Growth-stageCybersecurity
Splitting systems delay from human delay: a working-hours speed-to-lead SLA
A one-hour SLA that actually runs
A one-hour SLA that actually runs
Leadership wanted to know whether inbound leads were being worked at all. There was no defined SLA, reps had blanket "try to get to your outreach within an hour" guidance with no enforcement and no measurement.
Pulled 90 days of leads out of the marketing platform across four cohorts, demo requests, contact-us form fills, free-trial signups, and purchased list pulls, and unified roughly ten thousand records into a single evaluation dataset with 26 calculated columns.
Elapsed time was recalculated against a defined working window so a lead arriving in the evening didn't get charged for overnight. Records were flagged as after-hours and as delayed-engagement (first touch on a different calendar day than creation).
A missing-pursuing flag distinguished leads old enough to have been worked but with no first-touch activity recorded (a real coverage problem) from leads that were simply too recent to judge.
OutreachResponse time was moved off the sequence-start trigger and onto an SDR-last-activity-date stamp fed by four channels: an active outreach sequence, calls placed through the dialer, LinkedIn Sales Navigator activity, and manually logged activity. The marketing automation user was explicitly excluded so nurture email could not fake a first touch.
The routing platform's first-response timer became the SLA primitive, with per-user business-hours availability configured so the clock only runs when the rep is working. Target: one hour on MQLs during business hours, with a 24-hour fallback for off-hours and weekend arrivals. Demo requests and free-trial fills were designated highest priority.
No SLA was placed on list-pull and scaled prospecting work, different reps batch their prospecting on different days and a timer would have penalized legitimate workflow variance.
Six-row CRM dashboard: executive KPIs (average speed to lead, average systems delay, average human delay, SLA hit rate); weekly trend lines for speed to lead and SLA hit rate; per-rep SLA hit/miss and average human delay; breakdowns by lead type; a systems-delay diagnostics row including marketing-platform-to-CRM sync time by week.
A one-hour SLA that actually runs
Live in production, calculated inside business hours, with breach alerts routed to both the assigned rep and their manager.
A defensible baseline instead of an argument. The 90-day study produced median response time by lead source, a bounded outlier definition at roughly six hours, and a coverage number for how many leads had no logged first touch at all.
5 steps
Deciding which system owns the MQL, and making the number defensible
A lead count marketing reports on
Lead routing and speed to lead
+1
6 steps
From an empty CRM to enrichment, territories and a live lead-routing engine
Full account base enriched
Attribution
5 steps
Rebuilding a channel taxonomy and the MQL workflows that were never firing
Channel taxonomy rebuilt
