203 free tools for growth & performance marketers

Work out your average order value (AOV) — revenue divided by orders — and see how lifting it widens the margin you can spend to acquire each customer.

Derive the maximum allowable CAC your unit economics can fund, so you know how aggressively you can outbid rivals without breaking payback.

Roll every paid and organic channel into one blended customer acquisition cost, the honest number for what it really takes to win a customer.

Divide net burn by net new ARR to get your burn multiple, the cleanest read on how much cash you torch to buy each dollar of growth.

Pin down your customer acquisition cost (CAC) from total spend and new customers, the baseline every channel and payback decision builds on.

Stress-test how much rising CAC your margins can absorb before payback breaks, so a bad-auction quarter does not quietly sink your economics.

See how many months it takes to recoup customer acquisition cost from gross margin, the gate that decides how fast you can reinvest.

Combine your LTV:CAC ratio with payback period into one capital-efficiency score that tells you whether growth is actually paying for itself.

Measure the share of customers or revenue you lose each period, the leak that quietly caps growth no matter how hard acquisition works.

Find your contribution margin per order after variable costs, the most-overlooked number that decides how much you can really spend to acquire.

Build customer lifetime value (LTV) from order value, frequency, margin, and lifespan, so you know the ceiling on what each customer is worth.

Turn revenue and COGS into gross margin percentage, the figure that sets how much room you have to spend on growth and still profit.

Pit lifetime value against acquisition cost to get your LTV:CAC ratio, then judge it against the 3:1 line that signals a defensible model.

Track month-over-month MRR growth as a clean percentage, the pulse VCs read first when deciding whether your momentum is real.

Expose the CAC of your last, most expensive customer, so you spot the point where scaling spend stops being worth what it brings in.

Check whether expansion revenue is outrunning churn, the negative-churn signal that lets a business grow even if it never adds a customer.

Calculate net revenue retention (NRR) from renewals, expansion, and churn, the single number that proves your existing base compounds on its own.

Measure the share of customers you keep across a period, the flip side of churn and the foundation of every lifetime-value estimate.

Add growth rate to profit margin and test it against the Rule of 40, the shorthand investors use to balance speed against discipline.

Divide net new ARR by sales and marketing spend to get your SaaS magic number, a fast read on whether go-to-market is paying off.

Weigh new and expansion revenue against churn and contraction to get your SaaS quick ratio, a one-glance verdict on growth quality.

See what a few points of lift in first-to-repeat conversion is worth, because crossing the second-purchase line is where retention economics begin.

Calculate customer acquisition cost with industry benchmark context and a plain verdict, in basic or advanced mode, so the number means something.

Tell it your goal, account structure, and budget, and get the exact Google Ads reports, columns, and segments to build — no guesswork.

Tell it your objective, channel mix, and budget, and get the programmatic reports, dimensions, and supply-path breakdowns worth building — no guesswork.

Find the share of eligible impressions you actually win, the auction signal that tells you whether bids or budgets are holding you back.

Back into the highest bid you can afford from your target CPA and expected conversion rate, so you cap spend without choking volume.

Estimate the shaded bid first-price auctions actually need, so you stop overpaying for impressions the second-price logic would have discounted.

Pin the minimum ROAS that keeps a campaign in the black, the break-even line every target and bid decision has to clear.

Check whether spend is tracking to plan mid-month and project where it lands, so you catch under- or over-pacing before the budget is blown.

Divide spend by conversions to get cost per acquisition (CPA), the bottom-line price of a customer that decides if a channel earns its place.

Find your true cost per click (CPC) from spend and clicks, the number that tells you whether a keyword or placement is even worth bidding on.

Work out cost per install (CPI) from app spend and installs, the entry price you pay before a single user has done anything valuable yet.

Turn spend and leads into cost per lead (CPL), then judge it against the close rate that decides whether those leads are actually affordable.

