Break-even ACoS calculator by Radu Bobirnac
No script (for Notion, Wix and similar)Break-even ACoS calculator by Radu Bobirnac
Free to use. Provided as-is; results are estimates. Learn the decision behind the numbers. Work through the example, then apply this tool to your own reports. - Lesson 2: Find the products hidden by your blended ACoS (https://profitfirstppc.com/playbook/blended-acos/) --- ## Amazon Negative Keyword Calculator | Profit-First PPC Source: https://profitfirstppc.com/tools/when-to-negate/ When to Negate Is this search term worth more clicks? Use clicks, orders, spend and contribution per order to compare a term with its break-even conversion rate. Review the evidence before deciding to add a negative, collect more data or keep it running. The search term Search term Optional, just a label Clicks Orders Spend $ From your Sponsored Products Search Term Report: Clicks, 7 Day Total Orders and Spend for this term. The product it’s advertising Selling price $ per unit Profit before ads $ per unit: price minus Amazon fees and landed cost How sure before you add a negative? Higher thresholds reduce false positives for a single fixed test under the model, but cannot eliminate mistakes. Repeated checking and screening many terms increase the risk. Cheat sheet Clicks with no sale before you add a negative. Find the row for your product’s break-even conversion rate. Rule of thumb: at 95%, it’s about 3 ÷ that rate. Clicks with zero orders needed before a search term is proven unprofitable | Break-even conversion rate | 80% sure | 90% sure | 95% sure | Spend to know Break-even conversion rate = cost per click ÷ profit per sale before ads. The spend column uses your cost per click at the certainty you picked. How it’s calculated A fair test for every search term. Clicks cost money whether or not they convert. So the question isn’t “has it sold yet?” but “does it sell often enough to pay for its clicks?” Want break-even numbers for every product first? Run the Catalog Profit Check (https://profitfirstppc.com/tools/catalog-profit-check/), then pick a product here. Setting top-of-search premiums? Try the Placement Bid Calculator (https://profitfirstppc.com/tools/placement-bid-calculator/). Search term selling well? Review the uncertainty with Harvest Readiness (https://profitfirstppc.com/tools/harvest-readiness/) before you move it to exact match. Also a free JSON API for your own reports or an AI agent, no key needed: GET https://profitfirstppc.com/api/when-to-negate?clicks=24&orders=0&spend=28.80&profit_per_order=19.29. Details in the API spec (https://profitfirstppc.com/api/openapi.json). - Break-even conversion rate Cost per click ÷ profit per sale before ads. A search term converting below this loses money even when it makes sales. - The test If the term really converted at exactly break-even, how likely is it to get this few orders from this many clicks? A value below 5% flags evidence against break-even for a single test at the 95% setting. It is not a 95% probability that the term is unprofitable. - Clicks to decide How many more clicks with no new order it takes to get there, and what they cost at your current cost per click. - What it leaves out Sales from other search terms that this one helps, orders credited after the report was pulled, and multi-unit orders. Treat a close call as “watch it”, not “cut it”. For your website Embed this tool on your site. Paste this into your page’s HTML. Visitors use the calculator on your site; their numbers stay in their browser. Preview the embed (https://profitfirstppc.com/embed/when-to-negate/). Show the embed code Resizes to fit (recommended)Negative keyword calculator by Radu Bobirnac
No script (for Notion, Wix and similar)Negative keyword calculator by Radu Bobirnac
Free to use. Provided as-is; results are estimates. Learn the decision behind the numbers. Work through the example, then apply this tool to your own reports. - Lesson 3: Give search terms a fair test before adding negatives (https://profitfirstppc.com/playbook/when-to-negate-search-terms/) --- ## Amazon Placement Bid Calculator | Profit-First PPC Source: https://profitfirstppc.com/tools/placement-bid-calculator/ Placement Bid Calculator Set placement bids from what a click is worth. Use one campaign’s placement data to estimate click value at your target ACoS. Compare top of search, rest of search and product pages, then review the base bid and adjustments together. Your margin Break-even ACoS %, for the product this campaign advertises Margin to keep after ads %, sets your target ACoS Your bids Typical keyword bid $, the bid most keywords in this campaign use Bidding strategy Placement numbers, last 30 to 60 days In Campaign Manager, open the campaign and choose the Placements tab. Copy each row’s bid adjustment, clicks, spend, orders and sales. Placement numbers for this campaign | Placement | Adjustment today% | Clicks | Spend$ | Orders | Sales$ Your settings What each placement can afford Want help with placement decisions across your campaigns? Start with a free conversation about your business and advertising. We’ll discuss whether a closer review of your bids and placements makes sense. Book a free introductory call (https://profitfirstppc.com/book.html) Most you could pay today vs what a click is worth Per placement, at your target ACoS. - Most you could pay today, under what a click is worth - Most you could pay today, over what a click is worth - What a click is worth Details for each placement | Placement | Clicks | Conv. rate | CPC | ACoS | Sales per click | A click is worth | Most you pay today | Read How placement adjustments work They can only push bids up. That one rule decides everything else. Your keyword bid is the floor for every placement, so it has to fit the weakest one. - Raise only Each placement takes an adjustment from 0% to 900%, up to 10 times your bid. There’s no way to bid a placement below your keyword bid. - Campaign-wide Adjustments apply to every keyword and target in the campaign, so a +200% top-of-search premium triples every bid there. - Dynamic bids stack on top With “up and down”, Amazon can add up to 100% more at all placements, after your adjustment. A $1.00 bid with +50% on top of search can reach $3.00. - The weakest placement sets the bid Set your keyword bid to what the weakest placement’s click is worth, then use adjustments to lift the others to what theirs are worth. How it’s calculated What a click is worth, placement by placement. Need your break-even ACoS first? Run the Catalog Profit Check (https://profitfirstppc.com/tools/catalog-profit-check/), then pick the product here. Also a free JSON API for your own reports or an AI agent, no key needed: POST https://profitfirstppc.com/api/placement-bids with your numbers as JSON. Details in the API spec (https://profitfirstppc.com/api/openapi.json). - Sales per click Sales ÷ clicks for the placement. It combines conversion rate and order value in one number. - What a click is worth Sales per click × target ACoS (break-even minus the margin you keep). Pay more than this and the placement misses your target. - Most you pay today Keyword bid × (1 + adjustment), and × 2 at all placements with dynamic “up and down”. Settings cap the modeled bid at estimated click value where the minimum bid permits. Other bid modifiers are not included, and future results may differ. - What it leaves out Extra sales a higher bid might win, keywords with very different bids in one campaign, and placements with under 30 clicks, which are too thin to trust. For your website Embed this tool on your site. Paste this into your page’s HTML. Visitors use the calculator on your site; their numbers stay in their browser. Preview the embed (https://profitfirstppc.com/embed/placement-bid-calculator/). Show the embed code Resizes to fit (recommended)Placement bid calculator by Radu Bobirnac
No script (for Notion, Wix and similar)Placement bid calculator by Radu Bobirnac
