SeriesSense
Executive Summary
Vision Statement
To become the trusted authority for clear, accurate reading order information, empowering readers to make confident choices and enjoy seamless journeys through complex book worlds.
Problem Summary
Readers of romance and fantasy romance are increasingly frustrated by books marketed as 'standalones' that actually require prior knowledge from other series or books. This leads to confusion, wasted time, and a sense of betrayal, as highlighted by numerous top-voted Reddit comments and echoed in recent web discussions. The lack of clear, upfront reading order guidance—especially for interconnected worlds—forces readers to hunt through forums and websites, diminishing their reading experience.
Proposed Solution
SeriesSense is a web platform and browser extension that aggregates crowd-sourced and author-verified reading order information for interconnected book series. It flags true standalones, exposes hidden dependencies, and provides clear, spoiler-free guidance on what to read first. The platform integrates with popular book sites and offers a simple interface for both readers and authors to contribute and verify data.
Market Analysis
Target Audience
The ideal SeriesSense user is a voracious reader, aged 18-45, who enjoys romance, fantasy, and interconnected series. They value their time, dislike spoilers, and are frustrated by unclear reading orders. Many are active on Goodreads, Reddit, BookTok, and book blogs. Secondary audiences include librarians, book club organizers, and authors seeking to improve reader satisfaction.
Niche Validation
The Reddit post and its highly upvoted comments provide strong validation for this niche. Multiple users express direct frustration, confusion, and annoyance with the current state of 'standalone' marketing and the lack of reading order transparency. The pain point is urgent, repetitive, and widely shared, indicating a real market need.
Google Trends Keywords
Market Size Estimation
Active digital readers of romance/fantasy who use Goodreads, Reddit, BookTok: ~10M users in US, UK, Canada, Australia.
Initial obtainable market: 100,000–250,000 users via targeted launches in online romance/fantasy communities and book platforms.
Global English-speaking fiction readers: ~250M people. Assuming 20% actively read romance/fantasy genres, TAM is ~50M potential users.
Competitive Landscape
Existing solutions like Goodreads and Book Series In Order offer partial reading order info but lack clear flagging for true standalones and often rely on incomplete or unverified user submissions. FictFact (now defunct) attempted series tracking but did not solve the standalone confusion. No major platform offers integrated, author-verified, or community-flagged reading order clarity for interconnected series.
Product Requirements
User Stories
As a reader, I want to know if a book marked as 'standalone' actually requires reading previous books or series.
As a reader, I want to see a clear, spoiler-free reading order for interconnected series.
As an author, I want to verify and flag my books' reading order to reduce reader confusion.
As a publisher, I want to provide official series data to improve discoverability and reader satisfaction.
MVP Feature Set
Crowd-sourced and author-verified reading order database
Standalone vs interconnected flagging for each book
Browser extension for instant reading order info on major book sites
Simple UI for submitting reading order corrections and feedback
Non-Functional Requirements
Fast response time (<500ms) for reading order queries
High data accuracy and spoiler control
Scalable architecture for high traffic spikes
GDPR-compliant data handling
Key Performance Indicators
Monthly Active Users (MAU)
Number of verified reading orders
User-reported confusion/clarity scores
Premium conversion rate
Retention rate after first use
Data Visualizations
Visual Analysis Summary
The following chart visualizes the frequency and intensity of reader frustration with unclear reading orders, based on Reddit comment engagement and sentiment.
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Go-to-Market Strategy
Core Marketing Message
Stop wasting time and avoid spoilers—SeriesSense instantly reveals the true reading order for any interconnected book series, so you can read with confidence.
Initial Launch Channels
- Targeted posts in r/RomanceBooks, r/Fantasy, r/BookRecommendations, and related subreddits
- Launch on Product Hunt with demo integrations
- Collaborate with BookTok influencers and Goodreads group moderators
Strategic Metrics
Problem Urgency
High
Solution Complexity
Medium
Defensibility Moat
SeriesSense builds defensibility via a growing database of verified reading orders, user-generated flags, and author partnerships. Network effects emerge as more readers and authors contribute, improving data quality. Integration with major book platforms and a reputation for spoiler-free accuracy further strengthen the moat.
Source Post Metrics
Business Strategy
Monetization Strategy
Freemium model: free core features for all users, with paid premium tiers offering advanced filters, integration with Kindle/Goodreads, author dashboards, and ad-free browsing. Additional revenue from affiliate links to book retailers and premium publisher partnerships.
Financial Projections
Assuming 2% conversion of 100,000 active users to a $5/month premium plan, initial MRR is $10,000. With affiliate revenue and publisher partnerships, total MRR could reach $15,000–$25,000 within 12–18 months post-launch.
Tech Stack
Node.js with Express for scalable API development, with Python microservices for data aggregation and NLP (natural language processing) tasks.
PostgreSQL for relational data management, supporting complex series relationships and user contributions.
Next.js for its SEO, performance, and rapid prototyping benefits, combined with Tailwind CSS for flexible UI design.
Goodreads API for book metadata, Stripe for payments, OpenAI API for NLP-driven reading order extraction, AWS S3 for user-uploaded content.
Risk Assessment
Identified Risks
- Difficulty in obtaining accurate reading order data for less popular or indie series
- Potential resistance from publishers or authors who prefer ambiguity in series marketing
Mitigation Strategy
- Incentivize authors and publishers with 'verified' badges and improved discoverability
- Use NLP and community voting to triangulate accurate reading orders, flagging uncertainty where needed