SaaS (Repair Shop Management)
RepairDesk Accelerates Lead Qualification and Growth with Squig
RepairDesk, a global platform for repair shop management, transformed its lead management by automating both inbound qualification and large-scale re-verification of historical leads. With Squig, RepairDesk encoded the sales team's hard-won heuristics into an automated workflow that enriches, scores, and routes leads within minutes—freeing the team to focus on high-quality opportunities with richer context.
The Challenges
Manual inbound verification consumed sales time
The existing process was decent but manual. Sales reps verified and qualified each lead, applying nuanced rules learned over years. This resulted in high effort, inconsistent application of rules, and slower speed to first contact.
20k+ legacy leads needed validation and enrichment
The CRM held ~20,000 older inbound leads and trials. Many were outdated or incomplete. This led to unclear database quality, time-intensive batch work, and limited segmentation.
The Solution
Automated inbound qualification, enrichment, and scoring
Squig automated the entire inbound flow. It validated leads against the sales team's hard-learned rules, enriched missing firmographic and contact fields, and scored each lead with clear quality indicators. Enrichment and scoring now happen within minutes, giving reps immediate, actionable context and next-best actions.
Bulk re-verification and enrichment of 20k legacy leads
The same rules and enrichment process were run across ~20,000 existing records. Squig confirmed business status and fit against the lead matrix, enriched missing data at scale, and flagged non-operational or low-fit entries. Resulting segments supported targeted outreach and cleaner reporting.
Implementation
Enhanced lead scoring
Working with RepairDesk, Squig created a detailed lead scoring matrix using signals that would be impractical to implement manually. The system analyzed tech stacks, customer review quality, review velocity, owner name mentions, and other indicators to provide comprehensive scoring.
Historical lead identification
With the lead scoring in place, Squig was able to backfill the score on existing leads, identifying high-quality potential deals in the mix.
Iterative rollout
Started with small batches to validate accuracy, then scaled to hundreds per batch while enabling real-time processing for new inbound leads.
Collaboration loop
Teams worked in rapid feedback cycles to refine rules and improve scoring thresholds.
Actionable intelligence
The resulting scores gave clear indicators of lead quality, enabling faster and more confident action from the sales team.
Results
- Speed: New leads are qualified, enriched, and scored within minutes, accelerating time-to-first-contact.
- Focus: Sales now concentrates on high-quality leads and enters conversations armed with detailed insights, improving win rates and deal velocity.
- Data quality: The legacy database was cleaned, enriched, and segmented. Non-operational and low-fit leads were flagged or suppressed.
- Scale: Automated processing of ~20k records eliminated weeks of manual effort and established a repeatable playbook for future batches.
- Growth readiness: RepairDesk gained the ability to scale operations efficiently, with automated lead qualification providing the foundation needed to confidently expand their business without proportionally increasing sales headcount.
Conclusion
By automating inbound qualification and bulk re-verification with Squig, RepairDesk converted sales expertise into a consistent, always-on workflow. The team now moves faster on the best opportunities with richer context, while maintaining a cleaner, more actionable database—setting the foundation for scalable, efficient growth.