Enterprise deals now close in about 45 days, making enterprise a better bet than mid-market, says Tomasz Tunguz.
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Tomasz Tunguz said on ToplineQuotas at AI-native companies are rising because buyer budgets grew about tenfold, not because reps got 10x more productive, so one AI company's sales discipline won't transfer to another.ListenSales team, hiring & comp
3 sources
AI-native quota inflation reflects budgets that grew about tenfold on the demand side, not reps becoming ten times more productive. Listen
Tunguz said the supply side has not become 10x more productive; demand budgets have increased by a factor of 10, and that is what is driving quotas. He was agreeing with Asad Zaman, who said high AE output at AI companies may reflect demand flying at reps and high close rates from customers experimenting, so the signal has to be read with squinted eyes. Tunguz added that this is a market dynamic, so a sales discipline from one AI company does not transfer to another.
“It's not the supply side has changed and suddenly become 10x more productive. It's the demand side. Budgets have increased by a factor of 10 and that's what's driving quotas.”
Listen to the episode Episode Sales team, hiring & comp Link to this
Quota levels that peaked between 2.5 and 4 at Oracle and IBM five years ago are now routinely around 1.5 at early-stage startups. Listen
Tunguz said Oracle and IBM had the highest quotas in software at roughly 2.5 to 4 five years ago, and that it is now routine to see an early startup at about 1.5. AJ Bruno followed by questioning how buyers or investors can trust distribution forecasts when quota-to-OTE ratios may keep shifting from year to year.
“Oracle and IBM had the highest quotas in software somewhere between two and a half to four. And now it's kind of routine to see an early startup at like one and a half.”
Listen to the episode Episode Sales team, hiring & comp Link to this
AI companies are not as AI-pilled internally as people assume, though some engineering functions look like magic. Listen
Asad Zaman said he works with many of these companies and that they are still figuring out how to use AI in their departments. He said engineering can look like magic, but going to HR or go-to-market shows that it is not that different from other companies. He cautioned against treating AE productivity as proof of internal AI skill, since it may reflect demand and high close rates from experimenting customers.
“I can tell you that they're not as AI pilled internally as you would like to believe.”
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Evan Huck said on ToplineUserEvidence's pipeline sat flat at about 150 opportunities a quarter for eight quarters despite rising brand spend, then hit 450 per quarter within two quarters.ListenPositioning & marketing
2 sources
After eight quarters flat at about 150 opportunities per quarter despite rising brand investment, UserEvidence's pipeline reached 450 per quarter within two quarters. Listen
Evan said brand, content and community spending increased across those eight quarters with no visible movement in pipeline, and he resisted shifting to quick-hit events and ads. Opportunities then rose to 300 and later 450 in the space of two quarters. He framed the eight quarters as a test of how long the company was willing to keep investing in brand.
“we had eight quarters in a row where it was just 150 opps per quarter”
Listen to the episode Episode Positioning & marketing Link to this
Anecdotal evidence such as LinkedIn comments and inbound mentions can keep a board supportive of a brand investment before dashboard metrics show impact. Listen
Evan said the VP of marketing's board decks included screenshots of people's LinkedIn comments and mentions of inbound opportunities, such as hearing about the CEO's posts. He said this kind of anecdotal progress gave the board enough confidence to keep funding brand even without a dramatic dashboard impact at that point.
“sometimes it's the anecdotal stuff gives people enough confidence to continue the investment even though you weren't seeing like a dramatic, you know, HubSpot dashboard impact quite yet at the, at the board level.”
Listen to the episode Episode Fundraising & investors Link to this
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Andy Mowat said on [Un]ChurnedRoughly 75 to 80% of director-level roles are posted publicly, but only about 20% of VP roles and virtually no C-level roles, so senior candidates must go through networks and referrals.ListenHiring & team building
2 sources
Andy estimates that 75 to 80% of director-level roles are posted publicly, but only about 20% of VP roles and virtually no C-level roles are. Listen
Andy gave these as his own estimates of how often senior go-to-market roles are posted publicly. He said the share drops sharply as seniority rises. He tied this to the broader point that senior searches are run through networks and recruiters.
“I estimate that at the director level, 75 to 80% are posted, but you flip that to 20% posted at the VP level and at the C level, virtually nothing is posted.”
Listen to the episode Episode Hiring & team building Link to this
Applying through the front door rarely works, and cited a Whispered member in CS who applied to 200 roles without using a backdoor and had little success. Listen
Andy said recruiters often spend only about three seconds on each application. He said that unless a candidate is an absolute perfect fit, they will struggle, and AI screening may filter out even strong fits. He said the member should have used the referral route.
“I think the key thing that people just don't get is do not apply through the front door.”
Listen to the episode Episode Hiring & team building Link to this
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Dr. Chuck Bamford said on Revenue BuildersReplacing a generic ideal customer profile with explicit fit criteria and a precise prospect list lifted a packaging client's hit rate from about 5% to 41% over three years.ListenPipeline & demand generation
1 source
Narrowing a generic ideal customer profile to explicit criteria lifted one packaging client's hit rate from about 5% to 41%. Listen
Chuck says the client pitched whoever reached out, with a hit rate of about 5% on the proposals it made. He worked with it to define which customers were poor fits and which needed the product and would pay, then had students at Notre Dame build a precise prospect list, and three years later the sales team's hit rate was 41%.
“They had about a 5% hit rate on their, on the one they tried to pitch.”
Listen to the episode Episode Pipeline & demand generation Link to this
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Jonathan Moss said on The Revenue Leadership PodcastAn ROI pitch failed to get Experity's data team to prioritize go-to-market data; giving it two to three of the revenue org's budgeted FTEs worked.ListenHiring & team building
2 sources
Experity's ROI pitch failed to get the data team to prioritize GTM data, but allocating two to three FTEs of the revenue org's budgeted headcount to the data team succeeded. Listen
Moss's pitch was that acquisition, expansion and retention fund everything, including the data team, so GTM data is the easiest ROI. It produced only a little momentum. In planning, the revenue org instead gave two to three budgeted FTEs to the data team, which hired net-new people focused only on the GTM domain.
“we're actually going to allocate, you know, two, three FTEs of the overall revenue organization to this because it's so important”
Listen to the episode Episode Hiring & team building Link to this
When his company raised its Series C, Kyle Norton made an applied AI leader for sales the first role in the new headcount plan and placed it in the data and biz ops team. Listen
Norton says he carved this role out above anything else and didn't mind that it sat outside sales, because he just needed the work done. He has seen the same pattern elsewhere and thinks trading revenue headcount for dedicated data or AI capacity is probably replicable. He explains that data teams treat the revenue leader as one stakeholder among many, alongside product and the CFO.
“The first role that I put into the new headcount plan was an applied AI leader for sales.”
Listen to the episode Episode Hiring & team building Link to this
From 5 episodes that week, checked against their transcripts.
Most discussed this week: Hiring & team buildingAIStrategy & market