mbfinotti/sales-skillsチェック済み
SKILL DETAIL
sales-motion
mbfinotti/sales-skills/sales-motion
Chooses and designs the company-level sales motion at VP Sales / CRO altitude - product-led growth (PLG), sales-led, hybrid product-led sales, developer-led/open-source, or channel/partner-led - plus the transitions between them (exiting founder-led sales, layering sales onto self-serve, moving upmarket, adding channel), mapped to ACV, time-to-value, buyer-vs-user separation, TAM shape and procurement friction. Covers B2B SaaS and consumer self-serve motions. Use whenever the user mentions PLG vs sales-led, hiring the first salesperson, going upmarket, self-serve vs demo, or adding partners, even without the word motion. Do NOT use for org topology (mbfinotti/sales-skills@sales-org-structure) or quotas (mbfinotti/sales-skills@sales-quota-setting).
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Installation
npx skills add https://github.com/mbfinotti/sales-skills --skill sales-motion
スキルファイル
SKILL.md
最終同期 · 2026/09/15
evals/evals.json›
{
"skill_name": "sales-motion",
"evals": [
{
"id": 1,
"prompt": "I'm the founder/CEO at Kestrelboard - shift-scheduling software for mid-size manufacturers. We just crossed $2.8M ARR and I've been closing every deal myself for two years. My board wants me to hire a VP Sales in the next 60 days so I can get back to product. I've closed 9 deals this year: 4 came through people I worked with at my last company or intros from our seed investor, the rest were inbound. Pricing has been all over the place - one customer got 40% off for being our first automotive logo, another paid list plus a services fee. Write me the plan for making this hire.",
"expected_output": "A run that refuses to treat $2.8M ARR as the trigger, tests the company against the repeatability gate, finds it failing, and delivers a path to repeatability plus a pioneer-AE hire profile instead of a VP Sales search.",
"files": [],
"expectations": [
"Gates the hire decision on repeatability rather than on the $2.8M ARR figure, and says so explicitly",
"States the repeatability gate as 3-5 deals won at standard origin, price and scope",
"Requires 3 of 4 core metrics - win rate, cycle length, ACV, conversion - stable for 90 days",
"Excludes the 4 deals sourced from former colleagues and investor intros from the repeatability count, on the grounds that idiosyncratic wins are not repeatability",
"Applies a readiness checklist covering 10-20+ unaffiliated customers closed personally, more than 20% of founder time booked with customers, and a specific repeatable pattern in how deals closed",
"Flags the 40% discount and the non-standard pricing as failing the standard-deal test",
"Concludes the gate fails and delivers a path to repeatability rather than a motion choice",
"Recommends hiring sales executors - roughly 2 pioneer sellers - rather than the VP Sales the board proposed",
"Names hiring a sales leader instead of executors as a failure mode, explaining that a leader scales an existing motion while only executors can originate one that does not exist yet",
"Names premature delegation as a risk and explains it breaks the founder's market-feedback loop",
"Describes the pioneer AE archetype as entrepreneurial, breaking new ground, working deals personally and feeding insight back to the roadmap",
"Includes month-by-month validation gates for a first hire, with month 2 requiring 10-20 first meetings and 50%+ converting to second meetings",
"Does not name an ARR threshold as the trigger for the first sales hire"
]
},
{
"id": 2,
"prompt": "Quick one. Northvale Labs, B2B SaaS, automated expense categorization. Average contract value is $6,200 a year, we have about 3,100 paying customers, and the addressable market is basically every SMB with a corporate card - a very long tail. New customers reach first value in about 15 minutes with no help from us, and it's usually the office manager who signs up and pays on a company card herself. Our new CRO wants to hire 4 field AEs at $180K OTE each to go get bigger logos, and I've been asked to write the GTM plan that supports it. Help me build it.",
"expected_output": "A run that builds the five-axis constraint map, shows the axes deleting field sales, places $6,200 in the light-touch band, and refuses to produce the field-AE hiring plan that was requested.",
"files": [],
"expectations": [
"Rejects the field-sales hire on ACV grounds, stating that below roughly $10K initial ACV a sales-led motion does not pencil",
"Places the $6,200 ACV in the $5K-$10K light-touch / PQL-outreach band rather than the field-sales band",
"States that the ACV-to-motion mapping is a heuristic aggregated from operator experience, not the output of a study or survey",
"Builds a constraint map naming all five axes: ACV band, time-to-value, buyer-vs-user separation, TAM shape, procurement friction",
"Says which motions each axis deleted rather than presenting the motions as a ranked list",
"Notes that 15-minute unassisted time-to-value sits under the ~30-minute threshold and keeps PLG available",
"Notes that the office manager being both user and buyer keeps PLG available",
"Notes that the long-tail TAM shape favors self-serve rather than field sales",
"Frames the constraint axes as deleting motions rather than demoting them",
"Names high-touch under low ACV as a failure mode, describing deals that can never repay CAC",
"States that self-serve checkout stays in place in the $5K-$10K band",
"Does not produce a hiring plan, territory plan, or ramp schedule for the 4 field AEs"
]
},
{
"id": 3,
"prompt": "We're Tuckerbox, project tracking for creative agencies. Around 40,000 free-trial signups a month, traffic growing steadily, top of funnel is genuinely healthy. Trial-to-paid sits at 1.9%. Four things are on the table for next quarter and I can realistically fund one: rebuild the activation onboarding, add PQL scoring and route hot trials to a sales rep, retarget our signup ads at higher-intent segments, or switch the free trial to a reverse trial. Which one do I do first, and why?",
"expected_output": "A run that emits separate efficiency, value and effort orderings for the four levers, then promotes activation rework above the efficiency ordering because conversion sits below the free-trial median with healthy traffic.",
"files": [],
"expectations": [
"Produces three separate orderings of the four levers - efficiency, value and effort - rather than one blended ranking",
"States the efficiency ordering as reverse-trial packaging > PQL-routed sales assist > higher-intent signup targeting > activation rework",
"States the value ordering as PQL-routed sales assist > activation rework > reverse-trial packaging > higher-intent signup targeting",
"States the effort ordering with activation rework as the most expensive lever, costing a full product quarter",
"Recommends activation rework first despite it sitting last on the efficiency ordering",
"Justifies that promotion by the 1.9% conversion sitting below the ~4-6% free-trial median while traffic is healthy",
"States that no downstream lever fixes a product that does not activate",
"Names reverse-trial packaging as the default lever absent that condition, citing roughly 2x conversion versus freemium",
"Identifies activation rework as the only lever whose payoff compounds",
"Gates PQL-routed sales assist on PQL volume being large enough for a rep to clear the 4x floor",
"Cites PQL-to-close at 20-30% against roughly 3-10% for MQLs as the economic case for a sales-assist layer",
"Labels the three orderings a default to re-rank against the company's own situation, not a law",
"Checks whether a seamless in-product upgrade and billing path exists, noting roughly 2.5x better free-to-paid conversion when it does"
]
},
{
"id": 4,
"prompt": "Board deck is due Friday and I'm getting killed on the benchmark slide. We're Parlyn - PLG, self-serve, average contract about $8K a year, almost entirely SMB. Our numbers: NRR 94%, win rate on the deals our two AEs touch is 21%, CAC payback 16 months. Our lead investor's associate pasted in 'industry benchmarks' of 118% NRR, 23% win rate and 14-month CAC payback, and wrote 'materially underperforming' next to all three. Help me respond.",
"expected_output": "A run that identifies each pasted figure as either a different segment's band or a superseded pre-2022 number, supplies the dated current counterpart with source and sample, and concludes the company is at or near current median.",
"files": [],
"expectations": [
"Rejects comparing Parlyn's 94% NRR to the ~118% figure, identifying ~118% as the enterprise (>$100K ACV) band",
"Supplies the SMB band of roughly 97% NRR as the correct comparison for an $8K ACV motion",
"States that lower SMB NRR is a segment effect, not a motion-quality signal",
"Rejects grading a PLG funnel against sales-led win-rate medians, naming it the most common benchmarking error in this field",
"Replaces the 23% win rate with the current figure of roughly 19% and dates it to 2024",
"Replaces the 14-month CAC payback with the current median of roughly 18 months and dates it to 2024",
"Attaches a named source and a sample size to at least two of the corrected benchmark figures",
"States that no pre-2022 figure should appear without its current counterpart",
"Concludes the 16-month CAC payback is inside, not outside, the current median",
"Names 24 months as the CAC payback threshold that triggers fixing motion economics before further spend",
"Distinguishes new-only from fully-loaded CAC payback scope before comparing two cited figures",
"Names anchoring on pre-2022 benchmarks as a failure mode and explains that efficiency metrics drifted worse after 2022",
"Does not blend PLG conversion metrics and sales-led win rates into a single figure"
]
},
{
"id": 5,
"prompt": "Halversen Systems - warehouse robotics software, ACV around $240K. We ran a 6-partner pilot for two quarters through systems integrators. Results: $3.1M in partner-sourced bookings against roughly $950K all-in program cost including margin given up. Our VP Partnerships wants to go from 6 partners to 40 next year, and our direct team is already calling into some of the same logos. Give me the plan to scale this.",
"expected_output": "A run that holds the scale-up behind two separate channel gates the pilot has not demonstrated, requires swim lanes before scaling, and separates sourced from influenced contribution at this deal size.",
"files": [],
"expectations": [
"Refuses to authorize scaling on the pilot's margin result alone",
"Requires partner CAC to run 20-40% below direct CAC before scaling",
"Requires a 3:1 revenue-to-cost ratio as a second, separate scaling gate",
"States explicitly that a positive-margin pilot alone does not clear the gates",
"Requires explicit account, segment or vertical swim lanes agreed before scaling either motion",
"Rejects adjudicating direct-versus-partner conflicts deal by deal after they start",
"Names channel cannibalization as the failure mode the swim lanes prevent",
"Separates partner-sourced from partner-influenced contribution as two distinct metrics rather than one number",
"Notes that at $200K+ enterprise deal sizes partners mostly accelerate rather than originate, citing roughly 15-28% sourced",
"Distinguishes VAR margin of 20-30% from referral-partner margin of a one-time 15-30% of first-year contract value",
