Should I Defend This Organic Keyword with Paid?
[APP] ranks organically for [KEYWORD] in the [COUNTRY] App Store. Help me evaluate whether the keyword still deserves Apple Ads coverage. Use MobileAction MCP to retrieve: - [APP]'s current and recent organic rank for [KEYWORD] - search volume for [KEYWORD] - which competitors are advertising on the term - their MobileAction estimated impression share - [APP]'s connected first-party Apple Ads performance for [KEYWORD] Assess the case for maintaining paid coverage based on competitive pressure and observed paid efficiency. Do not assume that strong organic ranking makes paid spend redundant, and do not claim to measure incrementality. Give me three conclusions: 1. what the available data tells us, 2. what we cannot know from this data, 3. the safest next test you would recommend.
Brand Keyword Defense Audit
Audit Apple Ads competition around [APP] brand searches in [COUNTRY]. Analyze these keywords: - [BRAND KEYWORD 1] - [BRAND KEYWORD 2] - [BRAND KEYWORD 3] Use MobileAction Search Ads Intelligence to identify other apps appearing on these terms during the most recent supported period and show their impression share. Then use [APP]'s connected Apple Ads reports to show actual impressions, taps, installs, spend, CPA, CPT, TTR, and conversion rate for the same terms where available. Rank the three brand keywords by competitive pressure. Classify each as: - actively contested - lightly contested - currently uncontested in the observed data Recommend where [APP] should investigate stronger brand defense versus where current coverage may already be sufficient. Impression shares must be labeled as MobileAction intelligence. [APP] campaign metrics must be labeled as first-party Apple Ads data.
Harvest Discovery Search Terms into Keyword Tests
Analyze the connected Apple Ads search-term performance for [APP] in [COUNTRY] over the last 30 days and identify promising search terms that deserve dedicated keyword tests. Start with search terms generating installs or strong conversion efficiency that are not already represented by an equivalent exact keyword in current reporting. Then cross-reference those terms against MobileAction organic data for [APP]: - organic rank - search volume - relevant keyword metadata Create three groups: 1. strong paid signal + weak organic rank, 2. strong paid signal + strong organic rank, 3. promising but low-volume or insufficient evidence. Recommend the terms I should investigate adding as explicit keywords and explain why. Do not add them to the campaign or invent bids.
Broad-Match Leakage Diagnosis
Investigate whether broad-match traffic is hurting efficiency in [APP]'s Apple Ads campaigns in [COUNTRY] over the last 30 days. Use connected keyword and search-term reports to map expensive or low-converting search terms back to the keywords or ad groups generating them where the reporting allows it. Prioritize search terms with meaningful spend and weak install/conversion performance. Cross-reference the most important terms with MobileAction organic keyword data to see whether [APP] has meaningful organic relevance for those searches. Classify each term as: - relevant but inefficient - probably irrelevant - unclear Then draft a review list of potential negative-keyword candidates and match-structure changes. Do not upload negatives or change campaigns.
Apple Ads Wasted-Spend Triage
Analyze the connected Apple Ads performance for [APP] in [COUNTRY] over the last 30 days. At keyword level, find terms with meaningful spend that meet either of these conditions: - zero installs, or - CPA materially above the relevant campaign average. Do not automatically label every expensive keyword as waste. For each flagged keyword, compare spend, impressions, taps, installs, CPA, CPT, TTR, and conversion rate where available. Then classify it as: 1. clear efficiency problem, 2. expensive but still potentially valuable, 3. insufficient evidence. Where search-term reporting is available, use it to investigate irrelevant traffic. Recommend whether I should investigate pausing, lowering bids, tightening match structure, or leaving the keyword alone. Do not execute any campaign changes. Report the historical spend associated with the flagged terms, not projected savings.
Apple Ads Spend Concentration Audit
Analyze the connected Apple Ads account for [APP] in [COUNTRY] over the last 30 days and show where spend is concentrated. Break total spend down by campaign first, then drill into the campaigns responsible for the largest share. For those campaigns, compare spend, installs, CPA, CPT, TTR, and conversion rate at the most useful available level. Identify: - high-spend/high-efficiency areas - high-spend/weak-efficiency areas - low-spend areas with comparatively strong efficiency Do not assume efficiency alone determines how budget should be allocated. Recommend the three areas where I should investigate shifting emphasis, and explain the trade-off using observed data. Do not modify budgets or bids.
Find New Apple Ads Keyword Test Candidates
Find 15 non-brand keywords that [APP] should consider testing in Apple Ads in [COUNTRY]. Use MobileAction organic data and Search Ads Intelligence rather than generic keyword brainstorming. Prioritize keywords using: - meaningful search volume - [APP]'s existing organic relevance and ranking - available predicted conversion or max-reach signals - current competitive paid activity Explore themes around [SEED THEME 1], [SEED THEME 2], [SEED THEME 3], [SEED THEME 4], and [SEED THEME 5], but do not restrict the analysis to those seeds if MobileAction reveals stronger relevant opportunities. If connected [APP] Apple Ads reporting is available, exclude terms already receiving meaningful paid traffic. For every recommendation, show the evidence and classify it as: - lower-risk test - competitive test - exploratory test Do not invent a recommended starting bid unless actual comparable first-party performance data provides a defensible basis.
Paid Spend on Weak Organic Rank Keywords
Find keywords where the connected Apple Ads account for [APP] spent meaningful budget in the last 30 days but [APP] has weak organic rank in [COUNTRY]. For each one, show: - spend - installs and CPA - Apple Ads conversion rate - organic rank - MobileAction search volume - available chance score Split them into: 1. paid works despite weak organic rank, 2. paid and organic signals are both weak, 3. insufficient data. For group 1, identify terms worth investigating as ASO opportunities. For group 2, identify terms worth reviewing for paid relevance. Do not assume organic rank determines paid conversion or vice versa.
Organic + Paid Keyword Coverage Audit
Cross-reference [APP]'s organic keyword rankings with its connected Apple Ads keyword performance in [COUNTRY]. Find: 1. high-search-volume keywords where [APP] ranks organically in the top 10 but has little or no paid coverage, 2. keywords receiving meaningful Apple Ads spend where [APP]'s organic rank is already very strong, 3. valuable terms where both organic rankings and paid coverage are weak. For the second group, also check MobileAction Search Ads Intelligence to see whether [COMP A], [COMP B], and [COMP C] are actively advertising on those keywords before suggesting reduced paid coverage. Show organic rank, search volume, [APP]'s first-party Apple Ads metrics, and competitor impression share separately. Clearly label competitor shares as MobileAction intelligence rather than Apple Ads account data. Recommend where [APP] should investigate increasing, maintaining, or reducing paid emphasis. Do not claim paid incrementality and do not make campaign changes.