Compute cost per thousand impressions (CPM) from spend and reach, the rate card of awareness buying and your first lever on media cost.

Track how far your CPM has climbed year over year, so you can tell real auction inflation from a targeting or seasonality problem.

Get cost per view (CPV) from video spend and views, the price of attention that decides whether a creative is buying eyeballs efficiently.

Translate monthly churn into average customer lifespan, the time horizon that anchors every lifetime-value and payback calculation you run.

Calculate DTC CAC payback the honest way, with shipping and returns folded in, so the recovery timeline reflects what really hits the bank.

Convert a monthly target into the daily budget platforms actually spend against, so pacing matches intent instead of drifting off plan.

Size the minimum daily budget a Google Demand Gen campaign needs to exit learning, so you fund it enough to optimize instead of starving it.

Measure the share of leads that become customers, the conversion step that decides whether your lead volume is worth what you pay for it.

Divide total revenue by total marketing spend to get your Marketing Efficiency Ratio (MER), the blended read that platform ROAS keeps overstating.

Enter your targets and industry to get a benchmark-driven, full-funnel cross-channel media plan with poor, average, and best-case scenarios.

Find the minimum daily budget Performance Max needs to clear learning, so the campaign gets enough signal to optimize rather than flail.

Check whether you are ready for Performance Max, get the guardrails to set before launch, and a clean asset-group structure for your business.

Trace where each programmatic dollar actually goes — the ad-tech tax, viewability loss, and the working media you can recover.

See how a higher Quality Score cuts your CPC, so you can value an account cleanup against simply bidding more to win the same clicks.

Turn ad spend and revenue into return on ad spend (ROAS), then pressure-test it against the break-even line your margins actually allow.

Set a ROAS target that ties back to your LTV and CAC goals, so the number you hand the bidding algorithm reflects real profitability.

Compare platform-reported conversions to your source of truth and quantify the overstatement, so you stop crediting walled gardens for sales they did not drive.

See how much of your programmatic budget reaches a real, viewable person after ad-tech fees and waste, your true working-media share.

Convert CPC and click-through rate into an effective CPM (eCPM), so you can compare CPC and CPM buys on the same impression-cost footing.

Share your objective, funnel focus, and budget, and get the TikTok Ads reports, breakdowns, and creative metrics worth tracking — no guesswork.

Give it your goal, audience, and budget, and get the LinkedIn Ads reports, columns, and breakdowns that match B2B intent — no guesswork.

Work out average frequency — impressions per unique user — so you can tell healthy reinforcement from the wear-out that quietly kills response.

Quantify how much your ad platforms double-count against your real orders, so the conversions you report are the ones you can actually bank.

Estimate unique reach from impressions and frequency, so you know how many real people a campaign touched rather than how often it showed.

Estimate the branded-search lift your brand spend pulls through, so you credit upper-funnel media for the demand it actually creates.

Forecast the awareness lift a given spend level should buy, so you set brand-campaign expectations before the dollars go out the door.

See what share of total available impressions you are capturing, so you know how much headroom is left before more budget stops buying more.

Estimate your Conversions API Event Match Quality band from the identifiers you send, so you fix signal gaps before they throttle Meta delivery.

Find how many Meta ad sets your account can run without starving the roughly 50-conversion learning floor, so each one actually optimizes.

Plan a paid-social budget across prospecting, retargeting, and retention, with projected customers, CAC, ROAS, and a demand-versus-capture verdict.

Tell it your goal, objective, funnel focus, industry, and budget, and get the exact Meta Ads reports, columns, and breakdowns to build — no guesswork.

Score a YouTube ad against Google's ABCD creative framework and get a prioritized fix-list to lift view-through and conversions.

Explore YouTube Ads benchmarks by funnel stage — CPV, view rate, CPM, CTR — with a judge that reads each metric in context.

Plan a YouTube full-funnel campaign — nested audiences, formats, and budgets mapped to each stage from awareness to action.

