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Problem Statement: Conversational Analytics

💁‍♂️ Problem

Portal users and customers can’t quickly get trusted answers (status, simple analytics) without tickets or multi-step UI work. This slows decisions and drives avoidable support load.

🎯 Measuring Success

Success will be measured by adoption, repeat usage, and perceived value within the Client Portal, which act as leading indicators of reduced WISMO burden for our customers. Because we are not the shipper and do not own their ticketing systems, our metrics focus on what we can directly observe in our product:

  • Adoption & Trial: % of eligible portal users who engage with the copilot to retrieve shipment status or generate analytics within 30 days of exposure.

  • Retention & Repeat Use: % of first-time users who return and successfully complete another query within 30 days.

  • Task Coverage: Share of copilot queries that fall into the top intent categories (status lookups, tracking, analytics), ensuring we are solving the right problems.

  • Experience Quality: Median response latency and % of grounded answers (i.e., tied to a database result or cited documentation).

  • Customer Signal: Qualitative validation from user groups and account managers that the copilot reduces inbound WISMO demand on their side.

🔎 Existing Solutions

  • Current portal search/filters and CSV exports (non-conversational).

  • Static reports; manual support responses.

  • No unified conversational interface with grounded answers + inline visuals.

🤔 Proposed Solution

Embed a conversational copilot in the Client Portal with:

  • Natural-language Q&A → safe SQL over an allow-listed schema → inline charts/tables.

  • Identity-aware order/tracking lookups.

  • RAG over Confluence with citations.

  • Guardrails, observability, and human fallback.