This page is a catalog, not a brochure. Each example lists the trigger that fires it, the condition logic that gates it, the action chain that runs, the measured impact against the baseline, and the failure modes a RevOps lead should know about before shipping.
The inbound funnel is where speed matters most. These five flows cover the common inbound motions: web form routing, chatbot handoff, inbound-call context, event lead ingestion, and dormant re-engagement. Each is a template a team can fork and configure in under an hour.
Trigger: lead-created event from an inbound web form webhook. Condition: company size over 50 employees, country in {US, CA, UK, AU}, source utm_medium not in paid-social (which routes to BDR instead). Action: round-robin pick from AE pool filtered by territory, create first-touch task due in 1 hour, send Slack ping to the AE channel. Measured median form-submit to AE assignment dropped from 11 hours manual to 42 seconds across 19 sampled tenants.
Trigger: webhook from the chatbot vendor after qualification form completion. Condition: budget tier marked over $25K, decision timeline under 90 days. Action: upsert the contact and account with the chat context, enroll in the hot-inbound sequence, assign to the AE currently available (presence API check against Slack), create a 30 minute meeting hold on the AE calendar. The flow turns a qualified chat into a live conversation inside 4 minutes end to end.
Trigger: inbound-call ring event from Strkr Messaging. Condition: caller ID matches a known contact. Action: resolve the record, pop the context card to the owner (or route to the pool if owner is on another call), log the connect metadata on hangup, run Strkr AI call-summary on the transcript, write the summary and the next-step suggestion to the record timeline. The flow covers the full inbound receive loop without rep typing.
Trigger: inbound CSV from the event-platform export API. Condition: email domain not already on an account. Action: upsert the lead, enrich via the ICP data provider, enroll in the matching event-followup sequence (which varies by event tier), create a Monday-review task on the owner. Three team members handle 1,400 event leads in an afternoon versus a prior pattern of three days of manual data entry.
Trigger: scheduled daily. Action: query leads with no activity in 180 days and status Open, enroll in a reactivation sequence that opens with an industry research piece, flag the lead with a reactivation badge for 30 days to prevent duplicate enrollments, create a Monday rollup task for the BDR manager. One sampled tenant generated 11 reopened opportunities in the first quarter from previously-dormant records.
Trigger: lead-created event. Condition: Strkr AI spam-classifier score over 85 on the form content, or email domain matches the suppress list, or phone number pattern matches known spam signatures. Action: mark the lead as spam-suspected, write to a review queue instead of sales, notify the ops lead if the queue grows past 50 in a day. Prevents real reps from wasting a cycle on garbage inbound.
Pipeline hygiene is the Monday problem. A manager wants to know which deals moved, which went stale, which deserve attention this week. These four flows automate the detection; the manager spends the saved time on actual coaching conversations.
Trigger: scheduled Monday 7 AM in tenant timezone. Action: iterate open opportunities, apply condition last-activity-older-than-14-days AND stage not in {Prospecting}, create a review task on the owner, if the owner has 10 plus idle deals also notify their manager. The sweep runs before standup; managers see the Monday idle list fresh for the team meeting.
Trigger: scheduled daily. Action: iterate open opportunities, apply condition days-in-current-stage over stage-defined threshold (Discovery 14d, Proposal 21d, Negotiation 10d), create a review task if the first stuck, notify manager if stuck twice in a row. Teams see stage velocity improve by 20 to 30 percent inside the first quarter of running the alert.
Trigger: scheduled Monday 6 AM. Action: calculate pipeline coverage per rep (open pipeline value divided by remaining-quarter quota), condition on coverage under 3x, create a 1:1 agenda item for the manager on the rep. The ratio surfaces as a manager-dashboard widget; the automation ensures the number lands in the coaching conversation rather than quietly sitting in a report nobody opens.
Trigger: scheduled daily. Action: iterate opportunities with close-date in the past but stage not Closed Won or Closed Lost, flag as date-stale, create an update-close-date task on the owner. Managers avoid the quarter-close surprise of a deal pushed six times without the forecast reflecting it.
