Designing proactive decision support for e-commerce
Timeline
2–3 weeks
Platform
Mobile (iOS)
Role
Product Designer
Year
2025
A concept project exploring how AI can move beyond chatbots to become a proactive service layer within retail apps—helping users make better purchase decisions in real time.
Retail apps are optimized for transactions, not decisions.
Users often complete purchases without full awareness of better alternatives, leading to post-purchase regret and reduced trust.
94% of users drop off by Day 30
Users discover better deals too late
Decision-making lacks clarity and support
The issue is not lack of options, but lack of guidance.
Users often ask:
Am I getting the best deal?
Is there a better alternative available?
Should I buy this now or wait?
How does this compare to other options?
Am I spending within my goals?
Users don’t need more choices they need better decisions.
Value must be surfaced during the decision-making moment, not after the transaction is complete.
The experience introduces a set of AI-driven interventions that assist users across the shopping journey:
Smart Swap: Suggests better alternatives in real time
Goal Tracking: Encourages mindful spending
Comparison Cards: Builds trust through transparency
Together, these features transform shopping from a passive experience into an informed, guided journey.
Smart Swap : Real-Time Value Optimization
Smart Swap detects when a user is about to make a suboptimal purchase and suggests a better alternative in context. Instead of requiring users to search and compare manually, the system proactively highlights options that offer higher value.
Reduces post-purchase regret
Increases perceived value
Improves decision confidence
Designing AI as a proactive service layer, not a chatbot.
Instead of waiting for user queries, the system anticipates intent and surfaces relevant insights at the right moment helping users act with confidence.
Proactive, not reactive
Assist decisions, not just actions
Reduce friction, not add features
Build trust through transparency
Transparent Comparison for Better Decisions
Instead of hiding alternatives, the system surfaces side-by-side comparisons, allowing users to evaluate options based on price, value, and relevance. This builds trust by making the decision process visible and understandable.
Improves trust in the platform
Reduces cognitive load
Enables faster decisions
The experience is built around a continuous feedback loop:
User Action → AI Insight → Decision → Outcome → Learning
Each interaction improves the system’s understanding of user behavior, allowing it to deliver more relevant and timely suggestions over time.
Goal-Based Spending Awareness
Users can set spending goals, and the system provides real-time feedback on how each purchase impacts their progress. This shifts behaviour from impulsive buying to intentional spending.
Encourages responsible spending
Builds long-term engagement
Creates a sense of progression
Transparent Comparison
Surfaces side-by-side comparisons to help users evaluate options clearly.
• Improves trust in the platform
• Reduces cognitive load
• Enables faster decisions
The proposed system is expected to:
Increase user retention through meaningful engagement
Improve average order value through better decision support
Reduce post-purchase regret
Strengthen user trust in the platform
This project explores a shift from transactional design to decision-centered experiences where the system actively supports users in making better choices, not just completing actions.