Best Practices for Mobile Marketing Analytics

iOS SKAN 4 has broken the ability to map a user to the campaign they came from. So I have been doing a lot of digging to help the Game studios we work with monitor ROAS and LTV in a SKAN 4 world at Segwise.ai. Sharing a "101 on SKAN 4 attribution" from my learnings, would love to hear comments on how you have changed your Attribution and ROAS/LTV monitoring workflows to handle this! 1. Postback Structure: SKAN 4 now offers three postbacks (0-2 days, 3-7 days, 8-35 days), giving us more data points to work with. 2. Conversion Values: We start with 4-bit (0-15) for early postbacks, potentially dropping to 2-bit (0-3) later, depending on user engagement and privacy thresholds. 3. Campaign Management: We have 1,024 unique campaign IDs to work with. This means we need to be strategic about how we set up and group our campaigns. 4. Attribution Windows: SKAN focuses on 'first open' rather than 'install date'. This shifts how we should think about and create our cohorts. 5. Privacy Thresholds: Apple doesn't disclose the exact criteria, but we know that larger campaigns are more likely to receive detailed postbacks. 6. ROAS Calculations: Measuring D7 ROAS is trickier now. We're looking at new approaches like probabilistic models and cohort analysis to fill the gaps. 7. MMP Adaptations: Our measurement partners have shifted focus to data aggregation, modeling, and providing insights within SKAN's limitations. Has the value of these tools dipped now? Why am I still paying for every inorganic install? Planning on hosting a small meetup with a few UA folks on SKAN 4, would you be interested? Just drop a comment and I'll keep you posted. #MobileMarketing #SKAdNetwork #iOSAttribution #AppMarketing #AdTech

So, I've been diving deep into digital marketing for a decade now, specifically focusing on maximizing conversion rates. One of my favourite projects involved optimizing Google Mobile Ads for a client. We saw a decent conversion rate but knew there was room for improvement. I started by analyzing user behavior on mobile devices. We identified key pain points, like slow load times and confusing landing pages. To tackle these, we implemented a few strategies: ◾ Accelerated Mobile Pages (AMP): We optimized landing pages to load lightning-fast, reducing bounce rates. ◾ Compelling Mobile-First Ads: We created ads that were visually appealing and easy to understand on smaller screens. ◾ Precise Targeting: We leveraged Google's advanced targeting options to reach the right audience at the right time. The result? A 20% boost in mobile conversion rates! It was incredibly satisfying to see the direct impact of our efforts. Now, I'm curious: How have you optimized your mobile ads to drive conversions? Let's share tips and learn from each other!

90% of mobile time is in apps. Is your marketing strategy keeping up? Most marketers miss out by not analyzing mobile user behavior deeply. Phones are central to daily life. Understanding user interactions on your campaigns can reveal insights that personalize and improve marketing strategies. How to evaluate campaign effectiveness? ↪️ Monitor engagement metrics like opens, clicks, and interaction times. ↪️ Track conversion rates from actions such as app installs and purchases. ↪️ Gather user feedback through surveys and reviews to refine your campaigns. Here are some basics: ➡️ Segment data to tailor marketing efforts based on demographics and usage patterns. ➡️ Conduct A/B testing to continually optimize different aspects of your campaigns. ➡️ Employ analytics tools for deeper insights into user behavior and campaign performance. Are you maximizing mobile analytics to enhance your marketing?