2024 - 2025 • CallRailAccelerating product to market with service design
GenAI / B2B SaaS / Service Design
Drove product strategy and design with CallRail Labs, releasing 4 new AI-enabled features and one new product in 12 months.
Project duration
12 months
Role
Senior Designer
Team
Engineering Manager, Product Manager, Marketing Manager, Lead Designer, UX Designers (x4), Engineers (X8)
Tools
Figma/Figjam, FullStory, Maze, JIRA/Confluence
Our traditional 4-week product cycles slowed development and prevented us from systematically identifying emerging customer needs.
This insight allowed me to leverage my relationship with product and design leadership to co-create CallRail Labs - a research-driven framework that combined quantitative data from sales and marketing with qualitative customer insights to identify high-value product opportunities.
Beyond the immediate need for speed, I identified a deeper issue: our departments were sitting on a wealth of customer insights that rarely connected. Sales knew what prospects were asking for, marketing understood market trends and competitor movements, and design had direct user feedback - but these insights lived in silos, preventing us from spotting emerging opportunities.
Strategic Challenge
Need to coordinate development, testing, and launch of new alphas across multiple departments and functional teams.
Process and organizational bottlenecks prevent free flow of information to key stakeholders, lack of cross-functional teams.
Pain points
Need for an improved methodology to rapidly design, test, and iterate on new AI-based features.
Approach
I envisioned CallRail Labs as a framework for product discovery, powered by cross-functional collaboration.
Key Objectives
Rapid Validation
Prototype testing with customers within 48 hours of opportunity identification.
Go/no-go decisions based on actual user feedback, not assumptions.
Continuous pipeline of validated opportunities feeding development teams".
Discovery Process
Sales provides real-time feedback on what prospects were requesting.
Marketing shares search trend data and competitive intelligence.
Design conducts rapid generative research with customers to validate opportunities.
Engineering assesses technical feasibility early in discovery.
Research Integration
Weekly synthesis sessions combining sales call data, marketing analytics, and user research findings.
Create shared repository of customer insights accessible to all tiger teams.
Establish 'opportunity scoring' framework weighing market size, competitive advantage, and technical feasibility.
Organizational Impact
+15
New opportunities identified.
By integrating our research efforts and findings, CallRail Labs Tiger Teams identified more than a dozen new AI-powered feature opportunities.
-50%
Reduction in product development time.
The new framework aligned multiple functions with user needs through a shared research database and established a new cross-functional operating model.
Our combined research pool and rapid prototyping process allowed me to identify a new opportunity to serve an unmet need for CallRail’s sales and customer service clients.
Design Goal: Labs for Everyone
By surfacing Labs alphas in high traffic areas, we ensured enough engagement for gathering interaction data.
Design Goal: Lead Conversion
We used customer feedback to combine our most popular alphas into a new product for CallRail Agents: Convert Assist.
Convert Assist closed the gap in our product portfolio, giving customers the ability to create and monitor campaigns from first touch to lead conversion.
Convert Assist: Action Plan
LLM analyzes call transcript and customer provided context to write an action plan for follow up with a qualified lead.
Convert Assist: Smart Follow-Up
Building on the Action Plan, the GenAI model drafts an email template that the agent can use to maintain contact with lead.
Convert Assist: Call Coaching
Identifies key moments during the conversation, either as positives or areas for improvement.
Product Discovery
Business Impact
By giving teams autonomy while maintaining strategic alignment, we created an environment where calculated risks became learning opportunities rather than failures.
+9
AI features designed and tested.
Accelerated product discovery, user interviews, and usability testing.
+1
New product release.
Convert Assist bundles three of the most powerful AI features into one product: Action Plan, Smart Follow-Up, and Call Coaching.
+4
Features promoted to general availability.
Questions Asked, Appointment Scheduled, Multi-Conversation Insights, Self Reported Attribution.
24%
User adoption in Q1.
Opportunities identified through research and accelerated discovery provided real value to customers.