A conversation with
Last Updated
02.09.2026
Industry
Artificial Intelligence / Data Infrastructure
CRM
Hubspot
Team
Sarah+RevOps
Structured’s RevOps team was operating inside a CRM filled with outdated, misclassified, and unqualified accounts.
Critical firmographic and channel data was missing or unreliable. Account research was manual and inconsistent. Territory assignments were distorted by incomplete records. And there was no reliable way to identify which companies actually ran active channel programs — a prerequisite for Structured’s ICP.
As a result:
High-potential accounts were buried in noise
Reps spent 15–20 minutes researching every lead
Territories were unbalanced
Pipeline creation was slow and unpredictable
The team lacked visibility into their true Total Addressable Market and had limited confidence in their data.
Sarah's team had a CRM full of companies that didn't belong there.
Some had shut down their channel marketing programs years ago. Others never had any program, and the accounts that actually fit their ICP? Lost in the noise.
And here's the thing, ZoomInfo and Apollo don't have a filter for "companies with active channel marketing initiatives." That's not a data point they track. It's a niche specifically for Structured. So Sarah's team was stuck with three big problems.
20,000 accounts with no clear qualification criteria. Most records were missing accurate revenue, industry, competitors, and any research on whether they even ran channel programs. Nobody knew what was real.
Manually matching product to the customer. Someone had to dig through the internet to figure out which channel partner tools each prospect was using. Before anyone could work a deal, they spent 15 to 20 minutes just figuring out what exact product offering and positioning is gonna be relevant.
Inconsistent routing. For example, 60% of the book was assigned to just 1 rep. This was because of the incomplete firmographic data breaking their assignment rules. Inaccurate revenue or headcount was breaking their territory logic falls apart.
The result was slow pipeline, wasted effort, and no confidence in territory planning.
Sarah described her ICP in plain language. Companies with active channel marketing initiatives, in the right industries, at the right size.
Floqer's agents sourced 50,000+ companies, then systematically researched each one. They looked at channel program pages, partner ecosystems, job postings, and press mentions. Not just firmographics. Actual signals that a company runs a channel motion.
1,600 companies that actually fit, with 10,000+ contacts. Each account came with specific notes on how
Sarah described her ICP in plain language. Companies with active channel marketing initiatives, in the right industries, at the right size. We translated the entire process into an AI workflow.
Floqer's agents sourced 50,000+ companies, then systematically studied each one replicating the exact work Structured’s team was doing manually today. These workflows looked at channel program pages, partner ecosystems, job postings, and press mentions. Not just firmographics or Technographics. Actual signals that a company runs a channel motion.
1,600 hyper-targeted companies and 10,000+ decision-makers. Rather than a static list, each account was delivered with a bespoke scoring rationalea strategic roadmap detailing the specific market signals, organizational gaps, and timing triggers that make the account a high-priority opportunity.
The Salesforce data had useless industry classifications like "Software development." That tells you nothing. Is it fintech? SalesTech? PLG infrastructure?
Floqer enriched every account with precise industry classification mapped to Structured's internal verbiage used, revenue and headcount, competitor tools prospects used in past, and channel partner tech stack including PRMs, partner portals, and co-marketing tools.
Every account now has full context. Industry, tech stack, competitors, and the right product fit.
Contact accuracy and coverage went up ~45% compared to what they were getting from ZoomInfo.
With clean data, Floqer reassigned 20,000 accounts based on actual firmographics.
Here's how it worked. First, all accounts got reassigned to RevOps. Then Floqer enriched and validated industry, location, and company size. Finally, accounts got redistributed to the right AEs using AI driven rules based on Structured internal context.
Balanced books. Reps could actually plan their months.
Automated inbound qualification
When someone fills a form on Structured's site, Floqer takes over. It disqualifies competitors and internal fills. Finds the lead's LinkedIn and fills in missing fields. Enriches company data like revenue, industry, and headcount.
Then it does the research that used to take 15 minutes per lead. What channel tools are they using? Which Structured product fits their setup? Who are their current vendors and what's the competitive angle? All of that gets written to Salesforce before a rep ever sees the lead.
Then it scores and routes to the right rep. Or disqualifies if they're outside ICP.
When a human touches it, they already know exactly what to pitch and why.
Continuous signal monitoring
Floqer watches for intent signals monthly. Hiring activity. Tech stack changes. Leadership moves. Competitor mentions. When an account heats up, it gets re-scored and contacts get enriched without anyone asking.
Floqer enriched records with 80+ data sources, from business registries to industry‑leading EMEA providers.
They got verified emails and phone numbers, plus up-to-date decision‑makers fetched in real time.
Only complete, accurate records were pushed into HubSpot.