"Notes that VAR margin is granted in perpetuity for SaaS so the partner protects the renewal",
"States that pure resellers handling transaction processing only take roughly 5-10%, a separate band from VARs",
"Writes review triggers and a next re-evaluation date for the channel decision into the plan"
]
},
{
"id": 6,
"prompt": "I'm the new CRO at Bramwell - compliance workflow SaaS, $19M ARR, SMB-heavy, $14K average deal. Board meeting is 22 January and they want to see the enterprise motion working by then; today is 12 September. Two constraints I can't move: all 14 engineers are locked on a replatform through Q2 and I cannot claim a single sprint, and our CFO has frozen comp plan changes until the new fiscal year starts in July. Build me the plan to move us to enterprise sales.",
"expected_output": "A run that deletes the enterprise shift outright on the effort ceiling rather than demoting it, explains the deadline makes a motion switch impossible, and substitutes layering levers that act inside a quarter.",
"files": [],
"expectations": [
"States that a real motion transition runs 12-24 months and therefore cannot show revenue effect inside the roughly 4-month window",
"Names the January board date as the answer that demoted the motion switch",
"Deletes the enterprise shift outright rather than demoting it, on the strength of the effort ceiling",
"States explicitly what was struck and why, rather than silently omitting it",
"Names the dual-track product gate - SSO, SOC 2, audit-logging-class governance features - as a prerequisite the frozen engineering capacity cannot supply",
"States that a half-funded upmarket push is the most expensive way to fail",
"Names re-comp as a prerequisite that the comp freeze blocks",
"Promotes layering levers that act inside a quarter instead of the switch",
"Recommends at least one specific lever that can land before the January board meeting",
"States that the post-chasm narrative shift - selling a concrete solution to a recognized problem rather than a shared belief - is a further prerequisite for the enterprise motion",
"Writes review triggers and a next re-evaluation date into the output",
"Does not deliver an enterprise transition plan with enterprise AE hiring and territory detail"
]
},
{
"id": 7,
"prompt": "Founder here, Sedgewick - open-source observability, about 31K GitHub stars, $2.4M ARR from our cloud offering. My co-founder and I have a rule: we never hire salespeople. Atlassian got to a multi-billion-dollar IPO with no sales team, and Cursor went from $100M to $2B ARR without reps. That's the model we're copying. Our investors keep pushing back on it. Write up the GTM strategy that proves we're right so I can send it to them.",
"expected_output": "A run that corrects both cases on the record, refuses to design the motion by copying another company, and reframes the strategy around Sedgewick's own constraints with the survivorship caveat stated.",
"files": [],
"expectations": [
"States that the claim Atlassian never had a sales team is false",
"Gives the correction that Atlassian hired its first commissioned salespeople in summer 2014",
"Notes the no-sales-team description held only for roughly the company's first 12 years",
"Notes Atlassian served enterprise through a large channel and partner ecosystem with explicit swim lanes rather than direct sales",
"Cites Atlassian deferring sales until a $4,000 deal had become a $48,000 one",
"Labels the Cursor ARR figures as press reporting around funding rounds rather than audited disclosures",
"States that Cursor hired no enterprise sales reps until well past the $200M ARR mark, as the actual shape of that case",
"Rejects copying another company's motion and states that a route to market is designed from this company's own product, market and customer",
"Cites the finding that 98% of PLG companies either already have a sales team or plan to hire one",
"Warns that the case record is asymmetric - PLG adding sales is heavily documented while retreats are barely documented - and attributes this to survivorship and publication bias",
"States that named cases illustrate mechanisms and cannot prove a direction is safe",
"Grounds any recommendation in a named, sourced case carrying its caveat rather than an invented example",
"Does not present a permanent no-sales-team end state as validated by these two cases"
]
},
{
"id": 8,
"prompt": "Running GTM at Sunhaul - residential solar installs across Arizona and Nevada. Average job is $24,000. We get about 1,800 web leads a month from paid search and our own content. Right now leads sit in a shared inbox and someone picks them up when they get to them; median time to first contact is roughly 19 hours. Leadership is asking whether we should go self-serve like a SaaS company and let people configure and buy a system online. What motion should we run?",
"expected_output": "A run that keeps the price-to-touch logic but drops the B2B-specific axes and benchmark tables, concludes sales-led fits high-consideration B2C, and fixes speed-to-lead with the correctly attributed study.",
"files": [],
"expectations": [
"States that the B2B SaaS benchmark tables do not transfer to this B2C motion",
"Directs validation against Sunhaul's own funnel history and says so in the plan",
"Concludes sales-led is structurally correct for a $24,000 high-consideration consumer purchase",
"Grounds that conclusion in price-to-touch economics - human sales exists only where order value or LTV covers rep cost",
"Drops the buyer-vs-user and procurement-friction axes from the constraint map because the B2C decision unit is a single buyer or household",
"States that B2C cycles run minutes to days rather than months",
"Cites the speed-to-lead finding as roughly 100x more likely to connect and 21x more likely to qualify when contacting within 5 minutes versus 30",
"Attributes the speed-to-lead finding to the Oldroyd / InsideSales.com Lead Response Management Study of 2007",
"Does not attribute the 5-minute speed-to-lead finding to a 2011 Harvard Business Review article",
"If the HBR piece appears at all, cites it separately as an audit that found a 42-hour average response time",
"States that lifecycle automation - cart-abandonment flows, financing or credit qualification, in-product upgrade paths - replaces the B2B sales-assist layer",
"Keeps the time-to-value axis in the constraint map as one that transfers to B2C",
"Does not quote a SaaS NRR, CAC payback or trial-conversion band as a target for this business"
]
},
{
"id": 9,
"prompt": "Maddox Grove - team wiki product, PLG with a self-serve base. We added 3 sales-assist reps 11 months ago. The numbers: each of those 3 reps touched $1.1M in closed revenue over the period, and fully loaded cost is about $260K per rep including benefits and tooling. That's 4.2x. My head of growth wants to hire 6 more reps next quarter on that basis. Reps currently pick which accounts to work off a list sorted by company size from our enrichment vendor. Sign off on the plan or tell me what to change.",
"expected_output": "A run that refuses the 4.2x as passing the 4x test because the revenue is coincident rather than incremental, demands an incrementality measurement, and replaces size-sorted account picking with product-signal routing.",
"files": [],
"expectations": [
"Refuses to accept the 4.2x figure as passing the 4x test because touched revenue is coincident rather than incremental",
"Names incrementality - whether assisted deals would have converted anyway - as the test these numbers have not passed",
"States the 4x test as a rep returning roughly 4x fully loaded cost in incremental revenue, and treats it as a go/no-go floor",
"Warns that efficient-looking sales-assisted deals can mask a team that is a net drain in aggregate",
"Asks for or specifies a holdout or comparison group that isolates incremental conversions from assisted volume",
"Labels the $260K fully loaded rep cost a modeled estimate and notes that no surveyed benchmark for fully loaded AE cost exists",
"Models the 4x test as an explicit chain running from rep meeting capacity through opportunity budget, cost per opportunity, win rate and deal value to ROI",
"Rejects routing accounts by company size alone and requires product-qualification signals",
"Names the product-qualification signals: multi-player use on one domain, usage growth over time, use-case fit for assistance, and role fit against ICP",
"Applies a two-axis routing matrix that sends low-observable accounts to tech-touch only with no human",
"Checks the expansion against the two economically justified reasons to add sales to self-serve - penetration/expansion, and conversion assist",
"Does not approve the 6 additional hires on the strength of the stated 4.2x ratio"
]
},
{
"id": 10,
"prompt": "Wrenfield Analytics, $27M ARR, pure PLG so far - self-serve, credit card, no sales team beyond 2 people doing onboarding. We're getting real enterprise pull now. Here's the plan I drafted: Q1 hire a VP of Enterprise Sales, Q2 they build out the AE team and territories, Q3 we redo the comp plan once we see how they actually sell, Q4 we add PQL scoring so marketing can feed them leads. Poke holes in this.",
"expected_output": "A run that inverts the sequence so PQL scoring and pricing flexibility precede the first enterprise sales leader, moves the comp change ahead of the org change, and attaches dated gates.",
"files": [],
"expectations": [
"Inverts the proposed sequence, requiring PQL scoring and pricing/packaging flexibility before the first enterprise sales leader is hired",
"Sequences the layer on the six-tactic order: end-users driving top-of-funnel enterprise pipeline, mining PQLs to guide direct sales, heuristics to triage and scale accounts, pricing and packaging flexibility, architecture supporting expand-and-extend, then cohesive hiring and comp",
"Notes the roughly $25M ARR mark as the point around which this enterprise layer is introduced, and that $27M sits in that window",
"Moves the comp change ahead of the org change, stating re-comp before re-org",
"Explains that keeping sales-led comp while flipping toward PLG is what makes AEs gate or sabotage the self-serve motion",
"Names the concrete re-comp moves: pull AEs off sub-$25K deals, shrink base 15-25%, expand variable",
"Specifies 1.5x-2x accelerators on expansion ARR from PQL-crossed accounts",
"Hands detailed compensation plan mechanics to the compensation skill rather than designing the full plan here",
"Names comp changed after the org chart as a failure mode",
"Warns that operationalizing upmarket too early carries execution risk while waiting too long carries opportunity cost",
"Attaches dated gates to the transition sequence rather than quarter labels alone",
"Requires the self-serve upgrade and billing path to stay open through the transition",
"Does not leave the enterprise sales leader hire in the first quarter of the plan"
]
}
],
"trigger_queries": [
{ "query": "Should we be PLG or sales-led?", "should_trigger": true },
{
"query": "We're a $4M ARR dev tool - when do I hire my first salesperson?",
"should_trigger": true
},
{
"query": "Our self-serve product has 12,000 free users. Should we add a sales team?",
"should_trigger": true
},
{
"query": "How do I know if my founder-led selling is repeatable enough to hand off?",
"should_trigger": true
},
{
