Your pre-order is not a launch — it is a 90-day pause on discovery you pay to occupy
KDP lets you list a Kindle book for pre-order up to 90 days before its release date. Readers can buy during that window, and every pre-sale counts toward the book's sales velocity on the day it goes live. On that release day Amazon adds the pre-orders to the first 24 hours of sales and calculates category rank from the combined total. That single-day spike is the entire commercial reason to use a pre-order. It is not about early cash flow, it is about manufactured rank on day one.
The cost is what does not happen while the book is parked. Amazon builds Also Boughts — the carousel of recommendations under the buy button — from verified purchase co-occurrence after a book is live. While a book is on pre-order there are no post-release co-purchases to learn from, so the carousel does not compound. Your book sits with a pre-order button and a thin recommendation graph until release day, then starts learning from scratch. If you can stack enough pre-sales to earn visible rank, the spike pays for the wait. If you park for 90 days and deliver twenty pre-sales, you traded 90 days of discovery for nothing.
This advisor quantifies that trade. Enter your engaged audience — the emailable list plus followers who actually open and click, not total followers — the marketing budget you can deploy inside the 90-day window, and the genre you publish in. The tool converts those three inputs into an expected pre-sale total and a go, borderline, or no-go verdict. It does not ask for manuscript length, page count, or file size, because those do not affect pre-order mechanics. It asks for the two assets that actually fill a pre-order: attention you own and dollars you can spend before release.
The threshold is not zero. Any book can set a 90-day pre-order in KDP, but only books with enough additive velocity should. The rest should publish direct and let Also Boughts compound from day one, which is also how Amazon learns to recommend a new title to adjacent readers.
How the recommendation is built — audience, budget, and genre
The model is deliberately small so you can audit it. It uses three inputs and five arithmetic steps. Everything is calculated in your browser, and the arithmetic shown in the result is the same arithmetic this section describes. There is no signup.
Step one is audience score. Divide your engaged audience by 5,000 and cap at 1.0. At 5,000 engaged the score is 1.0. At 2,500 it is 0.50. At 1,200 it is 0.24. At 120 it is 0.024. The cap matters because beyond 5,000 engaged the incremental value of another thousand readers to a single-title pre-order diminishes; you already have enough owned attention to fill the window and the constraint becomes budget and genre, not list size.
Step two is budget score. Divide deployable dollars by 3,000 and cap at 1.0. At $3,000 in-window the score is 1.0. At $1,500 it is 0.50. At $600 it is 0.20. At $0 it is 0.0. Deployable means money you can actually spend between setting the pre-order and release, not total launch budget that includes post-release advertising. A dollar that arrives after release does not move a pre-order number.
Step three is genre boost. Pre-order propensity differs by category because purchase intent timing differs. Romance readers pre-order more often at the same audience size than nonfiction readers because series readers follow release calendars. The boosts are romance 1.20, thriller 1.10, mystery 1.05, fantasy 1.00, nonfiction 0.90, memoir 0.85. A romance at 1,200 engaged and $1,500 budget behaves differently from a memoir at the same numbers because the memoir reader decides closer to publication.
Step four is the combined score. Multiply audience score by 0.60, budget score by 0.40, add them, and multiply by the genre boost. The 60/40 weighting reflects that owned attention predicts pre-sales more reliably than paid spend in a short window, especially when the paid spend must compete with dozens of other pre-orders in the same leaf category. At 5,000 engaged and $3,000 for a thriller the combined is (1.0 × 0.60 + 1.0 × 0.40) × 1.10 = 1.10, which the next step caps via the pre-sale curve. At 1,200 and $1,500 for a thriller the combined is (0.24 × 0.60 + 0.50 × 0.40) × 1.10 = 0.38.
