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DTC Wellness · Case study

ENERGYbits

Marketing intelligence across a complex DTC stack

Built a complete marketing intelligence platform analyzing 15+ connected ad and content platforms, with blog generation pipelines and SEO, AEO, and GEO scoring before publish.

ServicesMarketing Intelligence

Content & search intelligence

15+ platforms. One publishing brain.

15+Platforms connected
3Search scores
  • Platform signals ingested
  • Draft scored for SEO · AEO · GEO
  • Editorial queue updated
  • Post scheduled
15+Platforms connected
3Search scores
1Intelligence layer
Before publishContent validation
The challenge

15+ platforms. One publishing brain.

With performance and content data spread across more than fifteen platforms, the team needed a practical way to turn fragmented signals into publish-ready decisions.

Too many data sources

Marketing context was distributed across ad, analytics, and content platforms.

Manual content workflow

Research, drafting, and quality checks required repeated effort.

New search landscape

Content needed to perform in traditional search and AI-generated answers.

The solution

A connected system designed around the way the team actually works.

We built a connected marketing intelligence platform with automated blog pipelines and SEO, AEO, and GEO scoring before content goes live.

01

Connected intelligence

Signals from 15+ platforms feed a shared decision layer.

02

Automated blog pipeline

Research and structured drafting move through a consistent production flow.

03

Pre-publish scoring

Every draft is evaluated for search, answer-engine, and generative-engine readiness.

Key capabilities

What the system does.

Data connection

  • 15+ platform integrations
  • Normalised marketing signals
  • Unified analysis

Content automation

  • Research pipeline
  • Structured drafting
  • Editorial workflow

Discoverability

  • SEO scoring
  • AEO scoring
  • GEO scoring
Results & impact

From fragmented work to a repeatable operation.

Quality checks happen earlier

Content is evaluated before publication, when improvements are easiest to make.

A scalable content operation

The team can increase output without multiplying manual research and coordination.

Visibility beyond traditional search

The workflow accounts for both search engines and AI answer experiences.

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