Free to use. Provided as-is; results are estimates. --- ## Amazon Keyword Harvesting Checker | Profit-First PPC Source: https://profitfirstppc.com/tools/harvest-readiness/ Harvest Readiness Is this search term ready for exact match? Review a converting term before giving it an exact-match test. Compare its estimated conversion rate with break-even and see how the campaign baseline affects the result. The model’s assumptions remain visible alongside the calculation. Short answer: this checker flags a term for harvest review when its model probability of positive ad-attributed profit at today’s CPC reaches your threshold, 90% by default. Its default campaign weighting is an uncalibrated assumption, not measured luck. It does not predict whether moving the term to exact match will increase profit. The search term Search term Optional, just a label Clicks Orders Spend $ From your Sponsored Products Search Term Report (auto, broad or phrase): Clicks, click-attributed purchases and Spend. Use purchases counted over the full number of days after a click shown in your report. Allow that window to pass for the latest date, plus time for report updates. The product and campaign Profit before ads $ per order: price minus Amazon fees and landed cost Campaign conv. rate %, of the campaign the term came from How sure before you harvest? Advanced: how skeptical to be Campaign average is worth clicks of evidence (default 30). Higher trusts early numbers less. Check a whole report Paste your search terms, get a harvest list. Copy four columns from your Search Term Report: search term, clicks, orders and spend. All rows use the profit and campaign baseline above, so check one product and comparable discovery traffic at a time. Search term, clicks, orders, spend One term per line, tab or comma separated. A header row is skipped. How it’s calculated Model and assumptions One order from three clicks gives an observed 33% conversion rate, with little evidence about repeat performance. This model combines that observation with a campaign baseline. The weighting is adjustable and has not been calibrated against historical Amazon data. Zero orders so far? That’s a different question: When to Negate (https://profitfirstppc.com/tools/when-to-negate/) tells you whether to cut it. Need each product’s profit before ads? Run the Catalog Profit Check (https://profitfirstppc.com/tools/catalog-profit-check/) first, then pick the product here. - Break-even conversion rate Cost per click ÷ profit per order before ads. At a $1.20 click and $12 profit per order, a term must convert above 10% to make money. - Adjusted conversion rate Combine the campaign baseline, weighted as k clicks (30 by default), with the term’s observations: (k × campaign rate + orders) ÷ (k + clicks). The assumed baseline weight is k ÷ (k + clicks): 91% at 3 clicks, 67% at 15 and 33% at 60. These are model weights, not measured percentages of luck. - Chance it’s profitable The term’s true rate follows a Beta distribution with α = k × campaign rate + orders and β = k × (1 − campaign rate) + clicks − orders. The tool reports the chance it sits above break-even. - The verdict Harvest now is a review flag at or above your model threshold. A suggested base bid assumes fixed bidding and no adjustments; it does not guarantee CPC. Wait is between the thresholds, with a conditional extra-click scenario. Don’t harvest is at or below 100% minus your threshold at today’s CPC. Worked examples Same conversion rate, different verdicts. Each row assumes $12 profit per order, a $1.20 click (so break-even is 10%), a 10% campaign rate and the default settings. Worked examples of the harvest readiness calculation | Clicks | Orders | Conv. rate | Adjusted | Chance profitable | Verdict | 3 | 1 | 33.3% | 12.1% | 60% | Wait; scenario: ~339 extra clicks | 15 | 3 | 20.0% | 13.3% | 73% | Wait; scenario: ~115 extra clicks | 60 | 12 | 20.0% | 16.7% | 97% | Harvest now at $1.20 | 80 | 3 ($1.50 click) | 3.8% | 5.5% | under 1% | Don’t harvest The same 20% conversion rate is a “wait” at 15 clicks and a review flag at 60. The common “sales above zero” rule treats all four terms the same way. Limits What it can’t tell you. The baseline weighting and probability threshold are starting assumptions. The model has not been calibrated against later Amazon outcomes. Its recommendations support review and do not establish that harvesting causes additional profit. - Use settled data Exclude recent dates whose attribution window has not ended, and allow for report updates. Use click-attributed purchases from the full window shown in your report. - Ad-attributed profit only Some harvested orders would have happened organically anyway. Branded terms are the most affected. - Today’s cost per click The chance is worked out at the term’s current cost per click. An exact-match bid that pays more per click raises the bar. - Timing, not overlap Whether to also add the term as a negative in its discovery campaign is a separate decision, and there isn’t good evidence either way yet. - Comparable traffic and purchases Use a baseline from comparable discovery traffic, excluding this term where possible to avoid counting its evidence twice. The model assumes stable CPC, conversion and profit per purchase, and at most one converting purchase per click. It cannot model multiple purchases per click, mixed product margins or changing auctions from these totals alone. - Extra clicks are a scenario The curve adds fractional expected orders at the current model estimate. Actual future orders are uncertain. The displayed click count is not a forecast, a guaranteed stopping time or a recommendation to spend that budget. For developers and AI agents Use it from code. The same calculation is a free JSON API. No key needed. The full spec is at /api/openapi.json (https://profitfirstppc.com/api/openapi.json). curl "https://profitfirstppc.com/api/harvest-readiness?clicks=60&orders=12&spend=72&profit_per_order=12&baseline_cvr=0.10" To check a whole Search Term Report, POST up to 500 terms at once: curl -X POST https://profitfirstppc.com/api/harvest-readiness \ -H "content-type: application/json" \ -d '{"defaults": {"profitPerOrder": 12, "baselineCvr": 0.10}, "terms": [{"searchTerm": "insulated water bottle", "clicks": 60, "orders": 12, "spend": 72}, {"searchTerm": "water bottle with straw", "clicks": 9, "orders": 1, "spend": 10.80}]}' Each result has a verdict (harvest_now, wait, do_not_harvest or no_evidence), a one-sentence headline, probabilityProfitable, estimatedCvr, luckShare, extraClicksNeeded and suggestedStartingBid. The other free tools have APIs too: see llms.txt (https://profitfirstppc.com/llms.txt). FAQ Harvesting questions How many clicks before moving a search term to exact match? There’s no fixed number. It depends on how far the term converts above break-even. In the examples above, a term converting at twice break-even needed about 60 clicks to be a 97% model probability at the observed CPC. A term converting just above break-even can need hundreds. Should I harvest a search term after one order? One order alone gives limited evidence. The decision also depends on CPC, profit per purchase and a comparable baseline. At the default weighting, the baseline contributes 91% of the adjusted estimate after three clicks; that does not mean 91% of the performance is known to be luck. What is the break-even conversion rate for Amazon PPC? Cost per click ÷ profit per order before ad spend. At a $1.20 click and $12 profit per order, a search term must convert above 10% to make money. Should I also negate the term in the auto campaign? That’s a separate decision from timing, and there isn’t good published evidence either way yet. This tool only answers whether the term has proven itself enough to harvest. --- ## PPC Playbook | Free Amazon PPC Lessons Source: https://profitfirstppc.com/playbook/ PPC Playbook Learn how to make the next Amazon PPC decision. Work through product margins, search terms, placement bids and reporting with examples you can calculate yourself. Each lesson explains the decision and links to a tool for applying it to your own account. Start with lesson 1 (https://profitfirstppc.com/playbook/break-even-acos/) Give your weekly review a clear order. Seven focused checks connect these lessons to your reports, product margins and campaign decisions. Open one step at a time and finish with a written action plan. Start the guided weekly review (https://profitfirstppc.com/weekly-ppc-review/) Work through the lessons. Read the published lessons at your own pace. Preview the next lesson below; new lessons arrive on Tuesday