Rippit Reviews & Product Details

Rippit allows us to access all of our customer data across multiple platforms, ingest it, and understand it. I've been most impressed with how rich the feature set is and how many configurations are available. I also like that it gives non-technical users a view into how conclusions are made. Worksheets and AI columns allow us to understand how data is filtered and then used to get to answers. We've also had a great experience with our account manager, Brandon, who has gone out of his way to proactively assist us with different Rippit feature sets and use cases. Review collected by and hosted on G2.com.

The feature richness of Rippit means that it can be hard to figure out if something we need to do is included or not. 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.

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.

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.

The Claude Connected App in Rippit is the standout for us. Instead of exporting CSVs or waiting on a dashboard refresh, we can go from a support-data question to an answer directly inside Claude — using Rippit's own discovery tools (list data sources, describe tables and columns) before running anything heavier. That's let us build a small library of repeatable workflows on top of our ticket data: a weighted AutoQA scoring model across our QA classifiers, a bot-vs-human analysis that shows us exactly where our chatbot hands off and why, an escalation-risk scan that flags tickets before they become bigger problems, and a weekly digest that turns raw tickets into a ranked bug list and feature-request list for our product team. Work that used to mean manually combing through tickets is now something we can just run. Review collected by and hosted on G2.com.

Because a lot of the value comes from building custom workflows on top of the connector, there's a real learning curve for someone that is not as AI savvy. Review collected by and hosted on G2.com.

I run customer support operations for two product lines essentially on my own, with a BPO vendor handling front-line volume. Rippit is what makes that math work. The thing I reach for constantly is its ability to take a raw slice of Zendesk tickets and let me actually interrogate it — tag themes, score sentiment, flag reopens, extract the "why" behind a spike — without me hand-reading hundreds of tickets. It reads the full conversation, not just a subject line, so the categorization holds up. What used to be a day of manual tagging is now a worksheet and a few enrichment columns.

It's also become my single window into customer calls. Being able to pull Gong transcripts, summaries, and sentiment through Rippit means I can prep for onboarding and strategy calls, or understand what actually happened on one, without living in yet another tool. Tickets and calls in one place is a big deal when you're a team of one. Review collected by and hosted on G2.com.

Honestly very little. If I'm reaching: there's a real learning curve to building the right worksheet-and-enrichment workflow, and once you see how much it can do you start wanting it wired into everything, which is on me, not the tool. Review collected by and hosted on G2.com.

How quickly it helps create clear, professional content. It saves time by simplifying the process of presenting reports, analysis, and key insights in an engaging format. I especially appreciate its ease of use, AI-powered content generation, and the ability to produce polished results with minimal manual effort, making it easier to communicate findings to stakeholders. Review collected by and hosted on G2.com.

What I may dislikeOne area for improvement is that ticket IDs are sometimes missing or not captured consistently. This can make it more difficult to trace issues, reference specific tickets, and maintain accurate reporting. Review collected by and hosted on G2.com.