Long sales cycles, low conversion volume, and multi-stage purchase journeys make measurement and attribution harder, creating real obstacles to campaign optimization.
For B2Bs and brands selling high-ticket items, this is the reality.
A campaign launched today may take weeks or even months to show revenue, retention, or lifetime value – delaying your ability to use those measurements to refine bidding and targeting.
That’s where proxy metrics – also known as soft metrics, or micro-conversions – can come into play.
Let’s dig into proxy metrics.
What are proxy metrics?
Proxy metrics are early indicators of future outcomes.
They give you a way to measure momentum before final – or more downstream – results show up.
Some examples:
- Engagement rate on ads can foreshadow conversions.
- Add-to-cart events often predict sales.
- First-week retention can predict long-term customer value.
Leveraging proxy metrics can help teams:
- Course-correct campaigns earlier.
- Optimize budget allocation faster.
- Avoid waiting for lagging outcomes.
They help you move quickly and de-risk decisions when used effectively.
In some cases (e.g., when purchase cycles stretch beyond Google Ads’ 90-day latency window), you’re forced to find alternative ways to track performance.
Here, I look for the best predictors that occur within the first 90 days after a click and use those instead of the longer-term activity that won’t be recorded within Google’s limits.
Dig deeper: How to use GA4 predictive metrics for smarter PPC targeting
How do proxy metrics power algorithmic bidding?
The powerhouse digital ad platforms, Google and Meta, use machine learning to optimize campaign performance.
But algorithms need signals.
When businesses optimize only for end conversions that occur weeks later, the system struggles to learn, and “conversion”-focused goals end up harvesting cheap, low-quality users.
Proxy metrics bridge that gap.
Feeding the algorithm with earlier signals enables some important things to happen:
- Micro-conversions (such as email or free trial signups) can act as training signals for the bidding algorithm.
- Quality indicators (such as time on site or scroll depth) can refine targeting when conversion data is sparse.
- Predictive scoring models can translate raw behaviors into weighted signals that approximate revenue likelihood.
This approach helps algorithms learn who’s likely to convert and, with some proportion-based calculations, lets you bid according to the relative value of the proxy metrics you’re using.
How to use proxy metrics to build audiences and enrich insights
Beyond bidding, proxy metrics unlock smarter audience building and deeper insights.
Let’s start with audience building.
Segmenting users based on early behaviors (e.g., engaged video viewers, repeat site visitors, high click-through engagers) allows you to create lookalike audiences that align with future high-value customers.
Basically, instead of targeting “everyone who clicked,” proxy metrics can shift your focus to “everyone who looks like people who eventually bought.”
On the data front, proxy metrics help analysts run faster tests.
Instead of waiting months for LTV data, you can validate hypotheses using leading indicators.
For example, if an experiment shows a 20% lift in proxy metrics that historically correlate with revenue, you can make earlier investment decisions with confidence.
It’s the same principle when you’re running an incrementality test or media mix modeling (MMM).
In many cases, proxy metrics deliver stronger statistical significance or better model accuracy than long-term business metrics.
If your data is too thin to run incrementality tests or MMM with confidence, pick proxy metrics with enough volume and close proximity to your conversion event, and build from there.
Dig deeper: MTA vs. MMM: Which marketing attribution model is right for you?
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How to assess the reliability of proxy metrics
Proxy metrics can vary wildly in quality and reliability.
Some are high-fidelity predictors. Others are simply prerequisites that don’t always guarantee downstream success.
(Important note: Going too far up the funnel for your proxy metrics gives the algorithm license to prioritize lower-value activity.)
For example:
- Newsletter sign-ups often signal genuine interest and correlate strongly with future engagement or purchases, making them a dependable early indicator.
- In contrast, add-to-cart events are necessary before a purchase, but are notoriously leaky, as many shoppers abandon their carts without checking out.
- Similarly, a video view might suggest curiosity, but it’s a weaker proxy for revenue than a trial activation.
It’s critical to:
- Rigorously validate which proxies have a consistent relationship with long-term outcomes.
- Calculate a ratio of proxy events to desired events that can be used in assessing the value of proxy metrics.
- Continuously revisit these assumptions as markets and customer behavior evolve.
To choose the right proxies, consider these four factors:
- Correlation strength: Does the metric consistently correlate with the desired business outcome (e.g., revenue, retention, LTV)? Test this historically with data and strike a balance between metrics with sufficient volume to be useful and proximity to the ultimate purchase event.
- Timeliness: How quickly does the metric show up relative to the final outcome? Strong proxies deliver early signals that shorten feedback loops.
- Actionability: Can the team act on this metric? A good proxy should inform bidding strategies, audience creation, or campaign optimization.
- Stability: Does the proxy remain predictive across campaigns, segments, and time periods? Or does it fluctuate too much to be reliable?
Metrics that score well on all four dimensions (e.g., trial-to-paid conversions in SaaS, newsletter signups in ecommerce) can be safely used as guiding signals.
Metrics that are weak in correlation or stability should be treated with caution. They may be useful for contextual insight, but should not be relied upon as a bedrock for optimization.
Putting proxy metrics to work
Proxy metrics aren’t foolproof, but with strategic use and a few advanced calculations, they can be a powerful tool in hard-to-measure campaigns.
Their benefits – more precise bidding, sharper insights, and larger audience segmentations – make the work of identifying and applying the right metrics well worth it.