mornings, starting at 9:05 AM Eastern. - Lesson 1 · Available now Find the ACoS your product can afford (https://profitfirstppc.com/playbook/break-even-acos/) Accompanying tool: Catalog Profit Check (https://profitfirstppc.com/tools/catalog-profit-check/) Read lesson 1 (https://profitfirstppc.com/playbook/break-even-acos/) - Lesson 2 · Available now Find the products hidden by your blended ACoS (https://profitfirstppc.com/playbook/blended-acos/) Accompanying tool: Catalog Profit Check (https://profitfirstppc.com/tools/catalog-profit-check/) Read lesson 2 (https://profitfirstppc.com/playbook/blended-acos/) - Lesson 3 · Available now Give search terms a fair test before adding negatives (https://profitfirstppc.com/playbook/when-to-negate-search-terms/) Accompanying tool: When to Negate (https://profitfirstppc.com/tools/when-to-negate/) Read lesson 3 (https://profitfirstppc.com/playbook/when-to-negate-search-terms/) - Up next · Lesson 4 Choose search terms for an exact-match test Compare two search terms with the same conversion rate and different evidence. Use Harvest Readiness to plan an exact-match test. Accompanying tool: Harvest Readiness Planned October 27 New lessons publish on Tuesdays. Subscribe to the RSS feed (https://profitfirstppc.com/playbook/feed.xml) to get each one as it comes out. Use the tools as you learn. The lessons explain the decision. The calculators let you apply it to your own products and reports. Each tool includes its formulas and limits. Explore the seven free tools (https://profitfirstppc.com/tools/) Need to look behind a report total? Search Term Report Checker (https://profitfirstppc.com/tools/search-term-report-checker/) helps you inspect the search terms behind the numbers used in the lessons. See the work in context Read the published case studies (https://profitfirstppc.com/case-studies.html) for account snapshots, workflows and the limits of the evidence. [Image: Radu Bobirnac presenting a worked exercise on calculating maximum cost per click at an industry conference] --- ## Break-Even ACoS Explained | PPC Playbook Source: https://profitfirstppc.com/playbook/break-even-acos/ ← PPC Playbook (https://profitfirstppc.com/playbook/) Lesson 1 of 7 · Product economics Find the ACoS your product can afford. What is my break-even ACoS, and why is it different for each product? Short answer: Break-even ACoS is the contribution a product has before ads, divided by its selling price. Different fees and landed costs give each product a different line. Set your advertising target below that line to leave the contribution you want to keep. By Radu Bobirnac · Published October 3, 2026 Try Catalog Profit Check (https://profitfirstppc.com/tools/catalog-profit-check/) One ACoS, two different results If two products both have a 25% ACoS, are they doing equally well? Before you look at the example, choose the missing number you would want: sales, clicks, or the margin each product has before advertising. Start with the margin. Advertising cost of sales, or ACoS, is ad spend divided by ad-attributed sales. It tells you what advertising consumed. Your product economics tell you what was available to spend. Work through the numbers These are teaching examples, not customer products. Both sell for $40. Amazon fees are $10 per unit. The difference is the cost of getting each product into Amazon’s warehouse. At the same 25% ACoS, Product A leaves $6 per sale and Product B loses $2. | Per unit | Product A | Product B | Selling price | $40 | $40 | Amazon fees | $10 | $10 | Landed cost | $14 | $22 | Contribution before ads | $16 | $8 | Break-even ACoS | 40% | 20% | Ad cost at 25% ACoS | $10 | $10 | Contribution after ads | $6 | −$2 Product A has $16 left before ads: $40 minus $10 minus $14. Divide $16 by the $40 price and its break-even ACoS is 40%. Product B has only $8, so its line is 20%. The same 25% ACoS leaves $6 on A and loses $2 on B under these assumptions. The formula Contribution before ads = price − Amazon fees − landed cost Break-even ACoS = contribution before ads ÷ price Target ACoS = break-even ACoS − margin to keep Maximum CPC at target = price × target ACoS × ad conversion rate Break-even leaves no contribution after advertising for costs you have not included. To keep 10% of revenue after ads, subtract 10 percentage points. Product A’s target becomes 30%. At a 10% ad conversion rate, its target maximum CPC is $40 × 30% × 10% = $1.20. CPC means the average cost per click. Use rates as decimals in the multiplication: 30% is 0.30 and 10% is 0.10. You can now explain why an account-wide ACoS target can be too generous for one product and unnecessarily restrictive for another. A published case to examine I managed an electronics catalog with audio accessories, surge protectors and streaming devices. The October 1–31, 2024 snapshot shows $236,400.97 in ad-attributed sales from $16,785.89 in spend: a 7.10% ACoS. Those figures establish the reported advertising ratio. The published case does not include the product cost file, so it cannot establish each product’s contribution after ads. The useful next question is whether 7.10% sits below each advertised product’s own break-even line. Read the electronics case and see the console screenshot (https://profitfirstppc.com/case-studies.html#electronics). Try it on your products - Open Catalog Profit Check (https://profitfirstppc.com/tools/catalog-profit-check/). Enter one product’s price, Amazon fees and landed cost. Use one currency throughout. - Set “Margin to keep after ads” to your chosen percentage of revenue. For Product A above, enter 10 to see a 30% target. - Add a second product with different costs. Predict its break-even line before looking at the result. - Add ad conversion rate if you want a maximum CPC. Enter 10 for a 10% conversion rate in the page’s percentage field. - Record each product’s break-even ACoS and target ACoS. These will be the starting points for lesson 2. Check my products (https://profitfirstppc.com/tools/catalog-profit-check/) What still needs your judgment The calculator estimates contribution from the costs you enter. It does not calculate your full company profit or prove that ads created extra orders. Include storage, returns and other relevant costs in your cost assumptions if you want a stricter line. Mixed products and multi-unit orders need a margin basis that matches the sales being measured. A launch campaign may deliberately run above target. Make that a named test with a budget and a review date. Do not turn an exception into the default for the entire catalog. Explain it to your team “Our target follows what each product can afford. Product A can spend 30% of revenue on ads and still keep the 10% contribution we chose.” Put this check into your weekly review. Follow the guided review to connect this decision to your reports, product margins and proposed changes. Each step names the evidence to keep. Use this step in your weekly review (https://profitfirstppc.com/weekly-ppc-review/#review-margins) Lesson 2: Find the products hidden by your blended ACoS (https://profitfirstppc.com/playbook/blended-acos/) See the full Playbook (https://profitfirstppc.com/playbook/) Want to connect your margins to your bids? Start with a free introductory conversation. I’ll ask about your business, advertising and goals, and we’ll discuss whether a closer review would help. Book a free introductory call (https://profitfirstppc.com/book.html) Definition reference: Amazon Ads guide to ACoS (https://advertising.amazon.com/library/guides/acos-advertising-cost-of-sales). --- ## What Blended ACoS Hides | PPC Playbook Source: https://profitfirstppc.com/playbook/blended-acos/ ← PPC Playbook (https://profitfirstppc.com/playbook/) Lesson 2 of 7 Find the products hidden by your blended ACoS. How can a good account ACoS hide products that lose money on ads? Short answer: Blended ACoS combines products with different margins and sales volumes. A strong product can cover another product’s loss. Compare each product’s ACoS with its own break-even line before treating the account total as a verdict. By Radu Bobirnac · Published October 13, 2026 Try Catalog Profit Check (https://profitfirstppc.com/tools/catalog-profit-check/) The question Your account ACoS is 21%, comfortably below its sales-weighted