Advertising Technology Blog

Subscription app revenue surged in 2021, with App Store up 33% and Google Play up 78%. Key challenges include user loyalty, conversion, and privacy. Deep measurement via in-app events, deep linking, and predictive analytics is crucial for UA and re-engagement.

True ROI requires accurate attribution data to avoid the bleeding cash cycle. Robust attribution platforms collect, standardize, and integrate cost data via APIs, enabling granular optimization. Privacy and security are critical.

Mobile re-engagement strategies must adapt to Apple's ATT, which limits IDFA use. Marketers can use 1st-party data, segmented owned media, and incrementality measurement. Success requires diversification across paid, owned, and earned channels, plus optimized push notifications and timing of privacy prompts.

App conversions measure user actions like purchases or sign-ups. Key types include app store, install-to-event, and install-to-purchase conversions. Optimize via ASO, UX, A/B testing, and seamless checkout to boost rates.

Gaming marketers face fierce competition, privacy changes, and high user expectations. Key metrics include CPI, LTV, ROAS, and retention. Creative formats like rewarded videos and playable ads drive engagement. SKAdNetwork requires strategic conversion value mapping. Granular measurement underpins success.

mCommerce is mobile buying/selling. It's booming, hitting $2.2T in 2023. Consumers prefer apps for convenience and security. Success requires fast load times, easy checkout, and personalization.

Data discrepancies in mobile attribution arise from differing models, lookback windows, and time zones. Accurate measurement is crucial for ROI. Using a single source of truth via MMPs and raw data helps mitigate issues.

App monetization involves strategies like in-app purchases, subscriptions, and advertising to generate revenue from free apps. Key metrics include retention, ARPU, and LTV. Choosing the right model depends on app type and user behavior.

Reach-based incrementality accurately measures ad lift by considering only users exposed to ads, correcting ITT's noise. Example: 50% higher lift than ITT's 16.67%.

App engagement is vital for retention and monetization. Key metrics include sessions, retention, and DAU/MAU. Strategies: effective onboarding, personalization, push notifications, and deep linking improve engagement and reduce churn.

Programmatic advertising automates media buying using AI, enabling real-time ad sales and personalized targeting. It spans channels like display, video, and social, offering efficiency and lower costs.

Despite high ATT opt-in rates near 50%, IDFA collection lags because 55% of apps haven't deployed the prompt. Over 30% of iOS devices are restricted or ex-LAT, limiting measurement. Deploying ATT can double consent rates to 24%, improving attribution and ROI.

The Nordics have high mobile usage, with increased app installs during the pandemic. Women dominate mobile gaming but men spend more. Poor UX and privacy concerns remain, though users welcome iOS 14 changes. Marketers should measure, invest in mobile, prioritize UX, and build trust.

ROX measures financial impact of customer experiences on campaigns, focusing on contextualized, personalized, and frictionless CX to boost engagement and LTV.

SKAdNetwork reveals advertiser-publisher connections, showing Social and Gaming apps drive 92% of paid installs. Privacy thresholds cause conversion value nulls, impacting optimization. Advertisers must adapt campaign structures to overcome NOI decline and leverage limited data for LTV predictions.

Mobile shopping apps drive 3x higher conversion than mobile web. Granular measurement, deep linking, fraud protection, and re-engagement are key. Personalization and privacy compliance balance is crucial for success.

App Clips are lightweight iOS app extensions under 15MB for instant actions like ordering or paying without full installation. They reduce friction, use QR/NFC triggers, and support Apple Pay and Sign in with Apple.

Apple enforced ATT in April 2021, ushering a privacy-centric era. Predictive analytics predicts user LTV without IDFA, using early engagement signals. This reduces reliance on user identity, enabling effective targeting while respecting privacy.

UA managers optimize campaigns by adjusting bids and targeting, but rely on gut feelings due to delayed LTV data. Predictive analytics can forecast LTV early using deep learning, but is resource-intensive and requires large datasets.

Mobile ad fraud wastes billions yearly. Categories: attribution hijacking (real users, fake clicks) and fake installs (bots, device farms). Fraudsters evolve, exploiting industry complexities. Key to combat: education, secure SDKs, post-attribution detection.