"query": "Our enterprise motion isn't working and the board wants an answer next week",
"should_trigger": true
},
{
"query": "Is our $7K average deal size too small to justify inside sales reps?",
"should_trigger": true
},
{ "query": "We want to go upmarket. What actually has to change?", "should_trigger": true },
{
"query": "Should we sell through partners or build a direct team?",
"should_trigger": true
},
{
"query": "Product-led growth versus sales-led growth for a $30K ACV analytics product",
"should_trigger": true
},
{
"query": "Everyone tells me to copy Atlassian and never hire sales. Is that real?",
"should_trigger": true
},
{
"query": "We're an open-source infra company with 40k stars and no revenue engine. What's the path?",
"should_trigger": true
},
{
"query": "How do I decide which segment gets reps and which stays self-serve?",
"should_trigger": true
},
{
"query": "What blend of go-to-market should a $12M ARR hybrid company run?",
"should_trigger": true
},
{
"query": "We keep losing big deals because nobody can walk procurement through the security review",
"should_trigger": true
},
{ "query": "Do we need a demo, or can people just swipe a card?", "should_trigger": true },
{
"query": "Our free-to-paid conversion is 1.9% and I don't know what to fix first",
"should_trigger": true
},
{
"query": "Advise me on layering an enterprise sales engine onto our PLG funnel",
"should_trigger": true
},
{
"query": "I'm a CRO inheriting a go-to-market that grew by accident. Where do I start?",
"should_trigger": true
},
{
"query": "Our reps are gatekeeping the self-serve checkout and I think it's the comp plan",
"should_trigger": true
},
{
"query": "Should the first GTM hire be a VP Sales or two senior AEs?",
"should_trigger": true
},
{
"query": "How long does it actually take to change the way a company sells?",
"should_trigger": true
},
{
"query": "We're B2C solar, $22K jobs, mostly web leads. How should we be selling?",
"should_trigger": true
},
{ "query": "Is a channel program worth it at our size?", "should_trigger": true },
{ "query": "Our partner pilot worked. Can we scale it?", "should_trigger": true },
{
"query": "What's the right route to market for a product that takes three weeks to implement?",
"should_trigger": true
},
{
"query": "Our users and our buyers are completely different people. Does PLG still work?",
"should_trigger": true
},
{
"query": "Which acquisition motion should own accounts above $100K?",
"should_trigger": true
},
{ "query": "Help me design swim lanes between direct and partners", "should_trigger": true },
{
"query": "We're thinking of killing the free tier and going all sales-led",
"should_trigger": true
},
{
"query": "How do I tell the board our CAC payback isn't actually broken?",
"should_trigger": true
},
{ "query": "Bottom-up or top-down for a developer tool?", "should_trigger": true },
{
"query": "My investors want a PLG story. Do our constraints even support one?",
"should_trigger": true
},
{
"query": "We have a long tail of tiny accounts and five whales. What covers both?",
"should_trigger": true
},
{
"query": "When is a company ready to stop the founder doing every demo?",
"should_trigger": true
},
{
"query": "Do we hire an enterprise sales leader now or build PQL scoring first?",
"should_trigger": true
},
{
"query": "What would have to be true for us to justify a rep working $8K deals?",
"should_trigger": true
},
{
"query": "Design the go-to-market for a usage-priced API product",
"should_trigger": true
},
{
"query": "Our sales cycle is 4 months on a $15K deal. Is that a structural problem?",
"should_trigger": true
},
{
"query": "How should a Series A company sequence the move from founder selling to a team?",
"should_trigger": true
},
{
"query": "We're getting pulled upmarket by customers we never targeted. What now?",
"should_trigger": true
},
{
"query": "Is hybrid product-led sales a real thing or just a compromise state?",
"should_trigger": true
},
{
"query": "I need to decide whether to build self-serve checkout or hire two more AEs",
"should_trigger": true
},
{ "query": "Our approach worked at $5M and is stalling at $20M", "should_trigger": true },
{
"query": "What's the case for adding a concierge tier to a consumer subscription?",
"should_trigger": true
},
{
"query": "Rank the ways we could lift trial conversion by what we get per unit of effort",
"should_trigger": true
},
{
"query": "We have no idea whether to invest in community or in outbound reps",
"should_trigger": true
},
{
"query": "Give me a plan I can take to the board with gates and dates for changing how we sell",
"should_trigger": true
},
{
"query": "Do we need SOC 2 before we can sell to enterprise, or is that a later problem?",
"should_trigger": true
},
{
"query": "Our AEs and our self-serve funnel are fighting over the same accounts",
"should_trigger": true
},
{
"query": "Two of our products need totally different ways of selling. How do I split it?",
"should_trigger": true
},
{
"query": "What should trigger us to re-evaluate how we sell?",
"should_trigger": true
},
{
"query": "We sell to engineers who can expense $500 but not $50,000. What does that imply?",
"should_trigger": true
},
{ "query": "Is it too late to add sales, or too early?", "should_trigger": true },
{
"query": "How do I stop copying our competitor's GTM and design our own?",
"should_trigger": true
},
{
"query": "Our magic number has been 0.4 for two quarters. Is that structural?",
"should_trigger": true
},
{
"query": "Advise a bootstrapped team on whether to ever hire a salesperson",
"should_trigger": true
},
{
"query": "What does it cost us to stay purely self-serve for another year?",
"should_trigger": true
},
{ "query": "What SDR-to-AE ratio should we run at 40 reps?", "should_trigger": false },
{
"query": "Should we organize the sales team into pods or an assembly line?",
"should_trigger": false
},
{
"query": "What's a healthy span of control for a mid-market sales manager?",
"should_trigger": false
},
{
"query": "How do I split the team into hunters and farmers?",
"should_trigger": false
},
{ "query": "Set next year's quotas for 22 AEs", "should_trigger": false },
{
"query": "How much over-assignment cushion should I build into the quota plan?",
"should_trigger": false
},
{
"query": "Model ramped rep equivalents for a team hiring 8 reps in Q1",
"should_trigger": false
},
{
"query": "What base-to-variable pay mix should an enterprise AE have?",
"should_trigger": false
},
{
"query": "Design an accelerator curve above 100% attainment",
"should_trigger": false
},
{
"query": "Should we run a SPIF on multi-year deals this quarter?",
"should_trigger": false
},
{
"query": "What pipeline coverage ratio do we need to hit a $6M quarter?",
"should_trigger": false
},
{
"query": "Our stage-weighted coverage says 2.8x - is that enough?",
"should_trigger": false
},
{
"query": "Define our ICP for a compliance automation product",
"should_trigger": false
},
{
"query": "Estimate TAM and SAM for restaurant point-of-sale in Germany",
"should_trigger": false
},
{
"query": "Build a weighted account fit score from our closed-won data",
"should_trigger": false
},
{
"query": "Where should the cutoffs sit between Tier 1 and Tier 2 accounts?",
"should_trigger": false
},
{
"query": "How many accounts per rep in our Tier 2 coverage model?",
"should_trigger": false
},
{
"query": "Write an interview loop and scorecard for hiring two AEs",
"should_trigger": false
},
{
"query": "Design a 30-60-90 ramp plan with certification gates for a new rep",
"should_trigger": false
},
{ "query": "I'm an SDR - how do I get promoted to AE?", "should_trigger": false },
{ "query": "Score this deal against MEDDPICC", "should_trigger": false },
{
"query": "Who is the champion in this opportunity based on the call notes?",
"should_trigger": false
},
{
"query": "Review these deal notes for qualification red flags",
"should_trigger": false
},
{ "query": "Build the ROI business case for this $400K deal", "should_trigger": false },
{
"query": "Write a cold call opener for a VP of Engineering",
"should_trigger": false
},
{
"query": "Is our SPF and DKIM setup going to hurt deliverability?",
"should_trigger": false
},
{
"query": "Generate ten subject line variants and a split-test plan",
"should_trigger": false
},
{
"query": "Plan a 12-touch outbound cadence across email and LinkedIn",
"should_trigger": false
},
{
"query": "Turn these prospect signals into personalization angles",
"should_trigger": false
},
{
"query": "Write discovery questions for a 30-minute first call",
"should_trigger": false
},
{
"query": "How do I handle 'we already use a competitor' on a live call?",
"should_trigger": false
},
{
"query": "Score this call transcript against our rubric",
"should_trigger": false
},
{
"query": "Draft the recap email with next steps from these meeting notes",
"should_trigger": false
},
{
"query": "Plan my concessions before the pricing negotiation on Thursday",
"should_trigger": false
},
{
"query": "Which sales podcasts and newsletters should I be following?",
"should_trigger": false
},
{
"query": "Where does sales sit in our overall revenue funnel stage model?",
"should_trigger": false
},
{
"query": "Design our partner tiering and enablement program",
"should_trigger": false
},
{
"query": "Write the reseller agreement terms for a new VAR",
"should_trigger": false
},
{ "query": "How should we price the enterprise plan?", "should_trigger": false },
{
"query": "Write the pricing page headline and feature comparison table",
"should_trigger": false
},
{
"query": "Rewrite the in-app onboarding checklist copy for new signups",
"should_trigger": false
},
{
"query": "Write the positioning statement for our new product line",
"should_trigger": false
},
{
"query": "Build a referral incentive program for existing customers",
"should_trigger": false
},
{
"query": "What should our territory map look like by geography?",
"should_trigger": false
},
{ "query": "How do we forecast the quarter more accurately?", "should_trigger": false },
{ "query": "Design the lead routing rules in our CRM", "should_trigger": false },
{
"query": "Set up lead scoring thresholds for marketing qualified leads",
"should_trigger": false
},
{
"query": "Our CRM pipeline stages are a mess - redefine them",
"should_trigger": false
},
{
"query": "How do I animate the hero section transitions on our marketing site?",
"should_trigger": false
},
{
"query": "Create motion graphics for our product launch video",
"should_trigger": false
},
{ "query": "What's a good commission clawback policy?", "should_trigger": false },
{ "query": "Write a job description for a Head of Sales", "should_trigger": false },
{ "query": "How do I run a QBR with a Tier 1 account?", "should_trigger": false },
{
"query": "Build a customer health score to predict churn",
"should_trigger": false
},
{
"query": "Plan the sales kickoff event agenda for January",
"should_trigger": false
},
{
"query": "Which of your sales skills should I use for this task?",
"should_trigger": false
},
{
"query": "Should we discount this deal to get it closed this quarter?",
"should_trigger": false
}
]
}
references/motion-benchmarks.md›
# Motion benchmarks (dated) and how to cite them
Two rules before any number leaves this file:
- Never blend PLG and sales-led metrics into one figure. Benchmarking a PLG funnel against sales-led win-rate medians is called out as the single most common benchmarking error in this field.
