Connect Google Play Store to Claude

Multi-Client Google Play Store Health Radar

Using the Catchr MCP, analyze Google Play Store for [List of Client Accounts] over [Reporting Period] against [Comparison Period]. For each account, review Store listing conversion rate, Store listing acquisitions, and Store listing visitors and break the results down by Country and Traffic Source. Focus on store acquisition and install performance. Rank accounts as Healthy, Watch, or Critical using [Client Targets or Historical Baseline], and show the evidence behind each status. Return a client-ready table with the account, main change, supporting fields, business implication, recommended next action, and one sentence for the next client meeting. Separate observed changes from possible explanations, respect the reporting grain, and do not claim causation when Google Play Store only shows correlation.

Client-Ready Google Play Store Performance Brief

Using the Catchr MCP, review Google Play Store for [Client Account] during [Reporting Period] versus [Comparison Period]. Review Store listing visitors, Daily User Installs, and Daily User Uninstalls and break the results down by Search Term and UTM campaign. Explain what improved, what declined, and which changes are material for store visibility, acquisition, installs, ratings, reviews, versions, and markets. Produce an executive summary, three evidence-backed wins, three risks, and a prioritized action plan with owner and review date. Include a compact evidence table that ties every conclusion to the returned fields. State any unavailable field, incompatible reporting level, or small-sample limitation before recommending action, and write the final recap in language an agency account manager can use with the client.

Google Play Store Opportunity and Risk Map

Using the Catchr MCP, compare Google Play Store across [List of Client Accounts] for [Period] using [Materiality Threshold] and [Client-Specific Targets]. For every account, review Daily User Uninstalls, Total Average Rating, and Active Subscriptions and break the results down by UTM Source and Package Name. Investigate rating, review, and version-level risks and market, device, and listing-conversion opportunities. Build an opportunity-and-risk map ranked by business relevance, confidence, and urgency. For each finding, show the account, observed change, supporting fields, plausible explanations, first validation step, and recommended client action. Keep each client separate before creating a portfolio summary, and avoid applying one account's baseline, currency, attribution rule, or reporting definition to another.

Morning Google Play Store Priority Queue

Using the Catchr MCP, pull Google Play Store for [List of Client Accounts] over [Recent Period] and compare it with [Baseline Period]. For each client, review Active Subscriptions, Amount, and Review Star Rating and break the results down by SKU Id and Date. Flag changes beyond [Alert Threshold], separate high-value issues from low-volume noise, and rank the work I should handle today. Return a queue with the client, issue, exact evidence, likely impact stated cautiously, first validation step, recommended action, and a short update I can send to the client. Do not merge accounts until each result has been checked against its own target, currency, timezone, and reporting grain.

Monthly Google Play Store Client Report

Using the Catchr MCP, create a monthly Google Play Store report for [Client Account] covering [Current Period] versus [Previous Period]. Review Review Star Rating, Current Device Installs, and Daily Device Installs and break the results down by Review Last Update and Review Submit Date and Time. Explain the most important movement in store visibility, acquisition, installs, ratings, reviews, versions, and markets, including what stayed stable and what needs attention. Write a plain-English report with an executive summary, a concise evidence table, three wins, three concerns, and three actions for [Next Period]. Attach an owner and success measure to each action. State the latest available date and any missing fields or intervals so the client can distinguish measured facts from assumptions or incomplete coverage.

Google Play Store Optimization Backlog

Using the Catchr MCP, analyze Google Play Store for [Client Account] over [Lookback Period]. Review Daily Device Installs, Daily Device Uninstalls, and Installs on active devices and break the results down by Country Code and Developer Reply Date. Identify the largest opportunities related to store acquisition and install performance and market, device, and listing-conversion opportunities, then create an optimization backlog ranked by expected impact, effort, and confidence. For every task, include the observed evidence, a specific action, an owner, a due date, a success metric, and a guardrail that would stop the test. Use [Minimum Volume] and [Materiality Threshold] to avoid reacting to noise, and label any recommendation that requires a field or business definition not available in the returned dataset.

Google Play Store Store Acquisition and Install Review

Using the Catchr MCP, analyze Google Play Store for [Account or Entity] over [Reporting Period] versus [Comparison Period]. Review Installs on active devices, Current User Installs, and Install Events and break the results down by App Version Code and Review Link. Concentrate on store acquisition and install performance. Identify the entities and periods driving the largest change, distinguish material movement from normal variation using [Minimum Volume] and [Business Target], and explain what the available fields can and cannot prove. Return a ranked findings table with evidence, business implication, confidence, and recommended next action, followed by a short decision summary. Keep calculations at a compatible reporting grain and do not invent a metric when Google Play Store exposes only a related signal.

