Unlock insights, sentiment, and trends from Instagram comments in Enterpret

Instagram comments are where your loudest fans, quietest critics, and the best ideas from loyal customers show up. With Enterpret’s new Instagram integration, you can finally tap into that unfiltered feedback—right from your company’s posts. No more endless scrolling. No more missed signals.

Now, Instagram joins the rest of your customer feedback channels inside Enterpret, giving you the full picture, all in one place.

Here’s what’s new:

• Full visibility: into every Instagram post, comments and nested replies included
• One place for everything: Instagram data sits alongside feedback from every other source
• Smarter sentiment tracking: Spot trends, surface product feedback, and see what’s really resonating—in real time

Whether you’re launching a product, running a campaign, or just want to know what’s landing—Instagram feedback is no longer out of reach, it’s part of the Voice of Customer with Enterpret.

Got questions about the Enterpret Instagram Integration? Check out our Help Center article.

Use Wisdom to automatically generate Stacked Bar Charts

Our latest Wisdom enhancement allows you to generate Stacked Bar Charts with a prompt.

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Here are some of our favorite use cases and prompts:

• Prompt to see what's driving churn (and where) : “For the last 12 months, what are the common reasons by device? Stack by device type.”
  • Why it’s great: Break down exit survey responses by platform (iOS, Android, Web) to spot device-specific issues fast. Maybe Android users are stuck on slow load times, while iOS users are rage-tapping through bad navigation. Now you’ll know.
• Prompt to see customer's top requests: “What are the common keywords mentioning ‘improvement’? Stack by user sentiment.”
  • Why it’s great: Pinpoint which features need love—and whether that feedback is coming from power users, new users, or frustrated ones. Prioritize your roadmap with confidence.‍
• Prompt to track a recent launch: “How are users talking about the new checkout flow by sentiment and usage segment? Stack by version."
  • Why it’s great: Monitor launch reactions in real time, filtered by version and customer type. You’ll see what’s working—and what needs a quick fix.‍
• Prompt to identify support themes that need proactive fixes : “What issues are repeatedly flagged in support tickets this month? Group by tag and volume.”
  • Why it’s great: Surface recurring problems—bugs, confusing UX, or workflow blockers—so your team can fix them at the root.

Other highlights from March

• Dynamic Custom Filters: Custom Filters are now live entities—update once, and changes are reflected in every Dashboard, Quantify, and Feed when it's updated.
• Feedback on Enterpret Reports: Anyone can now leave feedback directly on email and Slack reports so we know how our team can help make these reports more valuable.
• Exclude Current Period: Exclude the current day, week, or month from your views for faster way to cleaner, more accurate insights across Quantify, Dashboards, and Feeds.
• Auto-Generated Filter Descriptions: Let Enterpret do the writing. Custom Filter descriptions now generate automatically for less busywork.

Measure the impact of NPS on feedback for more informed decisions

The latest Quantify update allows you to measure the impact of NPS across feedback records. Select your desired field and NPS criteria, and we’ll calculate the NPS Impact for you. Measure the impact of NPS on feedback to gain a clearer understanding of how specific factors influence customer sentiment and decision-making.

Note: NPS Impact is determined by subtracting the NPS of records without the field from the NPS of all records.

Measure the impact of CSAT on feedback for smarter decisions

Building on our ability to measure NPS impact, we've introduced the same functionality for CSAT. CSAT Impact helps you quantify how specific factors influence CSAT by comparing scores with and without feedback.

Group by for Stacked Bar Charts

Now, visualize data across two fields in Stacked Bar Charts to uncover trends across customer types, regions, and company segments. Some popular use cases for Stacked Bar Charts include:

• Which version is contributing to a spike in feedback?
• Issues by region
• Are Free vs. Enterprise users experiencing different issues?
• Feature requests by segment (e.g., Free vs. Enterprise)
• Measure sentiment across different cohorts

Dashboard Media Widgets for more storytelling options

You can now add videos and images to your dashboards to tell a more compelling story or highlight key insights.

Supported formats for Dashboard Media Widgets:

• Images: gif, .jpeg, .jpg, .png, .webp
• Videos: Loom, YouTube, Descript

Use media widgets to enhance dashboard storytelling, provide context to trends, and showcase key takeaways more effectively.

Launched Custom Cohorts for more flexible analysis

Segment and analyze customer feedback—without manual tagging or complex queries.

• Effortless Segmentation – Quickly categorize large datasets without manual tagging.
• Flexible Metadata Mapping – Define metadata keys just like in Amplitude & Mixpanel cohorts.
• Enhanced Filtering – Use cohort tags to filter and analyze data more efficiently.
• Saves Time – No need for complex queries—just upload, map, and filter.

