Case Study · Global Services

Sprynt International — From Data Chaos to AI-Ready Insights

We built a unified data foundation—cloud data lake, inline analytics, and an AI knowledge base—so Sprynt could move faster, automate KPIs, and scale customer experience.

25

Faster decision-making

100

Automated KPI reporting

1

AI-ready knowledge base

Managers collaborating around a unified analytics dashboard

The Challenge

Sprynt International was expanding quickly—but their data lived in silos across CRM, contact centre, workforce, and operational tools. Reporting was manual and inconsistent, KPIs varied by team, and knowledge wasn’t centralised enough to power AI.

Key pain points

  • Disparate systems slowed decisions and obscured trends.
  • Manual reports consumed hours every week.
  • Inconsistent metrics created confusion and rework.
  • Knowledge was scattered—no reliable base for AI or automation.

Our Solution

We applied our workshop-led approach to map pain points end-to-end, then delivered a scalable data and analytics framework built for growth.

Cloud Data Lake

Unified data ingestion from CRM, contact centre, WFM, and operations into a governed, query-ready lake.

The Impact

Within months, Sprynt gained measurable outcomes that changed how teams operate.

  • 25% faster decisions with timely, trusted data.
  • Automated KPIs replaced manual reporting and spreadsheet chaos.
  • AI-readiness for future assistants and predictive analytics.
  • Stronger alignment across teams using one source of truth.

“Creative Communications Lab gave us visibility we never had before. Decisions that took weeks now take hours—and we’re ready for AI-driven CX.”

CX Lead, Sprynt International

Why This Matters

Data foundations determine CX outcomes. By connecting systems, embedding analytics where people work, and preparing knowledge for AI, Sprynt unlocked faster operations, lower overheads, and better customer experiences—without ripping and replacing core platforms.

FAQs

How CCL unified Sprynt’s data with a cloud data lake, inline analytics, and an AI knowledge base—25% faster decisions, automated KPIs, and scalable CX.

Disparate systems and manual reporting slowed decisions and obscured performance.

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