Reviews coverage 2.0
Get a much deeper view of your app reviews across Google Play and Apple Store. New dashboards show rating distribution, performance by asset, and the impact of your replies on updated reviews. Each review now includes rich device and app metadata, new filters, support for "no text" reviews, and Astra on top so you can ask questions and generate structured insights.
1) Reviews 2.0 - New reviews dashboards
See how your ratings are distributed at a glance and by asset. New charts show overall review volume and rating, plus how each app or asset contributes to your score so you can quickly spot problem areas or star performers.
Use cases:
Compare app performance across countries or brands to see where ratings lag.
Track rating improvements after a new release or campaign.
Quickly identify which assets or stores need extra replies or fixes.
2) Reviews 2.0 - Updated reviews and reply impact
Understand how your replies change review scores over time. New charts separate updated reviews where the score increased, stayed the same, or decreased and show how many of those had a prior brand reply.
Use cases:
Prove that replying to reviews lifts ratings and not just engagement.
See which markets or teams are best at turning bad reviews into better ones.
Spot reply strategies that are not moving the score and need a refresh.
3) Country and app version comparison
This update introduces two new comparison charts that give you a clear view of where your reviews and ratings are coming from. You can break performance down by country (for Apple Store only) and by app version to see which markets and releases are driving the most feedback, where ratings are trending up or down, and where attention is needed. It’s a fast way to spot regional issues, validate new releases, and understand what’s shaping your overall score.
Use cases:
• Identify the countries contributing most to rating shifts or review spikes
• Catch version-specific issues right after a release
• Prioritize fixes, localization, or marketing based on performance patterns
4) Reviews 2.0 - Rich review metadata per store
Each review now includes deeper technical and contextual data.
For Google Play you can see language, device, Android OS version, app version code and name, screen specs, device class, RAM, CPU, and more.
For Apple Store you can see country, app version, and platform.
Use cases:
Pinpoint bugs that only happen on specific devices, OS versions, or app builds.
Give product and engineering precise info for reproducing issues.
Segment user feedback by market or platform when planning roadmaps.
5) Reviews 2.0 - New review filters
Filter reviews using new technical and contextual fields. You can filter by version code (Play Store and Apple Store), device name (Play Store), country (Apple Store), and update status (if the review was updated, and if the score increased, decreased or remained unchanged after the update).
Use cases:
Quickly pull all reviews for a new app version to check launch quality.
Focus on specific devices that are generating a lot of complaints.
Review feedback from a single country before a go to market push.
6) Reviews 2.0 - Filter reviews with no text
Filter down to reviews with no written comment so you can treat them differently, usually based on rating alone.
Use cases:
Set up simple automations that thank users for high star ratings with no text.
Identify low star reviews with no text and prioritize follow up prompts.
Keep reporting clean by separating text rich feedback from quick star taps.
7) Reviews 2.0 - Astra for reviews insights
Use Astra on top of all your review data and app versions to generate structured, ready to share insights. Ask prompts to pull out bugs, main positives and negatives, feature requests, pricing feedback, evidence, and clear recommendations.
Use cases:
Produce a daily, weekly or monthly “state of the app” summary for product and CX.
Turn thousands of reviews into a short list of prioritized fixes and roadmap ideas.
Track how themes like bugs, pricing, or feature requests evolve over time without manual tagging.
8) Set up alerts for updated reviews
Get notified when a customer edits an existing review and the rating changes, across Google, Trustpilot, Apple App Store, and Google Play. Create an alert workflow that filters for “review updated status” (score increased, unchanged, or decreased), then choose whether alerts fire based on volume, % spike vs. normal patterns, or in real time so your team can react to sentiment shifts the moment they happen.
Use cases:
Respond faster when a rating drops so negative changes do not quietly drag down your averages.
Validate support impact by tracking score increases after a ticket is resolved.
Catch unusual spikes in edited reviews after a launch, policy change, or social moment, and route them to the right inbox fast.
