What I appreciate most about Rippit is how quickly the platform continues to evolve, especially around AI-powered workflows. The team consistently introduces thoughtful capabilities that solve real operational problems rather than AI for the sake of AI.

One of the biggest benefits has been the ability to analyze conversations at a scale that simply isn't possible through manual QA alone. Features like Ask Rippit, AI-assisted analysis, and now the Claude integration have made it much easier to explore trends, answer operational questions, and identify opportunities without needing to manually review large volumes of conversations.

I've also been impressed by how collaborative the product team is. Customer feedback is clearly reflected in the roadmap, and new features are released quickly, making it feel like the platform is constantly improving alongside our needs. Review collected by and hosted on G2.com.

The area I'd most like to see improved is the administrative experience. Rippit has made incredible progress on its AI capabilities, but some of the foundational administration workflows still feel like they're part of an older generation of the product.

Tasks like configuring users, assigning roles and permissions, and managing workspace access aren't always as intuitive as the newer AI experiences. As we've started adopting newer capabilities like the Claude integration, we've found ourselves relying on these legacy administrative workflows more frequently, which can create friction.

I'd love to see the same level of innovation applied to administration and access management. More flexible role-based permissions, a more modern user management experience, and continued investment in these core workflows would make the overall platform feel much more cohesive. Review collected by and hosted on G2.com.

The Rippit+Claude integration has been a complete game changer for me. Rippit was already way ahead of the curve on AI enriched conversation data, but now I ask Claude a question in plain English and it drives Rippit to pull the data, build a worksheet, tag the conversations, and write up the analysis. That conversational layer over real customer conversations is what sets it apart.

It lets me analyze customer conversations at a depth and scale I couldn't reach before. I recently ran a deep dive into why our Casino ticket rate was climbing and it surfaced the real driver, as well as fixes, in an afternoon. The old way, that's a team of three spending a week, and even then you're only reading a small relative sample. With Rippit and Claude I'm enriching thousands of full transcripts to tag root cause and theme, not guessing from a handful.

Performance holds up at that scale, which matters. And onboarding was a real differentiator: the Rippit team (shoutout to Robby) has been hands-on and actually shipped on our feedback. The honest ROI is that it's replaced work I'd otherwise need a team of analysts and with sql skills for. Review collected by and hosted on G2.com.

The main one is a learning curve. The ceiling is really high, but getting the most out of the Claude-driven analysis means learning how to ask the right questions, and my early sessions were much weaker than what I get now. To their credit, they're actively closing that gap: they're building more out-of-the-box skills, and they've been great about documenting our resources so the outputs come back more predictable. Robby also personally shared a few Claude prompts that helped me a ton. That last part is the caveat, I don't expect them to hand-hold every customer that way, so the more of that guidance that gets baked into the product, the better. It's a young product moving fast and I expect this to keep improving. Review collected by and hosted on G2.com.

One of the biggest upsides of Rippit is that it helps us move away from a classic, checklist-style QA tool and toward real conversation analysis. Rather than simply scoring agents against a fixed rubric on a small sample of tickets, Rippit lets us dig into the substance of every conversation at scale, pulling out root cause, contact reason, resolution quality, and product signal. That shift from “grading agents” to “understanding what’s actually happening in tickets” brings forward insights like avoidable volume, at-risk accounts, and recurring product issues things a traditional QA scorecard would never catch. Review collected by and hosted on G2.com.

One limitation we've run into is that analysis doesn't always run across all tickets — sometimes it only covers a subset, which means we can't always be fully confident the insights reflect the whole picture. For a tool built around understanding what's happening across every conversation, it would be a big improvement if enrichment/analysis could reliably run on the full ticket population every time, rather than sometimes only partial coverage. Review collected by and hosted on G2.com.

What I like best is the depth of Rippit's conversation analytics — and how easily I can get to it through the Claude integration. Instead of hand-scoring a handful of tickets, I ask a question in plain English and Rippit reads the full transcript of every conversation, chat and phone alike, and makes a real judgment on each one. It isn't keyword matching or skimming subject lines; it understands what actually happened in the conversation.

The example that sold me: I needed to catch escalations brewing across thousands of support conversations. Rippit tagged every single one for severity and whether the issue got resolved, then surfaced the critical, unresolved cases — including a phone call whose subject line gave nothing away but whose transcript was clearly urgent. A tag- or subject-based system would have missed it, and finding it by hand at that volume just isn't possible. Review collected by and hosted on G2.com.

Most of my friction is with the worksheet and filtering experience rather than the analytics themselves. The one that trips me up most is that filters are type-sensitive in a way that isn't obvious — if a column is stored as a number, the default text "contains" filter silently returns nothing, so it looks like a record is missing when it's actually right there. You only find out after some trial and error. Smarter filter defaults, or a warning when a filter can't match a column's type, would save a lot of head-scratching.