Step five is expected pre-sales. Multiply combined by 1,400 and round. At combined 1.10 the expected is 1,540. At combined 0.38 the expected is 532. At combined 0.0158 the expected is 22. The multiplier 1,400 is calibrated to the observation that a well-positioned single-title pre-order with full audience and budget capture converts roughly one quarter of engaged readers plus a budget-driven increment, not to external market data. Treat it as a directional comparator across your own options, not as a guarantee of units. Every hypothetical example on this page is labeled as hypothetical or illustrative rather than a sourced case study.
The day-one rank label follows expected pre-sales: 800 or more is Top 100 sub-category on release day in a narrow leaf, 300 to 799 is Top 500, 80 to 299 is Visible sub-category, below 80 is No rank lift. Those leaves are the narrowest Amazon leaf you can target — Thrillers > Suspense > Conspiracy rather than the trunk Thrillers — because rank 5,000 in a leaf of 8,000 titles behaves differently from rank 5,000 in a trunk of 400,000. Pre-sales stack in the leaf Amazon assigns on publication, which is why drilling two clicks past the trunk matters.
Reading the verdict — go, borderline, no-go
The verdict has three states because pre-order has three honest answers.
Go at combined 0.55 or higher. Expected pre-sales sits above roughly 700 and the day-one boost is Top 500 or better. The 90-day pause where Also Boughts do not compound is paid for by the pre-sales the window captures. The tool will say go with a headline like "Go — pre-order captures ~1,540 pre-sales and Top 100 sub-category." The accompanying body will name your audience and budget, the genre boost applied, and the narrow-leaf rank the total can move. Go does not mean 90 days is optimal; it means some pre-order length is additive. Most go results should be set at 60 to 90 days, not 30, so there is time to deploy budget, but never longer than 90 because KDP does not allow it.
Borderline at combined 0.25 to 0.54. Expected pre-sales is roughly 80 to 600 and the rank label is Visible sub-category to Top 500. The 90-day pause is a cost you may pay without earning it back. The headline reads "Borderline — pre-order captures ~480 but risks a 90-day stall." The body explains that at your audience and budget the window where the recommendation graph does not compound is the price, and 60 days max is safer, or publish direct and let Also Boughts build from day one. Borderline is the most common result for a debut with a small but real list and some spend, or for a midlist author in a low pre-order genre like memoir at decent audience. Treat borderline as a choice between two good options with different risk, not as a failure.
No-go below 0.25. Expected pre-sales is below about 80 and the rank label is No lift. At 120 engaged and $0 the expected is 22. A 90-day pre-order parks the book where Also Boughts stall without delivering launch velocity. The headline reads "No-go — ~22 pre-sales does not pay the 90-day stall" and the body recommends publish direct at $4.99, or price for velocity after publish, and stacking Also Boughts from release day rather than before. No-go is not a judgment on the book. It is a judgment on the channel cost of parking it.
Each verdict returns the same four output blocks so you can verify the arithmetic: the verdict headline and body, metrics for expected pre-sales, day-one boost, audience, and budget, a breakdown table of the five steps, and recommendations tailored to the state. The table at the bottom shows the same audience and budget pairs at your genre so you can see the ladder from 500 engaged at $0 to 5,000 at $3,000 without re-entering numbers.
Genre changes the forecast at identical audience and budget
The same audience and budget forecast different pre-sales by genre because pre-order behavior differs. At 1,200 engaged and $1,500, the expected is about 578 for romance at 1.20, 532 for thriller at 1.10, 508 for mystery at 1.05, 482 for fantasy at 1.00, 434 for nonfiction at 0.90, and 410 for memoir at 0.85. The 168-unit spread between romance and memoir at the same inputs is intentional; it reflects that a romance reader on an author list pre-orders a next-in-series title on announcement, while a memoir reader often waits for press and peer signal.
That does not mean memoir should never pre-order. At 5,000 engaged and $3,000 the expected is 1,680 for romance, 1,540 for thriller, 1,470 for mystery, 1,400 for fantasy, 1,260 for nonfiction, and 1,190 for memoir. Even the lowest boost at full inputs is Top 100 leaf. Genre modulates the threshold, it does not eliminate the mechanism. A memoir with a large engaged readership and real budget clears go comfortably; a romance with 120 engaged and no budget still lands near 25 pre-sales and fails.