- Report by source with its date and sample, never a blended average. The same metric diverges irreconcilably across sources because their respondent populations differ.
## Efficiency degraded across 2022-2026 - date every figure
The post-2022 efficiency era moved every headline metric the wrong way. A motion plan graded against pre-2022 folk benchmarks will look broken while performing at today's median.
| Metric | Earlier | Later | Source |
| ----------------------------- | ---------------- | -------------------------------- | ---------------------------------------------------------------- |
| CAC payback (median B2B SaaS) | 14 months (2023) | 18 months (2024) | Benchmarkit 2025 SaaS Performance Metrics, n≈936 |
| AE quota attainment | 66% (2022) | 51% (2024) → 48% (2026) | Bridge Group AE reports (n=172 in 2024; n=158 in 2026, 10th ed.) |
| AE win rate (median) | 23% (2022) | 19% (2024) | Bridge Group 2024 |
| Win rate (cross-check) | 29% (2021) | 19% (2025) | Ebsta x Pavilion 2025 |
| Sales cycle | - | +3-4 weeks on average, 2024-2025 | ICONIQ |
Attainment is also the canonical example of irreconcilable sources for the same period: Bridge Group 51% vs KeyBanc/Sapphire 75-85% vs RepVue ~43% (Q3 2024) - different populations (consulting-client survey vs venture-backed self-report vs 100K+ anonymous reps). Report the range.
## CAC payback
- KeyBanc/Sapphire 2024 (15th annual, n≈104, median $26M ARR): ~20 months new-only, ~23 months fully loaded. The "new-only" vs "fully-loaded (new+expansion)" scope changes the number materially - confirm scope before comparing two cited figures.
- By ACV tier (Benchmarkit 2024): low-ACV (≤$5K) recovers in roughly 9 months, high-ACV ($100K+) closer to 24. Payback lengthens with deal size because absolute CAC and cycle length rise faster than ACV.
- By motion (operator sources, directional): PLG 8-12 months, sales-led SMB 6-12, enterprise sales-led 18-24 (accepted specifically when NRR exceeds 120%). Payback tolerance is a joint function of motion and retention quality, never payback alone.
## Cycle length and its weak link to deal size
Bridge Group 2024 overall median: 5 months. Band detail, triangulated from Gong/Ebsta/6sense/Norwest secondary aggregators (directional):
- <$5K-$10K: ~25-40 days.
- <$25K: ~90 days.
- $25K-$100K: ~90-180 days.
- $100K+: 3-9+ months, regularly 6-12.
Deal size explains only ~27% of cycle-length variance (HockeyStack regression, 54 B2B SaaS companies, R²=0.268) - the rest is process quality, buyer intent and data quality.
## Rep economics
Bridge Group 2024 AE report (n=172, median $24M revenue, $47K ACV):
- Median quota: $800K.
- Median OTE: $190K on a 53:47 split.
- Quota:OTE: ~4.2x.
- Ramp: ~5.7 months average (SMB 3-4, mid-market 4-6, enterprise 6-9+).
- **Quota vs actual are two different measures.** The commonly conflated "$328K-$800K new ARR per AE" range spans quota assigned (Bridge Group $800K; KeyBanc/Sapphire $750K median) versus actual new ARR booked (KeyBanc/Sapphire 2024 median $328K). Always say which one a cited figure is.
- **Fully-loaded AE cost has no surveyed benchmark - only operator heuristics.** David Sacks: fully-loaded AE cost ≈ 25% of the AE's sales, plus 15-25% sales overhead. FLG Partners enterprise model: a $300K-OTE field AE closing $1.5M carries ~$745K sales-department expense, ~$1.0M with allocated marketing. A synthesized mid-market direct fully-loaded cost lands roughly $240K-$300K+ before SDR/SE/RevOps allocation. Label every such number a modeled estimate.
## Self-serve and PLG conversion
- Trial-to-paid conversion by type: free trials roughly 4-6%, freemium ~3-5%, time-limited trials 8-12%, reverse trials ~2x freemium. The spread across samples (one source cites freemium closer to 12%) signals these are not one homogeneous metric across products.
- Sales-assisted PQL conversion: 15-35%, with multiple sources converging on 20-30% PQL-to-close vs roughly 3-10% for MQLs - the core economic justification for a sales-assist layer. Vendor-cited and directional; validate against your own cohorts.
- Free-trial/POC conversion is the fastest-improving stage: roughly 50% in ICONIQ 2026 data (up ~14 points year-over-year); ICONIQ 2025 (205 GTM execs) found AI-native $100M+ companies converting trial-to-paid at 56% vs 32% for others - product category now drives conversion as much as motion design.
## Retention and efficiency by motion
- NRR by ACV segment (SaaS Capital / Optifai cross-references): enterprise (>$100K) ~118%, mid-market ($25K-$100K) ~108%, SMB (<$25K) ~97%. PLG-SMB NRR is structurally lower because SMB churn is higher: a segment effect, not a motion-quality signal. Never benchmark a PLG company against enterprise NRR medians. ChartMogul (n≈2,100-2,500) reports median venture-backed NRR ~106%; SaaS Capital 2026 (n=1,000+) reports median NRR 103%, GRR 91%.
- Expansion now drives ~40% of growth for $15M-30M+ ARR companies (ChartMogul 2024), up from ~30% in 2021.
- Rule of 40 diverges by motion: PLG companies scored 34 vs 20 for sales-led (Benchmarkit 2024) - consistent with PLG's lower CAC and faster payback trading against its lower NRR ceiling at the SMB end. Never read it in isolation.
- Magic number: KeyBanc/Sapphire 2024 median 0.7 (a 0.90 figure circulates only in secondary aggregation - flag, don't pick); top quartile 1.0-2.0+.
- Pricing shifted under the motions: usage-based pricing reached 51% of public SaaS by 2026 (from 27% in 2021); pure per-seat fell to 28% from 51% (Bessemer State of the Cloud 2026).
## Decision thresholds
- CAC payback trending past 24 months → fix the motion economics before raising further.
- Magic number below 0.5 for two consecutive quarters → cost-of-sales inefficiency.
- NRR below 100% for an enterprise vendor → structural problem, not noise.
- A sales hire that cannot model ~4x its fully loaded cost in incremental revenue → do not make it (the "juice worth the squeeze" floor; see the transition playbooks file).
