Sales ops · Production

Flock Safety uses Pursuit to detect leadership changes and speed public-sector prospecting

The problem

Flock Safety's reps lost momentum when outreach bounced because public-sector leaders had moved on, and sales ops depended on manual LinkedIn updates to detect departures. RevOps lacked a scalable way to maintain contact coverage or leverage public records for targeted outreach.

First attempt

The prior approach relied on manual feedback and LinkedIn updates to detect when key public-sector contacts had left, which slowed or stalled deals.

Workflow diagram · grounded in source
1
Leadership change flagged
ai_action
“Pursuit continuously flags silent leadership and staff changes—beyond what shows up in press—so reps aren't the last to know when a key decision maker moves on”
2
Radar signal list pull
integration
“Product-specific Radar profiles let reps pull instant, relevant account lists (e.g., LPR, drones) tied to real signals from council agendas, strategic plans, FOIA purchase data, and more—fueling precise, empathetic outreach”
3
Salesforce enrichment write-back
integration
“Pursuit's enrichment writes to mapped custom fields without overwriting Flock's existing sources, passes strict security review, and mirrors internal filters/territories”
4
Rep works the list
output
“Reps "get that list and immediately work through it," using agency-specific context (e.g., rising vehicle theft in council notes) to become trusted partners earlier in the cycle”
Reported outcome

Pursuit reaches sub-1% bounce rates in production, reducing dead-end outreaches, speeding prospecting through agency-specific signals, cleaning CRM data in Salesforce, and improving forecast accuracy for RevOps.

Reported metrics
Bounce rate in productionsub-1%
Dead-end outreachesreduced bounce-backs
Time to become trusted partnera lot quicker
Forecast accuracyimproved forecast accuracy
Reported stack
PursuitSalesforce
Source
https://www.pursuit.us/case-studies/flocksafety
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Pursuit reaches sub-1% bounce rates in production, reducing dead-end outreaches, speeding prospecting through agency-specific signals, cleaning CRM data in Salesforce, and improving forecast accuracy for RevOps.

What tools did this team use?

Pursuit, Salesforce.

What results were reported?

Bounce rate in production: sub-1%; Dead-end outreaches: reduced bounce-backs; Time to become trusted partner: a lot quicker; Forecast accuracy: improved forecast accuracy (source-reported, not independently verified).

What failed first in this deployment?

The prior approach relied on manual feedback and LinkedIn updates to detect when key public-sector contacts had left, which slowed or stalled deals.

How is this sales ops AI workflow structured?

Leadership change flagged → Radar signal list pull → Salesforce enrichment write-back → Rep works the list.

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