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Catalyst Digital Group | marketing-agency

Marketing Agency Connects 5 Tools in 12 Days with Custom AI Integration

Chicago, ILMarketing agency (50 active clients)2 weeks engagement
AI IntegrationAI Automation

Challenge

Catalyst Digital Group managed 50 active clients across a fragmented tool stack: HubSpot for CRM and email marketing, Google Analytics for performance data, Asana for project management, Slack for internal communication, and a custom React dashboard for client-facing reports. None of these systems shared data automatically. Account managers spent an average of 8 hours per week per client on manual reporting—exporting CSVs from Google Analytics, cross-referencing with HubSpot campaign data, updating Asana timelines, and assembling slides. There was no single source of truth for client performance. An account manager might quote one number from HubSpot and a different number from Analytics in the same meeting, because the data was pulled at different times and aggregated differently. Campaign performance data arrived 48-72 hours late because it depended on someone manually pulling the numbers. Clients noticed—and three accounts had churned in the previous quarter specifically citing "lack of real-time visibility" in their exit surveys. The agency had 8 account managers, each spending roughly a full day per week on reporting instead of strategy and client communication. At their billing rates, that represented over $320K in annual capacity lost to data assembly. The managing director had evaluated Databox and Supermetrics but found they solved the dashboard problem without fixing the underlying data fragmentation across operational tools.

Solution

We built a central integration layer using n8n as the workflow engine and custom REST APIs as the translation layer between systems. The architecture treats HubSpot as the CRM hub, with data flowing bidirectionally between all five tools through a normalized event stream. Every client interaction—whether it's a campaign launch in HubSpot, a task completion in Asana, a conversion event in Analytics, or a Slack discussion—gets logged as a structured event with a consistent schema. The real-time sync pipeline handles the data plumbing: HubSpot contact and deal updates propagate to the React dashboard within 30 seconds, Google Analytics goal completions trigger Asana task status updates, and Slack channel summaries get attached to HubSpot contact timelines. We built a conflict resolution layer that handles the inevitable race conditions when two systems update the same record simultaneously—last-write-wins with a full audit trail. The AI layer runs on top of the unified data. Claude API processes each client's weekly data to generate automated insight summaries: what campaigns performed above or below benchmark, which channels drove the most efficient conversions, where budget reallocation would have the highest marginal impact, and anomaly flags for metrics that deviated more than 2 standard deviations from their 30-day trend. These insights populate the client dashboard automatically and trigger Slack notifications to the responsible account manager when action is recommended.

Results

Full integration

Tools Connected

0 (all manual)5 tools in 12 days

-100%

Reporting Turnaround

48-72 hoursReal-time

-94%

Manual Reporting Time

8 hrs/client/week30 min/client/week

Single source of truth

Data Accuracy

Manual with frequent errorsAutomated with validation

+18% retention rate

Client Retention

3 churns in previous quarter0 churns since launch

Implementation Timeline

Days 1-3

Architecture & API Mapping

Documented every API endpoint across all 5 tools, designed the normalized event schema, built the n8n workflow backbone, and established the bidirectional sync between HubSpot and the React dashboard.

Days 4-7

Integration Build & Data Pipeline

Connected Google Analytics, Asana, and Slack to the central event stream. Built the conflict resolution layer, implemented the 30-second sync cycle, and validated data consistency across all systems.

Days 8-10

AI Insights Layer

Deployed the Claude API integration for automated weekly insight generation, built the anomaly detection logic, configured Slack notifications for actionable alerts, and populated the client dashboard with AI summaries.

Days 11-12

Testing & Launch

Ran the full pipeline against 10 pilot clients for 48 hours, validated insight accuracy with account managers, fixed edge cases around multi-touch attribution and timezone handling, then rolled out to all 50 clients.

Tools & Platforms

n8nHubSpot APIGoogle Analytics APIAsana APISlack APIAnthropic Claude APICustom REST APIs
Our account managers went from being data janitors to actual strategists. They used to spend Monday assembling reports—now they spend Monday reading the AI-generated insights and deciding what to do about them. Clients started commenting on how much sharper our recommendations got, and they have no idea it's because we automated the boring part.

David Kim

Managing Director

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