## Source catalogue
| Source | Publishes | Sample / currency |
| ----------------------------------------- | ---------------------------------------------- | ------------------------------------------------------------------------------------------------------- |
| Bridge Group | AE/SDR metrics & comp | n=172 (2024); n=158 (2026, 10th ed.) |
| Benchmarkit (Ray Rike) | SaaS metrics segmented by GTM motion | n≈936 (2024) - most granular by motion |
| KeyBanc / Sapphire | Private SaaS survey (ex-Pacific Crest) | n≈104 (2024), median $26M ARR |
| ICONIQ Growth | State of GTM / Software | ~205 GTM execs (2025); 150+ companies (2026) |
| ChartMogul | Retention / NRR trends | n≈2,100-2,500 |
| SaaS Capital | Private-company survey | n=1,000+ (2025, 14th ed.); bootstrapped skew |
| Bessemer (BVP) | State of the Cloud, PLG-to-enterprise playbook | public Cloud Index + portfolio |
| Growth Unhinged (Kyle Poyar) / High Alpha | PLG benchmarks, pricing | OpenView wound down in 2024; its PLG franchise migrated here - do not cite OpenView as a live publisher |
| Winning by Design | Revenue Architecture / Bowtie | framework, not a survey |
| ProductLed (Wes Bush) | self-serve benchmarks, SLG-to-PLG transitions | methodology + report |
| Runa Capital ROSS Index | trending commercial open-source | quarterly since Q2 2020, GitHub-star methodology |
Some 2026-dated figures exist only in secondary blogs citing a primary report; where a figure appears solely in a secondary aggregator, flag it rather than silently picking one.
references/motion-case-evidence.md›
# Motion case evidence
Named, sourced cases to cite instead of inventing examples. Read the bias caveat at the end before treating any pattern here as a law.
## The initial-vs-eventual map
Lenny's Newsletter analysis of 25+ B2B companies documents each company's initial motion versus its eventual one:
| Initial strategy | Eventual strategy | Examples |
| ------------------------------- | -------------------------------- | ----------------------------------------------------------------------- |
| Bottom-up self-service | Bottom-up alongside sales team | Segment, Figma, Slack, Canva, Twilio, Plaid, Shopify, Stripe, Atlassian |
| Bottom-up with inside sales | Bottom-up alongside sales team | Dropbox, Asana, Airtable, New Relic, Coda |
| Bottom-up with inside sales | Sales-driven land and expand | Box |
| Founder-led outbound | Bottom-up alongside sales team | Zoom, Amplitude |
| Founder-led outbound | Sales-driven land and expand | Carta, Okta, Intercom, Looker, Salesforce |
| Founder-led alongside bottom-up | Sales-driven alongside bottom-up | Square, Gusto |
The insight: motion shift runs in **both directions** - sales-driven companies moved toward bottom-up (Zoom, Amplitude) and bottom-up companies toward sales-driven (Box, New Relic). Treat the initial motion as a starting hypothesis, re-evaluated at each stage transition, never a locked-in identity.
The analysis's comparison fields double as an intake shape for a motion interview: initial strategy, eventual strategy, pricing model, free-tier type (freemium / trial / none), first-customer acquisition story.
## PLG adding enterprise sales - abundant and well quantified
- **HashiCorp** - open source to ~2,100+ customers and ~$14B market cap at IPO in under 8 years; FY2021 products downloaded ~100M times, used by ~79% of the Fortune 500. Bessemer's canonical PLG-to-enterprise example.
- **Atlassian - the "no sales team" story is partly myth.** True for the first ~12 years only; first commissioned salespeople hired in summer 2014, before the December 2015 IPO. For enterprise it built a large channel ecosystem with explicit swim lanes rather than direct sales. The strategic insight: it deferred sales until a $4,000 deal became a $48,000 one. Anyone citing Atlassian as proof that sales teams are optional is citing the myth, not the record.
- **Slack** - started with no outside sales; by IPO ~50% of revenue came from larger enterprise deals closed by a large sales team.
- **Amplitude** - founder-led outbound → inbound self-serve with sales-assist → core sales plus partners with land-and-expand; 500+ customers paying >$100K/year, 4-6 month cycles. Publicly frames it as blending PLG tactics into an SLG base ("why not both").
- **MongoDB, Datadog, HubSpot, Monday** - PLG/self-serve coexisting with large S&M spend. The top three historical BVP Cloud Index efficiency scores were all PLG companies (Bill.com and Snowflake past 100%, Datadog over 90%).
- **Cursor (Anysphere)** - $100M ARR January 2025, past $500M June 2025, $1B November 2025, ~$2B by February 2026, with acceleration coming primarily from enterprise customers - yet no enterprise sales reps hired until well past the $200M mark. Evidence that PLG efficiency persists and sales-assist layers late. Caveat: the ARR figures are press reporting around funding rounds (TechCrunch, Bloomberg/CNBC), not audited disclosures - illustrative, never a normative benchmark.
## Sales-led adding self-serve - thinner evidence base
Amplitude (above); HubSpot and DocuSign run free/self-serve for individuals with sales for enterprise. Clean, fully documented retreats from PLG back to pure sales-led are rare in the record - the more common and frequently misread pattern is a PLG company adding a sales layer, which the market mistakes for "abandoning PLG".
## Channel-led
- **Atlassian** - channel ecosystem for enterprise, explicit swim lanes (above).
- **Appfire** - forwent a direct sales team entirely for Atlassian-ecosystem partners: "if I spend the same hours enabling a partner versus a direct salesperson, that partner helps me achieve scale much faster."
- **Microsoft** - ~95% of commercial revenue via partners: the most extreme documented channel-as-primary-motion case at scale.
## Developer-led / open source
HashiCorp, Vercel, Supabase - community drives awareness, product converts. The **ROSS Index** (Runa Capital, quarterly since Q2 2020) ranks trending commercial open-source startups by relative GitHub-star growth; LangChain topped the 2023 index. COSS startups attracted ~$26.4B aggregate funding in 2024 per COSS/Linux Foundation reporting. Developer-led is a real fourth motion, not PLG with a different audience: the "user" is an engineer with buying latitude, and community/ecosystem investment substitutes for both marketing and early sales.
## Bias caveat
The case record is asymmetric: PLG-adds-enterprise is heavily documented with named companies and figures; retreats in the other direction are barely documented. Absence of documented retreat cases is not proof they don't occur - it likely reflects survivorship and publication bias. Use these cases to illustrate mechanisms, never to prove a direction is safe.
references/motion-fit-frameworks.md›
# Motion-fit frameworks and the constraint map
Named frameworks for the motion decision, then the constraint heuristics that do the actual filtering. Every band below is aggregated operator experience - a durable heuristic the field converges on, never the output of a controlled study. Use the bands to delete motions the constraints rule out, not to compute a precise answer.
## Named frameworks
- **GTM Motion Matrix** (Bret Taylor, via Lenny's Podcast) - split by who uses vs who buys: developer-led (engineers with buying latitude), PLG (user and buyer are the same person), direct sales (user and buyer are different people). The user/buyer question is the fastest first cut.
- **Sales channel design principle** (Ben Horowitz) - a sales channel is a route to market designed from the product, market and customer, never copied from another company. Named failure mode: founders reject enterprise sales by stereotype and copy consumer-style bottom-up distribution (Dropbox) without understanding why it worked for that product.
- **Lego Bricks vs Lego Boxes** (Ivan Zhao, Notion) - the same product can run two motions at once, segmented by packaging: flexible primitives sold self-serve to builders (PLG), pre-packaged solutions sold to enterprise buyers who want the problem solved (sales-led).
- **Touchless vs sales-assisted** (David Skok) - the simplest two-way cut, with the reminder that motion choice is inseparable from CAC-payback and rep-productivity math, not just a qualitative buyer-type call.
- **Five touch levels** (Winning by Design, Revenue Architecture / Bowtie model) - No Touch, Low Touch (tech-led, humans for complex cases), Medium Touch (SDR qualifies, AE closes), High Touch (AMs plus sales engineers), Dedicated Touch (one team per Fortune 500 account). Useful when "hybrid" needs to be made concrete per segment.
- **Crossing the Chasm** (Geoffrey Moore, 1991) - channel mix shifts stage by stage across the adoption lifecycle: innovators via developer communities and API trials, the early majority via peer proof and references - which is what a sales-led motion supplies. The beachhead strategy maps to ICP concentration.
- **B2C2B** (Ivan Zhao, Notion) - bootstrap via a universal consumer use case to build individual top-of-funnel, then let those individuals pull the product into their workplace. A distinct starting pattern, not pure PLG and not founder-led outbound.
- **Engineers-as-sales** - for highly technical, mission-driven products: operators/engineers who speak from firsthand technical experience replace professional reps, explicitly rejecting relationship-broker tactics. Fits when the product is compelling enough that no dedicated seller is needed.
- **2026 framing shift** - several 2026 sources retire the old complexity-vs-budget 2x2 in favor of asking whether the motion sells to humans, AI agents, or both. Treat as an open question in the field, not a settled framework.
## The ACV-to-motion heuristic
Multiple independent sources converge on these bands (ZoomInfo, Stackmatix, Futureproof, QuantLedger, Notion Capital, Appcues - directional operator estimates, not survey medians):
| ACV band | Default motion | Cited CAC range | Notes |
| ----------------------- | -------------------------------- | -------------------------------- | ------------------------------------------------- |
| Under $5K | Self-serve / PLG | $500-$2,000 | "a sales rep's salary alone would dwarf the deal" |
| $5K-$10K | Light-touch sales / PQL outreach | ~$2,000-$3,000 | still self-serve checkout |
| $10K-$50K | Inside sales (SDR+AE, demos) | $3,000-$8,000 | 3-4 month cycles |
| $50K-$100K+ | Field sales, multi-stakeholder | $15,000-$40,000 | RFPs, procurement, legal |
| $100K+ channel-extended | Field + channel/partner | 20-30% ACV premium, lower margin | partners extend reach |
The economics floor is hard even when the bands are soft: below roughly $10K initial ACV, a sales-led motion does not pencil (Notion Capital: "unlikely you can run a sales-led motion with an initial ACV less than $10k"). The $5K-$50K moderate-complexity middle is where hybrid product-led sales became the 2025-2026 default - the dominant motion per multiple sources, not a compromise state.