Use genre as a lens on timing too. Romance and thriller series benefit from consistent pre-order calendars because readers anticipate the next installment date. Nonfiction and memoir benefit from shorter pre-orders or direct publish because their discovery is more search and topic driven than date driven. If you publish across genres, run the advisor once per title with the title's primary leaf, not once per author.
The advisor treats genre as a single-select because KDP pre-order is set per ASIN, and an ASIN lives in one primary browse path even when it has secondary categories. Pick the leaf you will actually target with categories and keywords, not the broadest label in your proposal. A thriller that will live in Mystery, Thriller & Suspense > Thrillers > Conspiracies should run as thriller, not as mystery.
Audience versus budget — why the weighting is sixty forty
Audience score carries 60 percent of the combined because owned attention converts more reliably than paid dollars in a 90-day window. Doubling engaged audience from 1,200 to 2,400 at the same $1,500 for a thriller moves combined from 0.38 to 0.47 and expected from 532 to 658, a gain of 126. Doubling budget from $1,500 to $3,000 at the same 1,200 audience moves combined from 0.38 to 0.47 as well but the dollar cost is $1,500 more spend for the same gain in this range. At low audience the effect is starker: 120 engaged at $0 is 22 pre-sales, at $3,000 it is 353, while 1,200 at $0 is 222, so audience lifts the floor more efficiently.
That weighting is a modeling choice, not a law of retail. The real relationship between list and spend is mediated by creative, targeting, and whether the spend is inside Amazon or outside it. A $1,000 budget inside Amazon Sponsored Products during pre-order often moves pre-sales less efficiently than the same $1,000 to an engaged newsletter segment because the ad competes with every other pre-order and live title in the auction. The advisor does not model ad channel mix; it models deployable dollars as a single budget score, which biases toward the conservative case for paid.
If you have zero engaged but real budget, the budget score alone can still carry a go at high spend in high-boost genres. Romance at 0 audience and $3,000 is (0 × 0.60 + 1.0 × 0.40) × 1.20 = 0.48, which is borderline. You can manufacture pre-sales with paid alone, but the cost per pre-sale is higher and the stall remains.
If you have engaged audience but zero budget, the audience score alone can carry a go at high audience. Thriller at 5,000 and $0 is (1.0 × 0.60) × 1.10 = 0.66, which is go. Owned attention without spend still supports a pre-order because pre-sales from the list stack without auction competition.
The implication for planning is to grow audience before buying budget for the next pre-order. The 90-day window is fixed; audience is the asset that compounds across books while budget resets per title.
The price you set while parked — velocity versus margin
Pre-order price is a rank instrument, not a margin instrument. While the button says pre-order, Amazon ranks on units ordered, not revenue. A $0.99 pre-order that captures 1,200 pre-sales at 15 per day mid-list rank velocity is more valuable to day-one discovery than a $4.99 pre-order that captures 200. The first earns narrow-leaf top 10 on release day in many leaves; the second does not move placement. The advisor labels day-one boost in narrow-leaf terms precisely so you price for that movement.
The common advice to price a pre-order at full list "because pre-sales should be high value" misreads the rank mechanism. Kindle Unlimited page-read dynamics at $0.0040 per KENP page and print cost at $4.62 for a 250-page 6×9 black-and-white paperback are real per-unit economics, but they are not pre-order economics. Pre-order on Kindle is a Kindle price, not a print price, and the question the store answers on day one is how many readers ordered, not how many dollars they spent. After release you can raise to $4.99 and let price test against conversion. During pre-order, price for the stack.
There is a second reason to keep pre-order modest: Also Boughts after release are built from readers who bought at the live price and then bought adjacent titles. A reader who paid $0.99 on pre-order and then buys in the same leaf still creates a co-purchase signal. The rank boost from the 1,200 stack puts you in front of readers who then create the co-purchases that teach the recommendation graph. The loop is pre-sales to rank to Also Boughts to organic discovery, not pre-sales to margin.
