AI AGENT FOR CONTACTS
The end of manual list building: Meet the AI agent redefining audience targeting
Overview
AI-powered Contact Segmentation
Agent that creates smart customer
lists via chat, saving time while
boosting campaign accuracy,
engagement, and conversions.
MY ROLE
Led the end-to-end design and development of the Contact Segmentation Agent, driving cross-team collaboration while aligning product decisions with business goals and delivery timelines.
Design Lead & Project Owner
1
Translated customer pain points into intuitive AI workflows, defining agent behaviors and UX patterns that simplified segmentation for non-technical users and improved campaign efficiency.
Customer-Centric Strategy & Experience Design
2
Conducted competitive analysis on agent-led experiences, identifying gaps in contact management and defining how AI could streamline segmentation through chat-based interactions and smart recommendations.
Competitor Research & UX Designer
3
Worked closely with engineering during implementation, reviewing builds, validating edge cases, and QA testing flows to ensure design fidelity, usability, and a smooth production launch.
Developer Collaborator & QA Tester
4
PROBLEM STATEMENT
Managing contacts at scale was manual, repetitive, and inconsistent—making it difficult for customers to build accurate segments, discover high-value audiences, and run effective marketing campaigns.
GOAL
Create a smart segmentation experience that eliminates manual effort, enables reusable audience groups, surfaces high-value contacts, and helps customers launch targeted campaigns faster and more accurately.
RESEARCH & KEY INSIGHTS (SUMMARY)
User Pain Points
Customers struggled with manual filters, repetitive segment creation, and managing large contact lists, making targeted campaigns slow, inconsistent, and difficult to scale.
Market / Competitor Insights
Most platforms rely on rule-based segmentation and complex workflows, forcing users into dropdowns, spreadsheets, and repeated setup for every campaign.
Key Behavioral Findings
Users wanted faster ways to create audiences, reusable segments across campaigns, and automatic discovery of high-value contacts like inactive customers or loyal promoters.
"Segmentation needed to move beyond static filters toward an intelligent, adaptive experience that reduces friction, removes guesswork, and enables smarter targeting at scale."
Choosing the Right Solution Path
Based on research, I explored two possible ways to solve contact segmentation at scale.
AI Agent–Driven Approach
A conversational, adaptive segmentation experience powered by an intelligent agent.
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Natural language prompts replace complex filters
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Segments can be saved and reused across campaigns
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AI automatically surfaces high-value audiences
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Dynamic lists update in real time based on customer behavior
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Built-in performance analytics guide optimization
"While a traditional solution could reduce some friction, it wouldn’t fundamentally change how users create segments. An AI-driven approach allowed us to eliminate repetitive workflows, proactively surface opportunities, and create a scalable experience that works for both small and large customer databases."
Traditional Product-Led Approach (Without AI)
A rule-based experience built around filters, saved views, and manual segment creation.
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Advanced filtering with multiple conditions
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Saved segments with static rules
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Manual discovery of audiences
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Rebuilding or updating segments for new campaigns
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Limited scalability as contact volume grows
DESIGN STRATEGY
To translate the AI-agent approach into a meaningful user experience, I defined four core design principles:
Reduce Cognitive Load
Replace complex filters and rules with natural language inputs, allowing users to describe their audience in plain English.
Make Segments Reusable by Default
Enable users to save audience groups as static or dynamic lists, eliminating repetitive setup across campaigns.
Surface Opportunities Proactively
Use AI to recommend high-value segments based on behavior and lifecycle signals, helping customers discover audiences they might otherwise miss.
Keep Audiences Always Up-to-Date
Design dynamic segments that update in real time, ensuring campaigns always target the most relevant contacts.
Close the Loop with Performance Visibility
Provide segment-level analytics so users can understand impact and continuously optimize targeting.
"Managing contacts at scale was manual, repetitive, and inconsistent—making it difficult for customers to build accurate segments, discover high-value audiences, and run effective marketing campaigns."
KEY DESIGN DECISION
7 choices that shaped the Contact Segmentation experience.
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Shift from Filters to Conversational Input
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Design the Agent as a Task Partner, Not a Tool
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Make Segments Reusable Across the Ecosystem
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Enable Dynamic, Self-Updating Segments
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Surface AI-Recommended Audiences
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Integrate Segmentation Directly with Campaign Activation
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Provide Segment-Level Performance Feedback
User Flow &
Agent Interaction Model
AI-Recommended Segments
Pre-built audience templates • Reduced setup time • Lower manual effort • Discover high-value audiences • Scalable targeting from day one
Agent-Led Segment Creation
Conversational prompt interface • Quick intent options upfront • Filters auto-generated by AI • Reduced cognitive load • Faster audience creation
Advanced Condition Builder
Manual rule customization • Condition grouping logic • Real-time audience preview • Precision targeting • Confident decision-making
Segment Performance Tracking
Audience growth analytics • Segment churn visibility • Campaign effectiveness tracking • Engagement breakdown • Smarter iteration decisions
Segment-Based Campaign Activation
Use segments across campaigns • One-click audience selection • Trigger automations by segment • Eliminate manual contact selection • Target with precision at scale
Impact
The redesigned Contact Segmentation experience enabled businesses to manage and activate large contact databases with greater efficiency and control.
Customers reported that the workflow felt intuitive and flexible, making it easier to create and refine audience segments without complexity.
The solution significantly reduced manual effort, eliminating repetitive setup tasks and saving operational time.
Businesses were able to consistently target the right audience, improving the precision of marketing and review campaigns.
The streamlined setup improved usability and lowered the learning curve for new users.
THANK YOU FOR COMING ALONG ON THIS JOURNEY.