How the YouTube algorithm ranks and recommends video — the signals, the feedback loop, and what it means for your ads.

See how last-click undercounts YouTube — model view-through and incrementality against the attribution gap.

Enter your connected-TV budget, CPM, audience, and frequency goal to project unique household reach and the percentage of your audience covered.

Plan connected-TV reach and frequency from budget, CPM, audience size, and target frequency, with net reach, coverage, and average exposure.

Work out how many fresh creative concepts you need per quarter to outrun fatigue, so spend keeps performing instead of decaying on stale assets.

See how many creatives you can actually test per month at a readable significance, so your testing roadmap matches the volume your budget supports.

Enter budget, cost per result, and the conversions a test needs to read, and learn how many creative concepts you can fairly evaluate.

Model the ROI of a creative testing program from spend, ROAS, margin, production cost, winner rate, and uplift, so testing earns its budget.

Measure hook rate — the share who watch past three seconds — the first gate a paid-social creative has to clear before anything else matters.

Find the sample size you need to prove a hook-rate lift is real, so you stop crowning winners off a handful of noisy early views.

Generate a production-ready weather-triggered bid and budget script for Google Ads and Microsoft Advertising, powered by the OpenWeather API.

Enter YouTube spend, impressions, views, and conversions to get cost per view, view rate, CPM, and cost per conversion in one pass.

Forecast YouTube Ads views, conversions, ROAS, and CAC from budget, cost per view, view-to-site rate, conversion rate, and average order value.

Measure video hold rate — the share who keep watching past the hook — to learn whether a creative sustains attention or loses it after three seconds.

Measure the pace at which you are earning backlinks, so you can tell natural link growth from the spiky pattern that trips spam filters.

Find the month your content library's cumulative traffic would cost more to rent through ads than it cost to build, the case for owning demand.

Estimate the annual organic value your content earns, so you can defend a content budget against the paid spend it quietly replaces.

Model content as a power-law portfolio — run-rate value, two-year net and ROI, true cost per winner, and the lever that moves the most.

Combine LCP, INP, and CLS into a single Core Web Vitals score, so you know whether page experience is helping or quietly capping your rankings.

Turn indexable URLs, daily Googlebot fetches, and crawl waste into a full-recrawl cycle, freshness ratio, and a prioritized fix list.

Estimate your odds of capturing the featured snippet (Position 0), so you target the queries where structured answers are actually winnable.

Generate correct reciprocal hreflang annotations as HTML link tags or sitemap XML, with ISO-validated codes, x-default, and the return-link rule built in.

Paste text or fetch a URL to compute keyword density for every term, with stopword removal and custom filters, exportable to CSV, Excel, or Word.

Sort seed keywords into intent tiers and match types — Exact, Phrase, and fenced Broad — the RGM way, so structure follows intent from the start.

Combine up to four keyword lists into every variation, output in broad, phrase, exact, and modified match types, and export to CSV, Excel, or Word.

Check whether target keywords land in high-visibility spots — title, meta, headings, first and last sentence, URL, alts — and get a weighted prominence score.

Measure the distance between target keywords in any text to surface co-occurrence patterns, spot over-clustering, and export the results.

Paste reviews, articles, transcripts, or SERPs to extract bigrams through 5-grams with frequency counts, exportable to CSV, Excel, or Word.

Enter a URL and we run a real Lighthouse audit via Google PageSpeed — Core Web Vitals, technical and on-page SEO, schema, and AEO/GEO — sorted into an owner-tagged action plan.

Project your audience and monthly reach a year out, then see whether cadence, shareability, or conversion is the lever that grows you fastest.

See what your organic social reach is worth as ad spend you avoid, why reach rate beats follower count, and where the real value sits.

Translate slow load times into the conversions and revenue you lose, so a speed fix gets costed against the sales it quietly recovers.

Estimate organic traffic from search volume and your ranking position, so you can size the prize before committing to a keyword target.

