Explanation:

If the customer wants to track case resolution times by product category, the most relevant requirement is to build reports that are specifically structured to organize and filter case data by product. This can only be done effectively if the case records contain product category information, which may require custom fields. Once this data is captured, custom reports can be created to break down resolution metrics accordingly.

🅰️ Option A: Implement custom dashboards with visualizations of overall case volume and agent performance
While custom dashboards are useful for visualizing metrics, this option focuses on overall case volume and agent performance, not product-specific resolution data. Dashboards are typically built on top of reports, so without reports that break down resolution times by product category, the dashboard won’t deliver the insight the customer wants. This option is relevant for general performance tracking but not specific enough to meet the stated goal.

🅱️ Option B: Configure reports with filters to break down case resolution times by agent and case priority
Filtering by agent and case priority helps understand performance at the individual and urgency levels, but it does not provide visibility into product-level trends. The requirement is to see resolution times by product category, which this filter set does not support unless the product field is already incorporated into the data model and report filters — which, again, requires custom fields.

🅲️ Option C: Develop custom fields and reports to categorize cases by product and track resolution times per category ✅ (Correct Answer)
This is the most direct and relevant approach to the customer’s goal. If product information isn’t already captured on the Case object, a custom field like “Product Category” or “Product Line” should be added. Once populated (either manually, through automation, or via integration with a product catalog), reports can be grouped by product category and configured to calculate metrics like:

✔️ Average resolution time
✔️ Number of cases per product
✔️ Resolution rate by category

This gives the customer clear, actionable insight into which products generate the most service load and how quickly they’re being resolved, enabling more targeted improvements.

🅳 Option D: Utilize Einstein Analytics for advanced machine learning insights into case trends and root causes
Einstein Analytics (CRM Analytics) is a powerful tool for predictive and diagnostic analytics, offering insights into case trends, correlations, and even potential root causes using AI. However, it is not necessary for a relatively straightforward reporting task like tracking resolution time by product. It's more appropriate when you're analyzing complex patterns, building dashboards across multiple data sources, or trying to predict case surges. For this use case, standard reports and dashboards with properly structured data are more efficient.

🧩 Summary:
To effectively track case resolution times by product category, you must first ensure that product data is captured on each case (via custom fields if needed), and then build custom reports to group and analyze this data. This approach (Option C) directly addresses the reporting and analytics requirement in a scalable and maintainable way.

📚 Official Salesforce Reference:
🔗 Create Custom Report Types to View Survey Data