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Kickstart your incrementality testing with real-world use cases for mobile apps
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Alix Carman, Content Writer, Adjust, Jul 03, 2024.
AI’s presence in mobile app marketing is continuing to grow exponentially. Now, we’re well past the early adoption phase and entering the stage where it’s mandatory to adopt AI technologies in order to stay competitive. Time is ticking, and marketing teams are looking for the best opportunities to incorporate AI into their strategies for increased productivity and better results.
But with so many technologies and techniques, where to begin? Enter: InSight, Adjust’s next-gen incrementality solution powered by AI. Adjust clients have already performed hundreds of incrementality tests with InSight. Because it’s powered by AI, the capabilities of tests with InSight surpass what traditional methods can offer. Below is an inside look at just a few examples of tests—conducted across various app verticals—that have been run to help mobile marketers maximize their budgets.
Seasonality test examples
1. Testing marketing seasonality with incrementality
Seasonality–the fluctuations in consumer behavior due to time-specific events and trends–can influence user behavior and engagement with mobile apps. Testing the impact of marketing seasonality helps identify the best times to boost marketing efforts and optimize your budget.
| Vertical | Question | KPI | Variable | Constants |
|---|---|---|---|---|
| Shopping | Does increasing our campaign budget during Black Friday work? | Installs | Dates of campaign | Platform: iOS Country: United States |
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Test result: Significant organic cannibalization (-11.28%)
The test indicated that many installs would have occurred without the marketing efforts. This suggests that during Black Friday, the shopping app benefits from high organic traffic. To optimize future campaigns, the company should validate other channels during similar periods and leverage the organic traffic, possibly focusing on different time periods for paid efforts.
Some other examples of seasonality tests across verticals might look like:
| Vertical | Question | KPI |
|---|---|---|
| Finance | How does increasing marketing efforts during tax season affect the use of tax-related features? | Event: Tax calculator use |
| Dating | Is it worthwhile to increase marketing spend around New Year’s Eve? | Installs |
| Food delivery | Does increased food delivery promotion during the NBA finals increase in-app purchases? | Event: Complete order |
Channel test examples
2. Testing growth channels with incrementality
| Vertical | Question | KPI | Variable | Constants |
|---|---|---|---|---|
| Lifestyle | Would advertising on TikTok impact the number of event registrations? | Event: Event registration | Advertising channel | Platform: Android Country: Brazil |
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The analysis revealed a significant incremental lift in registration events. This confirms the effectiveness of the new advertising channel for Android users in Brazil. Moving forward, the company should check the return on ad spend (ROAS) for this campaign, run similar tests in other countries, and consider expanding the use of this channel for other campaigns.
Some other examples of channel tests across verticals might look like:
| Vertical | Question | KPI |
|---|---|---|
| News | Would search campaigns increase app discovery given we already have a large following on social media? | Installs |
| Travel | If we try a new campaign on Google Search sharing a discount code would that bring us more first-time bookings? | Event: First booking |
| Video streaming | Can this new, smaller, ad partner who offered us a lower CPI as an incentive be a source for new installs? | Installs |
Operating system test example
3. Testing platforms with incrementality
Users on different platforms, in this case operating systems, can respond differently to ad creatives and copy. By testing incrementality across iOS and Android, you can discover how each OS's user base reacts to your marketing efforts.
| Vertical | Question | KPI | Variable | Constants |
|---|---|---|---|---|
| Gaming | Does advertising on one operating system over another increase level-ups in-app? | Event: Level-up | Operating system (iOS vs. Android) | Platform: Android/iOS Country: China |
Test result: Insignificant lift (+6.82%) on iOS, insignificant organic cannibalization (-4.41%) on Android.
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The test indicated that the channel performed well for iOS conversions but slightly cannibalized organic installs on Android. To optimize, the company should run the test for other target variables like installs, test different time frames, and reallocate the Android budget to more effective channels.
Ad fatigue test example
4. Testing ad fatigue with incrementality
Ad fatigue occurs when your audience becomes tired of seeing the same creatives, leading to decreased engagement and effectiveness. For app marketers, it's crucial to identify and address ad fatigue to maintain campaign performance and user interest.
| Vertical | Question | KPI | Constants |
|---|---|---|---|
| Finance | Has this campaign reached ad fatigue? | Installs / Event: Loan approvals | Platform: iOS Country: Germany |
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Test result: Insignificant incremental lift for installs and insignificant loss for loan approvals.
The experiment showed that the campaign's impact on both events and installs across a number of target variables was not significant, suggesting ad fatigue. The company should consider changing the creative, messaging, or ad format to revitalize the campaign and regain effectiveness.
Regional test example
5. Testing new territories with incrementality
When looking at expanding an app internationally, testing new territories allows for the identification of markets with the highest potential for growth and profitability. By understanding regional differences in user behavior and acquisition costs, marketers can optimize their strategies to maximize returns and expand their user base effectively.
| Vertical | Question | KPI | Variable | Constants |
|---|---|---|---|---|
| Food delivery | Which new territory provides the most valuable installs? | Installs | Country | Platform: iOS |
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The incrementality test results revealed that while Territory A is generating slightly more installs with a strong lifetime value (LTV) at a lower cost, it is heavily cannibalizing users, making the extra installs less valuable. On the other hand, Territory B, despite being more costly, also has users with a strong LTV without the significant cannibalization seen in Territory A. Therefore, the value of additional installs in Territory A does not outweigh the negative impact of cannibalization, indicating that Territory B may be a more worthwhile investment despite the higher cost.
More ideas
18 bonus incrementality testing ideas
The above are just a few ways that Adjust clients have started leveraging the unparalleled power of incrementality testing with our next-gen incrementality solution, InSight. But the options for testing are limitless. Simply pick an in-app event or install volume and test away! Need some more inspo? Here are 18 additional ideas to get your creative juices flowing.
- How do different ad creatives impact installs?
- Which country has “hidden gems” when it comes to high-value users?
- Does ad personalization increase installs?
- Will an increase in spend help increase subscriptions?
- Do Search campaigns impact organic installs?
- Will a decrease in ad spend decrease daily streaks?
- What impact evergreen ads have on installs?
- What is the impact of SKAN campaigns on the overall installs of an app?
- How do weekend campaigns influence in-app purchases?
- What is the impact of seasonal promotions on new user sign-ups?
- Will a loyalty program increase repeat purchases?
- Will offering a limited-time discount boost first-time purchases?
- Does offering a free trial period boost subscription conversion rates?
- Which ad network brings in the most installs?
- How did an organic celebrity endorsement affect our paid campaigns, and should we have paused ad spend during that period?
- How are our paid campaigns positively affecting our organic installs through factors like delayed conversions and referrals (organic lift)?
- Is my app’s organic cannibalization detrimental, or can it still contribute to a positive overall install lift?
- What is the impact of using interactive ads on subscriptions?
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These examples showcase just a fraction of how Adjust clients are using the advanced AI-powered capabilities of InSight’s incrementality testing. The opportunities for testing are vast, empowering mobile marketers to continually refine their strategies and achieve better results. By selecting an in-app event or install volume to test, you can uncover valuable data to enhance your marketing efforts.
Ready to see how InSight can supercharge your campaign efficiency? Request a demo for a bespoke consultation with our team!
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