Not able to optimize complex decisions
Data-driven understanding of what’s driving business outcomes
Lack of skills and experience in running data science projects
Inability to predict future scenarios based on multiple business drivers
Higher ROI as insights are actionable for the business
Higher confidence in models resulting in higher adoption
Industrialized delivery model with high efficiency
Uncover hitherto unknown insights about the business
Clustering or Classifying customers based on context, behavior and response data
KPI prediction using seasonal and non-seasonal drivers; Detecting Anomalies and Structural Shifts
Using probabilistic models to attribute conversion to CTAs or Channels or Campaigns
AI Solutions using image and text analytics like site chatbots, ad recommender
Rule-based machine learning method for learning interesting relations between variables in large datasets
Pod structure
Data scientists skilled in marketing analytics
Pre-built starter sets
Can work with GCP, AWS, Azure