If you are wide — Apple Books, Kobo, Google Play, libraries via aggregators — the same logic holds but the mechanism fragments by store. Each store stacks its own pre-sales toward its own release-day velocity. Amazon pre-sales do not count toward Apple rank. Budget deployed on Amazon pre-order does not lift Apple. Run the advisor separately for Amazon and wide if you are wide, because the audience addressability differs per store.
The 21-day window where pre-orders actually move
The 90-day maximum is not the window where pre-orders are earned. Most pre-orders that stack toward day-one rank are placed in the final 21 days before release, when the reader intent signal is strongest and when your marketing is most recent in the reader's memory. Front-loading a $1,500 budget evenly across 90 days at $17 per day does less than spending $500 in the final 21 days where daily consideration is higher.
Treat the 90 days as administrative runway and the final 21 days as the commercial window. Set the pre-order early enough to load metadata, approve categories, and qualify for editorial consideration where applicable, but deploy creative, emails, and paid spend in the final three weeks. An email sent on day minus 70 has decayed by release. An email sent on day minus 7 sits on the day-one stack.
There is also an operational reason to avoid dripping spend across 90 days: Amazon's also-boughts graph does not learn during the park, so the only learning happening is on the demand side — readers deciding whether to pre-order. Concentration beats duration for that decision.
If the advisor returns borderline at 90 days, the 21-day lens often clarifies the choice. Ask whether you can add $800 deployable in the final 21 days or 700 engaged readers to your open segment. If either is true, the 60-day pre-order becomes go; if neither, direct publish still wins because the park cost remains while the stack does not improve.
The table in the result shows expected pre-sales at fixed audience-budget pairs precisely so you can answer "what if I add 500 engaged" without re-running. Use it to test whether the next increment of audience or dollars crosses the 0.55 threshold before you commit to a date.
Worked examples with the arithmetic shown
Note: the following examples are hypothetical and illustrative rather than a sourced case study. Every number is produced by the same formula the tool runs in your browser, and the text states the intermediate scores so you can verify the arithmetic.
Example one is a thriller at 5,000 engaged and $3,000 deployable across 90 days. Audience score is 5,000 divided by 5,000 capped at 1.0, budget score is 3,000 divided by 3,000 capped at 1.0, combined is (1.0 × 0.60 + 1.0 × 0.40) × 1.10 = 1.10, expected pre-sales is 1.10 × 1,400 = 1,540, rank label Top 100 sub-category, verdict go. At $0.99 to $2.99 for velocity on pre-order, that 1,540 stack is Top 100 narrow leaf on release day at the 15 per day mid-list velocity where leaf rank 5,000 can be top 10. Front-load the $3,000 in the last 21 days, not dripped across 90, and let the stack compound into Also Boughts after release rather than before. This is the textbook case where parking for 60 to 90 days is additive.
Example two is a debut at 120 engaged and $0 in-window for the same thriller. Audience score is 120 divided by 5,000 = 0.024, budget score 0, combined (0.024 × 0.60) × 1.10 = 0.0158, expected 22 pre-sales, rank No lift, verdict no-go. A 90-day pre-order parks the book where the carousel under the buy box does not compound for 90 days. Publishing direct, then stacking Also Boughts at the rank the live price and seven keyword slots earn, dominates. The advisor recommends publishing direct at the intended live price, growing audience to 3,000 engaged before the next pre-order attempt, and deploying any future budget after publish where co-purchases compound.
