Marketing Analytics at Scale
Machine learning to collect, store, blend and analyze unlimited data volumes, to reveal and share powerful commercial insights for Marketing.
Secure, Affordable, and High-Performance
conDati’s big data solutions for Marketing are developed on industry-leading technology in data warehousing, security, data science, and data visualization.
Unlimited data, on-demand
The conDati Hub collects and stores real-time inputs from standalone siloed systems with rapid response times.
The conDati Workbench employs the best of machine learning and data science to develop never-before-seen insights.
The conDati Analytics portfolio provides insights on the key topics you need to focus on, when you need to focus on them.
How It Works
Understand, predict, and improve
conDati Analytics provides marketing executives and marketing practitioners with a portfolio of cloud-based, purpose-built notebooks that address specific domains of marketing operations, performance, and contribution.
- New Insights: By combining and synchronizing data from multiple sources, conDati Analytics reveals hidden relationships and correlations, and enables direct comparisons among campaigns and over time — all with data as current as you want it to be, down to the second.
- Data-based Forecasting and Alerting: Machine learning techniques create predictive models for activity, conversions, and revenue that incorporate history and seasonality. Set alerts for real-time anomaly detection; drill-down to understand causal factors for high or low performance.
- Improved ROI: With causes and correlations revealed, optimization models show how to invest marketing resources to maximize revenue, profit, and customer success in order to achieve the greatest ROI on Marketing.
Where data meets machines
The conDati Workbench is the suite of data management and software development tools that we use to integrate and analyze large data volumes from multiple systems. Workbench is our internal toolkit to create advanced marketing analyses based on curated best-practices data science.
- Data Management: Retrieving and combining data from your most important marketing systems. Current APIs supported include Google Analytics, Adobe Analytics, HubSpot, Salesforce, Marketo, Cordial, Facebook and other social media, with many others in development.
- Software: conDati uses the most current and powerful open source development tools to create robust, secure, and maintainable applications and visualizations.
- Data Science: Machine learning algorithms, statistics, and analytic approaches applied to different problems in marketing, including synchronization, correlation, prediction, probability, and optimization.
“All the Data” means “All the Data.”
The conDati Hub is built on Snowflake’s award-winning cloud-based data warehouse. With Snowflake, conDati can deliver complex analytics and visualizations on big data, at scale, with high-performance and security.
- Scale: conDati can collect, store, and analyze as much data as your systems produce. We don’t need to limit the size of the database, or resort to statistical sampling.
- Performance: Data elements appear in the Hub as soon as they are generated by the source system, so data latency is reduced to seconds. conDati’s data management technology provides rapid response time to the browser for analyses, dashboards, and reports.
- Security: The data from every conDati client is held in its own self-contained Docker instance: we will never mix your data with anyone else’s data. Snowflake and the underlying AWS services add best-in-class practices in physical and cybersecurity.
“Current martech systems only give you surface analytics, but there’s so much more that could be done. The problem is that a typical person sees a raw data stream and runs away screaming. What’s extraordinary about conDati is that it turns that raw data into actionable intelligence that a normal person can actually understand, consume, and act on.”
Digital Marketing Specialist, Transtar Industries
How AI Should Enhance Your Martech Stack
When you rely on humans to do things that, arguably, machines do better, the end result is inefficiency, less creativity (because those creative humans are being used as human adding machines) and, ultimately burnout and a less productive team.