Marketing Data Science Platform
conDati marketing data science as a service platform helps marketing leaders gain a unified view of their campaign performance in real-time, increase conversions by 10-20x, improve operational efficiencies by 30-80%, and provides deeper insights and foresights.
At the core, conDati’s data science platform is AI/ML-driven to automatically ingest and analyze data faster and on an infinitely larger scale than the human eye can process – including benchmarking cross-channel campaign performance, forecasting results including pipeline and revenue, optimizing campaign performance with intelligent recommendations, and providing precision attribution with an algorithmic and unbiased approach.
Specific optimization recommendations on where and when to stop, start and continue for higher campaign and ad spend return. One example is easily activated bid adjustments where machine learning scans for performance lift across hundreds of variables, taking saturation into consideration.
Real-time machine learning driven forecasting of marketing results and spend across the entire funnel; from web visitors to MQLs and SQLs to pipeline and revenue with built-in anomaly detection and alerts, to give you forward looking visibility and insights that fit with the objectives and seasonality of your business.
Algorithmic and non-heuristic approach to attribution modeling for a non-biased view across channels and touch points. This helps marketers understand the most valuable touch points (not only the last touch), the next best action for engagement, and patterns detection that leads to conversions.
Anticipate and Activate
- Forecast results from top funnel goals like web visits to pipeline, sales revenue and customer engagement metrics
- Forward looking visibility and insights, at scale
- Fit with the seasonality of your business – yearly, weekly, daily seasonality plus holiday effects
- Built-in anomaly detection and alerts
- Robust to missing data and trend-shifts
Identifying Opportunity using Lower Funnel KPIs
- Specific campaign optimization recommendations / bid adjustments
- Optimized to lower funnel conversions / revenue
- Tied to saturation models for optimized budget allocation
- Machine learning scans for performance lift across hundreds of variables – audience and creative attributes
- Batch upload or automation to activation platforms
Algorithmic-driven and cross-channel attribution
- Provides a simple way to understand the 80/20 rule on cross-channel and multi-touch attribution
- Gives an unbiased view by leveraging advanced data science modeling of conversion paths (non-heuristic , non-linear and not based on last touch)
- Detects patterns for successful and unsuccessful conversions at scale
- Filter journeys by audience segment e.g. loyal vs new customers
Compare attribution models (Markov, uniform, last click, first click)
- Customizable and scalable nodes which are highly scalable for content and engagement journeys
Pepperdine University Streamlines Marketing Reporting for More Effective Campaigns at Less Cost
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