Company Context

PulseBoard is a B2B SaaS analytics platform used by 4,000 mid-market companies to monitor customer support, sales, and product usage data. The company recently launched an AI-powered insights dashboard for operations leaders, but adoption among executive stakeholders remains low despite strong underlying model performance.

Problem

PulseBoard's product team found that department heads and analysts use the AI insights feature weekly, but only 18% of executive users review the output more than once per month. Interviews suggest a communication gap: non-technical stakeholders find terms like confidence score, anomaly detection, and model drift confusing, and they are hesitant to act on recommendations they do not fully understand. As a result, renewal conversations are getting harder because buyers do not clearly see business value.

The CEO wants a product approach that helps technical concepts feel understandable and actionable without oversimplifying the product to the point of losing trust or accuracy.

Deliverables

1. Identify the primary user segments involved and define their core needs when consuming AI-generated insights.
2. Propose how you would redesign the product experience to translate technical concepts for non-technical stakeholders.
3. Prioritize the most important features or changes for an MVP launch.
4. Define how you would measure whether the new experience improves comprehension, trust, and business impact.
5. Explain the key trade-offs you would make between simplicity, transparency, and technical precision.

Constraints

• MVP must launch within 10 weeks.
• Only 1 designer, 2 frontend engineers, and 1 data scientist are available.
• The underlying ML models cannot be retrained during the MVP window.
• Legal requires that the product avoid misleading certainty claims in any AI explanation.