First-Party Data Strategies for Mobile Marketing

The day ATT rolled out, I watched our lookalike audiences become 40% less effective overnight.

For years, we'd relied on third-party data to power our targeting. We bought segments from data brokers. We trusted platform algorithms to find our customers. We never really owned anything—we rented access to data that wasn't ours.

When Apple flipped the switch, all of that evaporated. The data we'd been renting disappeared. The targeting we'd depended on stopped working. And the competitors who'd invested in first-party data? They barely noticed.

That was the moment I understood: first-party data isn't just a nice-to-have. It's the only data that's truly yours. And in a privacy-first world, it's the only data that's going to survive.

The Difference I Didn't Understand Until It Was Too Late

First-party data is information you collect directly from your users through your own properties—your app, your website, your CRM. It's what they tell you, what they show you through their behavior, what they buy from you.

Third-party data is what you rent from others. It's segments someone else created, behaviors someone else tracked, inferences someone else made.

The difference? You own first-party data. It's accurate because it's based on actual interactions with you. It's compliant because you collected it with consent. And it doesn't disappear when a platform changes its privacy policy.

What I Wish I'd Started Collecting Years Ago

After the ATT crash, I audited what we actually knew about our users. It was embarrassingly little. We had install dates, some events, basic demographics if they'd created an account. That was it.

Here's what we started building:

Behavioral Data (The Gold Mine)

Every meaningful action in our app: what features they use, how often they return, what content they engage with, where they drop off. This behavioral data is incredibly predictive—and it's entirely yours.

Declared Data (The Gift)

Information users voluntarily provide: preferences, goals, interests, profile details. When users tell you about themselves, that data is priceless. Treat it accordingly.

Transactional Data (The Foundation)

Purchase history, subscription status, revenue per user, payment methods. This is the data that makes LTV modeling possible and lookalike audiences effective.

CRM Data (The Relationship)

Email engagement, support interactions, NPS scores. This data tells you about the relationship, not just the transactions.

The Infrastructure Mistake That Cost Us Six Months

We started collecting data everywhere. App events, website visits, email clicks, support tickets. Within three months, we had data scattered across twelve different systems with no way to connect them.

User 47291 in our app. visitor_abc123 on our website. john@email.com in our CRM. All the same person—but we had no idea.

So we built what we should have built first: a unified data foundation.

What We Built

• Customer Data Platform: Single source of truth for user profiles. Everything connects here.
• Identity resolution: Connecting anonymous users to known profiles across devices and channels. The same person, unified.
• Data warehouse: Central storage for analysis. All our first-party data in one queryable place.
• Activation pipelines: Pushing audiences to ad platforms, email systems, product personalization. Data that doesn't activate is just overhead.

Six months of work we could have avoided if we'd thought about infrastructure first.

How We Actually Use First-Party Data Now

Lookalikes That Actually Work

Our best-performing lookalike audiences now come from our first-party data, not platform-generated interests. We build seed audiences from our highest-LTV users, create tiered lookalikes (1%, 5%, 10%), and refresh the seeds monthly with recent converter data.

These audiences outperform third-party segments by 3x on average. Because they're based on people who actually look like our best customers, not probabilistic guesses.

Suppression (The Money We Stopped Wasting)

Before first-party data activation, we were showing ads to people who'd already installed. Paying to acquire customers we already had. Embarrassing waste that we couldn't see.

Now we suppress existing installers from acquisition campaigns. Suppress recent purchasers from retargeting. Suppress unsubscribed emails from win-back. Every dollar goes to new opportunity.

Personalization (The Experience Upgrade)

First-party data enables personalization at scale. Dynamic creative based on browsing history. Personalized offers based on purchase patterns. Custom landing pages for different segments. Users feel like we know them—because we do.

"The companies winning in the privacy-first era are the ones who built real relationships with customers, not the ones who rented access to everyone else's data. First-party data is the proof of a relationship."

The Consent Problem We Had to Solve

Here's the uncomfortable truth: collecting first-party data without consent is just third-party data with extra steps. You might own it, but you can't use it.

So we rebuilt our consent experience.

What Actually Works

• Clear asks: "We'll use this to personalize your experience." Not legal jargon—plain language.
• Easy opt-outs: If someone wants to stop sharing, make it simple. Fighting for data damages the relationship.
• Transparency: Show users what data we have and how we use it. Trust is built through visibility.
• Honoring preferences: If they opt out of marketing, they're out everywhere. Not just one channel.

The Value Exchange

Users share data when they get something in return. Personalized recommendations they actually want. Exclusive offers that matter to them. A better experience worth the exchange. We stopped asking for data and started earning it.

The Metrics That Told Us It Was Working

• Match rates: What percentage of our users can we actually match to ad platforms? We went from 35% to 72%.
• Audience sizes: How large are our usable segments? Big enough to drive meaningful scale.
• Performance lift: First-party audiences now outperform third-party by 180%. Not comparable.
• Data completeness: 64% of profiles now have key attributes filled. Up from 12%.

The Competitive Advantage Nobody Can Take Away

Here's what I understand now that I didn't before: first-party data is a competitive moat that deepens over time.

Every user interaction adds to your dataset. Every purchase improves your LTV models. Every engagement refines your understanding. Your competitors can't copy your first-party data because it's unique to your relationship with your users.

Third-party data is a commodity anyone can buy. First-party data is an asset only you can build.

When the next privacy change comes—and it will—the companies with strong first-party data will barely notice. They own their relationships. Everyone else will scramble again, looking for the next shortcut.

There are no shortcuts. There's only the work of building real relationships and collecting the data that proves they exist.