Last week, I was browsing r/marketing when I stumbled across this question that made me stop scrolling:
"Marketers managing ads across platforms - what's your reporting workflow and how do you track ROI? Do you use any tools other than Excel and Google Sheets?"
The responses were... enlightening. And by enlightening, I mean they confirmed what I suspected: most of us are flying blind when it comes to actual ROI measurement.
The Spreadsheet Nightmare Is Real
One marketer laid it out perfectly:
"Excel and Google Sheets are fine for small scale or one channel reporting. But the moment you go multi-platform (Google, Meta, LinkedIn), things get messy fast."
Sound familiar? You start with one Google Ads campaign. Simple enough - throw the numbers in a spreadsheet, calculate your ROAS, call it a day. Then you add Facebook ads. Now you need another tab. Then LinkedIn. Another tab. Suddenly you're the person with 47 spreadsheet tabs trying to figure out which platform is actually making you money.
But here's the kicker - even if you manage to wrangle all that data into one place, you're still missing the bigger picture.
Platform Attribution Is Lying to You
Let's talk about the elephant in the room: platform attribution is broken. Google Ads will happily tell you it drove 100 conversions. Facebook will claim credit for 80 of those same conversions. LinkedIn says it influenced 60 of them.
Quick math check: 100 + 80 + 60 = 240 conversions from what was actually 50 real customers.
One Reddit user explained their solution:
"Once we started analyzing influence across the funnel like assisted conversions, multi-touch journeys, our budget allocation decisions got way sharper."
The problem is that platforms only see their slice of the customer journey. Facebook doesn't know that your customer saw a Google ad first, visited your site three times, read two blog posts, then finally converted after clicking a retargeting ad.
The Real Cost of Bad Attribution
I learned this lesson the hard way with a client who was convinced Facebook ads weren't working. Facebook's dashboard showed a 2.5x ROAS - not great, but not terrible. We were about to pause the campaigns.
Then we dug deeper. Turns out Facebook was driving 40% of the top-of-funnel traffic that was later converting through Google Ads searches. Kill the Facebook campaigns, and Google Ads conversions dropped by 35% two weeks later.
This is why another Redditor mentioned they "apply a scaling factor to our attributed revenue to make it match our channel experimental results." They're basically saying the attribution is so off that they have to guess at what the real numbers should be.
The "It's Complicated" Problem
Here's what one marketer shared about their tracking setup:
"A customer comes to the site via an ad click, our internal tracking resolves source and performs identity resolution, then the data dumped into bigquery. If the customer makes a purchase, our MTA allocates credit based on the last X number of days."
Reading that made my head spin, and I do this for a living. Most small businesses don't have a data engineering team to build custom attribution models in BigQuery.
But you know what? You don't need to.
A Simple Framework That Actually Works
After years of helping businesses untangle their attribution mess, here's what I've found works for most companies:
1. Start with your CRM, not your ad platforms
Your CRM knows the truth - it knows which leads became customers and how much they spent. Start there and work backward.
2. Use UTM parameters religiously
Every. Single. Link. I mean it. Your Google ads should have utm_source=google&utm_medium=cpc&utm_campaign=whatever. Your Facebook ads should have utm_source=facebook&utm_medium=social&utm_campaign=whatever.
Yes, it's tedious. Do it anyway.
3. Look at the whole funnel, not just the last click
Set up Google Analytics to show assisted conversions. You'll probably discover that your "worst performing" channels are actually driving your best customers - they just take longer to convert.
4. Use first-party data
Ask customers how they heard about you. I know, revolutionary concept. But a simple "How did you hear about us?" field in your checkout process will tell you things no attribution model can.
Automate Your ROI Tracking with AI
Instead of wrestling with multiple tools and complex attribution models, you can automate the entire ROI tracking process using AI-powered workflows.
How Toffu Solves the Attribution Nightmare
Rather than trying to build custom data warehouses or learn complex attribution platforms, Toffu's automated workflow capabilities can handle the heavy lifting of ROI tracking across platforms:
Automated Data Collection: Set up daily automated analysis that pulls performance data from Google Ads, Facebook, LinkedIn, and other platforms into organized Google Sheets reports.
Cross-Platform Correlation: AI identifies patterns and relationships between different marketing channels that manual analysis would miss.
Intelligent Reporting: Generate weekly ROI summaries that highlight which campaigns are actually driving revenue, not just platform-reported conversions.
Setting Up Automated ROI Tracking
Here's how to implement intelligent ROI tracking using Toffu's automation:
Start a conversation with Toffu and say:
"Set up automated ROI tracking across my Google Ads, Facebook, and LinkedIn campaigns. I want daily data collection in Google Sheets, weekly performance summaries, and email alerts when ROI patterns change significantly. Focus on identifying which channels are actually driving revenue, not just conversions."
Advanced Attribution Analysis
Unlike manual spreadsheet tracking, AI can identify complex patterns:
- Channel interaction effects: How Facebook ads influence Google Ads conversions
- Customer journey analysis: Which touchpoints actually matter for your business
- Seasonal attribution patterns: How attribution changes during different periods
- Predictive ROI modeling: Forecasting which campaigns will deliver the best returns
Implementation Strategy
Week 1: Set up automated data collection from all your advertising platforms using Toffu's scheduled tasks.
Week 2: Implement cross-platform correlation analysis to identify true ROI patterns beyond single-platform attribution.
Week 3+: Develop predictive ROI models that help you allocate budget before campaigns start underperforming.
The Bottom Line
Your marketing ROI numbers are probably wrong. Not because you're bad at math, but because you're trying to solve a complex attribution puzzle with incomplete data and platform bias.
The solution isn't more complex tracking or fancier tools (though those can help). It's getting comfortable with the fact that attribution will never be perfect, and building systems that give you directionally correct insights instead of precisely wrong numbers.
As one marketer put it perfectly: "We cross check platform reported view through data with our CRM and web analytics. When direct signals are missing, we use probabilistic modeling."
Translation: they make educated guesses based on multiple data sources instead of trusting any single platform's claims.
Stop trying to track every click and start focusing on the metrics that actually matter for your business. Your sanity (and your marketing budget) will thank you.
Ready to automate your ROI tracking? Learn more about Toffu's automated workflow capabilities, scheduled task automation, and Google Sheets integration that work together to solve your attribution challenges.