Accelerating publishing through AI

Target User:

Indie authors

Team:

2 Product Managers

5 Developers

1 Business Intelligence - Data analyst

2 ML engineers

1 UX designer

My Role:

UX designer & Research

Focus area

Human-AI interaction

Usability test

Background:

Kindle Direct Publishing offers cover creator to their 1 million+ users. Currently, cover creator offer assets lacks modern stock images, fonts and templates. The information like book title, author name are repopulated on cover if author use KDP cover tool to create covers.

Problem Statement

In Amazon's vast marketplace, compelling book covers make or break success. Authors face impossible choices when its comes to cover creation. Kindle Direct Publishing offers cover creator to their users. The cover creator generates accurate files compatible with specifications. However, design templates and assets are old and costly to keep updated. They spend hundreds on professional designers or settle for amateur DIY results or wrestle with complex software and risk rejection from publishing platforms.

User Needs

Indie authors need to transform their cover creation nightmare into a delightful, few-click journey that delivers sales-magnetic designs. They want professional, platform-perfect covers without draining their wallets or drowning in design complexities.

Solution

Our AI-powered solution can transforms the book cover design landscape forever. The system combines three powerful engines: a Design Intelligence Engine that analyzes millions of successful covers to understand genre-specific patterns and emotional triggers, a Smart Typography System that optimizes text for maximum impact and readability, and a Technical Compliance Module that ensures platform-perfect specifications across all formats.
By analyzing author’s uploaded manuscript, book details, and previous titles, the system generates multiple design options tailored to unique author brand and genre requirements. Authors can shortlist their preferred designs, and the AI learns from these preferences to generate even more refined options. This intelligent feedback loop ensures each new cover not only stands out in the marketplace but also maintains visual consistency with your author portfolio, all while perfectly adhering to publishing platform specifications.

Design Process 🔒

Reach out to kasturiparanjpe@gmail.com for more information.


Amazon - 2024

UX strategy

Participatory design

Juniper Networks - 2020

Data visualization

Information architeture

Amazon - 2023 - 2024

Human-AI interaction

Usability testing

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