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Case StudiesMarketing Analytics

Marketing Report Automation Agencies

AI-Powered Analytics for Agency Reporting

Client

InsightsBot

Headquarters

United States

Timeline

4 months

Technology

DECISION INTELLIGENCE

Marketing Report Automation for an Agency case study by EdgeFirm

Weekly reporting cut from 20 hours to 2, client-reported

Analyst capacity grew from 5 to 6 clients each to 12 to 15, client-reported

At a glance

The challenge

Marketing analysts spending 20+ hours/week on manual reporting across 15+ platforms

The solution

AI-powered analytics platform with unified data integration, anomaly detection, and automated insight generation

The results

  • Weekly reporting cut from 20 hours to 2, client-reported
  • Analyst capacity grew from 5 to 6 clients each to 12 to 15, client-reported
The problem

Marketing Report Automation for Agencies With AI

InsightsBot is an AI-powered marketing analytics platform for agency reporting. It unifies 15+ data sources, detects anomalies in real time, and generates written insights automatically. The agency reports that weekly reporting per analyst fell from 20 hours to 2 (client-reported), which let the same team take on more clients.

Scope of work

6 capabilities carried the build

Design and deploy a marketing analytics platform that automates reporting across 15+ platforms and delivers AI-generated insights for analysts to review.

01

15+ platform API integrations with unified data model

02

Real-time anomaly detection across 100+ metrics per client

03

AI-powered insight generation with GPT-4

04

Automated report generation with customizable templates

05

React dashboard with conversational analytics

06

Slack and email delivery integrations

Technology

The stack behind it

GPT-4, LangChain, PostgreSQL, dbt, React, 15+ API integrations

OpenAIOpenAI
LangChainLangChain
AWSAWS
PostgreSQLPostgreSQL
RedisRedis
dbtdbt

AI/ML

GPT-4 for insights, Prophet for forecasting, custom anomaly detection

Data Pipeline

PostgreSQL, dbt transformations, Redis caching

API Integrations

15+ platforms (Google, Meta, LinkedIn, TikTok, HubSpot, Shopify, etc.)

Backend

FastAPI (Python), Celery for async processing

Frontend

React with real-time updates, PDF generation

Infrastructure

AWS (EC2, RDS, S3), CloudWatch monitoring

Delivery

Slack API, SendGrid email, scheduled reports

How we built it

Our development process

Universal API Integration

Reliable connectors for 15+ marketing platforms with automatic retry, rate limiting, credential refresh, and data normalization. Versioned storage handles retroactive data changes from platforms like Facebook.

Real-Time Anomaly Detection

Two-stage detection covers 100+ metrics per client. A fast pre-filter uses cached bounds, then parallel deep analysis runs only on the candidates.

“EdgeFirm transformed our entire business model. Before InsightsBot, we were stuck at 45 clients because reporting was our bottleneck. Every analyst spent 20+ hours a week on manual data pulls and report writing. Now we serve 96 clients with the same team. The AI-generated insights are often better than what our senior analysts produced. Our clients get faster reports with deeper analysis, and our analysts actually enjoy their jobs again because they're doing strategy, not data entry.”

Jennifer Martinez

After launch

What changed after launch

Weekly Reporting Cut From 20 Hours to 2

Client-reported. Weekly analyst time on reporting dropped from 20 hours to 2 hours. Time moved to strategy and client relationships.

More Clients Per Analyst

Client-reported. Each analyst now manages 12 to 15 clients instead of 5 to 6. The agency grew from 45 to 96 clients with the same team.

Unified Data From 15+ Platforms

Reliable connectors pull data from 15+ marketing platforms into one data model, so analysts no longer copy figures between tools by hand.

InsightsBot shows how AI can take over the manual work in marketing reporting. By automating data collection, anomaly detection, and insight generation, we helped an agency cut weekly reporting from 20 hours to 2 per analyst (client-reported) and serve more clients with the same team. The key lesson is to automate the repetitive steps and keep analysts in charge of strategy.

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