Understanding the Leading/Not Leading Feature in Core dna

The Leading/Not Leading feature seamlessly integrates with Core dna to enhance marketing analytics and campaign optimization by categorizing marketing activities into two distinct roles: leading and not leading. By differentiating between these two states, marketers gain valuable insights into whether specific actions or channels lead to desired outcomes.

Key Specifications

How Leading/Not Leading Works

Within Core dna, the Leading/Not Leading feature utilizes complex algorithms that draw from various data sources connected to your marketing campaigns. Once these data points are collected, the feature differentiates activities by analyzing performance and results through key metrics of engagement, conversion, and ROI.

Leading activities are those that significantly drive forward your campaign objectives. Metrics such as high conversion rates, increasing engagement, and optimal ROI characterize these activities.

Not Leading activities, in contrast, show lower performance metrics and are often areas that need reevaluation and strategic changes to boost campaign effectiveness.

Practical Use Case

Consider a new product launch campaign initiated via Core dna. The marketing team can use the Leading/Not Leading feature to monitor different promotional channels, such as social media, email marketing, and PPC ads.

By identifying these patterns early, marketers can allocate resources more effectively, prioritizing "Leading" channels to max ROI while adjusting "Not Leading" strategies to mitigate wasted spend.