Lumana Case Study: 41 Meetings in the First Month, 3x More Qualified | Floqer
How Lumana's GTM team used Floqer to replace manual research with an automated motion that booked 41 qualified meetings in the first month
A conversation with
Omri Orgad
VP of GTM Engineering
Philip Arbeiter
Head of Sales Development
Idan Spiegler
Lead Intelligence and Pipeline Ops
Molly Young
Senior Manager of RevOps
At a glance
Lumana, an AI video security platform, used Floqer to automate account research and Salesforce enrichment across K-12, higher education, and senior living. In the first month, Lumana booked 41 qualified meetings (roughly 3x its prior monthly rate), enriched 10,000+ accounts, cut pre-call research from 15-20 minutes per account to zero, and saved $50K+ on event attendee lists.
| Metrics | Values |
|---|---|
| Meetings Booked in First Month | 41 |
| Accounts Enriched | 10K+ |
| Minutes of Manual Pre-Call Research | 0 |
| Active Workflows Running | 4 |
About Lumana
Lumana is an AI-powered physical security platform that helps organizations monitor, manage, and respond to security events across multiple sites using intelligent video analytics. Their platform is built for multi-location environments: K-12 schools, higher education campuses, senior living communities, and enterprise facilities, where security complexity scales with every new building added.
The Challenge
Before Floqer, Lumana's research process looked like this:
On the rep side: before any cold call or discovery, an SDR would open four or five browser tabs, which took about 15 minutes. They had to piece together information about recent news, the prospect's website, incident reports, and procurement portals.
On the ops side: RevOps was manually classifying accounts in Excel, which was time-consuming and inaccurate, creating inefficient territory assignments.
- Reps burning 15-20 minutes per account on pre-call research
- Inconsistent research quality
- Cold calls without context
- CRM fields half-filled
The Fix
1. ABM Scoring
Floqer built an ABM scoring workflow that autonomously researches each account before a rep ever sees it, prioritizing high-fit opportunities.
2. CRM Maintenance & Automated Account Scoring
Floqer runs every account through automated enrichment, providing complete profiles without manual input.
3. Event List Building
Floqer automates the process of building attendee lists from LinkedIn activity, saving costs on manual research.
4. Automated Outbound Sequencing
Floqer's sequencing tool identifies target personas, enriches contacts with relevant information, and automates outreach.
Before and After Floqer
| Metric | Before | After |
|---|---|---|
| Pre-call research | 15-20 minutes per account | 0 minutes; security context lands in Salesforce automatically |
| Industry classification | Manual, in Excel | Automatic vertical classification |
| Event lists | Purchased lists | Built from LinkedIn signal activity; $50K+ saved |
| Qualified meetings | Roughly a third of today’s rate | 41 in the first month, 3x the prior monthly rate |
The Results
In its first month running Floqer, Lumana booked 41 qualified meetings, enriched more than 10,000 accounts and 100,000 contacts, and saved over $50,000 on event attendee list purchases.
What's Running Now
| Workflow | Status |
|---|---|
| ABM Account Scoring | Live |
| CRM Enrichment & Account Scoring | Live |
| Event List Building | Live |
| Automated Outbound Sequencing | Live |
| SFDC Adhoc Enrichment Button | In Build |
| Intent Integration | Roadmap |
| GovSpend & Pursuit SLED Research | Roadmap |
Why It Worked
Floqer automated the research process that traditional databases could not handle, providing essential security data directly in Salesforce before any call is made.