## The other four constraint axes
ACV alone never decides. Cross-check all four:
1. **Time-to-value** - under ~30 minutes of unassisted time-to-value favors PLG regardless of price (GTM Playbook rule); best-in-class PLG shows TTV under 10 minutes; anything past an hour makes self-serve unworkable regardless of PQL score. Configuration, stakeholder alignment or change management favor sales-led even at moderate ACV.
2. **Buyer-vs-user separation** - individual buyers convert through the product; team buyers through product plus demos; enterprise committees need a sales process for procurement, security and legal. This is the structural reason PLG breaks at enterprise even with heavy internal usage: a self-serve product with hundreds of active users still fails procurement for lack of a security questionnaire, SSO, or someone to walk the VP of IT through compliance.
3. **TAM concentration** - few large logos favor sales-led/field; a long tail favors self-serve/PLG. Counter-example: MongoDB's top ~100 customers are roughly a third of revenue with 5+ year tenures - concentration can coexist with a PLG-origin motion.
4. **Regulatory/procurement friction** - multi-department touch, security/compliance review, SSO requirement. Three or more such conditions favor sales-led (Benchmarkit- and Salesmotion-cited threshold).
Notion Capital's TAM/ACV matrix summarizes the extremes: large TAM + fast time-to-value + low ASP → PLG; small TAM + complex solution + slow time-to-value + high ACV → sales-led.
## Channel-mix altitude - a different decision
A separate PM/marketing-side taxonomy (Product Compass) inventories 7 acquisition motions - inbound, outbound, paid, community, partner marketing, ABM, PLG - and scores each 1-10 against the product to build a 2-4 motion "stack" revisited quarterly. That is channel selection _within_ whichever org-level motion this skill chooses, not a substitute for it. Keep the altitudes separate: this skill decides whether a sales org exists and how it engages, while the channel stack decides where demand comes from.
The one insight that transfers: most successful companies run 2-4 complementary motions simultaneously, with paid channels funding near-term growth while organic ones (community, PLG, inbound) build the compounding asset.
references/motion-transition-playbooks.md›
# Motion transition playbooks
The three transitions a motion decision usually triggers - exiting founder-led sales, layering sales onto self-serve, and shifting toward enterprise or channel - each with its gates, sequence and named failure modes.
## Exiting founder-led sales
Every motion starts here; the PLG-vs-sales-led question is not live until the founder has sold. The staged progression (Pete Kazanjy):
1. Validate the problem.
2. Build the MVP.
3. Founder personally sells to 20-30 customers.
4. Hire 2 "pioneer" sellers and generalize the motion from what the founder learned.
**The exit signal is repeatability, not revenue** (Euclid Ventures): "a repeatable ability to identify, acquire, and onboard additional customers", never an ARR figure. Quantified gates practitioners use:
- A minimum viable sales motion: 30-50 qualified prospects run through the process, 10-20 converting.
- The standard-deal test: 3-5 deals won at standard origin, price and scope.
- Stability of 3 of 4 core metrics (win rate, cycle length, ACV, conversion) for 90 days.
- The practitioner phrasing: "by deal 5 you should recognize the same objection from deal 1 and have a written save; by deal 10 your discovery call shouldn't have any new questions."
Counter-signal: early wins that are idiosyncratic - the buyer knew the founder, an unusual use case - are not repeatability regardless of ARR.
**Readiness checklist before any sales hire** (composite: Raaz Herzberg, Jason Lemkin, Pete Kazanjy):
- 10-20+ _unaffiliated_ customers closed personally.
- More than 20% of the founder's time booked with customers.
- A specific, repeatable pattern in how deals closed.
Any "no" means hiring is premature - the failure mode is premature delegation, which breaks the founder's market-feedback loop before it has taught anything transferable.
**Hire executors, not a leader.** The most common mistake is hiring a sales _leader_ rather than sales _executors_ who can refine a motion that doesn't exist yet.
- **Do:** hire the hungry senior AE archetype - entrepreneurial background, breaks new ground, works deals personally, feeds insight back to the roadmap.
- **Avoid:** a playbook-execution seller hired too early.
Recruiting mechanics live in mbfinotti/sales-skills@sales-hiring.
**Validate the transition month by month** (Kazanjy's ramp gates):
1. **Month 1:** onboarding. Red flag: can't absorb material.
2. **Month 2:** 10-20 first meetings, 50%+ converting to second meetings. No first meetings at all is fatal, act immediately.
3. **Month 3:** a subset reaches proposal. Meetings without progression is a coaching issue, not a hiring issue.
4. **Month 4:** meaningful closed revenue.
Named early-stage tactics worth citing instead of inventing examples:
- **Collison Install** (Stripe): close early enterprise deals by personally handling the technical implementation, removing integration risk.
- **$1 Invoice Test** (Jeff Weinstein): charge a token $1 to cross the psychological barrier of asking for money.
Treat the young motion as **source code** (Kazanjy): run small cohorts, observe what breaks, version the scripts and objection handling deliberately.
## Layering sales onto self-serve (PLG → product-led sales → enterprise)
**The dominant pattern is layering, not replacement.** Pocus's customer-base survey found 98% of PLG companies either have a sales team or plan to hire one.
The open question is _when_, never _if_ (Pete Kazanjy). Self-serve users at $19-29/month are lead generation, not the business; real enterprise revenue lives at $50K-$250K contracts. Dropbox added sales almost too late, Slack barely in time.
**Only two economically justified reasons to add sales to self-serve** (Lenny's Newsletter, "The Transition"):
1. **Penetration/expansion** - unify disparate pods of self-serve users inside one organization into a single contract (Slack/Zoom account managers). Fits multi-player products.
2. **Conversion assist** - raise conversion of high-value signups that stalled before activation. Fits when deal value justifies human intervention.
**The 4x economic test** ("will the juice be worth the squeeze"): a salesperson should deliver roughly 4x their fully loaded cost in incremental revenue. Treat ~4x as the go/no-go floor. Model it as a chain:
```
rep meeting capacity/month → monthly opportunity budget
rep cost ÷ opportunities = cost per opportunity
opportunities × win rate = wins
wins × deal value = revenue
revenue ÷ rep cost = ROI (target ~4x)
```
Kyle Poyar's caution: efficient-looking sales-assisted deals can mask a team that is a net drain. Validate that assisted conversions are _incremental_ (would not have converted anyway), not just profitable-looking in aggregate.
**Route accounts to humans on product signals, not titles alone.** Zapier's four product-qualification signals:
- Multi-player use: multiple active users on one domain.
- Usage growth over time.
- Use-case fit for assistance.
- Role fit against ICP.
Zapier found that sales touchpoints improved retention as well as upmarket conversion. The two-axis routing matrix crosses observable factors (title, company size, domain) with behavioral factors (activation depth, frequency, multi-user):
- High-observable + low-behavioral: conversion-assist outreach.
- High-observable + high-behavioral: expansion play.
- Low-observable: tech-touch only, no human.
**Bessemer's timing and sequence** for the PLG-to-enterprise layer, keyed to roughly the $25M ARR mark ("many of our highest-performing PLG portfolio companies… scale to $100 million of ARR and beyond by successfully introducing an enterprise sales engine as they passed the $25 million ARR mark"). Six tactics, deliberately in this order - build PQL scoring and pricing flexibility _before_ hiring the first enterprise sales leader:
1. Let end-users drive top-of-funnel enterprise pipeline.
2. Mine PQLs to guide direct sales.
3. Use clear heuristics to triage and scale accounts.
4. Introduce pricing/packaging flexibility.
5. Ensure the architecture supports expand-and-extend.
6. Establish cohesive hiring and comp.
Reference companies: Auth0, HashiCorp, Imply, PagerDuty, Twilio. Counter-signal both ways: operationalizing upmarket too early "can be disastrous if not executed well"; waiting too long carries its own opportunity cost.
**Re-comp before re-org** (Kyle Poyar). Keeping sales-led comp while flipping toward PLG is what makes AEs gate or sabotage the self-serve motion. The concrete fix, done _before_ the org chart changes:
- Pull AEs off sub-$25K deals.
- Shrink base 15-25%.
- Expand variable.
- Pay 1.5x-2x accelerators on expansion ARR from PQL-crossed accounts.
Plan mechanics belong to mbfinotti/sales-skills@sales-comp-design - what lives here is the sequencing rule.
**Keep the self-serve path open.** Best-in-class free-to-paid conversion is 2.5x higher when a seamless in-product upgrade/billing path exists (OpenView-era finding); its absence forces inefficient sales-assisted closes even on small accounts. The PLG + sales flywheel (Shaun Clowes): PLG feeds sales qualified leads and usage data; sales feeds back leads that aren't ready - running both is a resilience play, "very hard to knock over".
## Shifting toward enterprise
What changes structurally when the motion moves upmarket - product, narrative and buyer psychology, not just headcount:
- **Dual-track product gate** (Aparna Chennapragada) - every feature must now satisfy the end-user experience _and_ organizational governance (security, admin controls, compliance). SSO / SOC 2 / audit-logging-class features are a prerequisite for the motion, not a follow-on.
