Quick calculators and advanced simulators for marketing & advertising to make data-driven business decisions.
Conversion Funnel Optimization
ActiveSimulate your funnel step by step. Find where leads drop off.
Digital Ad Campaign ROI
ActiveSimulate ad spend returns. Compare channels and strategies.
CAC Payback and Magic Number Calculator
ActiveMeasure your customer acquisition efficiency: CAC, payback in months, and SaaS Magic Number. Decide when to scale paid acquisition with confidence.
Sector context
An SMB marketing lead faces the chronic dilemma of defending budget without clean attribution: how much growth came from paid ads, how much from SEO, how much from the product itself? Every platform (Google, Meta, TikTok, LinkedIn) reports its metrics favorably, and the sum always shows more conversions than actually happened. At the same time, finance pushes back: CAC went up and payback is getting longer. The marketing simulators help isolate what is under your control: CAC by channel, cohort payback, funnel efficiency, and normalized campaign ROI.
Key metrics
Indicators an SMB operator in the sector should know before modeling decisions.
CAC (Customer Acquisition Cost)
Total marketing + sales spend / new customers acquired. For SaaS it's usually 3–6 months of LTV; for e-commerce, a single transaction must absorb CAC plus margin.
LTV (Lifetime Value)
Average gross margin a customer contributes across their full relationship. The LTV/CAC ratio should be at least 3.0 for SaaS and 1.5–2.0 for e-commerce.
ROAS (Return on Ad Spend)
Attributed revenue / ad spend. ROAS of 3.0 means each dollar spent generates three of gross revenue; not the same as margin.
CAC payback period
Months a customer takes to repay their own CAC. The longer it is, the more working capital you need to grow.
Conversion rate by funnel stage
% moving from impression to click, click to lead, lead to opportunity, opportunity to customer. Each stage with its own benchmark.
How to pick the right simulator
If your question is how much you can spend acquiring customers without breaking unit economics, the CAC payback simulator tells you exactly how many months you need to recover spend by channel. If the full funnel worries you (impression → click → lead → customer), the funnel conversion simulator models each stage and isolates where efficiency is leaking. To defend ROAS in a board meeting or to a B2B client, the ads-campaign ROI simulator compares spend to attributed revenue with sensitivity to the attribution model used (last-click, multi-touch, time-decay).
Practical example
Hypothetical case in US dollars. Plug your real numbers into the simulator to validate your own scenario.
A B2B SMB spends $25,000 USD/month on Google Ads and Meta Ads. The current funnel delivers 1,200 clicks/month (average CPC $20.80), 240 leads (click→lead 20%), 60 opportunities (lead→opportunity 25%), 18 new customers (opportunity→customer 30%). CAC: $25,000 / 18 = $1,389 USD. Each customer pays $300 USD monthly with 70% gross margin, i.e. $210 USD monthly margin. CAC payback: 6.6 months. The simulator lets you flex stage conversion rates: lifting click→lead from 20% to 25% (realistic with a better landing page) would drop CAC to $1,111 USD and payback to 5.3 months.
Common modeling mistakes
Traps we see when reviewing sector planning. Avoid them before closing your own model.
Adding up attribution from each platform
If Google attributes 100 conversions and Meta attributes 80, they're not 180 — both attribute the same customer. Use unified attribution (GA4, Northbeam, or an MMM model).
Confusing ROAS with margin
A ROAS of 4.0 in a category with 25% gross margin means you're almost break-even. ROAS is only useful read against margin, not revenue.
Measuring LTV at 30 days in e-commerce
Repeat purchase is a curve, not a rule. Compute LTV at 12 months with your own cohort data; don't assume the sector average.
Ignoring organic baseline
If organic marketing already brings in 30% of customers, attributing all of them to ads artificially inflates ROAS. Subtract the baseline before declaring campaign success.
Scope and limitations
Multi-touch attribution is a heuristic, not causation. The simulators assume that incremental changes in conversion rates are isolable, which doesn't always hold when several changes are tested at once. For rigorous experiments, use A/B tests with sufficient sample size and duration; the simulator models the after of the experiment, not the experiment itself.
Start here
The simulators with the most adoption in the sector. Each tackles a different business question.