# RevOps Sherpas — llms-full.txt > Full text of every public RevOps Sherpas page. The Gong partner mid-market revenue teams trust: structured implementations, historical call migrations, bi-directional CRM integrations, and telephony integrations. This file is intended for AI answer engines (ChatGPT, Claude, Perplexity, Gemini, Apple Intelligence) and other LLM-based crawlers that want the content of the site without rendering JavaScript. The canonical short index is at /llms.txt. Organization: RevOps Sherpas (https://revopsherpas.com) Founder: Andrew O'Driscoll (https://www.linkedin.com/in/aodriscoll/) LinkedIn: https://www.linkedin.com/company/revops-sherpas/ Contact: info@revopsherpas.com --- # Home — / RevOps Sherpas is the Gong partner mid-market revenue teams trust. We combine RevOps expertise with the engineering depth required to handle real-world Gong deployments — structured implementations, historical call migrations, CRM integrations for systems Gong doesn't natively support, and telephony integrations that stream live calls into Gong without rip-and-replace. We work with mid-market RevOps leaders, CROs, and Gong Account Executives on four service lines: Implementation, Call Migration, CRM Connect, and Telephony Connect. Two of our CRM Connect integrations (Zoho and Pipedrive) are listed on the Gong Collective marketplace. Our SugarAI connector is listed on the SugarAI Marketplace. --- # Gong Implementation — /implementation Structured Gong deployments built for mid-market RevOps teams. Four packaged tiers — Quickstart, Upgrade, Plus, and Professional — covering everything from kickoff and configuration to user provisioning, call routing, scorecards, trackers, deal workflows, forecasting, and adoption enablement. A Gong implementation isn't a one-time configuration project. Go-live is the trailhead, not the summit — value compounds (or decays) based on the operating work that follows: tracker hygiene, deal workflow tuning, scorecard iteration, forecast calibration, and rep coaching cadence. Our packages are designed to deliver a clean go-live AND set up the operating cadence that keeps the platform delivering. Packages: - Quickstart — fast deployment for teams under 50 reps, standard configuration. - Upgrade — for existing Gong customers needing to modernize trackers, scorecards, and deal workflows. - Plus — full deployment with forecasting, deal workflows, and custom integrations. - Professional — enterprise-grade rollout with multi-region, multi-business-unit configuration. --- # Call Migration — /call-migration Production-grade migration of historical calls and meeting recordings into Gong, fully attributed to users, contacts, and CRM records. Engineered pipeline with profiling, test migrations, validation, and post-load reconciliation. Supported source platforms include: Apollo, Attention, Avoma, Chorus, Circleback, Clari, Fathom, Fellow, Fireflies, Gong-to-Gong, Jiminny, Kaia, Loom, Mediafly, Modjo, Novacy, Rewatch, Salesloft, Sybill, tl;dv, UpdateAI, and Zoom. Why this matters: every call that doesn't make it into Gong is a gap in Gong's AI account briefs, deal warnings, win-loss analysis, and coaching coverage. A clean historical migration restores the time-series Gong needs to reason about your pipeline and reps. --- # CRM Connect — /crm-connect Bi-directional integration between Gong and the CRMs Gong doesn't natively support. Restores the pipeline view, AI account and deal briefs, deal warnings, forecast signals, and win-loss analysis that depend on CRM objects. Supported CRMs: Zoho CRM, Pipedrive, SugarAI (formerly SugarCRM), NetSuite, ConnectWise, and custom CRMs. Zoho and Pipedrive integrations are listed on the Gong Collective marketplace. Pricing starts at a $5,000 annual minimum. --- # CRM Connect for Zoho CRM — /crm-connect/zoho Bi-directional, fully managed integration between Gong and Zoho CRM. Sync accounts, contacts, leads, and deals from Zoho into Gong so Gong can attribute every call, generate AI account briefs, surface deal warnings, and run win-loss analysis on Zoho-native pipeline. Gong call summaries and outcomes are written back to the matching Zoho records. Built by RevOps Sherpas, designed for Zoho One and Zoho CRM customers who run on Gong. Pricing starts at a $5,000 annual minimum. --- # CRM Connect for SugarAI — /crm-connect/sugarai Bi-directional, fully managed integration between Gong and SugarAI (formerly SugarCRM). Listed on the SugarAI Marketplace. Sync SugarAI accounts, contacts, leads, and opportunities into Gong; write Gong call summaries and outcomes back into SugarAI. Pricing starts at a $5,000 annual minimum. --- # Telephony Connect — /telephony-connect Stream live calls from phone systems Gong doesn't natively support into Gong, with reliable recording delivery, participant and CRM mapping, speaker separation, and active monitoring. No rip-and-replace of the underlying telephony required. Supported telephony platforms: Elevate (UC + CC), Intermedia, Talkdesk (non-Salesforce), Twilio Voice (not Flex), VICIdial, and Zoom Contact Center. --- # Contact — /contact Talk to a RevOps specialist about your Gong deployment, migration, or CRM integration. Email info@revopsherpas.com or book a call from the Contact page. --- # Field Notes (Blog) — /blog Operator-grade frameworks, blueprints, and field reports for Gong-powered RevOps teams. --- ## Asking isn't just faster than searching. It's better. URL: https://revopsherpas.com/blog/asking-isnt-just-faster-than-searching Category: Field Notes Author: Andrew O'Driscoll — https://www.linkedin.com/in/aodriscoll/ Published: 2026-05-18 Read time: 7 min Retrieval used to eat the consulting hour. When asking replaces searching, the reasoning gets the time it deserves — and the first hour of a Gong engagement changes shape. Asking