Trigger: opportunity owner-changed event. Action: notify the new owner on Slack with the account context, create a handoff task on the previous owner, create a one-week welcome task on the new owner. The flow prevents the common I did not know this was mine friction after a territory shift or an offboarding reassign.
Trigger: opportunity stage changed to Proposal or later. Condition: opportunity has fewer than 2 linked contacts, or no decision-maker role present. Action: create a stakeholder-coverage task on the owner, flag the opportunity in the manager pipeline review widget. Enterprise sales teams avoid losing a deal because single-threading went unnoticed until too late.
The lifetime value curve bends on renewal and expansion. These three flows pull signal from product usage, support tickets, and executive-sponsor churn into the CSM dashboard before the quarterly review would surface it.
Trigger: account health-score field changed. Condition: delta more negative than minus 15 points over 7 days. Action: create a risk-review task on the CSM, notify the manager if the health drop coincides with a renewal within 60 days, enroll in the save-play sequence. Sampled tenants caught churn risks sixty days earlier than they used to on the quarterly-review cadence.
Trigger: contact-updated event. Condition: contact role in {Champion, Economic Buyer, Executive Sponsor} AND status changed to Inactive or employer changed. Action: flag the parent account on the risk dashboard, create a stakeholder-rebuild task on the account owner, notify the exec sponsor at Strkr for strategic accounts. Captures a leading indicator that pure product-usage signal would miss.
Trigger: scheduled daily. Action: iterate accounts with renewal date within 90 days, create a renewal-review task on the CSM, enroll in the renewal-prep sequence (which varies by tier), set the account to a renewal-active status that shows on the pipeline. The runbook turns renewal from a quarterly scramble into a scheduled, visible, measurable motion.
Trigger: product-usage event (seats-added, feature-adopted) over threshold. Condition: no open expansion opportunity on the account in last 60 days. Action: create a draft expansion opportunity, enroll in the expansion-play sequence, create a check-in task on the AE. The flow turns usage signal into a pipeline-tracked motion rather than a lost opportunity.
Trigger: support ticket priority changed to Critical. Condition: account tier Enterprise or ARR over $100K. Action: notify the CSM on Slack, create a status-check task, flag the account on the risk dashboard until ticket resolved. Prevents a bad week on support from becoming a bad quarter on renewal.
Trigger: NPS response received. Condition split: Promoter triggers an advocate-nurture enrollment plus a referral-ask task; Passive triggers a feedback-call task on the CSM; Detractor triggers an immediate escalation to the CSM manager plus a leadership review flag. One trigger drives three outcome paths through a branch node.
Operations work is invisible when it works. These three flows automate the glue that keeps a team shipping: deal-close handoff, invoice generation, approval routing.
Trigger: opportunity stage changed to Closed Won. Action: create an onboarding project, notify the success manager on Slack, generate the counter-signed PDF via Strkr document automation, send the welcome kit email, mark the account as paying-customer status. The transition that used to require eleven manual steps becomes one stage change plus a fan-out flow.
Trigger: project milestone marked Complete AND milestone has invoice-generation flag set. Action: generate invoice PDF from the Strkr document template, send to the billing contact via email, create an AR-followup task if unpaid at 15 days, log the invoice on the account billing tab. One flow replaces the manual invoice-generation sequence from spreadsheet to PDF to email.
Trigger: opportunity discount-percent field exceeds 15 percent. Action: pause for approval from the AE manager (for 15 to 25 percent) or the VP (above 25 percent). On approval, continue the flow to proposal generation. On rejection, send the AE a notification with the reason. Human-in-loop step keeps compliance on policy without rep manual escalation routing.
Trigger: user-created event. Condition: role in {AE, BDR, SDR, CSM}. Action: create a 30 day onboarding project with 24 pre-defined tasks (certification checks, system access verifications, mentor assignments), notify the manager on Slack, enroll in the new-hire email sequence. Replaces a 40 minute manual setup per new hire with a 2 minute flow.
Trigger: scheduled weekly. Action: iterate contacts, apply conditions for missing-title OR missing-email OR missing-phone, create a data-completion task on the owner batched by rep so each rep sees one task listing the records to update. Cleaner data in two months without the quarterly data cleanup project nobody wants to own.
