The ultimate list of A/B testing ideas to supercharge your mobile app growth strategy
Looking to optimize your app's performance but unsure of where to start with A/B testing? You're not alone. Mobile app A/B testing is a powerful technique for improving user engagement, retention, and conversion rates, but it can be overwhelming when you're not sure what, when, or how to test. We'll walk you through how to get started.
Why A/B testing matters for mobile app marketers
Before we dive into the specifics, let's briefly discuss why A/B testing marketing and in-app behavior is crucial for mobile app marketers.
Defining your ‘why’ to find your ‘what’
Unsure about what to test? Start by conducting a usability audit of your mobile app. An audit can be executed by using a combination of the following methods:
- By app staff: Navigate through your app as if you were a new user, paying close attention to usability issues, navigation challenges, potential friction points, and opportunities for improvement.
- By feedback: Gather feedback from real users through app store reviews, customer support inquiries, and in-app surveys to gain valuable insights into their pain points and suggestions for improvement.
- By analytics: Analyze user behavior data using analytics tools. Look for churn, or drop-off points in the user journey, such as high bounce rates on specific screens or low engagement with particular features. These data points can guide your A/B testing efforts.
- By focus group: Assemble a diverse group of representative users for direct, real-time feedback on your app's usability, design, and functionality. Instruct participants to interact with your app while encouraging them to express their opinions and share their experiences, opinions, and ideas openly.
Leveraging the above methods, focus on identifying areas where users might encounter difficulties or friction. Look at points in the user journey with high churn to identify:
- Navigation issues
- Confusing user interfaces
- Slow loading times
- Unintuitive user flows
These pain points can be excellent candidates for A/B testing. Next, define clear goals and KPIs for testing the improvement of these areas. Ask yourself:
- What specific outcomes are you looking to improve?
- How will you measure success?
- What is the current baseline for these metrics?
Examples of A/B testing metrics include user retention, in-app purchases, click-through rates, conversion rate, and revenue per user, among others. Having a solid understanding of your objectives will guide your testing efforts and help you prioritize what to test.
Start small and iterate
It's best to start small. Choose one element to test at a time, as testing multiple variables at once will give you unclear results as to which is ultimately impacting your metrics.
Marketing A/B testing
Before a user reaches your app, you can learn a lot about what, exactly, converts with marketing A/B testing, including A/B testing ads, A/B testing social media, and A/B testing email.
- Text variations
- Ad (i.e. image vs. animation)
- Landing pages
- Formats (i.e. interstitial vs. banner)
- Placement (i.e. in-app banners vs. within content)
- Frequency cap
- Scheduling (i.e. times of day or days of the week)
- Targeting (i.e. segment A vs. segment B)
- Personalization (i.e. tailored to individual users vs. generic)
- Contextualization (i.e. related to surrounding content vs. generic)
- Pricing model (i.e. cost per click vs. cost per impression)
- Network selection
ASO A/B testing
Consider what you can test to optimize your organic traffic as well, bringing in users at a lower overall cost.
- Description (i.e. with vs. without social proof)
- Promotional text (i.e. discounts, seasonality)
- CTA (i.e. download now vs. try for free)
- Icon (i.e. color, style)
- App screenshots (i.e. layouts, captions, number, styles, order, seasonality)
In-app A/B testing
There are a wealth of variables that you can test within your app, from onboarding through retention.
Call to action buttons
- Placement (i.e. floating vs. anchored)
- Shape (i.e. rounded corners vs. traditional rectangle)
- Text (i.e. different message, font, or text size)
Push notifications or in-app messages
- Time of day (i.e. 8 a.m. vs. 8 p.m.)
- Frequency (i.e. once per day vs. once every other day)
- Use of emojis
- Navigation swipe direction (i.e. left to right vs. right to left)
- Breadcrumbs (i.e. with vs. without)
- Style (i.e. hamburger vs. sidebar)
- Gesture-based controls (i.e. swipe vs. pinch)
- Tooltip (i.e. with vs. without)
- Loading animation
- Quick profile set up with social media logins
- Search bar placement
- Notification format (i.e. in-app message vs. push notification)
- Prompt format (i.e. chatbot vs. multiple choice question)
- Time of day
- Placement in user journey
- Questions asked
- Screen reader compatibility
- Voice commands
- Profile customization options (i.e. avatars vs. uploaded photos)
- Social media sharing
- Gamification (i.e. badges vs. points)
- Offline mode
- Model (i.e. freemium vs. rewarded ads)
- In-app ads (i.e. formats, sizes, placements)
- Pricing tiers (i.e. cost, feature bundling, trial durations)
- Promotions (i.e. limited-time discounts, bundles, loyalty programs)
- Checkout flow (i.e. number of steps, wishlist feature, payment options, pricing information)
ATT opt-in prompt
- Placement (i.e. splash screen vs. app home screen)
- Language (i.e. formal vs. informal)
- Size (i.e. full screen vs. modal window)
Get more information on A/B testing for App Tracking Transparency opt-ins.
Monitor and iterate continuously
A/B testing is not a one-time effort; it's an ongoing process. Continuously monitor the results of your tests and make adjustments accordingly. What works today may not work tomorrow as user preferences evolve. Here are a few A/B testing tools you can leverage:
Attribution: Adjust's attribution data allows app marketers to identify the causal relationships between test variations and user actions, helping them make informed decisions about which changes to implement or roll back.
Segmentation: When testing audience variables such as demographics, behavior, location, or device type, Adjust’s Audience Builder makes it possible to gain deeper insights into how different subsets of the audience respond to A/B test variations. This can reveal valuable patterns and trends that might not be apparent when analyzing the entire user base as a whole.
Pulse: Adjust's Pulse offers a time- and cost-saving solution by providing customizable smart alerts. These alerts can be tailored to specific A/B test scenarios and sent through convenient channels like Slack or email. For example, a mobile marketer could set an alert for a variant of a campaign when it exceeds or falls below a designed KPI.
Learn more about Pulse use cases.
Incrementality: When analyzing aggregated, rather than device-level, data, incrementality measurement is a crucial A/B testing tool. It focuses on isolating the true impact of a campaign by comparing it to a control group that has not been exposed to the marketing material. Adjust does this with synthetic control groups, using the aggregated data of similar apps. This helps mobile app marketers understand whether a campaign is having a negative impact on KPIs, cannibalizing organic installs, having no impact on KPIs, or having a positive impact, and what degree of uplift (or downlift) is occurring as a direct result of the campaign.
Learn more about incrementality measurement.
Getting started with A/B testing in mobile app marketing when you're unsure about what to test may seem daunting, but it's entirely manageable. Begin by setting clear goals, conducting a usability audit, and analyzing user feedback and behavior. Start with small, manageable tests and iterate from there. Over time, you'll develop a deeper understanding of your users and how to optimize your app for success. A/B testing is a powerful tool in your arsenal, and with persistence, it can lead to significant improvements in your mobile app's performance.
To learn more about how to leverage Adjust’s next-generation measurement tools, request a demo.
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