Understand what customers dislike.Turn reviews into priorities.

Give your AI a business, app or product and a review source. Dativue retrieves public reviews, so you can see repeated praise, complaints and improvement requests.

See real results

Paste into your AI

Your customer review brief

Understand the experience behind the rating.

Repeated praise and complaints

Separate recurring themes from isolated reviews.

Context for each theme

Keep ratings, dates and helpful votes when returned.

An improvement shortlist

Prioritize questions to investigate and changes to test.

Original sources included

Understand the experience behind the rating.

Review analysis that keeps customer themes connected to ratings, dates and available source links.

Repeated praise and complaints

Separate recurring themes from isolated reviews.

Context for each theme

Keep ratings, dates and helpful votes when returned.

An improvement shortlist

Prioritize questions to investigate and changes to test.

Real sources. Better research.

Dativue brings these public sources into your AI. You choose the target and market; your AI connects the evidence to the decision you want to make.

Place and business reviews

Public business feedback and available owner responses

App reviews

Ratings and written feedback from the store you choose

Product reviews

Public shopping feedback when supported for your target

A useful answer. In your AI.

Repeated praise and complaints
Context for each theme
An improvement shortlist

See what Dativue actually found.

A real research example. The source links and collected metrics sit alongside the recommendations they support.

Two concerns from Notion app reviews

100 returned review records · selected examples

Collected 26 Sept 2026

Research request

Retrieve public Google Play reviews for Notion and identify concerns worth investigating.

Two reviews raise different concerns: mobile editing and the emphasis on AI. Ratings and helpful votes are separate from the interpretation.

Investigate mobile editing friction

Product investigation

What the data shows

A 4-star review dated 26 February 2026 describes mobile editing problems and had 68 helpful votes.

What to do next

Reproduce the editing behavior before choosing a fix or writing a reassurance.

Notion app review source4 stars · 68 helpful votes26 Feb 2026

Separate AI positioning from core utility

Messaging research

What the data shows

A 1-star review dated 27 September 2025 objects to the emphasis on AI and had 345 helpful votes.

What to do next

Interview users about core note-taking needs. Test messaging that explains optional AI features clearly.

Notion app review source1 star · 345 helpful votes27 Sept 2025

Returned records include older reviews despite a newest-sort request. Two reviews do not establish complaint frequency. Individual review URLs were unavailable; links open the original app listing.

Your question. A clear research path.

01
Copy the prompt into your AI.
Your AI checks its Dativue connection and helps you complete the supported setup if needed.
02
Add the context it asks for.
Describe your target, market and goal. The prompt asks only for essentials you have not already supplied.
03
Review the evidence and next step.
Get your customer review brief, with returned measurements, source links and clear recommendations.

Understand what customers dislike.

Copy the prompt into your AI. It asks for the missing context, helps connect Dativue if needed, then runs your research.

Understand what customers dislike

Help me understand what customers dislike using Dativue.

Connect Dativue if needed
Ask for the context that matters
Return evidence and a useful next step

First check whether Dativue is already connected and its research tools are available in this AI app. Reuse an existing connection. If it is missing, read https://dativue.com/SKILL.md and help me complete the supported setup for this app. If login or account approval is needed, give me the connection link and wait for me to finish. Verify access with a free research_credit_quote call before saying Dativue is ready. If this app cannot connect, explain the supported next step. Then return to this research.

Before using any research tool, review what I have already provided. If essential details are missing, ask me one concise round of questions about the business, place, app, or product, the review source, country and language, and the decision I want to support. Do not repeat questions I have already answered. Wait for my response before running research. Quote only if I ask for an estimate. If a search call requires a maximum hold above the approval threshold, ask me to approve that maximum before running it. Once you have enough context, group repeated praise, complaints, requested improvements, and owner responses while preserving ratings, dates, helpful votes, and source URLs. Do not enrich public reviewer labels.

Use search_reviews for the exact business, app or product and chosen source. Keep the requested sorting and disclose the available date range. Group praise, complaints and requested changes. Preserve ratings, dates, helpful votes, owner responses and source links where returned. Do not infer missing review URLs or enrich reviewer identities. Clearly label the selected sample, not all customers.

Keep the research bounded to the question I asked. Quote a multi-call plan when a spending bound is needed and ask for approval when its maximum exceeds Dativue's approval threshold. When a call returns pending, poll its exact jobId with research_job_status instead of repeating the paid call. Use only public data. Keep original URLs, collection dates and returned metrics. Separate retrieved evidence, calculations and your recommendations. Mark missing information N/A and explain unavailable sources without inventing results.

A few things to know.

What will this workflow give me?

Repeated praise and complaints: Separate recurring themes from isolated reviews. Context for each theme: Keep ratings, dates and helpful votes when returned. An improvement shortlist: Prioritize questions to investigate and changes to test. The exact detail depends on the public data returned for your target.

Do recent reviews always come back in date order?

The workflow requests your preferred sorting, then checks the returned dates. Availability and sorting vary by source. The brief states the actual sample and does not imply that a partial result covers every review.

Do I need to install Dativue first?

Copy the prompt first. Your AI checks for an existing connection and helps you follow the supported setup if needed. Some AI apps require you to add a connector in settings. You complete account login and approval yourself.

Can I use this for my own market?

Yes. Describe your target, country, language and goal. Your AI asks for missing essentials and adapts the research to your answers. Available sources and detail can vary by market.

How are research credits handled?

The workflow keeps research bounded and asks for approval when required by your account's credit threshold. A quote can show the maximum hold before a larger plan. Actual search charges may be lower, and unused held credits are returned.

Choose the next question you want your AI to research.

Browse all workflows

Understand what customers dislike.Turn reviews into priorities.

Understand the experience behind the rating.

Understand the experience behind the rating.

Repeated praise and complaints

Context for each theme

An improvement shortlist

Real sources. Better research.

A useful answer. In your AI.

See what Dativue actually found.

Two concerns from Notion app reviews

Investigate mobile editing friction

What the data shows

What to do next

Separate AI positioning from core utility

What the data shows

What to do next

Your question. A clear research path.

Copy the prompt into your AI.

Add the context it asks for.

Review the evidence and next step.

Understand what customers dislike.

A few things to know.

Find where your brand is mentioned

Find content trends

Analyze a competitor

Understand what customers dislike.Turn reviews into priorities.

Understand the experience behind the rating.

Understand the experience behind the rating.

Repeated praise and complaints

Context for each theme

An improvement shortlist

Real sources. Better research.

A useful answer. In your AI.

See what Dativue actually found.

Two concerns from Notion app reviews

Investigate mobile editing friction

What the data shows

What to do next

Separate AI positioning from core utility

What the data shows

What to do next

Your question. A clear research path.

Copy the prompt into your AI.

Add the context it asks for.

Review the evidence and next step.

Understand what customers dislike.

A few things to know.

Explore another workflow.

Find where your brand is mentioned

Find content trends

Analyze a competitor