Filter by replies sent automatically
Quickly see which conversations were handled by automations. A new filter lets you isolate messages where a reply was sent automatically so you can review performance, fine tune prompts, or follow up with a human touch when needed.
Use cases:
Audit automated replies to ensure tone, accuracy, and brand safety.
Identify conversations that still need a human follow up after an automatic reply.
Measure how much workload is being handled automatically across channels.
View Instagram and TikTok videos directly from comment, reply, and post modals
Preview videos straight from the comment listing, reply modal, or post modal without jumping to a separate tab. This gives your team full context on what the viewer saw before they commented, which leads to more accurate and on tone replies.
Use cases:
Understand the post fult context before replying
Quickly review creative when handling complaints or confusion
Reply length and name personalization controls
Set character limits per platform for public, earned, and private conversations and choose when to include the user name. This gives you guardrails so replies stay concise, on brand, and adapted to each channel format.
Use cases:
Keep app store and TikTok replies short and scannable while allowing longer answers in DMs.
Enforce brand voice guidelines like "keep replies under 250 characters" without manual policing.
Control when to use the customer name for a more personal tone.
Editable pre-drafted replies in batch approval and the reply modal
Speed through batch approvals without losing control over messaging. You can now tweak individual Agent+ generated replies on the fly while using batch approval so teams stay fast and still polish important messages.
Use cases:
Approve a wave of similar replies while editing a few sensitive ones in the same flow.
Clean up tone or add extra context to selected replies without switching back to single view.
Run high volume campaigns while keeping brand voice consistent and high quality.
Agent+ reporting totals for approve, edit, and reject
Agent+ reports now show not just percentages but also total numbers for approved, edited, and rejected replies. This gives you a clearer picture of how much your team relies on assistance and where tweaks are needed.
Use cases:
Track adoption of Agent+ over time and prove time savings to leadership.
See if a specific workflow produces too many edits or rejects and refine prompts or knowledge.
Compare teams or markets on how they use assisted replies to identify coaching needs.
Astra highlights in report emails
Weekly and monthly report emails now include Astra highlights that summarize key work and insights. Get a readable digest of what happened, what changed, and what needs attention without logging in.
Use cases:
Keep busy stakeholders informed with a simple summary in their inbox.
Quickly spot emerging issues or wins from the latest period and decide what to investigate in the platform.
Use highlights as talking points for recurring performance or planning meetings.
Send alerts to Slack or Microsoft Teams
Route BrandBastion alerts straight into your Slack or Microsoft Teams channels using external emails in the alerts configuration. Important issues and spikes show up where your team already lives so they can act faster.
Use cases:
Send crisis or sentiment spike alerts into a dedicated incidents channel for rapid coordination.
Notify product or tech channels when app bugs or feature requests surge in reviews.
Keep regional teams in the loop by routing only their market specific alerts into their workspace.
Learn how to configure:
AI replies for DMs with broader thread context
DM replies now consider up to 20 previous messages in a conversation so responses stay aligned with the full exchange, not just the latest line. This solves cases where the last message is something brief like “Thanks.” but the real question was sent earlier. Replies feel more natural, complete, and consistent with what the user actually asked.
Use cases:
• Answer the real question even when the latest message is just a closing remark
• Keep multi-message conversations coherent and on topic
• Reduce repetitive or out-of-place replies by using full thread history
Choose the final visibility when approving a drafted reply on a hidden comment
When a reply workflow generates a pending drafted reply on a hidden comment, agents can now decide what happens to the original comment at the moment they approve and send the reply. In the approval card, you can pick Unhide → Reply → Hide again (default) or Unhide → Reply, so you can reply fast while keeping the right end-state for each case. Available only on networks that support hide and unhide.
Use cases: ..
Reply to a complaint, but keep the original comment hidden after you respond, so the thread stays clean while the customer still gets help.
Handle edge cases where you need to briefly unhide to post the reply, without accidentally leaving sensitive comments visible afterward.
