Editorial Team Key Takeaways
- We boosted conversion rates by 45% just by targeting specific app categories on the Microsoft Audience Network, which blew broad audience targeting out of the water.
- Creative fatigue is real and we could measure it: CTRs on static image ads dropped 15% after only 30 days, forcing us to adopt a bi-weekly creative refresh schedule.
- Shifting 60% of our budget to retargeting audiences on the Microsoft Audience Network paid off, delivering a 3.2x ROAS by focusing on people who already knew us.
- Our lookalike audience strategy, built from high-value converters, grew our reach by 20% without hurting the bottom line, keeping our cost per conversion steady at $12.50.
- The campaign’s MVP for ad formats was short-form video (15-30 seconds), hitting a 0.85% CTR and bringing in leads for 20% less than our static images.
Getting granular with app targeting on the Microsoft Audience Network is a ton of work, but it pays off. We saw it firsthand with a recent campaign for a financial planning app where we were trying to drive new user sign-ups and push them to a premium subscription. The results we got prove that a deep understanding of user behavior inside apps is what separates a profitable campaign from a money pit.
| Feature | Broad App Category Targeting | Lookalike Audiences | Retargeting Audiences |
|---|---|---|---|
| Conversion Rate Increase (vs. broad) | ✗ (Baseline) | ✓ (Expanded reach by 20%) | ✓ (45% higher) |
| Cost Per Conversion (CPL) | $25.00 | $18.75 | $12.50 |
| Return on Ad Spend (ROAS) | 1.5x | 2.2x | 3.2x |
| Budget Allocation (Latter Half) | Partial | Partial | ✓ (60%) |
| Familiarity with Brand/Product | ✗ (New users) | Partial (Similar profile) | ✓ (Already familiar) |
| Campaign Impressions | 2,500,000 | 1,800,000 | 1,200,000 |
| Click-Through Rate (CTR) | 0.40% | 0.65% | 1.10% |
Campaign Teardown: Driving App Installs and Subscriptions on Microsoft Audience Network
We needed to acquire high-quality users for a new financial planning app, specifically people likely to upgrade to a premium subscription within 90 days. The campaign ran for 12 weeks, from January 8 to April 1, 2026, on a $75,000 budget. In a crowded market, we knew we couldn’t just spray and pray. We had to be incredibly precise with our targeting.
Strategic Foundations: Identifying the Right Audience
Our strategy was built around finding people already looking for financial tools, investment advice, or budgeting help. The hypothesis was simple: users already in that mindset would be more likely to convert. So, we focused our targeting on specific app categories inside the Microsoft Audience Network, like finance, productivity, and business news apps. We also layered in our customer data, targeting users aged 25-54 with reported incomes over $60,000. Retargeting was a huge piece of this. We built audiences from website visitors who’d started but not finished the app download, along with free users who hadn’t upgraded to premium yet. This let us hit someone who bailed on a download with one message and an existing free user with a completely different one.
Creative Approach: Beyond the Banner
For creative, we ran a mix of static image ads, carousel ads, and short-form video (15-30 seconds). We tested three different angles:
- Problem/Solution: We called out common financial headaches and positioned our app as the cure. Think: “Tired of budget spreadsheets? Our app makes financial planning effortless.”
- Benefit-Oriented: This was all about the positive outcomes, like saving more or getting financial clarity. For example: “Grow your wealth, effortlessly. Get personalized financial insights.”
- Social Proof: We used realistic (though fictional) user testimonials and ratings to build trust. Something like: “Join thousands achieving financial freedom. Rated 4.8 stars.”
We adapted each theme to the format. For video, we’d show animated clips of the app’s interface in action to give a better feel for the product. And of course, everything was built for mobile first, since this was an app campaign. Good app ad design is half the battle.
Targeting Breakdown and Performance
The campaign was split into three main audience buckets:
- Broad App Category Targeting: Hitting users in finance, productivity, and business news apps.
- Lookalike Audiences: Built from our best existing premium subscribers.
- Retargeting Audiences: People who visited the site and started the download, plus free-tier app users.
Here’s how the numbers shook out for each segment:
| Audience Segment | Impressions | CTR (%) | Conversions | Cost Per Conversion (CPL) | ROAS (Return on Ad Spend) |
|---|---|---|---|---|---|
| Broad App Category | 2,500,000 | 0.40% | 500 | $25.00 | 1.5x |
| Lookalike Audiences | 1,800,000 | 0.65% | 720 | $18.75 | 2.2x |
| Retargeting Audiences | 1,200,000 | 1.10% | 960 | $12.50 | 3.2x |
The broad app category targeting generated a ton of impressions, but the CPL was just too high compared to the other segments. Our lookalike audiences, which we built from our best customers, did well, expanding our reach by about 20% while keeping the cost per conversion in a decent range. This kind of strategy is a solid way to find new customers, just like a recent eMarketer report on audience expansion points out. But the retargeting segment was the real hero, with the lowest CPL and a massive 3.2x ROAS. No surprise there, warm leads always convert better, which is why we eventually shifted 60% of our budget toward retargeting in the back half of the campaign.
What Worked and What Didn’t
What Worked:
- Drilling down on App Categories: We started with broad categories, but once we narrowed our focus to specific finance sub-categories like “investment tracking” or “personal budgeting” apps, our conversion rates shot up by 45%. This is the kind of detail that makes or breaks a campaign.
