Question from Reddit:
I’m trying to set up a Google Ads campaign that allows me to optimize the campaign not just for “install” events for our software product; I am instead trying to play the long game with this campaign and optimize for length of subscription (ie, LTV of the users.)
Based upon your experience, what do you think is the most effective way to do this?
Here is the approach that I THINK will probably work for this:
- Set up our software product so that it’s integrated with Google Analytics. This should allow us to track various events like, number of page visits, session time, and basically everything else that Google Analytics allows you to track.
- Set up a specific goal inside of Google Analytics that basically measures: length of subscription. There’s probably a number of ways you could do this. Since ours is a software product where to use it, you need to be a subscriber, it’s likely just a matter of measuring ANY event that indicates active usage — and somehow mapping that onto time-duration. Off the top of my head, I actually don’t know what specific measurement I’d set up in Google Analytics for this — so this is the part I need the most help with. Getting this right is also vital for ensuring that I’m actually optimizing for the right thing, over the long run.
- Once the appropriate goals are set up in Google Analytics, I should be able to link my Google Analytics account to my Google Ads account, import the goals, and then set the campaign up to optimize for those goals. Here it’s tricky as well, because this kind of depends upon how the Google Analytics goal is set up. Will I create different goals for the different subscription lengths? “6 months subscribed”, “10 months subscribed”, etc? Is there some way I can rank-order these in order of importance — to say, the “12 months subscribed goal” is more important than the “11 months subscribed” goal, and so forth down the list? The simplest framework would be, similar to how you can set up an ecommerce campaign to optimize for largest purchase size — could I just set up one singular Google Analytics goal that just measures “length of subscription”, and I can just import that “number of months subscribed” metric into Google Ads, and optimize the campaign so we try to maximize THAT specific metric? The fallback option might be: Go way less granular than this, just set up one single “person has been subscribed for 6 months” goal, and optimize for that. Ideally though, I’d like to be able to stratify this and optimize the campaign for the absolute maximum LTV of the customers.
Any insights as to the optimal way to go about setting such tracking and optimization via Google Analytics and Google Ads would be HIGHLY appreciated. Thank you!
Answer from Nabil:
The short answer is:
The most effective and robust way to optimize your Google Ads campaign for maximum length-of-subscription (LTV) is to bypass the complexity of trying to model this within Google Analytics and instead implement Value-Based Bidding by sending server-side, real-time subscription data back to Google Ads.
You should continue to track the initial purchase event in GA4, but the key is to use a server-side solution, combined with the Google Ads API and the Google Analytics Data API, to calculate the expected Lifetime Value (LTV) of a user based on subscription data and send that estimated future value as a Conversion Value with the initial purchase event.
For existing subscribers, you should update this value with more concrete subscription revenue over time using Enhanced Conversions for Leads or a similar method, allowing the Google Ads bidding algorithm to optimize for the highest value users from day one.
The long answer is:
Your idea of using GA4 to track various lengths of subscription, like “6 months subscribed” or “10 months subscribed,” is conceptually sound for measuring LTV, but it creates two significant problems for Google Ads optimization.
First, Google Ads’ machine learning models need fast feedback to optimize effectively, but waiting 6 to 12 months for a conversion event to fire is too long for the algorithm to learn.
Second, you are introducing complexity by creating a tiered system of many different goals, which Google Ads will struggle to rank-order and bid on accurately.
The true solution is to leverage the power of the Google Ads API and your existing customer data to perform Value-Based Bidding, specifically by sending a dynamic Conversion Value at the time of the initial purchase event (when the user subscribes).
This process involves integrating your internal SaaS subscription management system, which holds the current and past usage data, with your marketing stack using a server-side solution like Stape or Google Cloud Platform.
Here’s the detailed approach: When a user completes the initial subscription (the purchase event), instead of sending a value of “1” or the first month’s cost, your server-side solution uses the Google Analytics Data API to retrieve any initial user or session data, and more importantly, it accesses your internal CRM/Subscription data to perform a real-time LTV calculation.
This calculation could be based on several factors, such as the user’s plan tier, geography, or any predictive LTV model you have.
The result of this calculation – the Estimated Future LTV – is then sent back to Google Ads as the Conversion Value for that initial purchase event.
By using the Google Ads API to send this dynamic, high-quality LTV data, you can set your campaign to use the Maximize Conversion Value bidding strategy.
The algorithm immediately sees that one user’s subscription is worth, for instance, $300 (high LTV) while another is worth $50 (low LTV), and it will automatically prioritize bidding for users who exhibit the high-LTV characteristics.
Furthermore, you can use the HubSpot API or a similar integration point from your CRM to periodically update the Conversion Value for these users as they continue to subscribe or upgrade.
By using the Google Ads API’s Enhanced Conversions for Leads (or a similar feature for sales data), you can send an updated, more accurate revenue value back to Google Ads every month, providing continuous, actual LTV signals, allowing the bidding engine to constantly re-optimize for the highest value customers.
This API-driven, server-side method is the only way to effectively play the “long game” with an LTV-based strategy.
About The Author
