How Sales Teams Decide Which Accounts to Prioritize Amid Data Overload and Gut Instincts | RevGenius

How Sales Teams Decide Which Accounts to Prioritize Amid Data Overload and Gut Instincts | RevGenius

Pat H.
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As in how do I as a RevOps leader handle resource planning?
Peter P.
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Hey, thanks Pat H. -- less about resourcing. More about helping the team decide "who do I focus on this week". Of everything in the pipe for sales or in the book for success teams, which accounts are actually worth someone spending time on right now? Could be a chance to close them, signs they're ready to expand, or signs they're about to leave. Of all the signals your teams get, how do you then help them act on them?
elicamner
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The way I've seen this play out: it's almost never a signal gap, it's a synthesis gap. Most teams already capture more than enough (scores, intent, activity, stage). What's missing is the last mile that turns all of it into "here are the 3 accounts you touch this week and why." That synthesis still lives in your best rep's gut or your best manager's read, which means it doesn't scale and it walks out the door when they leave. The teams that handle it well usually aren't winning on tooling, they're winning on ritual. A standing weekly decision where the signals get forced into explicit calls: push this, kill this, work this, with the reasoning attached. The Clay table or saved view feeds the ritual, it doesn't replace it. The ones still guessing on Monday usually have great dashboards and no forcing function. Curious whether you're seeing the gap more on the sales side or the CS book, because "about to expand" and "about to churn" are really different signals and most teams treat them the same.
Shafali K.
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My two cents As an SDR, I devise a framework that evolves with based on what messaging. lead magnets and value are driving traction. Usually after that the GTM motion is more reps on that framework (Example: less salesy and more curosity driven messaging, deliver value first without asking for anything) Then a thoughtful weighted formula based on buying intent, offer urgency and market timing, can help predict which accounts that are engaging enough are worth the time Again, enterprise deals, probably need in person visits too But it is possible to spin a quick and dirty algorithm to predict the accounts that must be chased The GTM motion is where the thought must be invested
Sujoy C.
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This is a really interesting observation. When you are working solo / small team, it is easy to go off-track. AI can show you the top three priorities every week, but it needs to have full access to your CRM + Gmail and requires high data hygiene, which can be hard for small companies / solo founders
Akshayata S.
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Peter P. two things that I used, when supporting sales teams in enterprises and now my own consulting practice.
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Capture the signals - not just those coming from Clay or Linkedin Insights or 6sense etc, but also your own "tribal knowledge" - being in the field gives you a gut. I combine these into a simple spreadsheet or tableau dashboard depending on available resources. Then look at it everyday
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Building a mental model of why something sold, then adding that to the above set of signals after every win.
It is possible to automate this "gut" stuff, AI or otherwise it does need the right kind of human-in-the loop approach. And it needs discipline and a regular cadence. I think it is observable - to a great extent, just not 100% coz you know - life.
Peter P.
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Thanks everyone for your comments. Wish there was an easier way to reply inline to each of you, but... Slack.
Peter P.
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elicamner thank you. "Synthesis gap not signal gap" is where we come down on this, too. To your question re: sales and success -- we live both sides, but there are very different appetites from the two teams. And of course (I hate to say it, but I have to) it depends on a lot of org setups and incentives. CS teams would love to have that synthesized signal to help them do the more proactive thing CS-LinkedIn loves to talk up. But they're either not incentivized to work that way or they don't have the budget to get the signals they want/need. On recent calls with CS teams I heard "I learn about our customer health through osmosis" and "I usually have about 15 tabs open before a customer call". Not many people have faith in the NPS, CSAT, scores as predictors. Sales teams are usually more incentivized to find the the signals that move the needle on deals, so this and Growth teams are where I'm getting more interest lately. Anyway, you're right. "About to expand" and "about to churn" have different signals, so we're trying to give both teams the ability to decide how those signals are setup. Your point about the rituals matches what we see. Signals feed the ritual. And signals teams trust make the rituals a lot more effective. When you've seen the weekly decision meeting work well, who runs it -- the manager, RevOps, reps themselves?
Peter P.
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Thanks, Shafali K.. You mention a quick and dirty algo. Do you have one that you built yourself or is it more at a team level? And curious data goes into it. This is a really interesting bit to me: I was speaking with a rev leader a few months ago. His team built this amazing spreadsheet they all worked from, but it was getting too hard to manage and the guy who originally wrote most of it was leaving. This leader was asking which parts of the formulas were actually useful versus which bits were just decoration.
Peter P.
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Sujoy C. totally agree. I run a lot through CLI with Claude or Codex now -- pulling from multiple APIs/MCPs including GMail, CRM, Slack, call recordings, our own product, etc. Data hygiene is super critical, which is hard enough to maintain. And then there's the sometimes questionable answers the LLM sends back. Do you do this with AI right now? Curious how well it scales.
Peter P.
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Akshayata S. 😆 life indeed. I break routines all the time. Ha. How do you keep the observation loop happening? AI is definitely making it easier to keep the CRM updated (at least there seems to be more comments in the closed lost reason boxes 🤷‍♂️ ), but so much of what can improve our 'algorithms' around this has to come from the humans.
Akshayata S.
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Peter P. I implemented a manager- rep weekly 1-1 checklist. with the option to capture observations in one place (google doc). And I offered the sales manager/ VP to share the document with us so we could provide insights/ AI driven analysis. Not all teams agreed to this. but the ones that did, saw improvements for sure. Then combined thi with our own Gong/ peopleAI and other tool data. Also recommended that this become point of discussion during forecast/ clari capture. Triangulating multiple sources gave us good view of what was happening. And oh, the template for closed won and closed lost - I had already implemented in SFDC long ago. so that definitely helped.