See the expected click-through rate for each SERP position, so you can forecast the traffic a ranking move from page two to the top actually buys.

Enter a domain to pull its real sitemap (or paste a list) and visualize the site’s URL structure and depth, with a cleanup roadmap.

Surface the revenue sitting dormant in your CRM and what winning it back is worth versus acquiring strangers, your cheapest growth lever first.

Calculate click-to-open rate (CTOR) from clicks and opens, the post-MPP engagement read that survives Apple's inflated open numbers.

Measure the share of abandoned carts you recover and what each point is worth, so you size the flow that earns the most per hour to build.

Divide clicks by emails delivered to get click rate, the engagement signal that predicts deliverability long before revenue shows up.

Score your sender foundation across authentication, compliance, list hygiene, and measurement, so you find why mail lands in spam before a send tanks.

Enter list size, revenue per email, and how fast extra sends fatigue your list to find the send frequency that maximizes profit, not just opens.

Compare a treatment group to a randomly held-out control to measure the true incremental revenue per recipient your email program actually adds.

Net new subscribers against unsubscribes and bounces to get monthly list growth, the read on whether your audience is compounding or quietly shrinking.

Calculate email open rate from opens and deliveries, with the caveat that Apple's Mail Privacy Protection has inflated it since 2021.

Enter list size, growth, deliverability, frequency, AOV, and flow coverage to forecast monthly email revenue and where it comes from.

Work out revenue per email send, the per-campaign yield that tells you whether another send is earning its place or just burning the list.

Score an email for spam risk, deliverability, length, and compliance with CAN-SPAM, GDPR, and CASL, plus AI-style subject alternatives and exports.

Calculate unsubscribe rate from opt-outs and sends, the early-warning gauge that flags a content or cadence problem before deliverability suffers.

Project annual email revenue from campaigns and triggered flows, and see the share flows contribute, the engine that runs without a human hitting send.

Project your customer base and revenue two years out, with LTV, LTV:CAC, and a verdict on whether retention or acquisition is your bigger lever.

Get the right lapse window for your send frequency, size your at-risk and never-active segments, and set a sunset policy that protects deliverability.

Estimate the ROI of replenishment reminder emails timed to a product's reorder cycle, so well-timed nudges turn one purchase into a habit.

Calculate SMS click-through rate from clicks and messages delivered, the engagement read on a channel where every send carries a real per-message cost.

Price the hidden cost of list-burn from send cost, conversion, AOV, opt-out rate, and subscriber LTV, so SMS profit reflects churn, not just clicks.

Enter subscribers, send frequency, click and conversion rates, AOV, and opt-out rate to forecast SMS revenue and the cost of growing your list.

Score an SMS for length, segments, cost, spam-filter risk, and compliance with TCPA, 10DLC, CTIA, and GDPR, with multi-format export.

Recommend the right Google Smart Bidding strategy from your goal, volume, and value tracking, so you pick tCPA, tROAS, or Max Conversions on evidence.

Estimate the net annual revenue a welcome series adds from the first-purchase lift on new subscribers, usually the highest-ROI flow you can build.

Calculate the revenue a welcome flow earns per signup, so you can value the single automation that greets every new subscriber for you.

Measure the incremental revenue a reactivation campaign pulls from lapsed customers, so you only credit win-backs that would not have returned alone.

Map a concrete email and SMS sequence for any lifecycle stage — onboarding, win-back, post-purchase — with timing, triggers, and a prioritized rollout roadmap.

Get the right number of engagement-based segments for your list size and send cadence, plus a prioritized plan to build and maintain them without over-segmenting.

Enter a domain and we read its live DNS to audit SPF, DKIM, and DMARC — then hand back the exact records to fix your email authentication.

Build a prioritized email A/B testing roadmap — highest-impact tests first, split into short- and long-term, with owner and effort tagged on each.

Tell it your business model and key events, and get the GA4 reports, explorations, and dimensions to build for decisions that matter — no guesswork.

