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Failed payment EMR account block - Grace Period
Currently all services and accounts get temp blocked, would be great to have 7-14 days grace period before this happens. Credit cads expire, banks change life happens. An immediate block seems too harsh.
jameda.de = znanylekarz.pl
Please add a German equivalent (same company) for Poland. https://www.jameda.de = https://znanylekarz.pl They differ only in name
MCP Connection is limited to local machine
The MCP connection is currently limited to a local machine on which the config file is configured. Hence, the MCP connection does not work when used on mobile devices app (e.g. Claude iPhone app) or on Claude.ai. The MCP connection when configured and set up, it only shows up as connector listed under the connections list only on the Desktop App where it was configured. This limits not able to use from our mobile devices. Request to consider expanding the MCP setup to be a “web'“ type. PS: Attached are some screenshots of conversation with Claude AI. Thanks, Anil
Wall of Love Enhancement
I would like to request a configurable Wall of Love (WOL) that displays only video submissions. Mixing written and video reviews can be overwhelming, and a dedicated video-focused view would improve clarity. My preferred options are: A filter control to view only video testimonials (e.g., a “Video Only” filter). Alternatively, a standalone “Video Testimonial” feature within the Integrations section. Lastly, could it be possible to rename it from WOL to something less Campy and more broader in reach: Suggested options with rationale: Video Testimonials Wall: instantly communicates the primary content type and preserves “wall” as a recognizable UI metaphor. Video Spotlight: conveys a curated, highlighted set of video reviews, implying quality and focus. Video Reviews Hub: signals a centralized, easily navigable collection of video feedback. Video Moments Gallery: adds a dynamic, human touch by framing entries as moments. Video Feedback Wall: maintains familiarity with “wall” while explicitly calling out video feedback.
"No Search Results" returns as error for end user on Sales Intelligence Form/Page
The attached photo is shown when a user searches for their business and has no results. JSON shows this is a normal search that just found nothing. Can we have the ability to edit this message so end users do not see it and think there is an error? Even the icon / color changing would be a nice touch. Thank you!
Before / After — UI dashboard exploration for Embed My Reviews
Exploring an alternative design direction This document presents a UI exploration intended to spark discussion and gather feedback. EMR already delivers a comprehensive set of features. This idea simply explores whether a different visual hierarchy, information architecture and visual language could make the experience feel calmer, easier to scan and more distinctive. Current experience The current dashboard surfaces a rich amount of information and gives visibility to many aspects of review management from the first screen. This exploration looks at an alternative way of presenting that information by adjusting visual hierarchy and reducing the number of elements competing for the user's attention at any given moment. Proposed direction The concept is organized around a single primary focal point—the overall rating—followed by three sections that reflect a salon owner's natural workflow: Where I stand — overall rating and milestone progress. How I'm collecting reviews — conversion funnel, review pace and AI insights. How I'm performing on Google — listing performance, trends and search visibility. Rather than introducing additional components, the proposal focuses on clarifying hierarchy and making it easier to understand what deserves attention first. The existing gamification experience is still present but expressed through a quieter circular progress indicator, allowing it to support the experience without becoming the dominant visual element. Why explore warm neutral tones? One aspect of this exploration is the use of a warm taupe/off-white background instead of a pure white canvas. I don't know if you've noticed : For exemple Granola (AI Note taker)
Rename Stop Negative Feedback to "Show Private Feedback" or similar
As per title: Can we rename Stop Negative Feedback to "Show Private Feedback" or similar?
Allow PII access scoping on API tokens for DFY use cases
By default the API returns contacts anonymized, with PII (name, email, phone) excluded unless the token holds a specific reviews.pii ability. For a DFY agencies who legitimately manages the client's own contacts, this means they can't match API results back to the real people my client is asking about. I had to fall back on a manual CSV export to identify contacts. Request: make reviews.pii cleanly grantable on white-label/agency tokens (with appropriate consent and audit), so DFY operators can run contact-level verification programmatically without exporting CSVs.
