CPP Performance and Traffic Alignment Audit
Analyze the Apple Ads custom product pages used by [APP] in [COUNTRY] over the last 30 days using connected first-party Apple Ads data. Compare CPP-level performance using the available impressions, taps, installs, spend, CPA, and conversion metrics. Then use keyword or search-term reporting to identify the main search themes associated with each custom product page where the data allows it. Flag CPPs that appear weak relative to [APP]'s relevant campaign or account baseline. For each weak page, tell me whether the evidence points more strongly to: - a traffic or search-intent mismatch, - a creative or messaging hypothesis worth testing, - or insufficient evidence. Then use MobileAction CPP Intelligence to compare relevant competitor approaches from [COMP A], [COMP B], and [COMP C] targeting similar search themes. Keep [APP]'s first-party Apple Ads performance and MobileAction competitor intelligence clearly separated. Recommend tests only. Do not change CPP assignments or campaign settings.
Did a Bid Change Improve Performance?
Review the recent bid changes for [CAMPAIGN / AD GROUP / KEYWORD] using MobileAction bid-history data. Find the most recent meaningful bid change and compare Apple Ads performance during an equal-length period immediately before and after the change, staying within the supported reporting window. Compare: - impressions - taps - installs - spend - CPA - CPT - TTR - conversion rate Show the old bid, new bid, change date, and observed before/after performance. Explain whether performance improved, worsened, or stayed broadly similar after the change. Do not say the bid change caused the result; explicitly mention other variables this data does not control for. Finish with the next test you would recommend.
Optimize for Post-Install Quality Using MMP Goals
If my MobileAction account has an MMP goal/integration available, analyze Apple Ads performance for [APP] in [COUNTRY] against [GOAL] over the last 30 days. Compare campaign and keyword performance using both Apple Ads acquisition metrics and the available goal metrics such as goal conversions, goal revenue, or ROAS. Identify cases where: - acquisition CPA looks strong but post-install value looks weak - acquisition CPA looks expensive but downstream quality looks strong - both acquisition and downstream quality are strong Recommend which segments deserve further investigation for scaling or reduction. Clearly state which metrics come from Apple Ads and which come through the MMP integration.
Predicted vs Observed Keyword Conversion
For these keywords in [COUNTRY] — [KEYWORD 1], [KEYWORD 2], [KEYWORD 3], [KEYWORD 4] — compare MobileAction's available predicted conversion, max-reach, or install estimations with [APP]'s actual connected Apple Ads keyword performance from the last 30 days. Show predicted values and observed Apple Ads conversion metrics separately. Do not treat the two conversion measures as identical definitions or expect them to match exactly. Instead, identify: - keywords where both signals are strong - keywords where both are weak - keywords where prediction and observed paid performance disagree materially For the disagreement cases, tell me what additional questions I should investigate rather than inventing a cause. Clearly label all MobileAction predictive values as estimates and Apple Ads metrics as first-party observed performance.
