1mind's AI agent sources 80% of its own pipeline, and its CEO says sellers won't exist.
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Amanda Kahlow said on ToplineWas blunt that "I don't think there will be sellers." Separately, she said a customer's AI agent closed a $110,000 events deal end to end, though the agent is not yet taking over most strategic enterprise deals.ListenSales team, hiring & comp
3 sources
She does not think there will be sellers in the future. Listen
She said softening this would be dishonest, and that the best thing for sellers and the market is to be honest about what is coming.
“I don't think there will be sellers.”
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A 1mind customer's superhuman closed a $110,000 events deal end to end, Amanda says. Listen
She said the deal was for an events business and that the agent had the conversations, solutioned, shared booth options and went for the close. She said the buyer knew they had just bought. She also said the agent is not yet taking over most strategic enterprise deals.
“We did have a customer where she closed a hundred and ten thousand dollar deal”
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About 80% of 1mind's own pipeline is sourced by its superhuman, Mindy. Listen
She said they use their own product wherever possible, partly to keep costs down and show that it works. She gave this as a figure from their own operation, with no breakdown of how it was measured.
“like 80 some percent of our pipeline is sourced by Mindy, our superhuman.”
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Kyle Norton said on The Revenue Leadership PodcastAI pre-call research in the dialer, including a nearby-customer name drop, lets Owner's BDRs make 150 to 200 calls a day and reach 20 to 30 decision-makers, roughly 5x their start.ListenPipeline & demand generation
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AI pre-call research in the dialer lets BDRs make 150 to 200 calls a day and talk to 20 to 30 decision-makers, roughly 5x their starting point. Listen
Owner matches each prospect's zip code to the nearest existing customer and loads that into Salesforce, then injects an AI pre-call research window into Salesloft. The window supplies a local name drop and the pain point ranked as most broken in the prospect's current setup. Kyle said the result is probably 5x what BDRs did when they first started, when they were just pressing the button.
“So my BDRs make like 150 to 200 calls a day now, and they talk to 20 to 30 decision-makers. And that is uh like probably 5x what what it was when we first started”
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An e-connect model estimates whether a prospect will pick up the phone, and it led to a 2.3x lift in decision-maker connects. Listen
E-connect is one of several machine learning scores at the top of Owner's funnel, alongside scores for estimated deal size and estimated win rate. Scores feed enrichment and AI pre-call research, which together tell the rep what to say on the call.
“We've got this thing called e-connect now, how what is our estimation of whether or not that person will actually pick up the phone call, which led to like a 2.3x uh lift in decision-maker connects.”
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A fixed cold call structure runs pattern interrupt, credibility, relevance, intrigue, then offer of value, with a local name drop as the opener. Listen
Owner's cold call follows this order, and Kyle said some steps carry personalization drawn from AI research. The pattern interrupt is a local name drop, where the rep says they work with a nearby customer the prospect probably knows. Kyle named the framework PICRIOS as a joke about the Greek goddess of cold calling.
“It's PICRIOS, the Greek goddess of cold calling, so we joke. And so it's pattern interrupt, credibility, relevance, intrigue, offer of value steps.”
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Asad Zaman said on ToplineTemplated SMB AE roles will go to AI first, but without a continual-learning breakthrough AI struggles to match top strategic reps, a 10-year path or more.ListenAI
1 source
AI will struggle to match top strategic reps without a continual-learning breakthrough, so he sees a 10-year path or more. Listen
He says SMB AE roles are tightly templated, so AI can get effective there, while enterprise and strategic selling has little templating and relies on reps' judgment. He is hazy on how quickly AI eats labor budget as complexity rises. If current models keep improving he sees a 10-year journey, possibly faster if a continual-learning breakthrough arrives.
“I think without a breakthrough and continual learning, it is really difficult for me to imagine these AIs are going to be able to compete with the best of that.”
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Cassie Vaughn said on [Un]Churnedmonday.com committed its CSMs to double the time with customers this year and put them on variable pay tied to retention and growth, as more revenue comes from existing customers.ListenRetention & customer success
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monday.com committed its CSMs to spending double the time with customers compared with previous periods, because retention became a top metric for the year. Listen
Cassie Vaughn said monday.com made retention one of its true north metrics for this year and wanted to give it a higher profile during a period of very fast growth, which she said is rare for a company at its stage. She said the team is investing in more human touch in the high-touch segment, especially on-site or hands-on work with customers.
“this year we committed our CSM to spending actually double the amount of time that we have spent with customers in the past.”
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monday.com gave CSMs variable compensation tied to both retention and growth, to align them with account management. Listen
Cassie Vaughn said monday.com changed its compensation model this year so CSMs have variable pay on retention and growth. She said the retention piece is what lets CS organisations prove they influence revenue, and that taking a stake in the game is what that requires. She said it also rewards CSMs who do strong work but do not get to celebrate when a deal closes.
“They have variable compensation on both retention and growth.”
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monday.com's sales team moved to variable comp first, and CS followed, once it became clear more revenue would come from existing customers. Listen
Cassie Vaughn said monday.com historically did not pay variable comp to sellers, because its culture held that the best sellers loved the product most. She said the sales team went first, CS followed as a fast follower, and the shift required buy-in for new funds, operational flows and systems. She said that, especially after crossing the billion-dollar threshold, it became clear the company was going to generate more revenue from existing customers, which made retention a top focus.
“especially crossing the billion dollar threshold for our company, we were going to start generating more revenue from our existing customers”
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Marcy Stoudt said on Revenue BuildersCROs at large companies who wait for governance and IT to hand them an AI strategy are letting smaller competitors take share.ListenLeadership & culture
2 sources
Waiting on IT or governance to lead AI strategy lets smaller competitors take share. Listen
Marcy says her biggest fear for CROs at large companies is that they are waiting for governance and IT teams to produce a solution while smaller competitors move ahead and take share. She treats this as a reason not to wait for a formal program before acting.
“my biggest fear for our CROs at large companies as you're waiting for your governance and your IT team to come out with solution while your smaller competition has just taken share”
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Treating AI as a technology stack decision misses the leadership questions of how to position, win and invest. Listen
Marcy says her first instinct was to ask what AI tech stack to use. Her mentor Edwin pushed back, asking why she was thinking like that, and told her there was no license agreement and to figure it out. She says she then realized the real questions were what the work looks like today, how to position the company, how to win, and how to invest to make that happen.
“But eventually I realized you know i need to hire What does it look like for me today? How do I position myself how do I win and then How do you invest to make that happen”
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From 5 episodes that week, checked against their transcripts.
Most discussed this week: AIStrategy & marketSales process & deals