Insights on marketing measurement, media mix modeling, and growing your business.
Saturation curves show the non-linear relationship between marketing spend and results. Learn how they work, why every channel hits a ceiling, and how to use them to stop wasting budget.
Marketing attribution models help you understand which channels drive conversions. Learn how first-touch, last-touch, linear, time-decay, position-based, and data-driven models work, where they fall short, and what to use instead.
Diminishing returns cause each additional dollar of ad spend to produce less revenue than the last. Learn how saturation curves work, which channels saturate fastest, and how to spot the warning signs before your budget is wasted.
Geo-lift testing measures marketing incrementality by comparing results between geographic regions that see your ads and regions that don't. Learn how it works, how to design a test, and when to use it.
Diminishing returns in marketing mean each additional dollar of ad spend produces less revenue than the last. Learn how to identify saturation points, read response curves, and reallocate budget before you waste money.
Adstock measures how advertising impact carries over beyond the initial exposure. Learn how adstock works, why decay rates vary by channel, and how media mix modeling uses adstock to measure true marketing performance.
Marginal ROAS measures the return from your next dollar of ad spend, not the average. Learn how to calculate it, why it matters more than standard ROAS for budget decisions, and how media mix modeling makes it actionable.
Cross-channel attribution connects the dots between your marketing channels so you can see the full customer journey. Learn how it works, why single-channel measurement falls short, and which approaches give you the most accurate picture.
Marketing effectiveness measurement goes beyond vanity metrics. Learn which KPIs matter, how to combine MMM, incrementality testing, and attribution for a complete picture of marketing performance.
Not all marketing KPIs are created equal. Learn which 12 metrics matter most, how to measure them accurately, and why some popular KPIs actively mislead your budget decisions.
Data-driven marketing uses analytics, customer data, and statistical modeling to guide strategy and budget decisions. Learn how to build a data-driven marketing strategy, the key techniques that work, and the common mistakes to avoid.
Marketing ROI measures the return on your marketing investment. Learn how to calculate it, why traditional methods fall short, and how modern approaches like media mix modeling give you a clearer picture.
Incrementality testing measures whether your ads actually caused sales - or whether those customers would have bought anyway. Here's how it works, when to use it, and how it fits with MMM.
ROAS (return on ad spend) measures revenue per dollar of ad spend. Learn the formula, how to calculate your breakeven ROAS, how it differs from ROI, and why ROAS alone can mislead your marketing decisions.
Most marketing budgets are built on last year's numbers and gut feel. Here's how to use data to allocate spend where it actually drives results.
Customer acquisition cost (CAC) tells you how much you spend to win each new customer. Learn the formula, why blended CAC hides the truth, and how to measure CAC by channel.
A step-by-step guide to implementing MMM - from data prep to budget reallocation.
MTA and MMM both measure marketing performance, but they work very differently. Here's how each approach works, where they fall short, and which one fits your business.
Learn how media mix modeling (MMM) measures which marketing channels actually drive results - without relying on cookies or last-click attribution.