Trigger: scheduled daily. Action: iterate accounts with contract-end-date in {30, 60, 90} days, create tiered reminder tasks on CSM, enroll in the renewal-countdown sequence, generate a renewal-prep doc from the template on day 90. One flow handles the full renewal timeline without a CSM maintaining a side calendar.
Not every automation example in a vendor demo applies to a team. The examples above work consistently because they share a set of structural properties: clear trigger, bounded condition, limited action chain, measurable outcome. Patterns that lack those properties tend to fail in production.
The best automations fire on a event (lead created, stage changed, task completed). Scheduled sweeps over the full database tend to run slow and surface too many false positives. When a scheduled flow is required (Monday hygiene, renewal watch), the inner condition should be tight enough that fewer than 5 percent of records qualify on any given run.
Condition trees with more than five clauses tend to break on edge cases nobody tested. The simpler the condition, the fewer the production surprises. If the real logic needs fifteen clauses, split into three flows with simpler conditions and chain them through state transitions on the record.
Long action chains amplify small failures. A chain of 20 actions has 20 possible failure points; one error strands the record mid-chain. The best examples run three to five actions, with longer motions split into multiple flows that pass state via record fields or linked record creation.
Every example above ties to a measurable: time-to-assign on inbound, stage-velocity on pipeline, 90-day leading indicator on renewal, close-date accuracy on forecast. Automations without a measurement tend to drift into we built this but no one checks it status within six months. The number keeps the flow honest.
A flow that references a deleted field or hits an external 500 should write a dead-letter entry visible on the admin dashboard, not fail silently. The examples above all respect this posture: the ops lead sees Monday failures on Monday and fixes them before standup. Silent failure is the single worst outcome in automation ownership.
Writes from a flow should carry a flow-attribution tag on the audit log so a bad batch can be unwound by querying the attribution and reversing. The examples above produce field changes, task creations, and sequence enrollments; each is reversible by the same mechanism. Destructive operations (delete, archive) require manual approval even inside an automated flow.
Share which of the twenty-four flows above fits your motion and bring a sample record. We will configure the flow live and test against the record on the call.
Yes. Each example above ships as a reference template inside the Strkr Flow gallery. A RevOps lead opens the gallery, picks an example, and the template loads onto the canvas with the trigger wired, condition tree in place, action chain configured, and placeholder text where tenant-specific values go. The fork takes two to five minutes to adapt and publish; the heavy work of the flow design is already done.
Flows that share a trigger (both fire on lead-created, for instance) run independently; one does not block the other. If both flows try to write the same field with different values, the later-finishing flow wins the write under the standard last-writer-wins database semantics. Teams expecting coordination between flows should chain explicitly: the first flow writes a state field, the second flow triggers on that state change. The pattern avoids the implicit race condition.
Real tenants. The sampled impact numbers (42 seconds assignment time, 20 to 30 percent stage velocity improvement, 60 days earlier risk detection) come from a cohort of 19 Strkr tenants running the flow for at least one quarter. The sample is small enough that we do not claim statistical significance across the industry; it is specific enough to serve as a baseline for teams evaluating the pattern. Your mileage will vary based on prior baseline and discipline.
Pro and Scale tier tenants typically run between 40 and 120 production flows simultaneously without hitting any run-volume ceiling for mid-market usage. Starter tier caps at a lower run volume suitable for small-team pilots. Teams that approach the run-volume ceiling usually consolidate onto Strkr from middleware tiers precisely because the per-seat line is predictable at scale; the tier limits are documented on the pricing page.
Yes. Every published flow version is editable; saving creates a new version and the diff view shows exactly what changed. Published flows continue running the old version until the new version is explicitly promoted to live. The pattern lets a team iterate on a flow configuration without disrupting records mid-flight. Rollback is one click.
The flow run history shows every evaluation: trigger match or no-match, condition evaluation result, action results per step. A flow that is not firing when expected almost always falls into one of three buckets: the trigger did not match (the event never emitted), the condition evaluated to false (common when a field is null where the condition expected non-null), or the action chain was gated upstream. The run history disambiguates in under a minute.
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