is faster than searching. The interesting part is what that does to the work. Most people working with data today would rather type a sentence than open a dashboard. That shift has happened almost everywhere at once, and it's now the default expectation. What's worth paying attention to isn't the speed gain. It's how the work itself moves when retrieval stops being the bottleneck. We learned this building for ourselves, on our own engagements. We walk into a customer's Gong instance and we're expected to form a real point of view in the first hour. Not a polite read. An actual diagnosis: what's working, what isn't, where the leverage is, and what we should do first. That's the job. ## The data is there. It's just scattered. A Gong instance is not one data source. It's many, each good at a different kind of question, and any honest read of one usually requires another. **The Gong UI** is excellent for the questions Gong has already decided are important. Call activity by rep, coaching scorecards, deal warnings, account briefs. If your question matches a screen Gong built, you're done in a click. If it doesn't, you're stuck. **CSV exports** cover the next layer. They give you what the UI shows, plus more, in a format you can pivot. The cost is that you're working with a snapshot and you have to stitch exports together yourself. Two exports from two different screens don't always share keys cleanly. **The Gong API** opens up the things the UI doesn't surface at all. Call metadata at scale, user-level activity, integration health, raw participant lists. It's the right tool when you need precision or volume, and the wrong tool when you want to look at something quickly. **Gong Data Cloud** is the warehouse-grade option for customers who have it. Full historical data, SQL access, joinable to everything else in your stack. It's the most powerful and the highest friction, and not every customer has it turned on. That's just the starting set. There are other sources we pull from too — the shape of the problem varies by customer. What stays constant is that the question a customer actually cares about almost never lives in one place. Recording coverage is breaking down in the West region is a UI question that becomes an API question the moment you ask why. License utilization is low is a CSV question until you want to know which licenses, on which teams, doing which kind of calls — at which point you're across most of them. ## Most of the consulting hour used to go to retrieval. If you're a Gong-literate consultant walking into a new instance, the bottleneck isn't analysis. It's reconciliation. You pull the call activity export, you pull the user license list, you query the API for recording status, and then you sit with all of it in a spreadsheet and try to figure out what the views together actually say. The reasoning part — the part the customer is paying for — happens last and gets the least time. Retrieval and collation ate the day. Gong Lens changed that. ## What we built, and why We built an internal application called Gong Lens. It pulls together the data sets we were constantly cross-referencing into one view — recording health, feature adoption, license utilization, talk patterns, coaching activity, integration status — and lets us ask questions across all of it in plain English. Lens has two layers, and the distinction matters. The first layer is the familiar one. Dashboards for each data set, sortable, filterable, drillable. This is where we go when we want to see the shape of something. License utilization across a 200-seat instance has a shape. Coaching activity across managers has a shape. A dashboard shows you the shape; a sentence doesn't. ![Gong Lens — License Utilization dashboard](/blog/gong-lens-license-utilization.png) *Layer one: a dashboard for license utilization. Useful when you want to see the shape of something.* The second layer is an AI advisor that sits on top of all of the data sets and inside each one. We can ask scoped questions of a single data set or broad questions that cut across all of them. The dashboards are for the things we want to see at a glance. The advisor is for the questions we don't have a pre-built view for. That's most of the interesting questions. ![Gong Lens — AI advisor answering "Summarize org health"](/blog/gong-lens-ai-prompt.png) *Layer two: the advisor answering a broad question across every data set.* ## The kind of thing we can now answer in a sentence A flavor of what the first hour of an engagement looks like now: ![Gong Lens — suggested first-hour questions](/blog/gong-lens-questions.png) *A handful of the questions we reach for at the start of an engagement.* > "Which reps are hosting more than 50 calls a month but self-reviewing fewer than 5% of them?" This used to require pulling a call activity export, pulling a self-review export, joining on user ID, and filtering. Now it takes a sentence. The answer is usually a list of five to ten people, and the list is the conversation we want to have with the customer. > "Where is recording coverage breaking down, and are those misses controllable or not?" Controllable means a configuration problem we can fix. Not controllable means a user behavior problem or a telephony edge case. Knowing the split before the kickoff changes what we recommend. > "Of the seats this customer is paying for, how many are barely active?" And then the follow-up: *"Which teams are those inactive seats sitting in?"