Design A/B, incrementality, and traction tests with the sample size, duration, and success criteria spelled out, then export a clean test plan.

Work backward from statistical significance to the sample size and ad spend your A/B test needs, with market sizing so the plan is feasible.

Estimate how many weeks a test needs to reach its sample size, so you commit to a realistic timeline instead of calling it early on noise.

Find the visitors per variant an A/B test needs to detect your target effect, the number that decides whether a result will mean anything.

Enter control and variant data to get the probability the variant wins, the expected lift, and the risk of being wrong — the Bayesian read.

Score your experimentation program across research, design, statistics, prioritization, velocity, and culture to find the constraint holding it back.

Compute both absolute and relative lift between two conversion rates, so you report the change honestly instead of inflating it with the wrong base.

Find the average number of touchpoints before a conversion, so you size how long the path really is rather than crediting only the last click.

Pinpoint where users leak between funnel steps and how badly, so you fix the stage that is bleeding the most before optimizing anything else.

Estimate the bytes a GA4 BigQuery query will scan and what it costs, then see the savings from selecting only the columns and rows you need.

Paste GA4 event names to flag the bugs that fracture your data — non-snake_case names, reserved prefixes, and over-long strings — before they cost you.

Check whether your GA4 property clears the data-volume thresholds for predictive metrics and audiences, so you stop chasing features you cannot yet use.

Measure lift over a holdout group, the only read that separates conversions your marketing caused from ones that were going to happen anyway.

Find the minimum detectable effect (MDE) your sample size supports, so you know up front how small a change a test can credibly catch.

Score a CRO test idea against the concrete, evidence-weighted PXL questions for potential, confidence, and ease, for a bias-resistant ranking.

Convert the ROAS your Amazon, Walmart, or Instacart dashboard reports into incremental ROAS, so you know what the spend truly added.

Run a chi-square test on your A/B user counts to flag sample ratio mismatch (SRM), the silent bug that invalidates a test before you trust it.

Run a two-proportion z-test on two conversion rates to see whether the difference is real, so you stop shipping winners that are just noise.

Tell it your goal, where your funnel leaks, your traffic, and your research, and it recommends the specific experiment most worth running next.

Split budget between brand and activation on the Binet and Field 60/40 logic, so you fund long-term demand instead of starving it for short-term sales.

Get a recommended number of audiences, campaigns, ad groups, and creatives per platform, sized by budget, industry, and funnel stage.

Model bad, good, and best-case forecasts against your goal and budget before you build a single campaign, so the target is grounded in math.

Estimate the marketable revenue in your database, the money left on the table by batch-and-blast, revenue at risk to decay, and the fastest lever.

Calculate click-through rate (CTR) from clicks and impressions, the relevance signal that drives Quality Score, CPC, and everything downstream.

Work out conversion rate (CVR) from conversions and visitors, the efficiency number that decides how hard every click and dollar has to work.

Turn a keyword list into a tiered account skeleton — naming, themed ad groups, and a budget split — so structure is deliberate before you launch.

Get a recommended bidding strategy, objective, structure, and operating cadence from your channel, industry, funnel stage, and budget, with a checklist.

Score concentration risk across your channels, so you see how exposed you are when one platform's costs spike or its algorithm shifts.

Turn Google Auction Insights into a ranked competitor threat list and a messaging white-space map, so you attack where rivals are weakest.

Build a step-by-step measurement plan plus offline-conversion automation via Zapier or a native CRM, so the data feeding bids is actually clean.

Divide daily by monthly active users to get stickiness — the share of your monthly base that shows up daily — the truest read on habit.

Subtract market share from share of voice to get excess SOV, the spend-versus-presence gap that predicts future market-share growth.

Describe your problem in plain words and get routed to the exact guides, calculators, glossary, and training that fix it, no jargon required.

Score a responsive search ad on relevance and see how a higher Quality Score cuts your CPC against a weaker rival bidding for the same click.

