See which channels are linked to your conversions,
from the data you already export

Each ad platform reports its own credit for a conversion, and those numbers often add up to more than you actually sold. Export spend by channel and your results for the same weeks, put them in one file, and compare channels on the same footing instead of on each platform’s own count.

To see how each attribution model splits credit across your own channels, try the free attribution comparison tool.

What your file needs

• One row per week or month, covering at least two years.
• Spend for each channel.
• Sales or conversions for the same period.
• With only a few months of history, or a channel whose spend never changes, the model cannot separate the channels.
• The free tool analyzes up to 10,000 rows; a larger file is randomly sampled to that size.

What you get back

• How much of your results the model ties to each channel, and how much to baseline and seasonality.
• Return per unit of spend for each channel, with ranges.
• Where each channel’s returns start to flatten out.
• How far the split can be believed, stated in the report.
• The method named and the R code.

A limit worth stating

Exported platform data can show association between spend and results. It cannot by itself prove that one channel caused a sale, and the report says so where it applies.

To measure what a channel caused, leave a random group out and compare. What incremental impact actually means explains the idea, and the free incrementality test runs it on your file.