break-even line of 36%. Would you say every product is contributing? Pause before answering. An account total can be healthy while one product spends more than its own margin allows. Work through the numbers Continue with the two $40 products from lesson 1. This illustrative 30-day period has settled attribution, consistent sales definitions and one contribution rate per product. The account leaves $1,500 after ads while Product B loses $100. | Measure | Product A | Product B | Together | Ad-attributed sales | $8,000 | $2,000 | $10,000 | Ad spend | $1,600 | $500 | $2,100 | ACoS | 20% | 25% | 21% | Break-even ACoS | 40% | 20% | 36% weighted | Contribution before ads | $3,200 | $400 | $3,600 | Contribution after ads | $1,600 | −$100 | $1,500 The formula Blended ACoS = total ad spend ÷ total ad-attributed sales Weighted break-even ACoS = total contribution before ads ÷ total ad-attributed sales Product contribution after ads = product ad sales × product break-even ACoS − product ad spend The combined ACoS is $2,100 divided by $10,000, or 21%. It is not the simple average of 20% and 25%. The product with more sales carries more weight. For each product, estimated contribution after ads is ad sales multiplied by its break-even ACoS, minus ad spend. Product B leaves $2,000 × 20% − $500 = −$100. Product A’s $1,600 contribution makes that loss easy to miss in the total. If you choose to keep 10% of revenue after ads, A’s target is 30% and B’s is 10%. A is below target. B is above even its break-even line. They need different reviews despite sharing the same account. This does not mean turning B off will increase account contribution by exactly $100. Orders, traffic and spend can change after an intervention. It tells you where to investigate, using product economics rather than the account average. A published case to examine My sample cosmetics audit reported $2,591.91 in spend and $3,526.81 in ad-attributed sales, for a 73.5% ACoS. Return on ad spend, or ROAS, divides attributed sales by spend. Sponsored Products took approximately 90% of spend at a 1.11 ROAS; Sponsored Brands and Sponsored Display had reported ROAS values of 2.23 and 4.70. That snapshot illustrates why separating groups matters: the aggregate covered different advertising economics. It does not document the product-level losses in the teaching table. Without each group’s product margins, even a higher ROAS is insufficient to establish profit. Read the cosmetics sample audit (https://profitfirstppc.com/case-studies.html#cosmetics-audit). Try it on your numbers - Open Catalog Profit Check with the product costs from lesson 1. - Add “ACoS today” and “Ad sales / month” for the same settled 30-day period. Use a product-level report and check whether the sales column includes sales of other products. - Compare every product with its own break-even and target lines. Read the contribution estimate beside it before returning to the blended figure. - Choose one product to investigate. Write down whether the issue is low contribution before ads, high advertising cost, or both. - Download the result CSV if you want to keep the review. For the search terms behind a product, continue with Search Term Report Checker. Open Catalog Profit Check (https://profitfirstppc.com/tools/catalog-profit-check/) Inspect search term rows with Search Term Report Checker (https://profitfirstppc.com/tools/search-term-report-checker/). What still needs your judgment A product-level loss estimate depends on matching its margin to the attributed sales. Halo sales are credited purchases of products other than the advertised item. They can make a single margin misleading, as can mixed margins, changing prices and refunds. The tool does not separate advertising’s effect from orders that would have happened anyway. Before changing budgets, check inventory, campaign purpose and whether the losing product is part of a documented launch test. A healthy blended number gives you permission to ask more precise questions; it does not answer them. Explain it to your team “The account is contributing overall, but Product B is below its own break-even line. I want to inspect its search terms before changing the account’s target.” Put this check into your weekly review. Follow the guided review to connect this decision to your reports, product margins and proposed changes. Each step names the evidence to keep. Use this step in your weekly review (https://profitfirstppc.com/weekly-ppc-review/#review-margins) ← Lesson 1: Find the ACoS your product can afford (https://profitfirstppc.com/playbook/break-even-acos/) Lesson 3: Give search terms a fair test before adding negatives (https://profitfirstppc.com/playbook/when-to-negate-search-terms/) See the full Playbook (https://profitfirstppc.com/playbook/) Want to review which products your account average is hiding? Start with a free introductory conversation. I’ll ask about your business, advertising and goals, and we’ll discuss whether a closer review would help. Book a free introductory call (https://profitfirstppc.com/book.html) --- ## When to Negate Search Terms | PPC Playbook Source: https://profitfirstppc.com/playbook/when-to-negate-search-terms/ ← PPC Playbook (https://profitfirstppc.com/playbook/) Lesson 3 of 7 Give search terms a fair test before adding negatives. When should I negate a search term that has spent money without an order? Short answer: Start with the conversion rate the term needs to pay for its clicks, then check how unusual its results would be at that rate. Fifteen clicks is not a universal cutoff. Use settled orders and confirm relevance and exclusion scope before adding a negative. By Radu Bobirnac · Published October 20, 2026 Try When to Negate (https://profitfirstppc.com/tools/when-to-negate/) The question A search term has 15 clicks and no orders. Should you block it? The click count alone cannot answer. You need to know how often it must convert to pay for those clicks, and whether the reported orders have had time to arrive. Work through the numbers In this teaching example, a click costs $1.20 and a converting purchase contributes $12 before advertising. Break-even conversion rate is $1.20 divided by $12, or 10%. On average, one purchase per ten clicks pays for the advertising. Imagine the term really does convert at 10%, with independent clicks and a stable rate. The chance of no purchase on one click is 90%. The chance of no purchases on 15 clicks is 0.9 raised to the fifteenth power, about 20.6%. Zero orders is disappointing, but that result is still fairly common for a break-even term. At $1.20 CPC and $12 contribution, 29 zero-order clicks cross the 95% setting. | Settled clicks | Orders | Spend | Chance of zero orders | Tool result at 95% | 15 | 0 | $18.00 | 20.6% | Watch: 14 more clicks (about $16.80) | 29 | 0 | $34.80 | 4.7% | Review a negative The formula CPC = spend ÷ clicks Break-even purchase rate = CPC ÷ contribution before ads per purchase Chance of zero orders at break-even = (1 − break-even purchase rate) raised to the number of clicks For zero orders, review the flag when that chance is below 1 − confidence At 29 clicks, the chance falls below 5%. At the tool’s 95% setting, that is a flag to review a negative under this model. It is not a 95% probability that the term is unprofitable. The calculation asks how unusual this evidence would be if the term converted at break-even. Now predict what happens if contribution before ads doubles to $24 while CPC stays $1.20. Break-even falls to 5%. Zero orders need 59 clicks before crossing the same threshold: 0.95 raised to the fifty-ninth power is about 4.8%. A blanket “negate after 15 clicks” rule treats these products as if their economics were identical. Relevance is a separate check. If a query clearly asks for something your product cannot provide, you can review it for exclusion without buying enough clicks to complete a profitability test. A published case to examine My sample cosmetics audit identified $504 in spend on search terms with zero orders, 19.4% of the $2,591.91 total. The published review described gaps in negatives and broad or phrase traffic that was not converting. The $504 is a review queue, not a proven savings amount. The public case does not show every term’s clicks, margin and attribution maturity. Those