- **Narrative shift** (Geoffrey Moore) - before the chasm the pitch sells "we believe what you believe"; after it, "we need what you have" - a concrete, repeatable solution to a recognized problem. Founder vision-selling does not scale into a repeatable enterprise motion without this register change.
- **FOMO vs FOMU** (Matt Dixon) - enterprise buyers are moved by fear of messing up, not missing out; dialing up FOMO backfires in most reported cases. Counter-tactic, "pings and echoes": state a concern other buyers face at this stage and read whether the buyer confirms or refutes it.
- **Mission-First Value Chain** (Palantir-derived) - access → demonstrated value → contracts → growth, in that order; pushing sales methodology before value is established reads to the buyer like a bad first date.
- **Comp is a signal, not a fix** - a maturing land-and-expand motion outgrows the 50/50 new-logo-only plan (Sahil Mansuri: it rewards mercenary behavior at the expense of retention). Flag it, then hand design to mbfinotti/sales-skills@sales-comp-design.
## Channel / partner-led
- **Margins** (Bessemer GTM guide):
- VARs typically take 20-30% (higher in high-tax markets like India/Brazil), given **in perpetuity** for SaaS so the partner protects renewal.
- Pure resellers take 5-10% (transaction processing only), cited elsewhere at 20-40% when bundled with more.
- Referral partners take a one-time 15-30% of first-year contract value.
- **Sourced vs influenced are two metrics, never one.** Sourced = partner originated the deal (pipeline generation); influenced = partner accelerated a deal originated elsewhere. ACV drives the split: sub-$10K SMB/PLG deals run 55-75% marketing-sourced (partners mostly influence); $200K+ enterprise deals run only 15-28% sourced (partners mostly accelerate).
- **Channel CAC discipline**: channel CAC should run 20-40% below direct CAC to pay for its own margin give-up (Pacific Crest survey: up to 50% lower than field sales in the best cases). Scaling gate: partner CAC 20-40% below direct _and_ a 3:1 revenue-to-cost ratio - a positive-margin pilot alone is not enough.
- **Swim lanes before scale.** Jay Simons (Atlassian): "the direct sales motion can begin to cannibalize the opportunity for the channel partner." Agree explicit account/segment/vertical swim lanes before scaling either motion, never adjudicate deal-by-deal after conflicts start.
## Transition failure modes (all directions)
1. Running a high-touch motion under a low ACV - burns cash on deals that can never repay CAC.
2. No in-product billing path - the self-serve funnel stalls at upgrade and forces sales-assisted closes on small accounts (the 2.5x finding above).
3. Channel cannibalization - direct sales competing with partners for the same deal; fixed by swim lanes, not by escalation.
4. Premature delegation - sales hired before the founder's motion is repeatable.
5. Comp changed after the org chart - the re-comp-before-re-org rule inverted.
SKILL.md›
---
name: sales-motion
description: Chooses and designs the company-level sales motion at VP Sales / CRO altitude - product-led growth (PLG), sales-led, hybrid product-led sales, developer-led/open-source, or channel/partner-led - plus the transitions between them (exiting founder-led sales, layering sales onto self-serve, moving upmarket, adding channel), mapped to ACV, time-to-value, buyer-vs-user separation, TAM shape and procurement friction. Covers B2B SaaS and consumer self-serve motions. Use whenever the user mentions PLG vs sales-led, hiring the first salesperson, going upmarket, self-serve vs demo, or adding partners, even without the word motion. Do NOT use for org topology (mbfinotti/sales-skills@sales-org-structure) or quotas (mbfinotti/sales-skills@sales-quota-setting).
license: MIT
metadata:
author: Maya-Beth Finotti
version: "1.3.7"
---
# Sales Motion
You are a go-to-market advisor to sales leadership. Run the motion decision as a CRO would: assess motion-market fit against the company's constraints, design 2-3 candidate motions or blends, validate their economics, then plan the transition with explicit gates.
Stay at the macro altitude - this skill decides _which_ motion the company runs and how it changes, never how any deal, cadence or rep executes inside it. Designing the org that runs the motion belongs to mbfinotti/sales-skills@sales-org-structure; the quotas, comp and pipeline math built on top of it belong to their own sibling skills (see References).
## Invocation examples
Each ask enters at a different point. Run the interview first regardless.
- _"Should we be PLG or sales-led?"_ - full decision, steps 1-7.
- _"Should we add a sales team to our self-serve product?"_ - layering entry: steps 1-2 to confirm the constraints, then the layering playbook in step 6 and the 4x test in step 4.
- _"When do I hire my first salesperson?"_ - founder-led exit: step 1 decides everything; if the repeatability gate fails, stop there.
- _"Our enterprise motion isn't working"_ - diagnostic entry: rebuild the constraint map (step 2) and check the economics (step 4) against the failure modes below before proposing any change.
## Interview
Ask before proposing. One question per message; offer the multiple-choice options where given. Skip anything already answered by prior context.
1. Where is the company: (a) founder still selling, no repeatable motion yet, (b) early repeatable motion, first reps hired, (c) scaled motion being re-evaluated, (d) diagnosing a motion that is underperforming?
2. Is this B2B, B2C, or both - and what is the typical ACV or order value, and the pricing model (per-seat, usage-based, flat, transaction)?
3. Unassisted time-to-value: (a) under ~30 minutes, (b) hours to days, (c) weeks - needs configuration, integration or change management?
4. Who uses vs who buys: (a) the same person, (b) a user buying for their team, (c) a separate buyer - committee, procurement, security review?
5. TAM shape: (a) long tail of small accounts, (b) mixed, (c) few large logos?
6. What motion runs today, and what triggered this re-evaluation - plateau, board pressure, a competitor's move, upmarket pull from customers?
7. Which numbers do you actually have: CAC payback, NRR, trial or PQL conversion, win rate, fully loaded rep cost? Missing data changes how much the plan can claim.
8. By what date must the motion change show revenue effect - a board meeting, a fundraise, a fiscal year?
9. Do you want a one-off win or a compounding asset: (a) lift conversion this year with the motion as-is, (b) build the durable motion the next 3 years run on?
10. What is your effort ceiling: hires you can make, product-engineering quarters you can claim (billing paths, SSO/SOC 2), and the political capital available for re-comping or re-segmenting the field?
Re-rank the candidates against answers 8-10 before proposing anything, and say which answer moved what:
- **Hard date (Q8) inside ~2 quarters:** demotes any motion _switch_ - a real transition runs 12-24 months - and promotes the layering levers in step 6, which act inside a quarter.
- **Compounding mandate (9b):** promotes slow-building motions (developer-led, community-fed PLG, channel) despite their losing efficiency ratios on this year's revenue.
- **Low effort ceiling (Q10):** deletes the enterprise shift outright rather than demoting it - it requires the dual-track product gate and a comp redesign, and a half-funded upmarket push is the most expensive way to fail. Say what you struck and why.
## The motion menu - deliberately unranked
Five motions: self-serve/PLG, sales-led (inside or field), hybrid product-led sales, developer-led/open-source, channel/partner-led.
Do not rank this menu by efficiency - here a ranking would be false precision. A motion is selected by constraints, not preference: ACV, time-to-value, buyer-vs-user separation, TAM shape and procurement friction each _delete_ motions rather than demote them.
PLG looks like the efficient rung on paper: CAC payback of 8-12 months against 18-24 for enterprise sales-led. But it is simply unavailable past an hour of time-to-value or a committee purchase, and sales-led is unavailable below roughly $10K ACV because a rep's cost dwarfs the deal. Rank the _transition levers_ instead - step 6 does.
Blends are the norm, not the exception: most companies run 2-4 motions simultaneously, segmented by account size or packaging, and 98% of PLG companies either have a sales team or plan one (Pocus survey). The real question is rarely "which one" - it is "which blend, and which segment does each motion own".
## Brainstorm before deciding
A motion decision hardens fast - headcount, comp and product roadmaps get built on it within a quarter. Surface the assumptions first.
1. After the interview, present the constraint map (step 2) and the 2-3 candidate motions or blends it leaves alive, each with trade-offs and one explicit recommendation. Ask remaining clarifying questions one at a time - prefer multiple-choice.
2. Get explicit approval on the candidate before designing anything.
3. Build the motion plan section by section, validating each with the user before the next: constraint map → chosen blend and segment ownership → economics validation → transition plan → review triggers. A wrong constraint reading invalidates everything downstream, so never present the plan as one finished block.
4. Gate finalization on user approval of the assembled plan.
If your harness has persistent memory, store the approved decisions - chosen motion and blend, segment swim lanes, transition gates and dates, the economics assumptions - so later runs (and the sibling org/quota/comp skills) start from the recorded decision, not from scratch.
## Workflow
1. **Place the company on the founder-led ladder first.** The PLG-vs-sales-led question is not live until the founder-led motion is repeatable. The gate is repeatability, never ARR: 3-5 deals won at standard origin, price and scope, and 3 of 4 core metrics (win rate, cycle, ACV, conversion) stable for 90 days. If the gate fails, the deliverable is the path to repeatability, not a motion choice - gates, readiness checklist and first-hire profile: [motion-transition-playbooks.md](./references/motion-transition-playbooks.md).
2. **Build the constraint map.** Score the company on the five axes: ACV band, time-to-value, buyer-vs-user separation, TAM shape, procurement friction (three or more friction conditions favor sales-led). Use the ACV-to-motion table as what it is - a durable heuristic the field converges on, aggregated operator experience, not a study:
- Under $5K: self-serve.
- $5K-$10K: light-touch.
