Monitor app reviews with Subview

Choose a question and a consistent scope

Start with a specific question, such as which problems users report after a release or what they value most about a feature. Keep a note of the product, sources, period and filters so the next review can use the same scope.

1. Open Sources and identify the sources for your product. Keep platforms separate when comparing results before combining any findings.
2. Open Reviews for each source and select a Date Range. Use Rating, Country, Language or Version where available to explore a specific part of the feedback.
3. Start with all ratings, then examine critical and favourable reviews. A review of only one-star feedback answers a different question from a review of the whole set.

• Open Sources
• Understand source details and date filters

Set up a regular digest

A digest can include newly collected feedback and later changes to existing reviews. Its total is not a count of all reviews published on the platform during those dates. Keep separate frequencies separate when comparing successive emails.

1. Open Subscriptions, choose Add Subscription and select your product and sources.
2. Choose a frequency that fits your review routine, such as weekly, and create the subscription.
3. When an email arrives, check its sources and period, read any available AI summary and open the supporting reviews for themes you want to investigate.

• Open Subscriptions
• Understand digest selection and summaries

Check the evidence behind a theme

1. Read several supporting reviews and look for feedback that contradicts the theme. Check the original wording as well as any translation.
2. Inspect the rating, source, app version and available country or language context. Open Previous versions or a developer or company reply when they help explain the feedback.
3. Save links to the relevant reviews with your team's notes. Distinguish a recurring problem from an isolated report and state whether you read every matching review or a sample.

Explore a question with an AI assistant

If you have connected an assistant through MCP, it can read stored reviews and ready digests. Replace the product and dates in this example with your own, and choose the time zone you want to use.

Example request: For Product A, review feedback published from 1 October 2026 through 7 October 2026 in Europe/London. First confirm the product and sources you found. Include all ratings, read all matching reviews or state exactly what you sampled, and group recurring problems, positive themes and feature requests. Link to supporting reviews and distinguish isolated reports from recurring themes. State the coverage and any missing data.

This request uses publication dates. To discuss a particular email instead, ask the assistant to read the saved digest and explain its sources and period. Linked reviews show current content, which may differ from the saved email.

• Connect an AI assistant

Turn the review into a team decision

Record the finding, supporting links, a proposed next step and what evidence would confirm or challenge it in your team's usual planning tool. Suggestions from an assistant are proposals to assess against your product goals.

On the next review, keep the scope comparable and check whether the theme persists. A change in review volume or rating alone does not show that a product change caused it; compare with your own usage data, research or experiments.