Re-Flow

SITUATION


Re-Flow Field Management is a UK-based SaaS provider delivering field operations software to sectors including civils, traffic management, construction, and infrastructure. The platform supports real-time scheduling, mobile data capture, asset tracking, and compliance—digitising operations in traditionally manual industries.

Despite strong product-market fit, Re-Flow encountered a familiar SaaS growth ceiling: advertising activity scaled faster than insight.

Google Ads and LinkedIn Ads generated inbound demand, but lead quality varied widely. More critically, there was no automated link between advertising platforms and downstream sales outcomes. Campaigns were optimised around surface-level events (form submissions), while long B2B sales cycles obscured which channels, keywords, and audiences actually produced revenue.

Re-Flow’s objectives were therefore operational and commercial:

• Increase inbound demand without increasing wasted spend

• Improve lead quality and sales readiness through automation

• Attribute offline revenue back to paid media using real lifecycle data

• Enable AI-driven bidding and scalable growth based on profit, not volume

An initial systems audit revealed the need for automation-led attribution, deeper intent targeting, and a shift from campaign metrics to revenue signals.


Solution

OpScaling engineered an automation-first advertising and attribution architecture, using the CRM as a central data hub and Zapier as the orchestration layer connecting sales, marketing, and revenue systems.

The goal was simple: train paid media AI using real business outcomes.

Automation & Integration Layer

Zapier was deployed as the integration fabric, synchronising lifecycle events, deal status, and revenue data across advertising platforms, CRM, and supporting business applications. This removed manual data handling and ensured consistent, real-time signal flow.

CRM as a Data Source (Not the Destination)

Rather than treating the CRM as a marketing tool, it was positioned as a structured data layer feeding qualified signals into Google Ads and LinkedIn Ads.

Lifecycle stages—from enquiry to qualified opportunity to closed deal—were automatically synchronised and normalised for downstream optimisation.

AI-Driven Conversion & Value Mapping

Offline conversion events were automated and weighted to reflect real commercial value:

• Initial enquiry

• Sales-qualified lead

• Closed deal with revenue value

These signals trained Google and LinkedIn’s AI models to optimise towards lead quality and revenue, not form volume.

Paid Media Restructuring & Intent Alignment

Campaigns were restructured around high-intent, problem-aware searches such as:

• “Field management software”

• “Construction operations software”

Long-tail, intent-driven keywords reduced waste and improved efficiency, while LinkedIn campaigns targeted decision-makers by role, sector, and buying intent.

Automated Audiences & Lifecycle Retargeting

Automation enabled dynamic audience creation based on real engagement and lifecycle progression:

• Unqualified leads excluded from scaling campaigns

• Qualified prospects sequenced with tailored messaging

• Closed-won data used to refine targeting models

Lead Handling & Sales Automation

Supporting automations ensured that:

• Leads were captured consistently across all touchpoints

• Follow-ups were triggered based on behaviour and lifecycle stage

• Lead scoring prioritised sales effort using engagement and intent signals

• Internal handoffs and notifications occurred without manual intervention

Light AI logic was used to support prioritisation and workflow decisioning, improving speed without removing human control.

Impact

The shift to automation- and AI-led optimisation fundamentally changed how performance was measured and scaled.

Marketing & Performance Outcomes

• 35% increase in qualified leads, not just raw enquiries

• 30% uplift in total lead volume

• 18% reduction in CPC, driven by improved intent targeting

• 27% increase in CTR, reflecting stronger message–market alignment

• 4.2% conversion rate, supported by automated testing and audience refinement
  

Commercial Results

• ROAS exceeded 600% across Google Ads and LinkedIn

• Monthly ad spend stabilised at ~£8,000 with clear profitability

• Budgets scaled by 150% without loss of efficiency

• Long B2B sales cycles fully attributed from first click to closed revenue

Summary

By treating the CRM as a connected data layer and using Zapier to automate signal flow between sales systems and paid media AI, Re-Flow moved from lead-based advertising to revenue-led optimisation.

Campaigns were no longer optimised for clicks or form fills, but for actual commercial outcomes—enabling predictable scaling, accurate forecasting, and confident investment decisions.

This automation-first framework positioned Re-Flow to grow sustainably while maintaining efficiency, transparency, and control.