Case Studies

How teams turn the database into pipeline

Three workflows our platform is built around — from solo cold callers to agencies running multi-market campaigns.

Customer success funnel
Cold Calling · SaaS Sales

Building a trades cold-call machine across Western Canada

A small SaaS team selling software to trades businesses needed call lists for Alberta and Saskatchewan — owners and GMs of plumbing, HVAC, and electrical companies, not info@ inboxes and dead numbers.

The old way: reps spent the first hour of every day scraping directories and guessing at decision-makers — burning selling time on data entry, with numbers that rang to nowhere.

With JAYISAAC AI: one filtered search — industry + region + Owner/GM titles — produced a complete territory list with direct phones in minutes. Reps exported by city, loaded the dialer, and spent their mornings actually dialing.

The workflow

  1. Filter: Plumbing + HVAC + Electrical → AB/SK → Owner, GM
  2. Reveal contacts for the week's call block
  3. Export CSV by city → import to dialer
  4. Repeat with fresh segments weekly
~5 min
From search to dial-ready territory list
1 hr/day
Rep time recovered from manual list building
Direct lines
Owners & GMs — not gatekeeper inboxes
Agency · Multi-Market

An agency running outreach for clients in six cities at once

A marketing agency selling local SEO and ads packages needed separate prospect lists per client vertical, per city — roofing in Denver, landscaping in Surrey, movers in Winnipeg — refreshed every campaign cycle.

The old way: buying one-off scraped lists of wildly inconsistent quality from freelancers, with no idea what was verified and no recourse when half a list bounced.

With JAYISAAC AI: each client campaign became a saved filter combo. Same data standard across every market, segmented exports per client, and the credit model meant they only paid for contacts they actually used.

The workflow

  1. One filter set per client (industry + city + size)
  2. Reveal only the segment for this campaign cycle
  3. Export per-client CSVs for their outreach stack
  4. New cycle → fresh records, same filters
6 markets
Managed from one account
1 standard
Same verification bar in every city
Pay-per-use
Credits spent only on revealed contacts
CRM Enrichment · Local Services

Turning a dusty CRM into a working pipeline

A commercial services company had years of half-filled CRM entries — company names with no contact person, generic emails, disconnected numbers. Their "pipeline" was an archaeology site.

The old way: reps googled each account one at a time before calling, often reaching nobody and logging nothing.

With JAYISAAC AI: they searched their existing accounts in the platform, pulled current decision-makers with verified channels, and rebuilt account records with someone real to call. Dead accounts got identified and cut instead of haunting the forecast.

The workflow

  1. Search existing CRM accounts by company name
  2. Reveal current decision-maker contacts
  3. Export and merge into the CRM
  4. Purge accounts that no longer exist
Real people
Named decision-makers on every live account
Cleaner forecast
Dead accounts identified and removed
Same day
From stale CRM to callable pipeline
These case studies are illustrative workflow examples representing how the platform is designed to be used. As customers share measurable results, named studies with verified numbers will be published here — we don't invent customer quotes or fake metrics.

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