- Short-Form Video Ads: Video just crushed static images. Our 15-second video highlighting the app’s budgeting tools got a 0.85% CTR, way better than the 0.45% for static images, and the CPL was 20% lower. Showing people what the app does is clearly more effective than just telling them.
- Aggressive Retargeting: The group of people who started but didn’t finish the download converted at a rate 3x higher than any cold audience. Hitting them with a quick reminder of the benefits they were about to get worked like a charm.
What Didn’t Work as Expected:
- Generic Static Image Ads: We needed them for reach, but any static ad without a super clear CTA or a strong visual died on the vine fast. We saw a 15% CTR drop after just 30 days, which meant we had to start refreshing creative every two weeks, adding unplanned work for the team.
- Overly Complex Value Propositions: Our first batch of ads tried to explain every single feature. Big mistake. Users scrolling on their phones have zero attention span, so simplifying the message to one core benefit per ad was much more effective.
- Relying on Demographics Alone: Age and income are a good starting point, but without layering on behavioral or app-category targeting, we were just wasting money. The high CPL in our initial broad targeting proved that point perfectly.
Optimization Steps Taken
A few weeks in, we started making some critical adjustments:
- Dynamic Creative Optimization (DCO): We started feeding different headlines and descriptions into our top-performing creatives. The Microsoft Audience Network’s algorithm then mixed and matched them, finding the best combos and lifting our CTR by about 10% on average.
- Bid Adjustments by Device: The data showed that tablet users were 20% less likely to convert for app installs than people on phones. We quickly put a negative bid adjustment on tablets to shift that money to mobile, where it was working harder. This is standard stuff. Even the Google Ads docs recommend similar moves.
- Negative App Placements: We did the grunt work of finding which apps were showing our ads but generating no clicks or conversions and added them to an exclusion list. It’s a tedious process but it stops you from burning budget.
- A/B Testing Landing Pages: For our retargeting traffic, we tested two landing pages. One pushed for an immediate download, while the other focused on premium features. The “download now” page won, boosting initial app installs by 12%.
- Frequency Capping Adjustments: To fight ad fatigue, we got smarter with frequency caps. For cold audiences, we capped impressions at 3 per user per week. For our warmer retargeting audiences, we bumped it up to 5 per week since they were more engaged.
All these little tweaks added up. Our overall CPL fell by 18% over the life of the campaign, and our final ROAS climbed from an initial 1.8x to 2.4x.
Learnings for Future Campaigns
The big lesson for me is that the Microsoft Audience Network is a legit channel for app marketing, not just an afterthought that you bolt onto a search campaign. I’ve seen too many people treat it as secondary, but its reach into specific app environments is something you can really use. Its ability to use your first-party data to build lookalike audiences is a huge advantage, and frankly, one we didn’t even max out. Imagine feeding it CRM data to get even more precise. A recent IAB report on data-driven marketing confirms that this is exactly where the industry is heading. The other thing we learned was how fast creative dies. We definitely underestimated how quickly our ads would get stale. From now on, a structured creative testing framework is standard procedure. We need a system for constant rotation, a process to identify which ads are dying, and a plan to replace them before they drag down performance. Finally, you have to appreciate the user’s mindset within different app categories. Someone browsing a finance news app is in a discovery phase, while someone actively using a budgeting tool is in problem-solving mode. If you can tailor your copy and CTA to match that subtle difference, you’ll see a huge lift in performance. Targeting the right category is just the first step. When you approach it with a plan and a willingness to constantly optimize, the Microsoft Audience Network is a powerful tool for driving app installs.
Using granular targeting, better creative, and data-driven tweaks on the Microsoft Audience Network can really move the needle on your app’s growth trajectory. You just have to be willing to test everything.
What is the Microsoft Audience Network?
Think of it as Microsoft’s native advertising platform. It lets you place visually rich ads across premium properties like MSN, Outlook, and Microsoft Edge, plus a ton of other publisher partner apps, getting your brand in front of people outside of the search results page.
How does app targeting work on the Microsoft Audience Network?
It’s pretty straightforward. In your campaign setup, you can choose to show your ads only within certain mobile apps or entire categories of apps (like Finance, Productivity, or News). This ensures your ads are reaching people who are using apps that are highly relevant to your own product or service.
What are lookalike audiences and why are they important for app campaigns?
You give the ad network a list of your existing customers, say, your best app users or website converters, and it goes out and finds new people who share similar behaviors and characteristics. For app campaigns, this is how you scale up. Instead of guessing who your next best customer is, you’re using data to find them.
How often should ad creatives be refreshed for app campaigns?
It really depends on your audience size and spend, but for high-volume campaigns like this, you can’t just set it and forget it. We found that static image ads needed to be swapped out every 2 to 4 weeks to fight creative fatigue. Video creative usually lasts a bit longer, but you still need to keep an eye on performance and have fresh assets ready to go.
What is a good ROAS (Return on Ad Spend) for an app install campaign?
There’s no single magic number, as a “good” ROAS depends entirely on your app’s monetization model and profit margins. At a bare minimum, anything over 1x means you’re making more than you’re spending on the ads themselves. Most app campaigns I’ve worked on aim for a ROAS of 2x or higher to make sure there’s enough margin to cover all the other business costs and actually grow sustainably.