Rank ideas by ICE score — Impact times Confidence times Ease — so prioritization runs on a shared, repeatable rule instead of whoever argues loudest.

Work backward from a customer target and CAC to the marketing budget it takes, so the plan rests on math, not last year plus ten percent.

Score your marketing operation into a maturity composite, so you see which capability gap is capping growth before you spend on the next tactic.

Express marketing spend as a percentage of revenue, then benchmark it, so you know whether you are under-investing or overspending for your stage.

Track your north-star metric against target over time, so the whole team optimizes the one number that best predicts durable growth.

Generate a tailored daily, weekly, monthly, and quarterly Google Ads cadence with a realistic time budget, sized to your account and business model.

Rank initiatives by RICE — Reach times Impact times Confidence over Effort — so the roadmap reflects expected value, not just enthusiasm.

Divide revenue by headcount to get revenue per employee, the efficiency benchmark that flags whether you are scaling output or just scaling cost.

Work out how many marketers a revenue target requires, so headcount planning tracks the growth you are funding instead of guesswork.

Size your total, serviceable, and obtainable market (TAM, SAM, SOM), so growth targets are anchored to real demand rather than wishful spreadsheets.

Measure time to first value (TTFV) — how long until a new user hits activation — the lag that quietly decides retention and word of mouth.

Estimate the signal you lose to iOS App Tracking Transparency opt-outs, so you size the measurement gap before it skews every attribution call.

Project annual run rate (ARR) from current MRR, the forward-looking number that frames every fundraising and planning conversation in SaaS.

Divide bookings by deals to get average contract value (ACV), the deal-size benchmark that shapes how much you can spend to win each account.

Measure the share of marketing-qualified leads that progress to sales-qualified, the handoff conversion that exposes a marketing or sales gap.

Quantify the pipeline value marketing sourced, the attribution number that decides how much credit and budget the function actually earns.

Compare open pipeline to quota to get coverage ratio, then judge it against the 3-to-4x line that signals the quarter is realistically winnable.

Combine deal count, value, win rate, and sales cycle into pipeline velocity, the single number that shows how fast revenue is actually moving.

Measure qualified pipeline created per SDR per month, the productivity benchmark that tells you whether to coach, hire, or rethink the playbook.

Calculate the average days from deal creation to close, so you can forecast realistically and spot the stage where deals stall the longest.

Divide closed-won by total closed deals to get win rate, the conversion read that exposes whether the problem is lead quality or sales execution.

Share your goal, ad type, and budget, and get the Amazon Ads reports, columns, and breakdowns to track for profitable retail media — no guesswork.

Work out average purchases per customer, the repeat-rate input that turns a single order value into a real lifetime-value picture.

Turn affiliate revenue and commission into real, margin-adjusted profit using a partner-mix incrementality benchmark, so you pay for sales you caused.

Enter affiliate revenue, commission, network fee, margin, and an incrementality estimate to get the program's true ROI, not the inflated headline.

Turn your reported retail-media ROAS into true incremental profit using your margin and a research-based program-mix benchmark, so the number is honest.

Calculate take rate — marketplace fees as a percentage of GMV — so you see exactly how much of every dollar transacted the platform keeps.

Estimate the likelihood that AI answer engines will cite your page, so you target the content changes that actually move you into generated answers.

Paste a passage and score it against the seven levers that decide whether AI answer engines will cite you, with the specific fixes to make.

Paste questions and answers to get valid, properly escaped FAQPage JSON-LD, ready to ship and primed for rich results and AI extraction.

Expand a topic into the sub-questions AI engines actually fan out to, so your content covers the whole intent instead of one narrow query.

Enter your site name, summary, and key links to build a spec-compliant llms.txt that tells AI crawlers what matters and how to use it.

Enter a URL; we fetch the live page and score how ready it is to be cited by AI answer engines, with an owner-tagged action list.