Best Practices for Structuring Multiple Primary Conversions in Google Ads?

Question from Reddit user:

Right now we have one primary conversion at the account level that all campaigns are optimized for (because we only had one product). Now we have a new product with a different conversion path that we want to track separately and will have separate campaigns for.

Would you shift conversion tracking to the campaign level matching respective conversions?

My biggest concern is creating a new learning period for Google if I make this change. I really want to avoid a dip in conversions for any amount of time.

TIA for your insights/suggestions.

Answer from Nabil:

The short answer is:

What are the best practices for structuring multiple primary conversions in Google Ads?

You should shift conversion tracking to the campaign level for your new product, and the best way to do this without disrupting your existing campaign’s performance is to use Google Ads’ feature called Campaign-Specific Conversion Settings.

You won’t create a new learning period for your old, successful campaigns because you will leave their conversion setting as is, focused on the original primary conversion.

For the new product’s campaigns, you will select only its unique conversion action as the primary one for bidding.

This granular approach is standard best practice for managing multiple products with distinct conversion goals, and it minimizes disruption.

A robust tracking solution using the Google Ads API and a server-side tagging environment is the ultimate way to future-proof this structure and ensure maximum data quality.

The long answer is:

Your concern about creating a new learning period and causing a dip in conversions for your established campaign is completely valid, as it’s the main risk when changing the conversion goal for an active Smart Bidding strategy.

However, by utilizing Campaign-Specific Conversion Settings, you can implement your new conversion structure without touching the learning history of your existing campaigns.

The process involves two key steps: first, ensuring that both the original conversion action and the new conversion action are set up in Google Ads, likely imported from GA4 as a purchase or generate_lead event, and are currently set to Secondary at the account level.

This allows Google Ads to collect data for them without actively bidding on them yet.

Second, you will go into the settings for your new product’s campaigns and, under the “Goals” section, change the setting from “Use account-level goal settings” to “Use campaign-specific goal settings.” Here, you will select only the new product’s conversion action and set it as Primary, while ensuring the original product’s conversion is either not selected or is set to Secondary for this campaign.

Simultaneously, you will ensure your existing, successful campaigns remain set to “Use account-level goal settings” or are explicitly configured to only have their original conversion set to Primary.

By isolating the conversion goals this way, Google’s Smart Bidding algorithms will continue to optimize your old campaigns based on their historical data and proven goal, while the new campaigns start fresh learning periods focused solely on the new product’s goal.

To future-proof and add a layer of reliability to this setup, using the Google Ads API in conjunction with a server-side tagging platform like Stape or Google Cloud Platform is highly recommended.

You can use Google Tag Manager to collect conversion data on your website.

Instead of sending this conversion data directly from the user’s browser, you pass it to your server container.

The server container then uses the Google Ads API to send the conversion data back to Google Ads, effectively utilizing the Enhanced Conversions feature.

This server-side method is resilient to browser limitations, ad blockers, and cookie restrictions, ensuring the highest possible match rate and data quality for both your original and your new, distinct conversion actions.

This guarantees that your bidding strategies receive the most accurate data, maximizing their learning efficiency and campaign performance.

About The Author