Firebrand Flywheel
Maximizing backlist sales with intelligent, data-backed metadata ehancements
Unlock Hidden Revenue in Your Backlist
Your backlist is one of your most valuable assets, but identifying which titles are poised for renewed success can be difficult and time-consuming. Flywheel is an data-driven metadata optimization service that uses proprietary data models and machine learning to identify titles with the greatest opportunity for increased discoverability and sales.
By analyzing retailer trends, consumer behavior, and title performance data, Flywheel pinpoints the books most likely to benefit from targeted metadata enhancements. The result is increased visibility, stronger conversion rates, and meaningful sales growth—helping publishers maximize the value of their existing catalog without increasing marketing spend.
Flywheel tracks real-time retailer trends and consumer behavior to pinpoint the exact books most likely to benefit from targeted metadata improvements
Features of Firebrand Flywheel
Intelligent Recommendation Engine
We use data science and machine learning to analyze sales history and statistical trends. This allows us to accurately pinpoint which backlist titles will sell right now.
Targeted Metadata Enhancements
Let our experts optimize your keywords, BISAC subjects, and book descriptions. We utilize AI-supported tools to sharpen product information and drive conversions.
Success-Based Fee Structure
Enjoy a risk-free investment where you only pay a percentage of the net sales increase. We won't make money unless you make money.
Algorithmic Retail Optimization
Leverage natural algorithmic testing on major retail sites like Amazon to systematically increase glance views. Watch your sales rank and overall revenue climb.
Actionable Results Dashboard
Monitor your ongoing success with an intuitive dashboard. Easily review sales predictions, discoverability rankings, and conversion rates to track your exact ROI.
Automated, Hands-Free Execution
Streamline your workflow by letting our experts handle the heavy lifting. We implement data updates and continuous optimizations seamlessly, maintaining sales momentum with virtually no impact on your existing workforce's time.
Go Deeper: Flywheel
See how Flywheel unlocks the hidden revenue potential in your backlist catalog
Flywheel is a revolutionary backlist sales and marketing service powered by data science and machine learning. By analyzing historical sales data, statistical predictions, and current events, our recommendation engine strategically identifies which backlist titles are primed for optimization at the exact right moment.
The real value is in effortless revenue growth. With expert metadata enhancements, algorithmic retail testing, and a risk-free success-based fee structure, your team can consistently boost discoverability and conversions without draining their own time and resources.
Download our product flyer to explore the full capabilities of Flywheel and discover how it can create unstoppable momentum for your backlist book sales.
While Flywheel helps publishers identify individual titles with immediate sales-growth potential, our separate Metadata Review Service takes a broader view—analyzing the health of your entire catalog and providing a clear, actionable plan for metadata improvement.
Whether you're preparing for a catalog cleanup project, evaluating metadata quality across thousands of titles, or simply looking to improve discoverability at scale, our Metadata Review Service provides the insights needed to prioritize your efforts and maximize impact.
What We Assess
Our automated quality assessment benchmarks your catalog against publishing industry best practices across four critical metadata elements:
Keywords
Evaluate search terms and discoverability signals to identify opportunities for improved retailer and consumer search performance.
BISAC Codes
Verify that titles are categorized accurately and strategically to align with retailer merchandising systems and recommendation algorithms.
Author Biographies
Assess author information for completeness, consistency, and reader engagement potential.
Long Descriptions
Analyze consumer-facing copy to identify opportunities for stronger discoverability, merchandising, and conversion.
Countless studies prove that high-quality metadata directly correlates to increased book visibility and revenue. For example, a study by Nielsen showed that properly enriched titles can generate up to 75% higher average sales. However, knowing where to begin a data cleanup project across a vast catalog is often a daunting hurdle for publishers. Utilizing the powerful assessment tools also utilized in Flywheel, the Metadata Review Service runs your entire product list through an automated quality assessment, benchmarking four critical elements—keywords, BISAC codes, author biographies, and long descriptions—against proven industry standards. You receive a comprehensive action report paired with two 30-minute expert consultations (before and after your cleanup) to ensure your team's remediation efforts translate directly into increased discoverability and a maximum return on investment.
What You Receive
The result is a detailed metadata health report that highlights strengths, identifies gaps, and prioritizes opportunities for improvement. Armed with clear recommendations and data-backed insights, your team can focus resources where they will have the greatest impact on discoverability, customer engagement, and long-term catalog performance.

Frequently Asked Questions about Firebrand Flywheel
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How big does my publishing house need to be to participate in Flywheel?