Use the organization name as the default location name
When a new client signs up, they provide their business name, which EMR stores as the organization name. But if they only have one location, that location is saved as "Default location" rather than the business name. Since I can use the MCP to manage clients, this makes locations almost impossible to identify by name. I had to look a client up by organization ID because the location name carried no information. Request: when an organization has a single location, automatically name that location after the business/organization name instead of "Default location." Renaming the org in the UI should ideally propagate to the location too.
Expose the reason for a "Not sent" status via the API
When asking the MCP, "How many people have been asked to review in the last 30 days?", the API returns the outcome of an invite (e.g., added, invited, opened, clicked, redirected, etc.), which is great. However, when a contact shows as "Not sent", the API provides no reason for this status. It would be helpful to include the reason why a contact was not asked (for example, if they were blocked by the 90-day deduplication filter because they had already been contacted three weeks earlier via a reactivation campaign). Currently, this information is only visible in the EMR contact activity timeline, not through the API.
Unsubscribed contacts still show "Sending in 1 hour" — should display "Sending cancelled"
When a contact is unsubscribed from a campaign, the scheduled-send label ("Sending in 1 hour") remains visible. This creates confusion: the contact is clearly marked as Unsubscribed, yet the UI still suggests a message is queued. Where it appears: Contact activity timeline (recent activity popup) Per-contact row in the campaign sending list Mockup idea :
Detect Recently Removed Reviews Without Full-History Scans
I’d like to share a possible approach for developing this feature in a way that does not significantly increase infrastructure costs. From what I can tell, detecting removed reviews would require full scans across the entire review history, because the only way to know whether a review was deleted is to check whether it is still published at the source. I understand that doing this frequently for all reviews, across all accounts, could become very expensive. However, it looks like there may already be a way to detect at least recently removed reviews without any additional full scans. My understanding is that the current sync process seems to fetch recent reviews, rather than re-scanning the full historical dataset every time. I cannot confirm the exact implementation, but I believe it may not only fetch reviews since the last sync, but rather reviews from “some time back”. The reason I say this is because I noticed that some reviews inside EMR were previously marked as responded, but now appear as not responded. After checking the source, I found that those reviews had actually been removed from Google Places / Google Maps. This is a very interesting signal. If a review was previously known by the platform, was previously marked as responded, and later the response is no longer detected during the normal recent-review sync, that may already be enough to infer that the review was likely removed / deleted, without requiring any extra full-history scan. So, at least for recently deleted reviews, this feature may already be technically feasible with little or no additional infrastructure cost. Of course, this method would not be 100% complete. Very old reviews deleted long after they stop appearing in the “recent reviews” sync window would probably not be detected this way. But the key question is: Is it better to have a system that detects recently deleted reviews, even if it is not perfect, or to have no system at all? In my opinion, a partially complete but cost-efficient solution is much better than no solution. A possible implementation could be: Detect reviews that were previously known in the system but are no longer consistently present in the source during normal recent syncs Mark them with a status such as Removed / Deleted Use that status across the product Once that status exists, it would already unlock a lot of value: Filter reviews that were removed / deleted Exclude them from analytics and review counts Exclude them from the “pending response” filter Exclude them from review display widgets Improve accuracy across multiple parts of the platform There could also be an optional complementary layer to improve historical completeness, although this would involve additional infrastructure costs. For example: Add a button to scan the full review history for removed reviews Limit its use to once per month, if triggered manually Or run it automatically once per month, if deemed acceptable from an infrastructure-cost perspective This is not intended as an alternative to the low-cost method described above, but rather as an optional way to improve accuracy if the developer wants this feature to get c
Monthly AI Insights report displays weekly data instead of monthly data
The AI Insights (analysis) and the AI Insights reports are currently linked in an incompatible way. When a monthly AI Insights report is created, the data included in that report still always refers to a weekly period. In other words, the report is sent monthly, but the information shown only covers one week rather than the full month. This makes the report frequency largely irrelevant, except when a weekly frequency is selected, since that is the only case in which it matches the analysis, which is weekly by default. Given this dependency between the AI analysis and the data displayed in the report, I suggest resolving the issue in one of the following ways: Keep the current link, but allow the AI analysis execution frequency to be configured as weekly, biweekly, or monthly. Break this link, allowing the report to generate an AI analysis based on its own frequency. In other words, the report period should match the period of the data shown in the report. Personally, I believe the second option makes more sense. ———————————————————————————-- Formal Bug Report: Steps to Reproduce Go to the AI Insights Reports configuration. Create a new report with the frequency set to Monthly. Wait for the report to be generated and sent. Open the generated report and review the data period covered. Expected Result A report configured with a Monthly frequency should include data covering the full monthly period. Actual Result A report configured with a Monthly frequency is sent monthly, but the data included in the report only covers a weekly period instead of the full month. Additional Notes The AI analysis appears to be tied to a weekly default execution period, and the report inherits that same weekly dataset regardless of the selected report frequency. As a result, the selected report frequency becomes effectively irrelevant unless the report is also configured as Weekly. Suggested Solutions Allow the AI analysis frequency to be configured as Weekly, Biweekly, or Monthly. Decouple the report from the current analysis frequency, so that the report period matches the data period shown in the report. Preferred Solution Decoupling the report from the analysis frequency makes the most sense, so that each report generates data according to its own selected period.
