AMAZON

Affordability

Making Amazon one of the most affordable stores to shop, without overwhelming the customers.

Years
2024-present

Role
UX Lead

Impact
50+ Affordability products · VP-led UX initiative · Scaling to 5 markets¹.

Context

Customers rely on affordability signals to decide where to shop

Discounts, Deals, BNPL. Bank discounts. Cashback. Savings. From 2021-2024, I led or contribute to over 50+ affordability levers and CX launches in Amazon.

Affordability Discovery Framework

Problem

Affordability complexity confuses and frustrates customers

Affordability options multiplied, but so did confusion, customers couldn't calculate the real price and abandoned.

In 2024, we tried showing every affordability/deals at once. A user study surfaced Installments, Coupons, Bank Offers, and Cashback simultaneously: 18 price points, 9 landed prices.

Customers couldn't calculate the actual cost. They froze.

Amazon's SVP of International Stores saw this and demanded immediate action.

“Can I see the mocks for this? The analysis is very concerning.”

Senior VP, Amazon International Emerging Stores (In response to the fragmented Affordability experience)

UX strategy and principles

From showing everything to surfacing the best option

Negative test results and high business stakes triggered a VP-sponsored UX workshop. Through customer pain point analysis, we reframed the problem: this wasn't a layout issue, we were forcing customers to figure out affordability on their own. That insight led us to four design principles to evolve our affordability approach:

Feature the Best

One best option for pay-now. One for pay-later

Transparency Over Ambiguity

Real costs upfront. No hidden math

Honor Payment Intent

Adapt to what the customer came to do

Solidify Value & Trust

Make savings feel real

Short-term solution

Radical simplification through landed price clarity

Partnering with Product/Engineering, I proposed ML-powered treatments that personalize payment recommendations and collapse all affordability layers into the best pay now and pay later net effect prices per customer. These are two examples from a broader test matrix:

Agentic Shopping UX Vision

Long-term solutions

Affordability isn't a single-touchpoint problem. I defined a multi-year vision across 10 touchpoints from agentic AI shopping to post-purchase savings, to build trust, help customers save, and make value perception seamless across the entire journey.

Click to explore concepts across each touchpoint

10 touchpoints · 20+ concepts

Gen-AI Chatbots

Some concepts blurred for confidentiality. Full walkthrough available on request.

AI-augmented design process

Approach

In this project, I used AI-augmented approaches for vibe coding the prototypes, image generation, and agentic competitive benchmarking that improved productivity.

Vibe coding

✦ Rapid concept exploration and validation using generative AI video models.

Image generation

✦ Streamlining the creation of high-fidelity visual assets with multimodal assistance.

Agentic Benchmarking

✦ Evaluating and scaling autonomous agent performance across complex environments.

Near-term experiments (0 to 1)

Driving toward the vision

Driving toward the north star through near-term experiments, each launch is a building block toward the full vision. Weekly collaboration with product and engineering, grooming a 2026 roadmap of 12 experiments, 3 launched with positive business results:

“Recommended” label

✦ 8-Figure impact · Live in BR Q1’26