The Flywheel service is available to mid-size and larger publishers. We have found that a minimum of 500 backlist titles (3 years old or older) is a good starting place. Additionally, due to the nature of the data being utilized, this service is currently only available to publishers using the Amazon Vendor Central program. Advantage, KDP, and Seller Central do not currently provide the data needed to support Flywheel’s recommendation engine.
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How do we signal relevance to retailer algorithms for older backlist titles whose sales have flatlined?
Retailer algorithms often deprioritize books with stale, unchanging data. Flywheel takes advantage of natural algorithmic testing on major retail sites like Amazon by strategically injecting targeted metadata changes—such as refreshed keywords and BISAC subjects—at the optimal time. This active “data freshness” helps the algorithm re-index your titles, systematically increasing glance views, customer conversions, and your overall sales rank.
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How can we optimize our backlist metadata to appear in modern AI search engines and conversational recommendations?
Modern AI search tools require deep, semantically rich data to accurately recommend your titles. Flywheel’s metadata experts utilize proprietary machine learning tools to sharpen and expand your book descriptions and author bios using your already-published content. This process provides the dense, highly relevant context that advanced search algorithms crave, ensuring your books are highly discoverable.
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What is the most efficient way to audit and enhance metadata for a massive backlist of thousands of titles?
Manually auditing thousands of titles via spreadsheets is prone to error and wastes valuable staff time. Flywheel’s Recommendation Engine does the heavy lifting for you. Using data science and machine learning, the system analyzes statistical predictions, current events, and your historical sales data to pinpoint exactly which titles in your vast catalog have the highest potential to sell right now, allowing you to focus your efforts only where they matter.
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As we update our backlist to meet strict new global compliance standards, how do we simultaneously ensure the data actually drives revenue?
Compliance and revenue generation must go hand-in-hand. While our Eloquence on Demand service automatically handles the technical delivery of highly compliant, modern ONIX feeds to your global partners, Flywheel acts as your strategic marketing engine. It ensures that the core data going into those feeds—such as modernized BISAC codes and optimized keywords—is actively working to uncover hidden sales opportunities and maximize your ROI.
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Should we invest in a full relaunch with new covers to revive dead backlist sales, or just update the metadata?
Updating metadata and digital assets is often a much more cost-effective and immediate way to build sales momentum. Flywheel's experts enhance your existing product descriptions to capture trending market themes, and can even create engaging A+ banners and additional product images to completely refresh the book's retail presence without the massive overhead of a complete cover redesign.
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What is the actual ROI on refreshing metadata for older backlist titles?
In a recent six-month period, Flywheel increased sales for four publishers by over 46,000 units, bringing in nearly $1 million in unexpected revenue. We see an average 10-15% increase in sales on backlist titles in the program. The ROI with Flywheel is entirely risk-free and guaranteed to be positive. Flywheel operates on a purely success-based fee structure—we only bill a percentage of the net increase in Amazon sales for the specific titles we enhance. We won't make money unless you make money.
Frequently Asked Questions about the Metadata Review Service
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Why should we invest time and resources in auditing our backlist metadata?
While most publishers focus heavily on new frontlist releases, industry data shows that approximately 70% of all book unit sales come from the backlist. Furthermore, studies indicate that titles with optimized basic metadata experience 75% higher average sales than those without. Auditing your backlist is a highly strategic, cost-effective way to drive immediate revenue without acquiring new content.
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Which specific metadata elements does the assessment analyze?
The review zeroes in on the four critical pillars that drive modern search algorithms: Keywords, BISAC subject codes, Author biographies, and Long descriptions. Optimizing these specific areas drastically improves discoverability.
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What deliverables and support do we receive with this service?
You receive a comprehensive action report detailing exactly where your current metadata falls short of industry standards, paired with a 30-minute expert consultation call to help your team build a practical, revenue-driving cleanup roadmap. Once your team completes the data remediation (which must be done within one year), we run the automated assessment a second time and provide another 30-minute consultation to validate your improved data compliance.
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How does this service help our catalog perform better on Amazon and other retail sites?
The vast majority of consumers find books via search engines rather than browsing category trees. Our automated assessment evaluates the density and structure of your data—such as keyword string lengths, character and word counts, and the use of meaningful, retailer-accepted HTML tags—to ensure your product listings are perfectly formatted to be indexed and prioritized by advanced retail search algorithms.
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What is the cost structure for the Metadata Review Service?
The Metadata Review Service is available for a small, one-time fee (typically ranging from $600 to $1,000, depending on product count). This gives your organization access to high-level strategic intelligence, actionable reporting, and personalized expert consulting to maximize your backlist ROI, completely free of any ongoing financial commitments.
