Writing · Blog
Siftbooks 2025 Vision
Loading...
For over two years, we've been building Siftbooks to help sensitive audiobook listeners enjoy the stories they love—without unwanted profanity or offensive content. We started with a simple premise: there should be an easy way to filter audiobooks.
And in those two years, we learned something critical:
👉 Manually editing audiobooks isn't scalable.
At first, we focused on editing audiobook content by hand. This was a necessary step—it allowed us to validate problem-solution fit, engage with users, and confirm demand.
But it also exposed a fundamental flaw: manual editing without an efficient tagging system will never scale.
The timing for an automated Siftbooks solution couldn't be better.
📈 Audiobooks are booming. The industry is projected to reach $10 billion by 2030, with more listeners than ever before.
🎧 Cultural shifts demand more inclusivity. A significant portion of audiobook listeners—parents, educators, and sensitive listeners—seek clean, customizable listening options, yet mainstream platforms like Audible fail to provide them.
🔍 Market gaps leave users underserved. Current alternatives—skipping sections, avoiding entire genres, or relying on unreliable content warnings—are inefficient and frustrating.
🚀 Siftbooks is positioned to fill this gap. By creating a seamless, scalable way to customize audiobook content, we're tapping into a multi-million-dollar opportunity.
We started with manual editing because:
1️⃣ It kept us close to our customers. We could refine the product based on real feedback.
2️⃣ It validated demand. If no one cared, we would have known early.
3️⃣ It required minimal technical buildout. We didn't need a fully automated system to test the market.
These were the right assumptions early on. But as we grew, it became painfully obvious:
❌ It took too long. The compounding time of manual editing was overwhelming.
❌ Scaling required an army of editors. Hiring a large team to manually review audiobooks wasn't viable.
💡 We learned that while manual work is great for validation, it's a terrible business model.
That brings us to MVP v2—a shift toward automation and scalability.
We focus on automating everything we can. We'll keep human oversight where it matters. We'll add manual touch points where they make sense.
This means:
✅ Automated Predictions: We accept our model's predictions to filter offensive words/phrases. We put in place speech-to-text for reliability.
✅ Mobile Automated Filter: Our app uses the content map to skip flagged content.
❌ Human Review: This won't be included in our initial MVP v2 but can be added in the 180 days following. This will allow us to make updates to the content map.
A big unknown is whether customers will tolerate initial flaws in filtering.
🚨 The risk: Inaccurate automated predictions could upset customers and ruin the business model before we scale.
Our short-term strategy:
🔹 Launch with an MVP that prioritizes speed and automation—even if it's not perfect.
🔹 Monitor user feedback
🔹 Roll out human-reviewed content maps in the following 180 days to improve accuracy.
Ultimately, we believe customers will choose a faster, imperfect solution over a slow, perfect one. The key is managing expectations and evolving quickly.
This shift requires focus, execution, and a clear path forward.
Our 90-day plan breaks this transition into:
📌 Sprint 1: Split Audio Chapters
📌 Sprint 2: Speech to text (Deepgram)
📌 Sprint 3: Run Predictions
📌 Sprint 4: Enable Mobile Listening
📌 Sprint 5: Fetch Content Map
📌 Sprint 6: Skip Filtered Audio
By the end of this roadmap, we will have:
🎯 A working prototype of an automated audiobook filtering system.
🎯 A pipeline that removes the manual touch points.
🎯 A scalable model that makes Siftbooks a real business—not just a project.
Now that we've validated the problem and built the foundation for a scalable solution, the next phase is all about traction. Without traction, even the best product doesn't survive.
To systematically find our best growth channel, we're using the Bullseye Framework—a five-step process from Traction by Gabriel Weinberg and Justin Marestraction. The goal is to identify one channel that consistently delivers predictable, scalable customer acquisition.
Rather than defaulting to the "obvious" channels (SEO, paid ads), we're consider all 19 traction channels to ensure we don't miss hidden opportunities. Here are some I suggest we explore:
✅ Viral Marketing (Referral Engine) – A referral program that rewards users for sharing Siftbooks.
✅ Search Engine Marketing (Google Ads) – Paid ads targeting VidAngel-related keywords (e.g., "VidAngel alternative," "clean audiobooks").
✅ Content Marketing – Blog posts on "best clean audiobooks", comparisons to VidAngel, and SEO-driven guides.
✅ Email Marketing – Capturing leads via free guides (e.g., "The Ultimate List of Clean Audiobooks") and nurturing them through automated sequences.
✅ Community Building – Engaging faith-based and family-friendly communities to create organic word-of-mouth traction.
✅ Targeting Blogs – Partnering with influential bloggers in parenting, homeschooling, and faith-based niches to drive referrals.
Each of these represents a possible path to traction. The next step is narrowing down the best ones.
We categorized our channels into three groups:
1️⃣ Viral Marketing (Referral Engine) → High-impact, low-cost user growth.
2️⃣ Search Engine Marketing (Google Ads/FB Ads) → Immediate traction potential if cost-effective.
3️⃣ Email Marketing → Cold manual outreach to VidAngel users we can find online.
4️⃣ Content Marketing → Long-term organic growth & credibility.
5️⃣ Community Building → Driving long-term brand trust and referrals.
6️⃣ Targeting Blogs → SEO benefits and third-party credibility.
Offline Ads, Trade Shows, Public Relations – May be useful later but not right now.
To validate the top three channels, we'll run small-scale experiments over the next 4–6 weeks:
After the 6-week testing period, we'll analyze results:
✅ If viral marketing works, we'll optimize incentives & gamify referrals.
✅ If Google/FB Ads convert profitably, we'll scale spend and refine targeting.
✅ If Email Marketing drives leads, we'll double down on manual outreach.
If none of these channels deliver sustainable traction, we'll reiterate the Bullseye Framework and test new channels.
Once we've identified our best traction channel, we'll fully commit to scaling it:
📌 Optimize the viral loop → Improve referral incentives, make sharing easier.
📌 Increase ad spend on Google/FB Ads → Scale winning campaigns while keeping CAC (customer acquisition cost) low.
📌 Leverage email marketing → Use lead nurturing to improve conversions. Additionally, find bulk email lists to contact.
Our goal is to create a predictable, scalable growth engine—one that brings in consistent new users at a cost we can sustain.
We've validated the need. We've built MVP v2. But without traction, nothing else matters.
This plan ensures we:
✅ Don't waste time on random marketing tactics.
✅ Systematically test channels and double down on what works.
✅ Turn Siftbooks from a product into a GROWING business.
This is how we win. Let's make it happen.
This roadmap gives us a clear, focused plan to get Siftbooks off the ground and into the hands of thousands. To accelerate this growth, we can explore funding opportunities with investors/advisors who share our vision for making audiobooks accessible to everyone. Now, it's all about execution.