Custom Package Visibility
Hi, I would like to submit feedback regarding Custom Package visibility. Right now, whenever a Sales Agent attempts to add a new account to his/her dashboard, they can see all of the available custom plans - even those that are designated as ‘hidden’. It would be helpful if we could designate certain plans to ONLY sales agents, and other plans to the general public. Secondly, it would also be useful if we could toggle off any client-facing visibility to the billing section. When our agency is fully responsible for managing customer reviews and direct billing, it becomes a challenge for/when they see the available plans (with pricing). Hiding the custom plans only solves half the problem, because now those customers who have signed up directly can no longer see the other plans to upgrade to. https://www.loom.com/share/5dcb9289baea4aac85642747214efe86
Stats for Weekly AI Analysis Reports
When setting up reports to be sent on a weekly basis for AI analysis, the reports seem to reflect the entire GBP history, not specifically the past week. What my clients would be interested in knowing: Summaries of both good and bad reviews from the past week, instead of minor changes from the entire GBP history. Thanks for your consideration.
Feedback on AI review flow
Hi team, First, the AI-generated follow-up questions are excellent. The contextual analysis by sector is very strong and becomes even better with proper briefing. However, I have an issue with the current review flow. When a customer gives a high rating (e.g. 5 stars), the system still allows follow-up answers that include clearly negative wording (e.g. “waiting time was disappointing”). The AI then combines positive and negative feedback and suggests copying this directly into a public Google review. This creates a problem: A satisfied customer can unintentionally publish a mixed or negative review on public platforms. In my view, this is not ideal for two reasons: It distorts the initial high rating (NPS-style inconsistency). It increases the risk of users posting unintended negative public reviews. What I would suggest instead: The AI should detect negative sentiment keywords in follow-up answers. If negative sentiment is detected after a high rating, the flow should switch from “public review generation” to an internal feedback form (private feedback / support loop). Ideally, there should be a final AI “review check” step before anything is sent to Google, to validate consistency between rating and text. In short, the system is very powerful, but it needs a stronger gating logic before publishing public reviews. Happy to discuss if needed. Best regards, Rudy Mence
Localize Rich Snippets Fields for United States
It would be helpful if the address fields in the SEO/Rich Snippets fields were localized to the United States, of whatever country uses very specific address fields. For Example:
Rewording the word "agency" in client dashboard
I understand that the AI Insights feature is designed for agencies to provide as an add-on. However, I hope the word “agency” here can be reworded, as we are using the white-labeled EMR platform, which is introduced under our own brands. Thus, I’m offering the platform as a SaaS product, not an agency service. The word “agency” here may be interpreted as there’s a provider on top of which may not be appropriate in a white-label business model. In my local market, the word “agency” is translated as “reseller”. It should change to “administrator”.
Allow drag & drop reordering of campaign sequence steps
Currently, reordering messages in a campaign sequence requires manually copying and pasting content between each step. Adding “drag & drop” to the message timeline would let users instantly rearrange the sequence while keeping all content, channels, and settings intact.
Contrast Issue: White Background and Font in widget
I set-up the widget with a black background. However, when you try to open a review to read the full testimonial, both the background and the font turn white, making the text impossible to read.