- $10K-$50K: inside sales.
- $50K-$100K+: field.
- $100K+: optionally channel-extended.
Full table, CAC ranges and the named frameworks behind it: [motion-fit-frameworks.md](./references/motion-fit-frameworks.md).
3. **Shortlist 2-3 candidates the constraints leave alive.** Design them as blends with explicit segment ownership - which motion owns which account band, and where the swim lanes sit (the Lego bricks-vs-boxes pattern: one product, self-serve for builders, sales-led for enterprise buyers). Never copy another company's motion; design from product, market and customer (Horowitz's channel design principle). Ground each candidate in a named case, not an invented one: [motion-case-evidence.md](./references/motion-case-evidence.md).
4. **Validate the economics per candidate.** Any human touch must pass the 4x test: a rep should return roughly 4x their fully loaded cost in incremental - not merely coincident - revenue. Check candidate CAC payback against the dated, by-motion bands; a channel candidate additionally needs partner CAC 20-40% below direct and a 3:1 revenue-to-cost ratio before scaling. Never blend PLG conversion metrics with sales-led win rates - the single most common benchmarking error in this field. All figures, dates and sources: [motion-benchmarks.md](./references/motion-benchmarks.md).
5. **Present the candidates and recommend one** (per the brainstorm sequence above). Name what each trade-off costs, which constraint deleted the losing options, and what new information would reopen the decision.
6. **Plan the transition with ranked levers and gates.** The dominant real-world transition is layering, not switching. When the move is PLG-adds-sales, sequence it on Bessemer's six-tactic playbook (PQL scoring and pricing flexibility _before_ the first enterprise sales leader, keyed to roughly the $25M ARR mark) and re-comp before re-org. When the entry ask is "lift free-to-paid conversion", rank the four levers by efficiency:
- efficiency: `reverse-trial packaging > PQL-routed sales assist > higher-intent signup targeting > activation rework`
- value: `PQL-routed sales assist > activation rework > reverse-trial packaging > higher-intent signup targeting`
- effort: `activation rework (a product quarter) > PQL-routed sales assist (a hire plus the 4x test) > higher-intent signup targeting (a campaign shift) > reverse-trial packaging (a pricing change, weeks)`
Default lever: **reverse-trial packaging** (~2x conversion vs freemium for a pricing change). Move up to **PQL-routed sales assist** once PQL volume lets a rep clear the 4x floor - PQLs close at 20-30% against 3-10% for MQLs, which is the whole economic case for the layer. The efficiency order starves **activation rework** - second on value, the only lever whose payoff compounds, and a full product quarter of effort; promote it anyway when trial conversion sits below the ~4-6% median despite healthy traffic, because no downstream lever fixes a product that doesn't activate.
These three orderings are synthesized from the per-lever figures, not lifted from a study that ranked them - treat them as a default, not a law, and re-rank against the interview: an org with idle product-engineering capacity gets activation rework near-free, and one that already runs a sales-assist team has already paid PQL-routed assist's main cost. Playbooks for every transition direction, including the enterprise shift and channel: [motion-transition-playbooks.md](./references/motion-transition-playbooks.md).
7. **Set review triggers and assemble the output** (shape below), run the Measurement check, and iterate until it passes. A motion is a hypothesis under review, not an identity: the 25-company evidence shows shifts in both directions, so schedule re-evaluation at each stage transition and on any threshold breach.
## B2B vs B2C
The constraint logic transfers; the machinery differs.
**Transfers, explicitly:**
- The price-to-touch economics: human sales exists only where order value or LTV covers rep cost, which is why high-consideration B2C (real estate, auto, solar, insurance) runs sales-led while low-ticket B2C is structurally self-serve.
- The time-to-value axis.
- The funnel-conversion disciplines.
- The layering logic: a consumer brand adding a concierge/assisted tier is the same 4x decision as PLG adding sales assist.
**Differs:**
- **No buying committee.** The B2C decision unit is a single buyer, sometimes a household; cycles run minutes to days, not months. The buyer-vs-user and procurement axes mostly drop out of the constraint map.
- **Lifecycle automation replaces the sales-assist layer.** Cart-abandonment flows, financing/credit qualification and in-app upgrade paths do the job PQL-routed reps do in B2B.
- **Speed-to-lead is the assisted-B2C equivalent of motion fit.** Contacting a lead within 5 minutes vs 30 makes you 100x more likely to connect and 21x more likely to qualify - Oldroyd/InsideSales.com Lead Response Management Study, 2007. Widely misattributed to a 2011 HBR piece (a separate audit that found a 42-hour average response); cite the two separately.
- **The benchmark tables don't transfer.** Everything in [motion-benchmarks.md](./references/motion-benchmarks.md) is B2B SaaS data; validate a B2C motion against the company's own funnel history and say so in the plan.
## Motion plan output shape
```
CONTEXT: stage on the founder-led ladder · current motion · trigger for re-evaluation
CONSTRAINT MAP: ACV band · time-to-value · buyer-vs-user · TAM shape · procurement friction · which motions each axis deleted
DECISION: chosen motion/blend · segment ownership and swim lanes · named case grounding it
ECONOMICS: 4x test result · CAC payback vs by-motion band (dated, sourced) · channel gates if applicable
TRANSITION PLAN: sequence with gates and dates · ranked levers chosen and why · re-comp/product prerequisites
RISKS: applicable failure modes · what would falsify the decision
REVIEW: threshold triggers · next scheduled re-evaluation
```
## Failure modes
- **High-touch under low ACV** - deals that can never repay CAC. Fix: return to the constraint map; below ~$10K ACV the rep math does not work.
- **No self-serve billing path** - the funnel stalls at upgrade and forces assisted closes on small accounts; a seamless in-product path carries 2.5x better free-to-paid conversion.
- **Channel cannibalization** - direct sales and partners competing for the same deal. Fix: swim lanes agreed before scale, never deal-by-deal adjudication.
- **Premature delegation** - sales hired before the founder's motion is repeatable; breaks the market-feedback loop. Fix: the step-1 gate.
- **Hiring a sales leader instead of executors** - a leader scales a motion; only executors can originate one that doesn't exist yet.
- **Comp changed after the org chart** - AEs gate or sabotage the new self-serve motion. Fix: re-comp before re-org.
- **Cross-motion benchmarking** - grading a PLG funnel against sales-led win-rate medians, or an SMB motion against enterprise NRR. Segment effects are not motion-quality signals.
- **Anchoring on pre-2022 benchmarks** - CAC payback, quota attainment and win rate have all drifted worse since 2022 and keep moving. A plan graded against an old number looks broken next to the current median; pull the dated figures from [motion-benchmarks.md](./references/motion-benchmarks.md) rather than recalling one from memory.
- **Copying a mythologized case** - "Atlassian never had sales" is false (first commissioned salespeople in 2014); Cursor's ARR figures are press-reported, not audited. Cite cases from [motion-case-evidence.md](./references/motion-case-evidence.md) with their caveats.
## Measurement
The plan is not done until all of these pass; iterate until 100%:
- The constraint map states all five axes and names which motions each axis deleted.
- Every benchmark figure carries its year and source; no pre-2022 figure appears without its current counterpart.
- The ACV-to-motion mapping is labeled a heuristic, never presented as study output.
- Every human-touch element shows a 4x test result; every channel element shows the CAC and 3:1 gates.
- The transition plan has dated gates, and any ranked menu shows its efficiency lines with deleted options named as deleted.
- Review triggers and the next re-evaluation date are written into the plan.
Outcome KPIs to track after the decision ships - against the motion's own band, never another motion's:
- CAC payback vs the by-motion band; trending past 24 months triggers a fix before further spend.
- Magic number; below 0.5 for two consecutive quarters signals cost-of-sales inefficiency.
- NRR vs the segment median (~118% enterprise / ~108% mid-market / ~97% SMB); below 100% for an enterprise vendor is structural.
- For a layering transition: PQL-to-close vs the 20-30% band, and incrementality of assisted conversions - not just their volume.
## References
- mbfinotti/sales-skills@sales-comp-design for the pay mix the motion implies - PLG vs enterprise pulls it in opposite directions, and the re-comp-before-re-org rule lands there.
- mbfinotti/sales-skills@sales-pipeline-coverage-modeling for pipeline math inside a sales-led or hybrid motion; the motion decides which segment band and cadence apply, and PLG conversion metrics must never be blended into its win-rate-based coverage ratios.
- mbfinotti/sales-skills@sales-hiring for recruiting the pioneer sellers and enterprise reps a transition calls for.
- mbfinotti/sales-skills@sales-icp-definition for the ICP the motion serves - the constraint map consumes it.
- mbfinotti/sales-skills@sales-market-sizing for the TAM estimate behind the TAM-shape axis.
- mbfinotti/sales-skills@sales-account-segmentation for the per-segment motion map - a company running different motions by segment needs the segment model before it can assign one to each.
- See [./references/motion-fit-frameworks.md](./references/motion-fit-frameworks.md) for the named frameworks, the ACV heuristic table and the constraint axes.
- See [./references/motion-benchmarks.md](./references/motion-benchmarks.md) for every dated benchmark, the decision thresholds and the source catalogue.
- See [./references/motion-transition-playbooks.md](./references/motion-transition-playbooks.md) for the founder-led exit, PLG-layering, enterprise-shift, and channel playbooks.
- See [./references/motion-case-evidence.md](./references/motion-case-evidence.md) for the named cases in both directions and the survivorship caveat.