Evaluating The ROI Of Multi-Channel Ecommerce Efforts

Most people don't know how to act on incrementality results. You've just completed some incrementality experiments, a media mix model, or some other kind of more sophisticated measurement exercise. Now what? Ideally your measurement tells you 3 key things: 1. The total ROI of your full marketing program 2. The ROI by channel or medium in isolation 3. The diminishing returns curve on spend + ROI 1. Total Program ROI Let's say your business needs to maintain a 4x ROI to stay profitable. But your marketing is only at a 2x incremental ROI. What do you do? a) You can stop marketing immediately b) You can try to optimize the tactics c) You can try to optimize the overall mix Before deciding, move on to question 2. 2. Channel ROI So your marketing overall is only at a 2x ROI, which isn't profitable. You have even spend between Google ads, Meta ads, and TikTok ads. Your measurement reveals that Google is at a 1x ROI, Meta is at a 2x ROI, and TikTok at a 3x ROI. If you shifted your entire budget into TikTok, you'd have a better program (3x ROI) but it still wouldn't yield the results you need as a business (4x ROI). Like above, you can completely cut or optimize. Optimization is certainly in order, but, how long can you afford to wait? A hybrid approach is often best, in which you reduce spend on the worst performers while investing modestly into testing. 3. Diminishing Returns Meta's 2x ROI in this example isn't stable at a 2x. Some dollars it is at 1x, some it is at 3x, some even at 0 and others at 10x. Finding that curve (which usually really looks more like a mountain and less like a plateau) is important. In your analysis, you find that Meta hits a 4x ROI (or better) with spend up to $2k per day. Right now you're spending at $5k per day. Again, you can try to optimize, scale, experiment into new things, but in the immediate you can cut back from $5k to $2k per day to gain solvency. Repeat for each of these channels, and you come out with something like this: Old Mix (2x ROI) • Google: $5k spend / day • Meta: $5k spend / day • TikTok: $5k spend / day Total: $15k spend at $30k of inc rev New Mix (4x ROI) • Google: $1k spend / day • Meta: $2k spend / day • TikTok: $3k spend / day Total: $6k spend at $24k of inc rev So in this case, our example put it into practice by: 1. Reduced overall spend to hit 4x ROI 2. Optimized mix based on ROI curves In the future, they: 3. Commit to an ongoing testing strategy 4. Remeasure incrementality every 60 days 5. Repeat media mix optimizations So, to recap: Figure out what you need to get out of marketing. Measure total marketing ROI (geo tests). Measure channel level ROI (geo tests). Measure the point of diminishing returns (modeling or experiments). Optimize the mix based on biggest ROI for the highest spend by channel, and waterfall down. #mmm #incrementality #measurement #marketing

STOP evaluating channels in isolation. This is the biggest mistake I see brands making today - judging each marketing channel by its own metrics without understanding how they interact. That’s why we've developed a Total Business Framework that completely transforms how we measure marketing effectiveness. Here's how it works →  When a customer sees your TikTok ad, searches your brand on Google, clicks a shopping ad, but doesn't purchase... then later clicks an email and buys - who gets credit? In most attribution systems, only the email. But that's not the full story. Our framework tracks how Meta, Google, TikTok, and your organic channels interact throughout the entire customer journey. It de-duplicates conversions and creates a holistic view of your marketing ecosystem by: Setting business-level targets first Instead of starting with "What ROAS do we need on Facebook?" we ask "What total revenue do we need to generate this month?" Then, we work backward to determine each channel's contribution. Measuring cross-channel impact We've observed consistent patterns: when you scale paid social, you typically see corresponding increases in email performance, direct traffic growth, and branded search volume. These aren't coincidences - they're predictable interactions. De-duplicating conversion path Using first and last-touch attribution models creates massive blind spots. Our framework uses multi-touch attribution that weights each touchpoint appropriately based on its position in the funnel. This approach has helped brands understand the true ROI of their marketing investments. Some discover that platforms performing "below target" in isolation are actually driving significant revenue through other channels. Others identify underperforming channels that look good on paper but aren't contributing to overall business growth. The framework helps us set monthly goals for EVERY channel, not just the ones we manage. This ensures the entire business grows synergistically - paid drives awareness, email captures leads, SMS converts sales, and retention strategies maximize LTV. In today's fragmented customer journey, looking at channels in isolation is like trying to understand a movie by watching one scene. You need the complete picture to make smart decisions.

Most budget debates sound like this: Let’s put $100K into Channel X because last quarter ROI looked solid. Translation: You’re gambling on a single point estimate. I introduce confidence bands, an idea borrowed from finance, to make marketing spend a calculated risk, not roulette. How it works: 1️⃣ Model Return Distribution: ↳ Take the last 12 months of channel ROI. ↳ Build a simple 80 % confidence interval (CI). ↳ GA4 + BigQuery make this a two‑line SQL script. 2️⃣ Assign Risk Tiers: ↳ Channels with narrow CIs = predictable (low risk). ↳ Wide CIs = volatile (high risk). ↳ Create three tiers: Core. Growth. Experimental. 3️⃣ Allocate by Risk Appetite: ↳ Core gets stable funding. ↳ Growth receives incremental budget as long as ROI stays within band. ↳ Experimental gets capped spend, think venture bets with predefined exit rules. Result: Budgets adjust automatically to performance volatility, not politics. One e‑commerce client reallocated 15 % of ad spend from volatile display ads to a stable influencer program and saw a 26 % lift in blended ROAS, no additional dollars required. Executives love it because it turns marketing magic into disciplined portfolio management. Which risk tier currently eats most of your budget? A) Core (predictable) B) Growth (moderate risk) C) Experimental (high risk)

The 25% marketing waste problem nobody's talking about. Here's a troubling pattern I've seen across hundreds of e-commerce brands: roughly a quarter of marketing budgets are being wasted - not because of poor execution, but because of flawed measurement. Our analysis shows brands using advanced measurement frameworks grow 20% faster than those using traditional methods - with minimal increases in overall spend. Yet 80% of brands still use last-click attribution, and most lack formal media planning beyond ""'spend more when ROAS looks good, pull back when it doesn't."" - leaving massive growth opportunities on the table. ‼️ The brands driving exceptional growth follow a systematic approach: ✨ Comprehensively collect and unify data across ALL channels & touchpoints ✨ Build models that identify both waste AND opportunity ✨ Create strategic testing roadmaps (not random experiments) ✨ Validate every assumption with rigorous incrementality testing When we applied this framework with a fashion retailer, we discovered 30% of their Google spend was duplicating conversions that would happen anyway. Reallocating to truly incremental channels drove 28% revenue growth on a flat budget. ✨ Even more fascinating are the counterintuitive findings: ✔️ Brand search is highly incremental - but only up to specific spend thresholds ✔️ Properly structured paid media campaigns drives significant repeat purchases ✔️ Ad structure can literally double incremental ROAS ✔️ "Performance" campaigns lift in-store and marketplace sales The uncomfortable truth: traditional attribution, general surveys, and models without expert calibration simply aren't enough anymore. Ask yourself: Do you truly know which marketing activities are driving incremental results? Because that knowledge is what separates thriving brands from struggling ones. #MarketingMeasurement #EcommerceGrowth #MarketingROI #IncrementalityTesting