details determine which terms merit a negative, a lower bid or more observation. This was an audit snapshot, not a completed improvement result. Read the cosmetics sample audit (https://profitfirstppc.com/case-studies.html#cosmetics-audit). Try it on your numbers - Choose one relevant term from a settled Search Term Report. Use clicks, spend and click-attributed purchases from the same full attribution window. - Open When to Negate. Enter the three totals and the product’s contribution before ads, or use the product from Catalog Profit Check. - Start with the 95% setting. Read both the result and the break-even conversion rate. - For an early or watch result, decide how much further testing fits your budget. The displayed extra-click cost is conditional on no new order and unchanged CPC. - For a negative flag, check the query’s relevance and the intended exclusion scope before changing Amazon settings. Keep a note of the reason and date. Open When to Negate (https://profitfirstppc.com/tools/when-to-negate/) What still needs your judgment The test assumes stable conversion, CPC and contribution, and at most one converting purchase per click. Recent report dates can miss later-attributed orders. Repeated checks and screening many terms increase the chance of false flags; the selected threshold does not remove that problem. A negative can affect more traffic than the one row you inspected. Review the match type and campaign scope. The tool does not choose those settings, account for assisted sales, or diagnose a listing that stopped converting. Explain it to your team “I checked this query against the conversion rate its margin requires. The evidence supports a review, and I confirmed the exclusion scope.” Put this check into your weekly review. Follow the guided review to connect this decision to your reports, product margins and proposed changes. Each step names the evidence to keep. Use this step in your weekly review (https://profitfirstppc.com/weekly-ppc-review/#review-negatives) ← Lesson 2: Find the products hidden by your blended ACoS (https://profitfirstppc.com/playbook/blended-acos/) Coming October 27 Choose search terms for an exact-match test See the full Playbook (https://profitfirstppc.com/playbook/) Want to talk through how you review zero-order spend? Start with a free introductory conversation. I’ll ask about your business, advertising and goals, and we’ll discuss whether a closer review would help. Book a free introductory call (https://profitfirstppc.com/book.html) Reference: Amazon Ads attribution guidance (https://advertising.amazon.com/help/GX7KDKHMWQYMJ385). --- ## Weekly Amazon PPC Review | Profit-First PPC Source: https://profitfirstppc.com/weekly-ppc-review/ The weekly PPC review Decide what to change in your Amazon ads this week. Review your reports, product margins, search terms and bids in seven steps. Record the actions to take, the decisions to hold and what you will check at the next review. Start the review (https://profitfirstppc.com/weekly-ppc-review/#review-data)Get the meeting template (https://profitfirstppc.com/weekly-ppc-review/#review-summary) [Image: Work the evidence. Then make the call. Reports, margins and decisions, set in cream and teal type on dark navy.] Before you begin Start with one product group. Choose one marketplace and two comparable reporting periods. Allow the full attribution window and reporting updates to settle. Keep recent delivery and stock checks separate from settled performance. What to bring to the review - Campaign and Search Term Reports for the periods you want to compare. - Price, Amazon fees, landed cost and other relevant costs for the products being reviewed. - Placement data if you plan to review placement bids. - A fresh, complete Sponsored Products bulk export before checking exact keyword coverage or preparing changes. Include zero-impression items. - Current stock, listing status, promotions and your previous change log. Missing a report or margin? Record the gap and hold any decision that depends on it. You can still review the evidence you have. Your review Review steps Finish with a written plan (https://profitfirstppc.com/weekly-ppc-review/#review-summary) Review each step and record your decision. 01Check the reports before the results.Decide: ready to analyze, or hold for better data. A confident recommendation starts with comparable data. Confirm the marketplace, currency, date range and attribution window before drawing conclusions. - Use matching purchase and sales windows. Separate duplicate rows, totals and overlapping exports. - Check that each report contains the detail the decision needs. A Search Term Report does not contain campaign placement totals. - Review stock, listing eligibility and recent promotions separately. A delivery problem needs a different response from weak conversion. Amazon Report Preflight A reusable skill for checking local exports before analysis. Install the complete skill in a compatible assistant, then supply the reports and account context. Get the report-checking workflow (https://profitfirstppc.com/tools/ai-skills/#amazon-report-preflight) Use your assistant for this step After installing the skill, copy this request into your assistant with the files. Review that environment’s data settings before sharing reports. Use amazon-report-preflight to validate these Amazon reports before analysis. Confirm marketplace, currency, date range, attribution windows, report grain and duplicate rows. Preserve the originals. Separate usable data from blocked inputs and list the missing context. Do not infer exact organic sales from differences between reports. Record: the usable files, settled date ranges and anything still blocking a decision. 02Know what each product can afford.Decide: the break-even line and the margin you want to keep. [Image: Each product. Its own limit. Start with its economics: know the costs, find break-even and choose a target.] An account average can hide products with very different economics. Review comparable products together and make the cost assumptions explicit. - Confirm selling price, fees, landed cost and other relevant costs. Recheck after a price change or promotion. - Calculate profit before ads and break-even ACoS. Choose a target below break-even that reflects the contribution you want to retain. - For search-term decisions, use contribution per attributed purchase. Adjust a one-unit estimate for multiple units or other products purchased. Catalog Profit Check Calculate product-level break-even ACoS, target ACoS and CPC limits. Optional current ACoS and ad sales put the difference into dollars. Check product economics (https://profitfirstppc.com/tools/catalog-profit-check/) A simple example: $12 contribution before ads on a $40 sale gives a 30% break-even ACoS. Keeping $4 after ads leaves $8 for advertising, or a 20% target ACoS. These are teaching numbers, not recommended targets. Record: the cost assumptions, break-even ACoS and target for each product group. Missing costs remain an open question. 03Explain the ACoS change before changing bids.Decide: what to investigate first. A higher ACoS can reflect more expensive clicks, fewer purchases per click, or less revenue per purchase. Each points to a different investigation. - Compare the same product group over comparable, settled periods. Note promotions, price changes and shifts in traffic mix. - Separate the arithmetic contribution of CPC, purchase rate and sales per purchase. Then check the underlying terms, placements and listing context. - If Ads and Business Report sales differ, check their definitions and dates before treating the gap as a business result. ACoS Change Explainer Compare two reports or typed totals to see how the components changed. The breakdown describes the movement; it does not prove its cause. Explain the change (https://profitfirstppc.com/tools/acos-change-explainer/)Reports disagree? Check the sales definitions ↗ (https://profitfirstppc.com/tools/amazon-report-mismatch-checker/) Record: the main numerical driver, your working explanation and the evidence still needed to test it. 04Give low-order search terms a fair test.Decide: investigate, keep testing, adjust a bid, or review a negative. Start with spend that has produced few or no purchases. Treat it as a review queue. The right response depends on relevance, settled evidence and the product’s margin. - Keep campaign, ad group and product context with every term. Separate search queries from product targets. - Check relevance first. For relevant terms, compare clicks and purchases with the conversion rate needed to cover their click cost. - Review exclusion scope and match type before adding a negative. Protect terms that need a strategic review; avoid a universal click cutoff. Start with the report. Inspect the term. Find the rows in Search Term Report Checker, then use When to Negate for a closer margin-based review. Review the search terms (https://profitfirstppc.com/tools/search-term-report-checker/)Check the evidence for one term (https://profitfirstppc.com/tools/when-to-negate/) A statistical flag is a reason to review. Repeated checks, multiple tests and changing conversion conditions affect how you interpret it. Record: the term, product context, evidence, proposed action and reason. Keep unproven “savings” out of the result. 05Choose terms that deserve more control.Decide: test exact match, collect more evidence, or hold. A first sale is a useful signal. An exact-match test still needs a relevant query, plausible economics and enough evidence to justify its budget. - Review converting terms in their original campaign and ad group. Use a comparable campaign baseline and product contribution. - Check the fresh bulk export for an existing exact keyword, its state and the products it advertises. Missing from one report does not prove missing from the account. - Plan the destination, starting bid and test budget. Confirm the destination is eligible and delivering before adding negatives that route traffic away from discovery. Harvest Readiness Review conversion evidence and uncertainty before an exact-match test. Its model uses an uncalibrated baseline weight; read the assumptions with the result. Review a harvest candidate (https://profitfirstppc.com/tools/harvest-readiness/) Record: the candidate, existing coverage, intended destination, test limits and what would justify the next change. 06Review bids, placements and budget together.Decide: where a controlled change is justified. A budget increase should have a reason beyond yesterday’s sales. Check click value, campaign purpose and stock before funding more traffic. - Use actual placement data. Compare attributed sales per click with the product’s target ACoS and note sparse samples. - Review the base bid, placement adjustments and dynamic bidding strategy together. A placement percentage is only one part of the setting. - Check budget constraints, inventory cover and listing readiness. Prioritize a bounded test where evidence and capacity support it; document strategic exceptions. Placement Bid Calculator Work through base bids and placement settings against estimated click value. Budget allocation remains your decision. Review placement settings (https://profitfirstppc.com/tools/placement-bid-calculator/) Record: the current setting, proposed setting, economic reason, spending limit and conditions for reviewing the test. 07Check the changes. Keep the reasoning.Decide: ready for review and upload, or blocked. [Image: Check the changes. Keep the reasoning. Evidence: keep the reason. Owner: assign the action. Review date: check the result.] Turn the review into a short, controlled change list. Each action should have a reason, a limit and a way to check what happened. - Compare proposed changes with a fresh, complete configuration export. Check IDs, parent entities, duplicates, negative conflicts, names and bid or budget limits. - Review the checked file before uploading through Amazon. Then inspect processing results and a fresh read-back; a prepared file does not prove a change was applied. - Confirm delivery before routing traffic. Set a review date that allows new performance to settle, and compare with the expectations in your change log. PPC Bulk File QA A local workflow for supported Sponsored Products keyword, negative, bid and daily-budget changes in the US, UK and Canada. Real client-export and Amazon upload acceptance validation remain pending. Get the bulk-file checking workflow (https://profitfirstppc.com/tools/ai-skills/#amazon-ppc-bulk-qa) Use your assistant for this step Install the complete skill first. Supply your proposed changes and fresh configuration export in your chosen assistant. Use amazon-ppc-bulk-qa to validate these proposed Sponsored Products changes against this fresh, complete bulk export. Preserve names and IDs. Check parent relationships, duplicate exacts, negative conflicts and bid/budget limits. Default to no more than 25 new exacts per campaign unless I specify another cap. Prepare the checked upload and before/after list only if the batch passes. Hold routing negatives until destination read-back and delivery are confirmed. Do not make live account changes. Record: the approved changes, held items, upload outcome, read-back, owner and next review date. Next week, begin here. Weekly action plan Use this template in your weekly meeting or change log. Fill it with findings from your tools and reports. A decision to hold or collect more evidence belongs in the plan too. The checklist tracks which steps you reviewed, not whether your account passed a test. Your weekly decision brief WEEKLY PPC REVIEW Marketplace / product group: Reporting periods / attribution window: Business goal / inventory constraints: WHAT CHANGED Finding / supporting report: Economic context / assumptions: WHAT WE WILL DO Current setting → proposed setting: Reason / evidence / test limit: Owner / target date: WHAT WE WILL HOLD Open question / missing evidence: What would change the decision: NEXT REVIEW Upload outcome / configuration read-back: Delivery confirmed / routing negatives held: Review date / expected signal: What happened after last week’s changes: Related lessons and tools Find worked examples in the PPC Playbook (https://profitfirstppc.com/playbook/) or browse the calculators and report tools (https://profitfirstppc.com/tools/). Sources, scope and data handling This page receives no reports and makes no campaign changes. Checklist progress stays in this page’s memory. Copying a request does not send it to an assistant; the assistant and tools you choose follow their own data settings. This is a review framework for Sponsored Products, not a complete account audit. The linked skills support US, UK and Canadian local exports within their documented scope. Report comparisons and profitability estimates depend on the inputs and assumptions you supply. Platform references: Amazon’s Sponsored Products Search Term Report (https://advertising.amazon.com/help/G3HEFZYWZF84NPS9) and Amazon’s targeting guide (https://advertising.amazon.com/library/guides/targeting-with-sponsored-products). Method-specific formulas and limits live on each linked tool. Written by Radu Bobirnac (https://profitfirstppc.com/about.html) · October 20, 2026. --- ## Privacy Policy | Radu Bobirnac, Profit-First Amazon PPC Source: https://profitfirstppc.com/privacy.html Privacy Privacy policy What this site collects, why, and what happens to it. Short version: form details help me prepare for your call or send what you requested. If you allow analytics, Google Analytics measures visits and tool use. I never sell your information. Last updated: 14 October 2026 Who runs this site profitfirstppc.com is run by Radu Bobirnac, an independent Amazon advertising consultant based in Ocean City, Maryland, USA. “I” and “me” on this page mean Radu Bobirnac. What I collect When you request an introductory call The form on the booking page (https://profitfirstppc.com/book.html) asks for your name, work email, Amazon store link, monthly ad spend range and main goal. It also lets you add your current ACoS and a note, if you want to. When you ask for the break-even spreadsheet The form on the home page asks for your work email only. When you book a call The confirmation page embeds a Google Calendar booking page. Loading that calendar connects your browser to Google. When you book, Google receives your name, email address and the appointment details and sends calendar invitations and updates under its own privacy policy. When you purchase an