Signalto Pipeline
A concept showing how marketing and machine learning can work as one system: content attracts the right audience, and a model helps sales focus on the accounts most likely to convert.
Campaign objective
Turn strong content into qualified sales conversations, and help sales focus on the accounts most likely to buy.
Creative direction
Content that answers the real questions buyers ask at each stage, presented as a clear series rather than one-off posts.
Execution overview
Stage-mapped content plan, targeted paid distribution, engagement tracking into the CRM and a predictive lead-scoring model reviewed weekly with sales.
Challenge
A B2B company publishes strong content but has no clear path from readers to qualified conversations. Sales spends time on low-intent leads while promising accounts go cold.
Approach
Map content to buying stages, distribute it through targeted paid and organic channels, and capture engagement signals consistently so they can be scored.
Solution
- Content plan organised by buying stage and audience segment
- Targeted paid distribution with conversion tracking
- Engagement data pipeline into the CRM
- Predictive lead-scoring model with transparent score drivers
- Weekly review loop between marketing and sales
Technology
- Analytics and tag management
- CRM integration
- Data warehouse
- Machine-learning scoring model
- Reporting dashboards
Results
This is a demonstration project, so there are no client results to report. If delivered, success would be measured by:
- Qualified pipeline attributed to content
- Cost per qualified lead
- Time from first touch to first sales conversation