Gap plays

Each play closes a specific gap. Pick it when its trigger matches a gap in the interview and its roles include the leader's function. "A gap on Q11" means the answer to Q11 sat below the first option; prefer gaps where the answer was one of the last two options.

Every play has the same parts: what it is, what good looks like, an example, and the result to check in 30 days. In the readout, rewrite the example in the leader's own context: their motion, their systems, their number.

Pipeline creation

1. Visitor-to-meeting

• Roles: marketing, RevOps, sales. Trigger: a gap on Q11 or Q6.
• What it is: identify visiting companies, check them against the ICP, and route each to the owning rep with a researched brief and a drafted first touch.
• Good looks like: every ICP visit becomes a rep-ready account within an hour.
• Example: a target account's VP of Finance reads the pricing page and two case studies on Tuesday morning. By 11am the AE has a brief (the company just opened a second office, the VP joined four months ago) and a two-line note to approve.
• In 30 days: response time from visit to first touch, measured weekly, and the meetings it produced.

2. Same-day event and webinar follow-up

• Roles: marketing. Trigger: a gap on Q13.
• What it is: attendee list in, enriched, one verified company fact per person, follow-up routed by role for the rep to approve.
• Good looks like: follow-up goes out the same day, and replies are tracked to pipeline.
• Example: the webinar ends at 1pm. By 5pm the 40 attendees from target accounts each have a note referencing what they asked in the Q&A, approved by their rep; the other 160 get a useful recap.
• In 30 days: one event followed up the same day, with reply and meeting rates against the last event.

3. Buying-group signal view

• Roles: marketing, RevOps. Trigger: a gap on M6 or Q6.
• What it is: person-level activity resolved into account, role, buying group, stage and next action, without raw intent noise.
• Good looks like: the team sees which accounts are actually in market, and who in them is moving.
• Example: instead of three separate alerts about three people, marketing sees "Account Y: champion, economic buyer and a new IT lead all engaged in 10 days; stage: evaluating."
• In 30 days: a weekly list of in-market accounts that sales agrees is right.

4. Signal-ranked account queue

• Roles: sales. Trigger: a gap on S2 or Q1.
• What it is: signals back-tested against recent wins drive a daily ranked queue with the reason to act now.
• Good looks like: reps start each day on the accounts most likely to move, and can see why.
• Example: the morning queue opens with "Account X: new CRO three weeks ago, lost to timing nine months ago, two visits to the integrations page. Call today."
• In 30 days: meetings booked from the queue against meetings from static lists.

5. Pipeline ownership model

• Roles: sales, founder. Trigger: a gap on S1.
• What it is: named owners and targets by segment and channel, reviewed weekly against contribution.
• Good looks like: everyone knows which pipeline is theirs to create.
• Example: mid-market pipeline is 60% BDR-sourced and 40% AE-sourced, with named accounts per person and a 20-minute weekly review of contribution against target.
• In 30 days: one month of weekly contribution reviews, and no "everyone prospect" week.

6. Speed-to-lead

• Roles: marketing, sales. Trigger: a gap on M7 or M2.
• What it is: every lead marketing hands over is researched, routed and followed up within the hour with a drafted first touch, and tracked.
• Good looks like: no lead waits more than an hour, and the report shows it.
• Example: a demo request comes in at 3:10pm; the rep sends a researched note at 3:35pm. A lead that sits for 45 minutes pings the rep's manager.
• In 30 days: the share of leads worked within the hour, by rep, every week.

Making best practice runnable

7. Top-rep method as a shared workflow

• Roles: sales, founder. Trigger: a gap on S6.
• What it is: capture how the best rep researches, qualifies and writes, as a workflow every rep runs on every account.
• Good looks like: new reps produce top-rep quality research in their first week.
• Example: the top AE's habit of checking the prospect's last earnings call and recent hires becomes the first step of every account brief, for everyone.
• In 30 days: the next new hire's first-week briefs, compared side by side with the top rep's.

8. Self-serve workflows with guardrails

• Roles: sales, RevOps, marketing. Trigger: a gap on Q10, or N3 shows one builder doing everything.
• What it is: operators describe a play in plain language and get a working workflow inside approved permissions and approval gates.
• Good looks like: the people who own a motion can change it without a ticket.
• Example: the CS lead builds a "champion left" play from an approved template; RevOps reviews what it can write, not how it works.
• In 30 days: three plays live that were built outside RevOps.

