While ROAS (Return on Ad Spend) has long been the go-to metric, POAS (Profit on Ad Spend) is emerging as a more accurate, profit-focused alternative for advertisers who want to be sure that all products are truly making money for their business.

POAS formula

At its core, POAS tells you how much profit you’re earning for every dollar spent on advertising:

POAS = Profit / Ad Spend

POAS % = (Profit / Ad Spend) * 100

This contrasts with ROAS, which measures revenue per dollar spent:

ROAS = Revenue / Ad Spend

The key difference lies in what each metric values. ROAS can paint a rosy picture of performance by focusing on gross revenue, but POAS digs deeper, accounting for actual profit margins, cost of goods sold (COGS), and operational costs—giving you a more truthful view of your ad performance.

Is POAS better than ROAS?

For many performance marketers, especially those running PMax campaigns, the answer is a resounding yes—but it depends on your goals.

In PMax campaigns, where Google's AI handles much of the targeting and bidding, advertisers must feed the algorithm with quality conversion value data. If you're optimizing toward revenue (ROAS), the algorithm might favor high-ticket, low-margin products. But with POAS, you guide the system to prioritize high-margin, high-profit conversions, leading to sustainable business growth.

Benefits of POAS 

Implementing a POAS-based structure in your Performance Max campaigns unlocks several strategic advantages:

• Profit-focused results: POAS helps your campaigns focus on making profit, not just making sales.
• Smarter budget use: PMax puts more budget behind products and audiences that bring higher profit.
• Better business decisions: Real cost data shows the true value of your ads.
• Stronger product control: Avoid pushing low-margin products by focusing on those that improve profit.

Downsides of POAS

While POAS offers clarity and profit-focused insight, it's not without its challenges:

• Data complexity: POAS needs accurate cost data (including shipping and returns), which many advertisers don’t have in one place.
• Delayed insights: Profit data sometimes lags behind revenue data (due to returns, fulfillment delays, etc.), which can complicate real-time decision-making.

As you can see, POAS helps drive smarter, profit-focused business decisions. To get the most value from it, you’ll need accurate data—especially around costs, returns, and shipping. But that doesn’t mean POAS is useless without full data. On the contrary, even with limited inputs, it still offers a valuable view into how your business is really performing.

Setup in Dotidot

STEP 1: Change Revenue tracking for Profit tracking

Instead of sending revenue to Google Ads, you send profit as the value in your conversion tracking tag. This means Google Ads’ built-in ROAS metric will actually be POAS because the “value” is already net profit. You’ll need your site backend or ecommerce platform to pass the profit figure dynamically to the tracking tag.

While this is quite different from one case to another, streamlined workflow looks like this:

1. Collect cost data: Your ecommerce system must know the COGS for each product (this might require SKU-based profit data).
2. Modify the conversion tracking code: If using Google Tag Manager, pass a variable like profitValue instead of revenueValue.
   gtag('event', 'purchase', {transaction_id: '12345',value: {{profitValue}}, currency: 'EUR'});
3. Verify data in Google Ads — conversion values should now match profit, not sales revenue.
4. Switch bidding to Target ROAS (now acting as POAS): Since you’re feeding profit in as the value, Target ROAS bidding will optimize for profit.

STEP 2 - Import ad cost and profit from Google Ads

1. Go to Data Sources and select the feed for your campaign.
2. In Data Enrichment, choose Google Ads product stats.
3. Name the enrichment as you wish (e.g., “Google Ads 60 days”).
4. Map the correct key between your data source and Google Ads — usually Product_ID.
5. In the Data Selection section, choose Price (this field holds ad cost in this context) and Conversion value.
6. In Time Range, select a period with enough data — 60 days is common.

Optional: also import Conversions to use as a safety filter (e.g., ≥60 in window).

STEP 3 - Calculate POAS

When you pass profit as the conversion value, Google’s “ROAS” is already POAS. So next, you need to create a new variable that calculates R/POAS from the additional data. 

POAS as a percentage is the most popular format, so let’s use it too: 

(Profit-Revenue / cost)*100 = POAS %

With this in mind, create POAS % variable:

1. Navigate to your data source
2. Go to Variables section and click “+”
3. Choose Numeric variable
4. Name it appropriately so you can easily identify it later in your data source. We’ll use “POAS_%”
5. In the Input field, replicate the formula above using data from your source
   (See the image below for how it should look)

STEP 3 - segment your products

1. Navigate to Product Sets → click “+” to create a new set.
2. Name the set (e.g., “High POAS”).
3. Select the POAS_% variable and set up a correct conditions with your thresholds, e.g.:
   High POAS: ≥ 160%
   Medium POAS: 101–159%
   Low POAS: < 100%
4. Repeat for all POAS buckets.

STEP 4 - Build the campaigns

The final step is the simplest: build your campaigns based on profit margin groups. Set budgets and tROAS accordingly:

• High POAS → largest budget, most aggressive Target ROAS (POAS)
• Medium POAS → moderate budget
• Low POAS → smallest budget or pause

Finally, product selection is a critical part of the setup—ensure that you include the corresponding product sets for each campaign.

‍