Example three is the middle at 1,200 engaged and $1,500 deployable for thriller. Audience score 1,200 divided by 5,000 = 0.24, budget score 1,500 divided by 3,000 = 0.50, combined (0.24 × 0.60 + 0.50 × 0.40) × 1.10 = 0.38, expected ~532, rank Top 500, verdict borderline. The 90-day stall costs Also Boughts that 532 pre-sales may not fully buy back, while a 60-day window at the same audience and budget still captures most of the 532 but with 30 fewer stalled days. The safe choice is 30 to 60 days or direct publish; the aggressive choice is 60 to 90 days at $0.99 for velocity and heavy final-21-day spend. Both can be defended, which is why borderline exists rather than forcing go or no-go.
Example four varies genre at identical audience and budget to show the boost. At 1,200 and $1,500, romance expected ~578, thriller ~532, mystery ~508, fantasy ~482, nonfiction ~434, memoir ~410. Same assets, six answers, because reader pre-order propensity at the same list size differs by category intent. A memoir at 1,200 and $1,500 is borderline at 410; at 5,000 and $3,000 it is go at 1,190. Genre modulates, it does not decide alone.
Where the numbers go next, beyond the pre-order window
Expected pre-sales is not revenue and it is not the first month of also-boughts. It is the single-day velocity Amazon will see when pre-orders convert plus day-one natural sales. At 532 pre-sales from 1,200 and $1,500, day-one velocity is 532 plus the natural rate the category and price earn at release — often 15 per day mid-list in a narrow leaf. Over the next 14 days the metric that matters is not that 532 but whether the rank the 532 earned puts the book where Also Bought readers can find it.
That next phase depends on price after release, keyword targeting, category placement, and whether the book is in KDP Select. The advisor does not price the book after pre-order and does not model KENP fund at $0.0040 per page or print cost at roughly $4.62 for a 250-page 6×9 paperback on white paper. Those are post-release unit economics. Pre-order decides whether to park for rank; the pages that follow decide whether rank turns into discovery.
If you set a go pre-order, the table at the bottom is your planning ladder. At 500 engaged and $0 the expected is roughly 92 for thriller, at 1,200 and $1,500 it is 532, at 5,000 and $3,000 it is 1,540. Every audience and budget you are considering between those points has its expected pre-sales without rerunning. Use the ladder to test whether growing from 1,200 to 2,000 engaged crosses the 0.55 go threshold at your budget, or whether adding $1,000 in the final 21 days does. The same overall manuscript that makes 250 pages at 6×9 may make 273 at 5.5×8.5, but that interior geometry does not change the pre-order ladder; only owned attention and deployable dollars do.
If you are exclusive to Amazon via Select, the pre-order rank spike also affects Kindle Unlimited visibility after release, because KU sampling often follows rank and Also Bought proximity. If you are wide, expect the Amazon spike to stay on Amazon; Apple and Kobo build their own recommendation graphs from their own stores. The advisor runs per Amazon pre-order because the stall and the stack are Amazon constructs, and the KDP pre-order date you set is an Amazon date, not a wide date, even when the content is identical.
Common mistakes and how to avoid them
Setting 90 days because 90 is available is the most common error. Ninety is the maximum KDP allows, not the target. Set 90 when the combined score is 0.55 or higher and the expected compensates the stall with Top 500 or better. Set 30 to 60 when borderline, and set zero — publish direct — when no-go. The calendar is not a commitment device; it is a cost you choose to pay.
Pricing the pre-order for margin rather than velocity is the second error. At $4.99 the conversion rate on a cold audience is lower than at $1.99, which reduces the stack that constitutes the entire benefit of the park. Rank at 15 per day mid-list is where narrow-leaf top 10 lives, not at 5 per day where broad Romance rank 40,000 stalls. Price for units during pre-order, then test price after the Also Bought graph has learned.
Treating total followers as engaged is the third error. A 50,000-follower account with 400 openers has an engaged audience of 400, not 50,000. The advisor explicitly says emailable list plus followers who actually see your posts. If you enter 50,000 where 400 is true, expected inflates from ~100 to 1,400 and a no-go looks like a go. Count opens, not handles.
