AMAZON, NEXT BILLION USERS

Designing a fully assistive e-shopping experience for emerging markets

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👉  THE PROBLEM

Consumers in emerging markets like India are not able to shop online due to transaction barriers.

đź“ś  CONTEXT
India is a mobile first nation where people where people access internet mostly through prepaid data and where there is only 1 hotstop per 3,900 people. Hundreds of millions of users face transaction barriers due to flaky internet, payment methods and other reasons such as trust, language, lack of access and education.
đź‘©   ROLE
Worked with the New Initiatives Team (marketing + tech team) at Amazon India for designing an e-commerce shopping experience for Rural India.

⏱   DURATION
May - July 2015
THE MISSION

The mission is to enable everybody in India shop online which led to the creation of Amazon Easy.

WHAT IS AMAZON EASY?

Amazon Easy is a service that will place tablet devices loaded with the Amazon Easy app at the brick and mortar stores/points in tier 3+ towns in India. Amazon Easy relies on a fully assisted shopping model.

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User Research .

Understanding user needs, behaviors and the domain



Competitior Analysis

We conducted competitor analysis across all the major e-commerce sites in India that were extending efforts to deliver products In rural parts of India.

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On-Field Research

Users were recruited on the field through a set of screening criteria and the places of study were chosen based on the matrix in the illustration.

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The study consisted of both foundational and evaluative approches to understand product gaps, users needs and behaviours.

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Finding + Analysis .

Top insights about users needs and behaviours



Five themes emerged after conducting an affinity analysis of the research data.

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Key insights about consumers in emerging markets.
Check out the theme cards below:
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Experience Mapping

We identified the major concerns and pain points users in rural India had around online shopping and generated an experience map highlighting these.

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Personas

Distinct personas of the customer (primary) and shop owner (secondary)were created highlighting their capabilities, concerns and wants.

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Concepts and Features .

How did we turn research insights into product features?



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Design and Prototype .

The Amazon Easy App



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THE ENTRY POINT

Prominent search bar, locally relevant verticals in home page allow easy search.

Problems solved:
• Return and support features in the nav bar create awareness and build trust in users.

• Locally revelant analogies are used such as Bag for Cart.

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PRODUCT DISCOVERY

The sub-category page is brand driven and quick filters help in quicker navigation.

Problem solved:
• Brand driven filters and brand based sub-category verticals are built to suit the mental categorization of users.

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PRODUCT DETAIL PAGE

Details on demand, visual representations and localized reviews help in product evaluation.

Problems solved:
• Prioritization of product details and locally relevant details helps in efficiency.

• Local reviews help users to relate more and evaluate products better.

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CHECKOUT

Users can edit products in bag and can checkout using OTP.

Problems solved:
• Mobile OTP based login and checkout eliminates the need for email ids.

• SMS based updates and feedback makes the process smoother for a mobile-first market.

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User Journeys and Architecture .

Proposed design structures



Proposed User Journey

A user journey for the assisted shopping model was proposed where the consumer orders from an in-store tablet with the assistance of the shop owner and waits to pick-up from the same store where the order will be delivered. The illustration besides shows the different steps the consumer has to go through.

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Architecture

Based on the several concepts generated, we narrowed down to a the final concept and generated information architecture for the tablet app.

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Reflections .

My top learnings at Amazon



OWNERSHIP

Own your decisions

As a UXer, I took the responsibility of communicating the value of user research horizontally and convinced the team to do more foundational research, which in turn helped me take data-driven decisions and influence product strategy.

ITERATE

Gather Feedback

The internship taught me the value of connecting with cross-functional teams and gathering feedback. Their feedback helped me iterate on my designs and on a higher level, it helped me grow more as a T-shaped designer.

STORYTELLING

Stories vs Presentations

People remember stories more. My first industry experience helped me hone my storytelling skills both as a researcher and designer.