That was exactly the turning point for Neofin, a company modernizing debt collection management in Brazil by combining technology, automation, and intelligence into the debt collection process.
Test individual elements or full journeys with advanced AI-powered segmentation, great performance, no-code rollouts, and flicker-free experiments.
The challenge: transforming a long backlog of tests into real learning
With a platform that eliminates manual tasks, reduces delinquency, and integrates end-to-end financial information, Neofin already had the expertise to help clients improve efficiency. But internally, they faced a barrier: the backlog of experiments on the site was growing, and the team needed to implement these strategies so they could start adding real value. Running AB tests was important, but the traditional process proved slow and not very scalable.
The most common approach for CRO specialists would be to rely on developers whenever a new test needed to be set up. In practice, this would mean long development cycles, code adjustments, sequential deployments, and a constant struggle for priority within the technology team.
At the same time, tools with visual editors are not always the most scalable option. Although practical, these editors create significant limitations in scalability and content management, affect website performance, generate design inconsistencies, introduce redundant code, and reduce control over the user experience, which makes no sense for a company with a mature digital operation concerned with performance.
Neofin needed a solution that was both fast and robust. Flexible, yet technically reliable. Standalone, without compromising the brand or website performance.
Autonomy, performance, and scale
Combining all of this is no easy task, since the goal was, fundamentally, to run multiple versions of a website in a single URL, with aggregated and segmented metrics for each variation. To achieve this, dynamic components are essential; their content adapts to each audience, eliminating the need to duplicate pages or generate new URLs.
Therefore, the Neofin team decided to use Croct's slots to gain more autonomy, a solution that required the technical team to work only on the initial setup. From then on, everything involving experience creation, AB testing, website-section personalization, and content changes happened directly on the platform, without new development or deployments.
This autonomy eliminated the main operational bottleneck and created room for a much faster pace of experimentation. Instead of waiting weeks for each test, the team could finally test, measure, and evolve the site in real time.
Furthermore, because Croct is headless and integrates natively with the website's frontend, Neofin maintained control over performance, design, compatibility, and rendering. This let them achieve the agility of visual editors, with the quality and consistency only a robust architecture offers. The combination of autonomy and technical governance enabled scaling experiments without compromising the user experience.
The second challenge: running 15 experiments simultaneously
Another key element of the strategy was that the tests would be numerous, simultaneous, and targeted at different audiences. The journey of a lead who arrives through a Google search differs greatly from that of someone who accesses the page organically or is already a customer.
Recognizing these differences, Neofin structured its experiences around specific audiences, considering both the origin of the visit and geolocation. Users who arrived through specific keywords received messages aligned with their searches, while visitors from different cities saw content adapted to their region. For the audience that didn't fit into these segments, a call-to-action experiment captured additional learnings. Each visitor experienced a version of the site that made sense for their context and motivation.
This strategy led to a significant result: in a single day, the team set up 15 simultaneous experiments, generating 37 content variations for a single element on the homepage. The team produced all this volume without overloading the technology team or sacrificing website performance. Neofin transformed its accumulated backlog into a continuous, sustainable learning engine.
The impact: speed of experimentation as a competitive advantage
This experience reinforces an important shift in growth culture. With more autonomy to test hypotheses, measure impact, and adjust the website based on results, marketing and product teams are beginning to see experimentation as a natural part of the operation, and no longer as something dependent on long cycles or disputes over technical priorities. Speed ceases to be a problem and becomes a competitive advantage.
By adopting a personalized, continuous experimentation approach, companies can align communication decisions with real visitor behavior, respect different journeys, and maximize results in each interaction.
Today, websites that use dynamic content with the Croct platform are constantly evolving, driven by data, intelligent segmentation, and operational autonomy. Want to know how to take your experimentation operation to the next level? Create your free account on Croct and discover how to transform your website into a continuous learning environment.