Common use cases for Custom Cohorts in Enterpret:

• Win/Loss Analysis
• Churn Risk Analysis
• Beta Tester Feedback
• Feature Adoption Tracking
• VIP Customer Monitoring

SCIM and Data Export to be Self-Serve

SCIM and Data Export is now self-serve via Workspace Settings, offering a more secure and efficient process and better support for enterprise organizations.

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Launched Custom Cohorts for more flexible analysis

Easily segment and analyze customer feedback without the headache of manual tagging or complex queries.

• Effortless Segmentation – Quickly categorize large datasets without manual tagging.
• Flexible Metadata Mapping – Define metadata keys just like in Amplitude & Mixpanel cohorts.
• Enhanced Filtering – Use cohort tags to filter and analyze data more efficiently.
• Saves Time – No need for complex queries—just upload, map, and filter.

Common use cases for Custom Cohorts in Enterpret:

• Win/Loss Analysis
• Churn Risk Analysis
• Beta Tester Feedback
• Feature Adoption Tracking
• VIP Customer Monitoring

Enabled SCIM and Data Export to be Self-Serve

SCIM and Data Export is now fully self-serve via Workspace Settings, ensuring a more secure and efficient process and better support for enterprise organizations

Shipped improvements to Wisdom models

We continue to ship improvements to Wisdom's underlying models. Here's what's new:

• ‍No more empty plans: The new Wisdom models always generates a plan—even when the previous version couldn't. No more dead ends!‍
• Understands quotes in context: Wisdom now recognizes quotes in context—it knows which tool to use and how to frame the question when handling quoted text.‍
• No more streaming: Analysis showed that streaming the first step takes nearly the same time as generating the full plan in 90% of cases. So, we’ve stopped streaming. The result? We can now introduce validators on the generated plan—making it stronger and more reliable.‍

Launched the ability for Wisdom to recognize and apply Custom Filters

‍Previously, Wisdom couldn’t detect or apply Custom Filters mentioned in queries. Now, it can identify and use them—making responses more precise and relevant!

Example: Your team has a cohort of defined users

Note: Custom Filters are user-defined filters. Instead of manually specifying the same filters repeatedly, users can create, save, and reuse these filters for more efficient querying.

Shipped a new Homepage for quicker speed to insights

We've introduced a new homepage experience to help all users get the most valuable insights more quickly. Users will see

• Quick access to the Wisdom prompts
• Create a Dashboard from Templates
• Auto-generated dashboard of your organizations more critical insights along with Charts

Streamlined the Wisdom Experience

Shipped new streamlined buttons for more top prompts and easier to find Wisdom Prompt Library.

Delivered a more intuitive flow for Unified Field creation & management

We shipped a usability improvement to make Unified Fields management more intuitive and reduce context switching. Instead of having to navigate to a separate management page users are now able to directly create and edit Unified Fields from: 

• Integrations page
• Metadata table

Continued improvement to Wisdom response times

We continue to make significant optimization in Wisdom's context retrieval system that has resulted in substantial latency improvements.

• Improved Performance: Significantly faster response times across all percentiles with noticeable speed improvements for complex queries.
• Enhanced Consistency: More predictable performance across different question types, ensuring reliable and steady response times.
• Maintained Quality: Same high-quality responses you expect from Wisdom, with strong context quality preserved and minimal recall impact

Bug Fixes and Improvements

• Streamlined the experience to remove a widget from a Dashboard
• Released an update to the saved artifact searches to be sorted by the most recent
• Unveiled optimizations for Workplace Setting UX
• New UI for main navigation menu

Shipped improvements to our Query models

We’ve made significant enhancements to our Query Models for sharper subquery generation, smarter keyword handling, and better performance.

• Sharper Subquery Generation:  No more filtering on generic terms or organization names—say goodbye to irrelevant results like “Feedback from customers” or “Feedback from users.”
• Smarter Keyword Handling: The new model handles specifics more effectively. Example: “What is the total number of support tickets in the last year?” The new model is capbabe of zeroing in on the specificity of support tickets and timeframe.‍
• Query Performance Boost: Enjoy a 2% gain in accuracy without any compromise on overall performance.

Launched Taxonomy Estimator for improved Label processing

We’re excited to roll out our new Taxonomy Estimator for label processing! Previously, whenever a label was edited, merged, or newly created, we reprocessed and re-tagged feedback records based on updated information within an hour (though we occasionally missed this target).

Now, with our latest update:

• Accurate Time Estimates: The Taxonomy Estimator provides iterative time estimates for label processing, giving you a more accurate idea of when your updates will be completed.
• Improved Reliability: If label processing gets stuck or fails, the system automatically restarts to ensure smoother and more reliable operations.

This update sets realistic expectations and reduces frustrations around label processing delays, ultimately enhancing user experience.

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