9. New-motion launcher

• Roles: RevOps, founder. Trigger: a gap on Q5.
• What it is: segment, signal, sequence and routing defined once and launched as a trigger, not a project.
• Good looks like: a new motion launches in days.
• Example: leadership decides on Monday to target newly funded companies; by Thursday the signal, routing, messaging and reporting are live, reusing parts from the inbound play.
• In 30 days: one motion launched in under a week, and a list of the reusable parts it used.

10. Brand-safe AI content

• Roles: marketing. Trigger: a gap on M5.
• What it is: a versioned positioning and claims library every content workflow is checked against before publishing.
• Good looks like: AI content sounds like one company and never makes a claim legal has not approved.
• Example: a draft says "50% faster onboarding"; the check flags it because the approved claim is "live in two weeks".
• In 30 days: the library exists, and a sample of 20 outputs has been checked against it.

The shared layer

11. One shared account record

• Roles: all. Trigger: a gap on Q7.
• What it is: one account record with ICP fit, history, signals and promises that marketing, sales, CS and RevOps all read and write.
• Good looks like: every handoff carries full context, without a meeting.
• Example: the CSM opening a new customer sees why marketing targeted them, what sales promised and who signed, in one place.
• In 30 days: the minimum shared record defined, with owners, and the two systems that lose the most context connected.

12. Move the logic to one place

• Roles: RevOps, founder. Trigger: the logic test showed logic split across systems.
• What it is: take the motion from the logic test, write its qualify, score, route and assign rules down in one place, and make every system execute that one definition.
• Good looks like: the owner of the motion can change it in a day.
• Example: inbound scoring moves out of the marketing automation tool and qualification out of a CRM workflow into one definition; the demand gen lead changes a threshold on Tuesday and it applies everywhere on Wednesday.
• In 30 days: one motion running from one definition, and one change shipped by its owner.

13. Evidence-backed CRM writeback

• Roles: RevOps, sales. Trigger: a gap on Q15, S4, R1 or R3.
• What it is: call and signal outputs enter the CRM through staging, with source, timestamp, confidence and deduplication.
• Good looks like: a CRM you would put in a board deck without a cleanup week.
• Example: an enrichment tool's guess at a new title waits in staging instead of overwriting the title the AE confirmed on a call last week.
• In 30 days: one noisy source routed through staging, and a before-and-after count of bad writes.

14. A clear line between agent work and human work

• Roles: sales, all. Trigger: a gap on S3 or N5.
• What it is: every step in the motion classified as automatic, approval-required or human-only, by risk and buyer impact.
• Good looks like: reps trust what runs on its own and know exactly what they own.
• Example: research and CRM logging run on their own; first touches to new prospects need one-click approval; pricing, negotiation and anything sent to an open opportunity stay human.
• In 30 days: the classification written down for one motion and in use.

Customers

15. Expansion signals to the CSM, with full history

• Roles: customer success, sales. Trigger: a gap on Q21 or Q22.
• What it is: usage, hiring, new-exec and champion-move signals routed to the CSM with the deal, promises and tickets in one brief.
• Good looks like: expansion conversations start informed.
• Example: a customer reaches 90% of their seats and posts two jobs for the team that uses the product; the CSM gets both, with the renewal date and the original business case.
• In 30 days: expansion conversations started from signals, and the pipeline they created.

16. Renewal-risk watch, 90 days out

• Roles: customer success. Trigger: a gap on Q23.
• What it is: usage drops, champion departures and support sentiment watched per account, with a play launched at 90 days.
• Good looks like: every renewal has a risk read before the call.
• Example: four months out, usage drops 30% and the champion changes jobs; a re-onboarding play starts before the customer says anything.
• In 30 days: the warning signals tested against the last ten renewals, and a play attached to each risk type.

17. Sales-to-CS handoff brief

• Roles: customer success, sales. Trigger: a gap on Q24.
• What it is: the deal record, call notes and promises turned into a handoff brief the moment a deal closes.
• Good looks like: no CSM ever asks "what did we promise?"
• Example: the deal closes Friday; Monday the CSM reads "promised SSO by end of Q2", linked to the call where it was said.
• In 30 days: every deal closed this month has a brief, and the CSMs say it was right.

