Operational Efficiency
Unify Marketing Data
Bring fragmented sources together into one trusted view of performance and activity
Problem
Important marketing data often lives across disconnected platforms, creating an incomplete view of performance and customer behavior. Teams spend too much time reconciling reports instead of using them. Decisions slow down when no one fully trusts the data or can see the whole picture in one place.
Solution
AI helps connect, normalize, and organize data from multiple marketing sources into a more usable and unified view. Teams gain faster access to clearer information across channels and systems. That reduces reporting friction, improves confidence in analysis, and supports better decision-making across the organization.
Capabilities
- Integrate data from all marketing platforms automatically
- Normalize metrics and definitions across data sources
- Flag data quality issues and anomalies in real time
- Build unified customer and campaign performance views
- Enable self-serve analytics access across the marketing team
Benefits
- Give every marketer access to a single, trusted version of performance data.
- Eliminate the version control arguments over which spreadsheet is right.
- Make real-time optimization decisions based on current data rather than last week's exports.
Timeline
Data source inventory complete, priority integrations mapped, initial ETL pipelines built and tested
Unified data layer live, primary dashboards operational, data quality monitoring active
Full stack integration complete, all major data sources flowing, self-serve analytics adopted by marketing team
Data Requirements
- Ad platform data (Google Ads, Meta Ads, LinkedIn Ads, spend, impressions, clicks, conversions)
- Marketing automation data (Marketo, HubSpot, campaigns, emails, leads)
- CRM pipeline and revenue data (Salesforce, HubSpot)
- Website analytics data (Google Analytics 4, Adobe Analytics)
- Social media analytics by platform
- Ecommerce or revenue data (Shopify, Stripe, ERP systems)
Integration Points
- Data integration / ETL platform (Fivetran, Airbyte, Stitch)
- Data warehouse (Snowflake, BigQuery, Redshift)
- BI and visualization (Tableau, Looker, Power BI)
- CDP (Segment, mParticle)
- Marketing data platform (Supermetrics, Funnel.io)
Team Requirements
- Marketing analytics lead (requirements, definitions, and use case prioritization)
- Data engineer (pipeline development and data quality)
- IT / data infrastructure lead (warehouse and security governance)
- Marketing ops (platform access and API configuration)
- BI developer (dashboard and reporting layer build)