How Context Turns Signal Engineering Into Real Growth

The Big Shift: From Targeting to Teaching

UA today is mostly automated. Meta’s Advantage+, Google’s UAC, Apple’s Pmax - they all optimize delivery by learning from the signals you send back.
The problem? Most teams are feeding them bad data.

If your “success” signal is a free trial start, Meta will find users who love starting free trials - not users who actually pay or stay.
Your campaigns perform exactly as well as the training data you provide.

That’s what Signal Engineering is about: intentionally designing the conversion signals you send so ad networks learn who your valuable users are, not just your cheap ones.

What Makes a “Good” Signal

According to recent talks by Thomas Petit and other growth experts, a good signal isn’t necessarily a purchase. It’s one that the algorithm can learn from - early, frequent, and predictive.

A strong conversion event should be:

Correlated with real revenue or retention
Frequent enough (10+ per day per campaign) for the algo to learn
Early enough (within 24 hours of install) to fit within attribution windows
Clean and consistent across networks

If you only send rare, late, or noisy events, the algorithm can’t find patterns - and your budget trains it to chase cheap users.

The Tradeoff: Volume vs. Quality

Optimizing too far down the funnel gives you accuracy but no learning volume.
Optimizing too high up gives you scale but no quality.

The art of signal engineering is finding the middle ground: events that are common enough to feed machine learning, but selective enough to represent long-term value.

That’s why many top apps test intermediate goals like “completed onboarding,” “finished tutorial,” or “engaged on day 3” instead of “free trial started.”

Predictive and Qualified Signals

Signals don’t need to be binary. You can qualify them early.

For instance:

A user who marks themselves as “business owner” during onboarding might have 3× higher ARPU.
A fitness app user who completes a quiz about “advanced training goals” could be worth 5× more than casual users.

Feeding those qualified events back to Meta or Google helps the algorithms target users who look like your best audience - before they even pay.

Where Context Comes In

Here’s where ContextSDK upgrades the entire concept.

Signal Engineering works well for what users do in-app.
But it ignores the biggest missing variable - what’s happening in their real-world context.

Imagine you could feed ad platforms a stream of moment-based conversion data - not just what a user clicked, but when they were actually receptive to your product.

That’s exactly what ContextSDK enables.

ContextDecision identifies whether a user is relaxed, commuting, or multitasking, and scores their receptivity in real time.
ContextPush uses the same intelligence to time push notifications for when users are most open.
Combined, these context-aware events become smarter training data for your ad algorithms.

Instead of teaching Meta that “any trial = good,” you teach it that “trials started in high-receptivity moments = real value.”

That’s not just cleaner data - it’s contextual signal engineering.

Why It Matters

Most ad algorithms already use probabilistic learning - they don’t need more data, they need better data.

When you feed them contextual conversion events, you’re helping them understand not just who converts, but when and why.
That subtle shift makes your campaigns:

More stable (less volatility across cohorts)
More scalable (more signals per day without quality loss)
More privacy-safe (no IDs or PII - all signals stay on-device)

It’s the bridge between user behavior and real-world intent.

Practical Example

Let’s say you’re running campaigns for a language learning app.

Traditionally, your optimization event might be “free trial started.”
With Signal Engineering, you change that to “completed first lesson.”
With ContextSDK, you go one step further:
“Completed first lesson during a high-receptivity moment (stationary, focused, phone unlocked).”

Now your campaign isn’t just finding users who start - it’s finding users who stick.

The New KPI: Context-Qualified Conversions

The next generation of performance marketing won’t be measured by CTRs or CPIs.
It will be measured by moment-qualified conversions - actions that happen at the right time, in the right state, by the right person.

That’s where ContextSDK shines:

You keep your existing funnel and ad stack.
You simply make every conversion smarter by adding a timing layer.
Your ad network learns to chase attention, not randomness.

Closing Thoughts

Ad networks don’t think - they learn.
And what they learn depends entirely on the signals you send them.

Signal Engineering taught us to design better events.
ContextSDK takes that idea into the real world - turning every install, push, and purchase into a context-aware signal that actually reflects user intent.

In short: