This episode teaches a practical, author-friendly playbook for building a repeat‑buyer machine using a five‑part story arc in your email funnel. You’ll get a clear framework that blends narrative marketing, format cross‑promotion (ebook, paperback, audio), and simple AI prompts to speed copywriting while keeping everything human‑reviewed. I break down subject-line hooks, timing, microoffers (previews, audio clips, workbook tie-ins), and conversion triggers that protect author brand and royalties. Expect exact language you can adapt, a short real-world case that shows the sequence lifting repeat purchases, and a one‑minute immediate action you can do today to draft your first funnel email. Feasible for solo authors with limited tech skills, this episode keeps instructions tactical so you can implement within a few hours and start measuring results.

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Many authors treat audiobooks as an afterthought. This episode flips the script: an audiobook-first funnel turns spoken-word assets into your primary marketing engine — driving reviews, newsletter subscribers, and cross-sales for ebook and print. In an eight-minute, highly tactical monologue you’ll get five numbered steps that cover choice of narration approach, low-cost production checks that protect conversion, how to craft an audio-first lead magnet, Amazon/Audible optimization tactics that amplify discoverability, and a compact launch sequence that converts listeners into buyers and subscribers. I walk through a concrete example of a nonfiction author who used a 10-minute free audio preview, targeted Audible promos, and a short narrator-hosted sequence to double email opt-ins and lift overall catalog sales. You’ll finish with one immediate action you can take today to start an audiobook-first funnel and a clear CTA to get publishing help for production or ACX strategy.

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Stop treating books as one-offs. In this episode you'll get a clear, tactical 5-step formula for designing a book series that creates catalog momentum, increases lifetime reader value, and makes cross-format production (ebook, paperback, audiobook, mini-workbooks) a repeatable play. I'll explain how to choose the ideal entry point, structure series cadence, stack formats for maximum per-reader revenue, and automate cross-promotion on Amazon and in your email funnel. You’ll hear a short case study of an indie author who turned a three-book set into a steady revenue engine by reordering releases and adding audio-first previews. By the end you’ll have three immediate tasks you can complete this week to start turning your manuscript into a scalable series. Stick around for a custom CTA to get hands-on publishing help from 22 Lions if you want a fast, guided rollout.

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Many authors see a burst of downloads on launch day, then tumble into silence. This episode gives a practical recovery plan you can implement in a single week to convert that stalled momentum into an evergreen sales engine. I walk through five numbered fixes—page conversion, targeted paid micro-buys, an audiobook snippet test, a low-cost promotional cadence, and a one-email funnel repair—explaining what to change, why it works, and the precise metrics to track. You’ll hear a short anonymized 22 Lions case: an author who tripled weekly revenue by prioritizing page conversion and running a focused $50 ad experiment. The steps are feasible, measurable, and safe for authors using AI tools responsibly. By the end you’ll have one immediate action to run in the next 24 hours and a clear sequence to follow over five weeks toward sustainable sales. Episode ends with a direct CTA to 22 Lions publishing services for hands-on relaunch support.

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Most authors focus on a single price or a one-off promo and miss the bigger opportunity: a coordinated price ladder across formats that turns one reader into multiple purchases. In this 8-minute monologue you'll get a clear 3-step framework for mapping reader value, choosing three strategic price points across ebook, print, and audio, and running low-cost tests that prove what actually increases lifetime revenue. I break the framework into numbered, actionable steps, share a brief case example of an indie nonfiction author who increased average revenue per buyer by 42% in one quarter, and finish with an immediate checklist you can apply today. No hype—just practical pricing mechanics, compliance notes for KDP/ACX, and metrics to watch so you can scale pricing decisions with confidence.

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Many authors publish and wait—then wonder why their book isn’t selling. This episode gives a tactical, numbered 10-point audit you can complete in one sitting to diagnose and fix the most common conversion leaks on an Amazon book page. I walk through metadata, cover psychology, blurbs, formatting signals, pricing, categories, keywords, review hygiene, audiobook cross-signals, and a fast ad micro-test. Each point includes the exact change to make, why it matters for both readers and Amazon’s algorithm, and an expected short-term metric to watch. I close with a real before-and-after mini case study showing a measurable lift after three targeted tweaks and a single immediate action you can complete in five minutes. This episode is practical, ethical, and designed for authors ready to iterate fast and prioritize what moves the needle.

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Before you spend on ads or rewrite your entire book, your ARCs hold the fastest signals to improve launch performance. In this compact news-recap Dan and Aria walk listeners through an ethical, low-cost "ARC Sprint": a repeatable workflow that uses AI to synthesize reader notes, quantify sentiment, and translate feedback into three high-impact actions you can ship in 48–72 hours. We cover how to collect structured ARC responses, run extractive summaries to surface recurring complaints and hooks, prioritize fixes by conversion impact, and convert top signals into a blurb rewrite, one targeted manuscript tweak, and two ad/metadata hooks. The episode includes prompt templates, a simple scoring rubric for prioritization, and a mini A/B test plan so authors and small publishers can validate changes quickly. Ideal for indie authors, ghostwriters, and small presses who want to turn early reader input into measurable sales lift without derailing a launch.

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Authors obsess over covers and ads but often overlook the goldmine in public reviews. This episode teaches a repeatable, ethical workflow for using AI to analyze competitor reviews, cluster common complaints and praise, and translate those signals into concrete updates: blurb tweaks, sample rewrites, micro-edits in the opening chapters, and targeted backmatter. Dan and Aria walk through a three-part framework authors can run in a few hours: scrape and cleanse review data, use AI to extract themes and sentiment, then prioritize and implement the top fixes that move the conversion needle. Listeners get tactical prompts, low-cost tooling options, and a short A/B test blueprint so changes are measurable. Ideal for authors with 1–10 titles who want a data-driven path to better conversions without rewrites or expensive redesigns.

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Too many indie launches fail because metadata — title, subtitle, cover, blurb, price — is chosen by guesswork. This episode teaches a practical, repeatable 'Pre-Launch Metadata Lab' authors can run in a week to validate the single metadata combo that will convert best on Amazon. Dan and Aria explain which off‑Amazon channels give the clearest signals (email polls, targeted micro-surveys, BookTok/Reddit blind posts, private reader panels), how to frame A/B prompts so results map to Amazon behavior, and a lightweight cadence for testing without delaying launch. You’ll get a simple decision rule to pick a winner, a checklist of tracking metrics to collect, and one ethical testing tactic that prevents gaming algorithms. Ideal for authors prepping a first book, a relaunch, or a catalog refresh — run the lab once and use the framework forever.

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Authors often pick a single price and hope for the best. This episode teaches a repeatable, ethical way to run short, controlled pricing windows on KDP using AI to generate test hypotheses, predict elasticity, and interpret signals (sales velocity, conversion rate, BSR, and KU read trends). Dan and Aria explain how to plan 48–72 hour price windows, what traffic and metadata to hold constant, how to use lightweight AI models to suggest test ladders and statistical stopping rules, and how to combine pricing experiments with small ad bursts to amplify learnings. You’ll get a simple 3-step framework to run your first test in under a week, plus sample dashboards, guardrails to protect royalty outcomes, and ways to avoid common mistakes that waste time or harm visibility. Practical, ethical, and designed for busy indie authors.

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