--- title: "Making DataScouts’ AI Product Easier to Understand, Trust and Use" url: "https://www.bitsoflove.be/our-work/how-datascouts-improved-adoption-through-better-ux" date_modified: "2026-04-20T09:56:42+02:00" --- # Making DataScouts’ AI Product Easier to Understand, Trust and Use ## Key takeaways DataScouts had already built strong AI capabilities into its Minerva platform. But users needed too much explanation before they could get value from the product, which slowed **adoption** and made sales demos longer than they needed to be. Bits of Love **audited** the full experience, identified where **friction** and uncertainty were getting in the way, and **redesigned the conversational UX** into a more guided flow. The result was a product that better aligned with analysts' thinking, made the AI easier to trust, and showed its value much earlier in both usage and sales. - Client DataScouts - Services Digital product strategy — User interface design — Data interfaces — - Links [Datascouts website](https://datascouts.eu/) ## **The Business Challenge: Powerful AI, But Too Much Had to Be Explained** Minerva is a research and intelligence platform used by senior analysts. It combines rich datasets with strong AI capabilities, giving users powerful ways to explore, interpret, and act on information. But that value was not immediately obvious in the product experience itself. New users were met with a relatively open interaction model and had to understand too much before they could move toward insight. The first step was often unclear. Users needed context before they could use the tool well. And in sales demos, too much of the value still depended on someone explaining the platform clearly enough. That friction had commercial consequences. When a product asks too much of users too early, **adoption slows**. The platform starts to feel more complex than it really is. And the intelligence behind it stays hidden instead of becoming a visible strength. DataScouts needed Minerva **to guide users more clearly,** reflect the thinking style of its target audience, and **make its value easier to grasp** from the first interaction. > “We had a powerful engine, but too much of its value still had to be explained. We needed the product to guide users more naturally and make the intelligence clearer much earlier in the experience” > > Ingrid Willems - CEO DataScouts ## **Our Approach: Replacing Open Complexity with Guided Clarity** We did not begin by adding more AI. We began by looking at how the existing intelligence was being experienced. First, we audited **the current flow from the perspective of the actual target users**. We reviewed the platform as if we were entering it in their role, looking for moments of hesitation, ambiguity, and unnecessary cognitive effort. We also refined the **segmentation** behind the experience, so the product could better match the expectations, language, and working logic of its most important audiences. Based on that analysis, we redesigned the conversational UX around a clearer, more guided interaction model. ### **1. From open input to guided starting points** Instead of leaving users alone with a broad blank starting point, the interface now helps frame the task, clarify intent, and guide the next steps. This makes the product easier to enter and r**educes the uncertainty** of getting started. ### **2. From hidden logic to visible reasoning** Trust is critical in AI products, especially in research contexts. We therefore worked to make the flow easier to follow and the system’s logic easier to read, so users can better **understand how outputs are generated** and what they are based on. ### **3. From system language to user language** We adapted the UX, UI, and **conversational tone** to better reflect how senior analysts think and work. The product now speaks more to the user’s logic and less to the system’s structure. ### **4. From technical capability to product behavior** We looked beyond interface decisions alone. Prompting, tone of voice, interaction style, and product personality were all part of the redesign. The goal was to make Minerva feel less like a powerful system that needs explanation, and more like a guided research environment that supports expert workflows. The result was a set of working prototypes and practical implementation guidelines for the DataScouts development team, enabling the redesigned experience to be carried through consistently across the platform. ## **Business Impact: Less Friction, Clearer Value, Stronger Product Demos** By redesigning how the AI is experienced, Minerva became easier to understand, easier to trust, and easier to demonstrate. Users are now guided more clearly toward value, without having to decode the platform’s structure first. That reduces first-step friction and makes the product feel more useful and better aligned with its audience’s expectations. The impact is also commercial. **Sales demos are less explanation-heavy** because more of the product’s value is communicated through the experience itself. Instead of relying on a guided tour around a complex system, the platform does a better job of showing its usefulness through the interaction. For DataScouts, this meant translating strong AI capability into a clearer product story and a more adoption-friendly user experience. The intelligence was already there. Our role was to make it legible, credible, and usable from the first interaction. > “Bits of Love didn’t just give us a new skin; they redefined how our software communicates value. Seeing the AI’s reasoning visualized has built a level of trust with our users that is now our biggest competitive advantage.” > > Ingrid Willems - CEO DataScouts ## Our view on AI At Bits of Love, we do not see AI as a separate hype layer. We see it as part of modern digital products. But the more intelligence a system contains, the more carefully the experience needs to be guided, framed, and communicated. We do not believe powerful products should leave users alone with complexity. Through product thinking, information design, and hands-on UX work, we help teams balance flexibility with direction, so users understand faster, trust more, and get to value sooner. Sometimes that means shaping an AI-enabled product end-to-end. Sometimes it means improving an existing platform that already contains strong AI, but does not yet make that value clear enough in the experience. ## Thinking about AI integration? If users **need too much explanation** before they see the value of your product, the issue may not be the intelligence underneath. It may be the experience around it. Bits of Love helps teams **audit, rethink and redesign AI-powered products** so they feel clearer, more guided and more useful from the first interaction. From product direction and conversational UX to prototypes and implementation guidance, we help turn technical capability into product clarity. 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