My bigger ask is around the reliability of saved and recurring work. I've had a scheduled job quietly return empty results — and cheerfully report "all clear" — because the underlying table and columns it referenced had changed, so it was silently filtering everything out. Since worksheets and columns are keyed by opaque IDs, that kind of drift is hard to catch until you go looking. I'd love clearer signals when a saved workflow's references go stale, plus a guardrail so a run that returns nothing isn't treated as good news. Review collected by and hosted on G2.com.

Rippit has been a game changer for me! I consider the team to be a part of CX as they've been an integral part of my journey since implementation a few months back. Using the tool is very straightforward and consistently a seamless experience whether I'm building monthly reports to identify key themes or friction points in Zendesk/Pylon integrations, developing the coaching program for frontline support, or using Claude to quickly analyze and/or test new skills. AskRippit is my favorite feature and let's be honest who can resist the fun frog mascots? 100% worth every penny. Let it rip! Review collected by and hosted on G2.com.

This is a tough one as there's not much I dislike about Rippit. Initially, it was hard to gain buy in for an organization who did not have a quality program prior. This has since been resolved with the rollout of the Claude connector. One update that would be beneficial is having a monthly/quarterly cadence to meet with the head of an organization to ensure the strategy remains in alignment. Review collected by and hosted on G2.com.

Rippit has become much more than a QA tool for us. The automated evaluations are great, but the biggest value is being able to quickly identify trends, understand why customers are contacting us, and perform risk analysis at scale. The AI-generated transcripts and summaries make it easy to find patterns and pull insights that would have taken much longer to identify manually. Review collected by and hosted on G2.com.

Sometimes the AI reports aren't fully accurate. I've noticed occasional issues with date ranges, and when analyzing large worksheets, the insights are often based on only a sample of tickets instead of the full dataset. It would be great if large datasets were analyzed more comprehensively by default. Review collected by and hosted on G2.com.

I appreciate Rippit's ability to transform complex data into clear, actionable insights in an efficient way. The flexibility to create customized worksheets and leverage AI-powered columns allows us to tailor analysis to our specific needs and quickly identify the most relevant information. I also value how Rippit empowers our teams to go beyond manual reporting, enabling us to spend more time on analyzing trends and customer insights rather than just compiling data. The initial setup was relatively easy, and while there was a learning curve, it became intuitive as we got familiar with its features. Overall, the more we use Rippit, the more value we get out of it. Review collected by and hosted on G2.com.

Overall, my experience with Rippit has been very positive. One area that could be improved is the accuracy of AI when interpreting dates. Occasionally, I notice that the AI associates a date mentioned in the notes with the analysis, even when it doesn't match the actual ticket creation date or the relevant event. Improving the contextual understanding of dates would make the analysis even more accurate and reliable. Review collected by and hosted on G2.com.

Ask Rippit and the AI columns you can create in worksheets is a great help in gathering voice of customer data quickly. I believe it is worth the price, it's become an extremely valuable tool for us. I believe it is worth the price, it's become an extremely valuable tool for us. I believe it is worth the price, it's become an extremely valuable tool for us. I believe it is worth the price, it's become an extremely valuable tool for us. I believe it is worth the price, it's become an extremely valuable tool for us. Review collected by and hosted on G2.com.

The UI is a little clunky, when trying to show it to new people I've often had to go over the same ground multiple times to get them to understand. When I have an issue doing something, Rippit often doesn't provide good feedback on how to correct it. Review collected by and hosted on G2.com.

Rippit does a great job of giving folks a headstart on various aspects of their interactions with customers. We use it both for QA and for general classification of customer sentiment and reaction. It's been fantastic at helping us understand what's really going on. I believe it is very much worth the price. Review collected by and hosted on G2.com.

It's currently a product in transition from one version of itself to another, and as such, there are some growing pains. It can be difficult to navigate the UI from time to time as well, but it's clear they are prioritizing improvements. Review collected by and hosted on G2.com.

I like Rippit for its deep dive analysis capability, which lets us thoroughly examine entire sets of conversations and gain more than just surface-level insights. This feature helps us spot trends sooner rather than waiting for a problem to arise. I also appreciate being able to set up specific worksheets and workbooks for various teams, which are great for identifying individual agent strengths, product issues, and escalations. The deep dive analysis and the ability to create customized reports are standout features for me. Additionally, the support was great in helping us get set up. Review collected by and hosted on G2.com.

I think the user interface could be a little bit more user-friendly. It can take multiple clicks to get to the place that you want to be. Additionally, some work items can only be handled by Rippit support staff, which means that you're waiting for a response to be able to complete certain actions. For example, adding additional columns to your workbook currently requires the Rippit support team to do it for you, and that can hinder your ability to run analysis until they've completed their work on their end. Review collected by and hosted on G2.com.