Sigma for Marketing Analytics

First, you’ll need a list of your ads and the platforms on which they ran. Each row should represent an ad/platform combination. If an ad ran on multiple platforms, the ad will populate multiple rows (one for each associated platform).

Next, you’ll need a column displaying how much money was spent for each ad/platform pair. In the example above, this is represented as the [Money Spent (USD)] column. Your column names don’t have to match this example.

Finally, you’ll need a conversion metric. In this example, we’ll look at sales leads. However, you may choose from a variety of other data points (e.g. products sold, account signups, initial conversion steps, website click-throughs, revenue from deals closed, or inboard sales contacts).

Data is easier to digest when it’s grouped into distinct categories. If multiple rows of data share a common value in a given column, you can group these rows based on that value. In this example, rows are grouped based on their value in the [Platform] column.

Entering a single formula automatically calculates data across every row in a table.  In this example, [Money Spent] / [Sales Leads] calculates the cost per lead of each individual ad on a platform.

Bar charts are great for displaying campaign spend attribution.
Add your ads and their calculated costs per lead to a bar chart to see a side-by-side comparison of your data.

Just like the rows in your table, each bar in your visualization represents an ad/platform combination. Color-code your visualization based on each ad’s associated platform to see which bars are associated with each platform.

Now all you have to do is sort your data! Sort your ads by their cost per lead, and your visualization will represent their ROI accordingly.