Humanizing AI: In-App Communication Strategy

Humanizing AI: In-App Communication Strategy

Driving financial engagement through personalized, intelligence-led messaging

Summary

Summary

Summary

I led the UX strategy & product to bridge the gap between AI decisioning and human-centered interface patterns. By treating the UI as a part of the machine-learning loop, we shifted from "shouting" at users to providing context-aware recommendations.

Outcome: first month

Outcome: first month

Outcome: first month

  • +10–30% improvement in click conversion, depending on the kind of communication (validated through controlled experiments).

  • +22% improvement in sales rate for products in the specific domain.

Research

Research

Research

1

Deep Benchmarking & Desk Research

  • Analyzed 41 apps: banks, digital wallets, fintech, investment brokers

  • Studied 8 main competitors to identify patterns in features, interface, and layout.

2

Journey Mapping

Mapped 15 financial products journeys, aligning different teams in a cross-transversal role to understand the overall experience from communication

Strategic Decisions

Strategic Decisions

Strategic Decisions

3

Context-Based Categories

I systematized communications into 8 life user goals categories based on user journey and pain points. This helped systematization for the AI algorithm.

4

Interruptive vs Passive

Not all messages deserve the same priority. I created a spectrum to create a shysthem related to IA

Communication Design System

5

Interface Patterns

By mapping interface patterns to specific user goal categories, I created a framework that connects AI logic to the user experience. These guidelines now empower internal teams to design consistent, context-aware AI communication across the product

6

Intelligent Components

Final components designed to appear contextually across the app — personalized and automated by AI based on each user's behavior and journey.

User closes message → Selects reason → AI learns → Better targeting

7

Guidelines: When to use each pattern

I created guidelines connecting user context to design patterns— so the AI knows when to interrupt and when to stay quiet.

Business Impact

Conversion Lift

10-30% higher conversion vs. traditional channels

Reduced noise

40% fewer dismissed messages after AI learning period

Team velocity

15 product teams now ship personalized communications