Great point Sunny S. and one I hadn't considered in my response. Its not just about the opportunity cost of taking revenue generating roles off of their core workstream, but the risk of giving those less well versed in creating and delivering tools/workflow that allow vast scale without any checks and balances to make sure what they are doing doesn't have existential risk associated with what they produce. Beyond GTM motions and the potential for wrong messaging etc, there's also security concerns, compliance concerns, GDPR etc. A proactive but unchecked rep could quickly cause some genuinely dangerous business/legal issues using AI incorrectly.
Igor K.: Apologies, I missed your response. My view is that its a gap in the market which is what we've been building a platform to address. If you're interested, we will be running beta testing soon, but in the meantime, feel free to take a look at how we are thinking about things on our website. Its quite a shift in approach so wont appeal to everyone. www.lucix.io
Welcome to RevGen, Mani ! I'm new here as well. Really enjoying the community and sharing of experiences and knowledge so far. A common one i've ran into with my sales teams over the last 10 years was assuming our champion always had the real budget authority, or was capable of pushing everyone on their side to get a decision made and deal closed. We'd get verbal commitments, pricing negotiations, timeline discussions — all green lights. Then deals would mysteriously stall in "final approvals" that stretched for months. The quiet killer was that we kept optimizing our pitch and process around these champions instead of figuring out who actually controlled the money. Growth looked healthy quarter over quarter until suddenly it wasn't — pipeline was inflated with deals that were never really viable. How are you spotting the difference between someone who thinks they can buy versus someone who actually can? That gap seems to be getting wider.
My experience at TR leading a sales team tasked with 'demonstrate X amount of AI utilization a month across XYZ types' is that most GTM teams are drowning in tool sprawl already — "learn to code AI agents" is something that needs to be considered carefully with a serious opportunity cost lens. What I think is probably a realistic short term path is having a dedicated person with both GTM experience and an AI agent creation skill set to take on that burden, that may be an existing revenue generator with a curious mind and a bit of pre-existing dev experience, or may be a dedicated hire. Otherwise, the big risk is you end up taking resources whose sole function is to generate revenue, typically with relatively short horizons (annual max), and distracting them with something that may significantly reduce their output in the short/midterm. But here's what I've noticed: the teams that understand at least the basics of how these things work make way better decisions about which tools to buy and how to implement them. They ask the right vendor questions, spot the BS demos, and don't get oversold on capabilities. What's your take — are you seeing teams that jumped straight to using AI tools without understanding the fundamentals struggle more with implementation?
Glad It was helpful. Drop me a DM and we can figure something out.
Honestly Dhaval D. — I've rarely seen it solved cleanly. It tends to break down along a few axes: deal size/cycle length, how convenient the stack is for sellers, and trust with specific reps. Best example I can give — the best seller I ever worked with was also the worst at CRM hygiene. He'd been CEO of the company before joining my team in a closing role. Would focus almost all of his energy on 3-5 deals a year while other reps juggled 15+, and close 1-2 big ones that equaled everyone else's 5. Terrible at updating the system. Exceptional at knowing where to spend his time. Was it frustrating? Absolutely. But he understood the reporting pressure I was under (having been CEO himself), so we built our own flow. I did more backend work to consolidate his info because our shared goal was hitting target, and I wanted him focused on what he did best. The bigger lesson for me: accountability becomes organic when reps feel like the process genuinely helps them sell — not just feeds a report. That means a stack that's enjoyable to use, workflows that give value back to the seller, and a culture where the data entry isn't homework. But here's the thing I'd push on — most accountability frameworks optimize for activity tracking. "Did you update the opp? Did you log the call?" The harder question is whether anyone is accountable for actually knowing what's happening inside the buying committee, not just what the champion reports back. That's the gap I see over and over.
Hey Dhaval D. - I'll share my view. My question wouldn't be so much about how to catch quiet deals and more about whether your team actually knows what's happening inside the buying committee when things go dark. Most "quiet" deals aren't really quiet, there's usually active internal debate happening that your champion either can't or won't surface. Over 10 years in RevOps/CRO roles, I'd say 60-70% of our "mysteriously quiet" deals fell into this bucket. Champion thinks they have control but doesn't, or real decision makers are having conversations your contact isn't invited to. The workflow alerts are table stakes, but the harder problem is knowing if you have a true champion and how engaged the actual committee is. That gap between what your contact tells you and what's really happening — that's where deals die quietly. Full disclosure: I'm building something in this space at lucix.io, but curious how many of your quiet deals fit this pattern vs genuine timing issues.
The top performers here share something critical — they're not selling to committees. BuiltWith sells data to individual researchers, Relay to solo operators, Gamma to content creators. Committee-sold SaaS rarely breaks $500K RPE because every additional stakeholder exponentially increases your cost of sale. The math works when you can close with one person who has budget authority and feels personal pain.
The measurement problem you're hitting is usually a symptom of treating trials like leads instead of buying processes. Most teams optimize for engagement metrics because they're measuring individual touchpoints rather than the collective decision that's actually happening. What I've seen work better is mapping backwards from the moment someone converts - not just what they clicked, but what internal conversations were happening, who else got involved, what specific capability convinced them. Then you can design communication that supports that decision architecture rather than just pushing activation. The behavior-driven messaging insight is spot on though. Time pressure assumes they're already convinced they need to buy something, but most trial users are still figuring out if the problem is worth solving at all.
The commitment gap is real, but tracking delivery isn't the root problem. The bigger issue is that most of these "follow-up commitments" are tactical band-aids for deeper misalignment inside the buying committee. When reps promise pricing models or feature demos without understanding if the committee even agrees on evaluation criteria, perfect follow-through still leads nowhere. The question becomes: are your reps making commitments that actually move the decision forward, or just feeding a process that's already stuck?