18. Customer value story

• Roles: customer success. Trigger: a gap on C2.
• What it is: usage and outcome metrics produce a customer-specific value summary for lifecycle touches and QBRs.
• Good looks like: every customer sees their own results before renewal.
• Example: sixty days before renewal, each customer gets a one-page summary of what they achieved, built from their own usage and reviewed by the CSM.
• In 30 days: value summaries sent to one cohort, and the CSMs' read on how they landed.

19. One retention model

• Roles: customer success, RevOps. Trigger: a gap on C1.
• What it is: renewals, expansions, contractions and churn modeled once and reconciled across the CRM and billing.
• Good looks like: one retention number everyone trusts.
• Example: finance and CS bring the same net revenue retention number to the board meeting, without a reconciliation call.
• In 30 days: canonical post-sale events defined and last quarter's renewals reconciled.

Running AI in production

20. Production gate for AI workflows

• Roles: all. Trigger: J1 at AI as an action engine or above, or a gap on N3.
• What it is: inventory the live AI workflows and give each an owner, a test set, an approval threshold, a rollback and a cost ceiling.
• Good looks like: every AI workflow in production has an owner and an off switch.
• Example: a one-page list of the eleven agents running today, each with a named owner, what it is allowed to do, and how to turn it off.
• In 30 days: the inventory done, and ownerless workflows either adopted or paused.

21. Change-control checks

• Roles: RevOps, founder. Trigger: a gap on N2.
• What it is: test cases run automatically when models, prompts, schemas or vendor APIs change.
• Good looks like: breakage is found by a test, not by a customer.
• Example: a model update changes how first-touch emails open; twenty saved real cases catch it the same day.
• In 30 days: a test set for the most important workflow, run on every change.

22. AI unit economics

• Roles: founder, RevOps, customer success. Trigger: a gap on N4, E1 or E4.
• What it is: cost per run tied to accepted outputs, meetings, opportunities, saves and expansions.
• Good looks like: a cost-per-outcome number ready for the next budget review.
• Example: the event follow-up workflow has a known cost per approved email and per meeting, shown next to the cost of an SDR doing the same work.
• In 30 days: cost per outcome measured for one workflow.

23. AI-to-revenue proof

• Roles: founder, marketing. Trigger: a gap on N6 or Q12.
• What it is: one workflow measured against a baseline or a holdout, through to pipeline and revenue.
• Good looks like: a defensible line for the board instead of activity counts.
• Example: half the territories run the new outbound workflow for a quarter and half do not; the difference in meetings and pipeline is the number that goes to the board.
• In 30 days: the baseline and comparison method set before the workflow scales.

24. Data access policy for AI

• Roles: all. Trigger: a gap on N1.
• What it is: data classes, least-privilege access and audit logs defined for each AI workflow.
• Good looks like: security signs off once, not per tool.
• Example: the renewal agent can read usage and tickets but not billing; security approved the classes once, and the log shows every read.
• In 30 days: one workflow's data classified, with access trimmed to its purpose.

25. Explainable recommendations

• Roles: sales, RevOps, customer success. Trigger: a gap on N7.
• What it is: every AI recommendation carries its sources, their dates, a confidence level and the reason for the action.
• Good looks like: a rep can agree or disagree with a recommendation in ten seconds.
• Example: "Call Account X this week" arrives with the three signals behind it, dated and linked, and a button to flag it as wrong.
• In 30 days: evidence attached to one recommendation workflow, and a count of flags.

26. Headcount versus agents plan

• Roles: founder. Trigger: a gap on E4.
• What it is: the next hire's week mapped into tasks, the tasks agents cover removed, and the human role redefined.
• Good looks like: a hiring plan the board understands.
• Example: before opening two SDR roles, leadership maps an SDR's week, sees research and list building are covered by agents, and hires one SDR focused on live conversations.
• In 30 days: the model built for the next open role.

When there is no clear gap

Say in one line that the basics are in place, then pick from plays 20 to 25. At 04 Shared AI layer the work is keeping production AI owned, tested and measured.