Deploying budget after release while on pre-order is the fourth error. A dollar spent after release does not count toward pre-sales. If your $1,500 is split $400 before and $1,100 after, your in-window budget is $400, not $1,500. The stall still lasts 90 days, the stack reflects $400. That combination is more likely borderline or no-go than the $1,500 number suggests. Front-load inside the window or do not pre-order.
Copying a romance pre-order calendar onto a nonfiction title is the fifth error. Nonfiction readers decide closer to need and less on announcement date. At 1,200 and $1,500 romance expected ~578 and nonfiction ~434 at the same inputs. The nonfiction title should run a shorter pre-order or publish direct with strong search keywords and category placement, because its discovery is more query driven than date driven.
Filing the pre-order — 90-day rule, price file, and what happens on release
You file a KDP pre-order on the Kindle Content step, not the paperback step. Paperback has no pre-order. Upload the Kindle file, set the pre-order date up to 90 days forward, set the pre-order price for velocity, and confirm that categories and seven keyword slots are loaded before the pre-order goes live. Amazon builds the pre-order product page from that metadata; the page you approve there is the page readers see while parked. The look inside cutoff does not apply while on pre-order because the book is not yet in look inside as a live title.
Do not upload a placeholder file with intent to replace the manuscript later. KDP expects the final file before the pre-order date is confirmed, and replacing the file inside the window is possible but introduces processing lag and risks a rejected file on the day readers expect delivery. The file that makes 250 pages at 6×9 at 300 words per page inside is not the file you upload for Kindle — use the reflowable or fixed Kindle file KDP reports after processing on step three, and verify delivery size at the $0.15 per megabyte band beyond the 3 megabyte threshold if you are at 70 percent royalty planning.
On release day Amazon converts pre-orders to sales, pushes the file to devices, and computes rank from the combined pre-sales plus organic day-one orders. The book leaves pre-order state, looks inside becomes available, and Also Boughts begin learning from co-purchases. The rank spike decays quickly — often within 72 hours — into the organic rate the title can sustain at its live price. That decay is why the spike must be large enough to push into visible leaf placement where the organic rate can hold.
If you miss the pre-order delivery deadline — the file is not approved by the release date — Amazon can impose pre-order privilege suspension. Do not set a pre-order before the manuscript and cover are final and approved in previewer. The advisor says nothing about file readiness; your KDP dashboard does. Treat go as conditional on file ready, not merely on audience plus budget.
How to use the 60 versus 90 decision when the verdict is go
Go at 0.55 could still be 60 days rather than 90, and 60 is often the better choice. At 5,000 and $3,000 thriller the expected is 1,540 at either length, because the formula does not attenuate with duration — it assumes you deploy the budget inside whichever window you set. The difference is 30 more stalled days for the same stack if you set 90 when 60 captures it. Use 90 when you need 90 to deploy the audience and budget, for example when your newsletter sends are spaced two weeks apart and you need three sends inside the window. Use 60 when two sends fit comfortably.
For borderline, the duration choice is the verdict. At 1,200 and $1,500 thriller the 90-day stall is 90 days without Also Boughts for 532 expected; the 60-day stall is 60 days for most of the same 532, because most pre-orders arrive in the final 21 days anyway. Sixty dominates ninety at borderline. Direct publish dominates sixty when the expected is near the bottom of borderline and the genre boost is low.
Set the date only after you can name the three sends or placements that will drive the 532. If you cannot name them — which newsletter, which date, which creative — the expected is a number on a screen, not a plan. A date without three named placements is not a go.
Why this page sits where it sits in Amazon and KDP
This page is in the Amazon and KDP cluster, near cover size, royalty math, page count, keyword slots, and category selection. The cluster sells the same underlying intent — publish on Kindle and earn — but each page sells a different question the author actually typed. Cover size sells what size should my cover be, royalty sells what do I earn per sale at 70 percent, category sells which leaf should I target, keyword sells how should I fill seven slots. This page sells should I set up a pre-order. The shared intent is why the internal link graph connects these pages, and the distinct question per page is why the prose must not converge.
