Quick Cover
Fnol
Motivation
Business goal
Enable users to report car accidents quickly and accurately during high-stress moments—reducing operational costs while improving customer satisfaction and retention.
Impact target
Increase claim completion rates, reduce follow-up calls by 50%, improve data accuracy to >90%, and achieve sub-5-minute submission times—driving customer retention and operational efficiency.
Product strategy
Ship an MVP AI-guided FNOL conversational as the primary mobile claim reporting path—adaptive for stressed users, with multimodal input (voice, photo, text), real-time validation, and empathetic microcopy to reduce cognitive load.
Category
AI / ML
MVP
Mobile-First
Conversational AI
Product Strategy
Process
Competitor analysis
We analyzed six major insurance apps across authentication, data capture, and validation to identify gaps. Most required traditional login, lacked voice input, and offered no real-time guidance.
Quick Cover differentiates through emergency-optimized authentication, multimodal capture (voice + photo + OCR), real-time AI validation, and conversational guidance—addressing critical post-accident experience gaps competitors miss.
User journey
We mapped the complete accident-to-resolution journey to identify where stress peaks and data quality drops. This helped us prioritize what to capture immediately (at-scene essentials) versus what can wait (calm, post-incident details)—reducing friction when it matters most while ensuring complete claims data.
Wireflows
Wireflows combined logic and interface to communicate interaction patterns across voice, photo, and text inputs. This allowed stakeholders to validate flows quickly and gave developers clear handoff specs—reducing build ambiguity and alignment cycles.
Iteration
We explored dozens of interaction patterns—testing different entry points, input methods, and validation moments. Volume matters: more iterations mean better-informed decisions before committing to high-fidelity work.
AI-guided conversational claims, report accidents in under 5 minutes, accurately and calmly.
MVP interface
We designed for stressed users in chaotic moments. The UI uses large touch targets, high-contrast text, and one clear action per screen. Voice, photo, and text inputs adapt to context—guided capture with real-time feedback ensures accuracy without adding cognitive load.
Outcomes
Evidence thresholds we use to measure success.
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