* The first is a commercial question dressed as an adoption question. The second tells the RevOps leader whether the next Gong renewal conversation should be about expansion, rightsizing, or a targeted enablement push in one specific team. > "Which managers haven't coached a rep this month?" Coaching is the part of Gong that most often goes dark first, and it goes dark quietly. A single answer to that question, on day one, reframes the entire engagement. You stop talking about features and start talking about behavior. None of these are exotic. They're the questions a good consultant has always wanted to answer in the first hour. They used to take real time. Now they take a sentence, and the time goes to what to do about the answer. ## Where this is going Lens is internal for now. We use it on our own engagements. We may commercialize it eventually — there's clearly demand for the shape of the thing, because every Gong customer we talk to has some version of the same fragmented-data problem. Gong might cover this ground too. Their AI investment so far has been on the conversation side: the spoken word, the email, the deal. That's the right place for them to be focused. Whether they extend that capability to the usage and adoption layer is their call, on their timeline. In the meantime, we needed it now, and necessity is a good reason to build. The bigger point isn't about our tool. It's that the data has been sitting in your Gong instance the whole time. The interesting question was always what to ask of it. For most of the last few years, the answer was "whatever was cheap enough to retrieve." That constraint is gone now, and the work that was already worth doing is suddenly worth doing first. If you want help getting your Gong instance to that level of usefulness, [book a call](/contact). --- ## Go-Live Isn't the Summit. It's the Trailhead. URL: https://revopsherpas.com/blog/go-live-isnt-the-summit Category: Field Notes Author: Andrew O'Driscoll — https://www.linkedin.com/in/aodriscoll/ Published: 2026-05-15 Read time: 5 min Most companies plant a flag at Gong go-live and call it the summit. Six months later the insights aren't sticking, reps haven't changed how they sell, and the configuration reflects who you were — not who you've become. Gong is one of the best investments a revenue team can make. The data is there. The insights are there. The visibility into what's actually happening inside your deals is all sitting in the platform, waiting to be put to work. The problem isn't the tool. It's what happens after the rollout. Most companies plant a flag at go-live and call it the summit. The implementation wraps, the kickoff email goes out, the box gets checked, and everyone moves on to the next initiative. Six months later the picture looks very different. The insights aren't sticking. Reps haven't changed how they sell. The business has evolved, and the configuration hasn't. Gong is still reflecting who you were when you bought it, not who you've become. That gap is where revenue leaks. Quietly, persistently, and in amounts most leaders would be uncomfortable putting a number to. ## Your business is moving. So is the product. Here's the part that doesn't get talked about enough. Gong itself doesn't stand still. The product team ships at a pace most enterprise platforms can't match, and the last twelve months are a useful case in point. At Celebrate in October 2025, Gong introduced Gong Orchestrate and positioned the platform as a Revenue AI Operating System designed to unify go-to-market workloads across the entire revenue organization. In February 2026, Mission Andromeda landed with another wave, headlined by Gong Enable, a standalone product with its own pricing tier that includes AI Call Reviewer for automated call grading against your own methodology. The same release expanded AI Ask Anything to query across your entire customer base, and introduced AI Deep Researcher for multi-step analysis on complex revenue questions. Underneath all of it, Model Context Protocol support now lets Gong exchange data and context with Microsoft Dynamics 365, Microsoft 365 Copilot, Salesforce Agentforce, and HubSpot CRM. That is in addition to ongoing investment in Deal Likelihood Scores, Call Spotlight, and the underlying Revenue Graph. If you implemented eighteen months ago and haven't revisited the configuration since, you are sitting on top of a platform that has materially changed. There are features you're paying for that you've never turned on. There are workflows that used to require a manual export and now run automatically. There are AI agents that could be reshaping how your managers coach, how your reps prep, and how your CRO forecasts. None of that value shows up by default. Someone has to evaluate what shipped, decide what fits your motion, configure it for your team, and get reps to actually use it. Most revenue orgs don't have anyone whose job that is. Implementation partners hand off. Internal admins get pulled into ten other priorities. CSMs are helpful but aren't going to architect a quarterly capability review. So the platform keeps evolving, and your adoption of it doesn't. Meanwhile the competitors who do have that function, formal or informal, are pulling ahead on the same tool you both bought. ## The work between the trailhead and the view. This is the work RevOps Sherpas was built for. The gap between how you sold last year and how you sell today. And the gap between what Gong was when you bought it and what Gong is now. We work with customers across the full adoption journey. We keep the configuration aligned to the way your team actually sells. We track what Gong ships, translate it for your specific motion, and turn the insights the platform surfaces into behavior your front line and your board can both feel. Go-live isn't the summit. It's the trailhead. The view you signed up for, the reason you wrote the check, lives on the other side of consistent, deliberate work after the implementation team rolls off. The tool you bought should keep paying you back for as long as you own it, and the value should compound, not decay.