We bridge the gap from "here's your marginal ROI curve" to "pause campaign X, scale campaign Y by 25%, test Z creative."
Weekly. Automatically. At the campaign level.
Because measurement without action is wasted effort.
We bridge the gap from "here's your marginal ROI curve" to "pause campaign X, scale campaign Y by 25%, test Z creative."
Weekly. Automatically. At the campaign level.
Because measurement without action is wasted effort.
The model sophistication doesn't matter if you can't answer:
- What do I do Monday morning?
- Which campaign do I pause?
- Where do I reallocate budget TODAY?
Insights without action = expensive decoration.
The model sophistication doesn't matter if you can't answer:
- What do I do Monday morning?
- Which campaign do I pause?
- Where do I reallocate budget TODAY?
Insights without action = expensive decoration.
Teams get lost between steps 4 and 5.
They see curves and calculations but can't translate to "move $50k from Google to TikTok by Friday."
That gap? That's where value dies.
Teams get lost between steps 4 and 5.
They see curves and calculations but can't translate to "move $50k from Google to TikTok by Friday."
That gap? That's where value dies.
The "what-if" machine:
- Same spend, better mix = free money
- Less spend, same results = efficiency wins
- More spend, projected returns = growth plays
These scenarios are where insights become decisions.
The "what-if" machine:
- Same spend, better mix = free money
- Less spend, same results = efficiency wins
- More spend, projected returns = growth plays
These scenarios are where insights become decisions.
"Diminishing returns curves"
Translation: Your NEXT dollar won't perform like your average dollar.
That 3.0x Meta ROI? Your next $100k might only return 1.5x.
This is where optimization actually happens.
"Diminishing returns curves"
Translation: Your NEXT dollar won't perform like your average dollar.
That 3.0x Meta ROI? Your next $100k might only return 1.5x.
This is where optimization actually happens.
"Total contribution by channel"
Translation: If you spent $1M on Meta and it drove $3M in sales, your average ROI is 3.0x.
Useful for historical performance, dangerous for future planning (because of #4...)
"Total contribution by channel"
Translation: If you spent $1M on Meta and it drove $3M in sales, your average ROI is 3.0x.
Useful for historical performance, dangerous for future planning (because of #4...)
"Look at our statistical fits"
Translation: We're proving the model actually works by showing predicted vs actual results.
If R² < 0.8, be skeptical. But this still isn't where the value is.
"Look at our statistical fits"
Translation: We're proving the model actually works by showing predicted vs actual results.
If R² < 0.8, be skeptical. But this still isn't where the value is.
"Here's what we collected"
Translation: We grabbed your spend data, sales data, and external factors (weather, seasonality, competition).
This just proves we have the ingredients. Not exciting, but necessary.
"Here's what we collected"
Translation: We grabbed your spend data, sales data, and external factors (weather, seasonality, competition).
This just proves we have the ingredients. Not exciting, but necessary.
Here's what you're actually getting (in plain English):
🧵👇
Here's what you're actually getting (in plain English):
🧵👇