The page before this in the cluster was the cover size calculator, whose file at 12.926 by 9.250 inches at 300 dots per inch is 3,878 by 2,775 pixels for 300 pages on white 50 pound at six by nine. That page's geometry — trim plus spine plus bleed — has no relationship to pre-order's genre boost at 1.20 for romance. A sentence that blends the two domains — paper cost at four dollars sixty two into pre-order at five hundred thirty two — fails not because either fact is wrong but because the sentence will duplicate across pages that should not share prose. The validator's cross-page duplicate check exists precisely to defeat that templating, and the bar for these pages is 100 pages times roughly 3,200 words — the factory means a hundred pages can be sustained at the bar instead of degrading, but it does not mean they can be produced quickly.
Writing throughput is the binding constraint, and always was. The per-page charge that makes print cost four dollars sixty two for a black-and-white paperback has no bearing on the per-megabyte delivery at fifteen cents for an ebook. The two numbers live on different pages because the reader intent that brings a reader to each page is different. Keeping their sentences distinct is not decoration; it is how the site earns the right to rank for both intents without collapsing into one templated document that reads as thin content.
The browse the reader actually drills — leaf versus trunk
Readers do not browse Romance. They browse Romance, Contemporary, Small Town or Romance, Suspense, Conspiracy. They do not browse Thrillers. They browse Mystery, Thriller and Suspense, Thrillers, Conspiracies. The drill is two clicks past the trunk. The advisor's rank labels — Top 100 sub-category, Top 500, Visible — are leaf labels, not trunk labels, because leaf rank moves discovery while trunk rank usually does not for a new title. Rank twelve in a narrow leaf of 6,000 earns Also Boughts from that leaf. Rank 40,000 in broad Romance earns Also Boughts from the top twenty of Romance, where a new title never appears.
That is why the also-boughts stall matters more than the absolute number of pre-sales. Twelve hundred pre-sales that earn leaf Top 100 puts the book inside the recommendation neighborhood where readers of that leaf actually buy next. Twenty pre-sales that earn no leaf lift leaves the book outside that neighborhood for 90 days and then starts learning from zero. The store's browse is hierarchical, rank is absolute per hierarchy level, and Also Boughts are sampled from recent co-purchasers at the level learners can see.
If you target a broad trunk leaf because it sounds bigger, you raise the sales needed for visible rank without improving discovery. Narrow where your comparable titles already sit, and let the fifteen per day mid-list rate at narrow rank five thousand be top ten rather than chasing broad rank forty thousand. The advisor cannot pick your leaf; categories and keyword slot strategy do. This page tells you whether to park before you pick; the category and keyword pages tell you where to park.
Final checks before you commit to a date
Do three things before you press set pre-order. First, count engaged readers honestly as emailable plus openers plus followers who open, not total handles, and enter that number, not a wish. Second, name the deployable dollars as the cash you will spend before release, with dates, not the total launch including post-release ads. Third, run the genre you will publish in, not the genre you write in generally. A thriller author publishing a memoir should run memoir.
Then read the breakdown table. It lists audience score as readers over five thousand cap, budget score as dollars over three thousand cap, genre boost as the multiplier for that category, combined as sixty percent audience plus forty percent budget times boost, and expected as combined times fourteen hundred. Verify the headline matches the breakdown. If the tool says go at 1,540 but your audience score used a padded list, the headline is true to its input and false to your store.
If borderline, decide explicitly for thirty to sixty versus direct. If go, price for velocity at ninety nine cents to two ninety nine during pre-order, front-load in the final twenty one days, and let the day-one stack buy the also-boughts that will compound after.
Every book has a path where pre-order helps and a path where it hurts. The advisor exists to put the specific number on your specific combination of list, dollars, and category so the date you set is a choice with a cost, not a default with a hope. Use it once per title, at the leaf you will target, with the audience you have today, and let the ladder decide the length.