audit Audit checkout is handled by Stripe when the purchase option is available. Stripe collects your payment and contact details; this site does not collect card numbers. The audit intake asks for your checkout email, Amazon store link, main goal and an optional note. I use those details to match your purchase and deliver the audit. Reports and product costs are requested separately by email. The intake form does not verify payment and sends no lead or purchase analytics event. When we work together I receive the advertising reports, product costs and account information needed for our agreed work. For a Sprint or ongoing management, you grant access through Amazon’s user permissions. You do not share your password. I use this information to deliver the work we agree on. What I don’t collect - The free tools don’t send your numbers anywhere. The Catalog Profit Check, When to Negate, the Placement Bid Calculator and Harvest Readiness run entirely in your browser. What you type is saved in your browser’s local storage, on your device, so it’s there when you come back. It never reaches me or any server. Clearing your browser data deletes it. - Report comparisons stay in the current tab. The ACoS Change Explainer (https://profitfirstppc.com/tools/acos-change-explainer/) and Amazon Report Mismatch Checker (https://profitfirstppc.com/tools/amazon-report-mismatch-checker/) keep typed totals and imported files in this tab’s memory. They do not upload or save them, or send them to an AI. Clear everything or close the tab to remove them. Downloaded reviews remain on your device. - Search Term Report files stay in the current tab. The Search Term Report Checker (https://profitfirstppc.com/tools/search-term-report-checker/) reads report and optional bulk-export files in your browser’s memory. It does not upload or save those files, or send them to an AI. Clear the report or close the tab to remove them. Saved Catalog Profit Check estimates can be used locally. If you explicitly open one term in another calculator, that term’s numbers are passed locally to it and follow its existing local-save behavior. Downloaded reviews remain on your device; sharing them is your choice. - The tool APIs don’t keep what you send. The same calculators are also available as a JSON API at /api/, for people who call them from their own code. Only data you choose to send there reaches a server. It calculates the answer, sends it back and stores nothing. The host’s short-lived logs (below) may record the request. - No advertising or remarketing tags. Analytics is configured with advertising storage, advertising user data, advertising personalization and Google signals disabled. After you submit the booking form, your first name is held in your browser for that visit only, so the next page can greet you. They’re removed when you close the tab. Optional website analytics Google Analytics 4 measures visits and interactions only after you choose “Allow analytics.” Before you choose, or if you reject analytics, this site does not load the Google Analytics tag or send analytics events. All calculators remain available. With your permission, Google receives page addresses and titles, referring page addresses, browser and device information, approximate geographic information derived from your connection, and events such as calculator use, CSV downloads, inquiry-form attempts, successfully submitted forms and clicks to the booking calendar. A successful-submission event identifies only which of the two forms was used. Analytics cookies recognize your browser across visits. Calculator inputs, search terms, reports, names, email addresses and form answers are not included in our analytics events. Query strings and URL fragments are removed from the page and referrer addresses supplied by our tracking code. For links from our public AI skills and repository, an allowlist of fixed labels identifies the skill, referral campaign and whether the link came from instructions or a report. These labels contain no client information. The skill scripts themselves make no usage-tracking requests. Your analytics choice is stored on your device for up to six months. Analytics cookies are configured to expire after six months and may be renewed by later visits. Use “Analytics preferences” in the footer to change your choice. Rejecting after acceptance stops further analytics collection by this site and clears its accessible Google Analytics cookies; it does not erase data already received by Google. If browser storage is blocked, your choice applies to the current page and you may be asked again. Form-attempt events and successful-submission events are separate. A successful-submission event is sent only after Netlify acknowledges the form submission, and only if you allow analytics. It does not prove the request is genuine or qualified; accepted Netlify submissions remain the authoritative request count. Clicking the calendar link records a handoff, not a confirmed appointment. Interactions inside Google’s calendar are not tracked by this site. Tools embedded on other websites Some calculators can be embedded on other websites. They work the same way there: your numbers stay in your browser, nothing is saved, and no analytics run inside the embed. Each time an embedded calculator loads, it records the tool’s name and the domain of the website showing it (for example, example.com), with a running count and the first and last date. Nothing about you, such as your IP address or the page you were reading, is recorded, apart from Netlify’s short-lived server logs. How I use it - To prepare for and follow up on the call you asked for, including your written quote. - To send you the spreadsheet you asked for, and at most one follow-up email asking whether it helped. - To reply to you about working together. - To confirm an audit purchase, request the information needed, deliver your audit and arrange an optional walkthrough. - If you allow analytics, to understand which pages and tools are useful and improve the site. I don’t send newsletters or marketing emails unless you ask for them, and I never sell or rent your information. Who else handles it - Netlify hosts this site and processes the forms. Like any web host, it keeps short-lived server logs, including IP addresses, to run and protect the site. See Netlify’s privacy policy (https://www.netlify.com/privacy/). - Stripe processes audit payments and receipts on its hosted checkout. See Stripe’s privacy policy (https://stripe.com/privacy). - YouTube plays the intro video on the About page. Nothing loads from YouTube until you press play; after that, Google’s privacy policy (https://policies.google.com/privacy) applies. Before you press play, the preview image comes from YouTube’s image server. - Google Analytics processes the optional analytics information described above. See Google’s privacy policy (https://policies.google.com/privacy). - Google Calendar provides the embedded booking page and handles appointments, Google Meet links and booking confirmations. See Google’s privacy policy (https://policies.google.com/privacy). I’m based in the United States, and these providers may store data in the United States or other countries. How long I keep it Form submissions are kept while we’re talking about working together, and for up to two years after our last contact, unless you ask me to delete them sooner. If we work together, I keep what I need for the engagement and for invoicing and tax records. Client reports and working files are deleted within 90 days after an engagement ends, except records required for invoicing and tax. Client names are kept private, and published case studies are anonymized. Your choices You can ask me what I hold about you, ask me to correct it, or ask me to delete it. Email me at bobirnacr+site (at) gmail.com (https://profitfirstppc.com/book.html), reply to any email I’ve sent you, or message me on LinkedIn (https://www.linkedin.com/in/radubobirnac). I’ll respond within 30 days. Depending on where you live, you may also have the right to complain to your local data protection authority. Changes If I change how the site handles your information, I’ll update this page and the date at the top. --- ## Sitemap | Profit-First Amazon PPC Source: https://profitfirstppc.com/sitemap/ Sitemap Find services and pricing, calculators, report checks, the weekly review and published Playbook lessons. XML sitemap for search engines (https://profitfirstppc.com/sitemap.xml). --- ## For AI | Profit-First Amazon PPC Source: https://profitfirstppc.com/ai/ For AI Read the published site, find the right PPC resource and use the calculators with structured inputs. Read the site Services, pricing, methods, case evidence and published lessons. Start with the reading guide (https://profitfirstppc.com/llms.txt) More formats - All published page text (https://profitfirstppc.com/llms-full.txt) - Content and tool catalog (JSON) (https://profitfirstppc.com/ai/catalog.json) - Page sitemap (XML) (https://profitfirstppc.com/sitemap.xml) - Published lesson feed (RSS) (https://profitfirstppc.com/playbook/feed.xml) Use the tools Seven calculators and report checks, with inputs, results and limits. Browse the tool directory (https://profitfirstppc.com/ai/#tool-directory) API and WebMCP OpenAPI specification (https://profitfirstppc.com/api/openapi.json) · Resolved tool schemas (https://profitfirstppc.com/ai/tools.json) WebMCP registers the seven tools on this page when supported by the browser. Calculations run locally using the same code as the calculators. Browser support varies; the JSON APIs are also available. HTTP API calls send the supplied values to the server. WebMCP tool calls do not send inputs to the server or read saved calculator inputs. Get a skill Check reports, proposed bulk changes or existing video in your assistant. Download skills and practice files (https://profitfirstppc.com/tools/ai-skills/) How skills fit Each ZIP includes instructions, scripts and a first exercise. Install it in a compatible assistant that can run the scripts, then review its findings before acting. This directory covers public content and tools. The text and catalogs rebuild with the site; unreleased lesson bodies and confirmation pages are excluded. Using the content and results Keep source URLs, reporting dates and limitations with any summary. Case-study snapshots show reported account results; they do not establish incremental lift. Teaching examples and practice files are illustrative. Tool results depend on the supplied costs, report scope and model assumptions. Tool directory Open a tool for its purpose, limits and an example request. Schemas are generated from the existing API specification. Catalog Profit Check Which products lose money on ads? Up to 500 products Limits: Rates are fractions: 0.30 means 30%. Contribution estimates require complete supplied costs; they are not net business profit. Inspect per-product errors even when the batch call succeeds. Open the tool (https://profitfirstppc.com/tools/catalog-profit-check/) · API usage (https://profitfirstppc.com/api/catalog-profit-check) POST https://profitfirstppc.com/api/catalog-profit-check { "marginToKeep": 0.1, "products": [ { "name": "Water bottle 750ml", "price": 39.99, "fees": 11.2, "cost": 9.5, "conversionRate": 0.12, "acos": 0.22, "adSales": 18400 }, { "name": "Bottle 2-pack", "price": 24.99, "fees": 9.1, "cost": 11.4, "conversionRate": 0.1, "acos": 0.31, "adSales": 9200 } ] } Input and result fields: OpenAPI specification (https://profitfirstppc.com/api/openapi.json). WebMCP name: calculate_catalog_profit. When to Negate Check one search term, or up to 500 Limits: Single-term binomial evidence under supplied assumptions. Statistical evidence is not certainty or proof of wasted spend. Open the tool (https://profitfirstppc.com/tools/when-to-negate/) · API usage (https://profitfirstppc.com/api/when-to-negate) POST https://profitfirstppc.com/api/when-to-negate { "clicks": 24, "orders": 0, "spend": 28.8, "profitPerOrder": 19.29 } Input and result fields: OpenAPI specification (https://profitfirstppc.com/api/openapi.json). WebMCP name: review_search_term_negation. Harvest Readiness Send one term's fields, or { defaults, terms: [...] }. Defaults apply to every term unless the term overrides them. Limits: Single-term, uncalibrated model. Does not estimate incremental profit from harvesting or guarantee future performance. Open the tool (https://profitfirstppc.com/tools/harvest-readiness/) · API usage (https://profitfirstppc.com/api/harvest-readiness) POST https://profitfirstppc.com/api/harvest-readiness { "clicks": 60, "orders": 12, "spend": 72, "profitPerOrder": 12, "baselineCvr": 0.1 } Input and result fields: OpenAPI specification (https://profitfirstppc.com/api/openapi.json). WebMCP name: review_exact_match_readiness. Placement Bid Calculator A click in each placement is worth (sales ÷ clicks) × target ACoS. Returns two options: rebalance (the weakest placement sets the keyword bid) and keep today's keyword bid. Placements under 30 clicks don't set bids. Docs: https://profitfirstppc.com/tools/placement-bid-calculator/ Limits: Rates are fractions. Low-evidence placements and minimum-bid exceptions need review; no Amazon settings are changed. Open the tool (https://profitfirstppc.com/tools/placement-bid-calculator/) · API usage (https://profitfirstppc.com/api/placement-bids) POST https://profitfirstppc.com/api/placement-bids { "breakEvenAcos": 0.482, "marginToKeep": 0.1, "keywordBid": 1.0, "strategy": "fixed", "placements": { "topOfSearch": { "adjustment": 50, "clicks": 400, "spend": 560, "orders": 60, "sales": 2400 }, "restOfSearch": { "adjustment": 0, "clicks": 300, "spend": 300, "orders": 24, "sales": 960 }, "productPages": { "adjustment": 0, "clicks": 250, "spend": 200, "orders": 8, "sales": 320 } } } Input and result fields: OpenAPI specification (https://profitfirstppc.com/api/openapi.json). WebMCP name: calculate_placement_bids. Search Term Report Checker Pure report analysis. No file upload or storage. Optional sales must use the same purchase attribution window. One currency per request. Orders greater than clicks remain descriptive and skip probability models. Bulk exact-keyword inventory is browser-only. Zero-order spend is not confirmed waste. Limits: At most 500 normalized rows. Zero-order spend is not confirmed waste. Same report context and attribution definitions are caller prerequisites. Open the tool (https://profitfirstppc.com/tools/search-term-report-checker/) · API usage (https://profitfirstppc.com/api/search-term-report) POST https://profitfirstppc.com/api/search-term-report { "rows": [ { "term": "water bottle", "clicks": 20, "orders": 0, "spend": 24, "sales": 0, "campaign": "Discovery", "adGroup": "Bottle", "matchType": "BROAD" } ] } Input and result fields: OpenAPI specification (https://profitfirstppc.com/api/openapi.json). WebMCP name: review_search_term_report. ACoS Change Explainer Six-order averaged arithmetic bridge for ACoS change. Same scope and attribution definitions must be checked by the caller. Not a causal diagnosis. Limits: An arithmetic allocation, not a causal diagnosis. Compare consistent scope, currency and attribution definitions. Open the tool (https://profitfirstppc.com/tools/acos-change-explainer/) · API usage (https://profitfirstppc.com/api/acos-change-explainer) POST https://profitfirstppc.com/api/acos-change-explainer { "before": { "clicks": 1000, "spend": 1000, "orders": 100, "sales": 5000 }, "after": { "clicks": 1000, "spend": 1200, "orders": 80, "sales": 3600 } } Input and result fields: OpenAPI specification (https://profitfirstppc.com/api/openapi.json). WebMCP name: explain_acos_change. Amazon Report Mismatch Checker Comparison-basis checklist and currency-compatible numeric gap. Not order-level reconciliation or an exact organic revenue calculation. Limits: A comparison-basis checklist, not order-level reconciliation or exact organic revenue. Open the tool (https://profitfirstppc.com/tools/amazon-report-mismatch-checker/) · API usage (https://profitfirstppc.com/api/amazon-report-mismatch-checker) POST https://profitfirstppc.com/api/amazon-report-mismatch-checker { "adsSales": 12000, "retailSales": 10000, "adsCurrency": "USD", "retailCurrency": "USD", "adsStart": "2026-08-01", "adsEnd": "2026-08-14", "retailStart": "2026-08-01", "retailEnd": "2026-08-14", "dateBasis": "interaction", "scope": "unknown", "settled": "yes" } Input and result fields: OpenAPI specification (https://profitfirstppc.com/api/openapi.json). WebMCP name: review_report_comparability.