Google Play Store Rating and Version Risk Analysis

Using the Catchr MCP, investigate Google Play Store for [Account or Entity] across [Period] with a focus on rating, review, and version-level risks. Review Install Events, Total User Installs, and Uninstall Events and break the results down by Review Text and Review Title. Compare relevant entities against [Target, Peer Group, or Historical Baseline], then locate the strongest opportunities and clearest deterioration. For every finding, show the returned values, comparison dimension, possible explanations, and next check required before action. Deliver a prioritized opportunity map with owner, action, expected signal of improvement, and review date. Treat associations as hypotheses unless the available Google Play Store fields establish a direct relationship.

Google Play Store Market and Listing Opportunity Map

Using the Catchr MCP, review Google Play Store for [Account or Entity] over [Lookback Period] to assess market, device, and listing-conversion opportunities. Review Uninstall Events, Daily Average Rating, and Daily Device Upgrades and break the results down by Reviewer Language ISO Code and Reviewer Language. Flag changes outside [Tolerance], rank them by materiality and confidence, and separate confirmed data observations from possible operational causes. Return an exception table with the affected entity, period, supporting fields, severity, owner, first validation step, and recommended response. End with three repeatable monitoring rules, including the threshold, minimum volume, and required field. Do not present an unusual value as proof of an error or business cause.

Google Play Store Data Quality Audit

Using the Catchr MCP, audit Google Play Store for [Account or All Connected Accounts] over [Period]. Review Daily Device Upgrades, Daily Crashes, and Canceled Subscriptions and break the results down by Device and Android OS Version. Check completeness, unexpected nulls, duplicate identifiers at [Expected Grain], invalid values, incompatible aggregation levels, and date consistency where the returned fields support those tests. Return rule-level failure counts and a severity-ranked exception sample with account, field, observed value, expected condition, and reproducible validation step. Distinguish source-data issues from extraction or modeling issues, and do not infer uniqueness, join keys, or business meaning unless confirmed in [Data Contract or Source Documentation].

Google Play Store Freshness and Coverage Monitor

Using the Catchr MCP, monitor Google Play Store delivery for [Account or All Connected Accounts] across [Lookback Period]. Review Canceled Subscriptions, Daily ANRs, and Discount Rate and break the results down by Financial Status and Hardware. Measure date coverage, latest available record, row or entity volume, missing intervals, and field population against [Expected Schedule] and [Freshness SLA]. Flag stale extraction, flatlined volume, schema coverage changes, and gaps beyond [Absolute and Relative Thresholds]. Return an account-level health summary plus an investigation table with first affected period, supporting fields, likely failure domain stated cautiously, owner, and next validation query. Separate genuine source inactivity from a pipeline issue whenever the evidence cannot distinguish them.

Google Play Store Drift and Reconciliation Review

Using the Catchr MCP, compare Google Play Store across [Current Window] and [Baseline Window] for [Account or All Connected Accounts]. Review Discount Rate, Item Price, and New Subscriptions and break the results down by Package Id and Promotion Id. Profile distributions, null rates, distinct-value counts, volume, and material changes at the declared reporting grain. Reconcile related fields only when their definitions and aggregation levels are compatible. Flag abrupt shifts beyond [Drift Threshold], inconsistent totals, and values that violate [Business or Data Contract Rules]. Produce a reproducible alert table with evidence, severity, probable domain, and next check, followed by a concise assessment of which analyses may be unreliable until each issue is resolved.

Replace [variables] Facts ≠ hypotheses Action + follow-up metric

Connect Google Play Store to Claude

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How to connect Google Play Store to Claude ?

Authorize the Google Play Store account in Catchr

Add the Catchr MCP as a custom connector in Claude

Choose, adapt, and run a prompt.

A simple client question should not trigger an hour of data prep.

Pull another CSV

Rebuild the context

Summarize it by hand

Ask the account. Get to the explanation.

Prepare data before every question.

Connect once. Keep asking.

Twelve Google Play Store prompts for analyzing real account data.

Google Play Store to Claude FAQs

What Google Play Store data can Claude analyze through Catchr?

How granular can Google Play Store analysis be in Claude?

Can Claude compare Google Play Store performance across periods or accounts?

Can Claude investigate unusual changes in Google Play Store?

What types of prompts work best for Google Play Store analysis in Claude?

Can I combine Google Play Store with other data sources in Claude?

Can Claude compare multiple Google Play Store accounts or entities?

What do I need to connect Google Play Store to Claude with Catchr?

How recent is the Google Play Store data, and how much history can Claude analyze?

Can Claude change anything in Google Play Store through Catchr?

How much does it cost to connect marketing data to Claude with Catchr?

Can I try the Claude integration before choosing a plan?

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