Overview
Provalytics is designed as a decision system, not just a reporting layer. At a high level, the platform helps teams move through five connected steps:- connect structured data
- organize it into usable inputs
- measure incremental business impact
- validate the model
- turn the output into budget and planning decisions
Step 1: Connect data
Provalytics can ingest data through native platform connectors and also through custom data routes such as Snowflake, BigQuery, S3, SharePoint, recurring email delivery, sheets, and manual uploads. The goal is flexibility: if the data is structured and matters to the business, Provalytics can usually help make it usable.Step 2: Organize the data into layers
Once connected, data is organized into layers that support reporting, validation, and modeling. This matters because clients rarely operate with perfectly uniform source systems. Provalytics was built to normalize those realities through custom data layers and repeatable ingestion patterns.Step 3: Measure business impact
The core measurement task is incrementality:What happened because media ran?That includes immediate effects, carryover or ad stock effects, and synergies across channels.
Step 4: Validate the model
Provalytics does not ask users to accept modeled results on faith. The platform surfaces validation through Proof, where teams can review R², MAPE, and predicted-versus-actual fit before using the results for reporting or optimization.Step 5: Turn the output into decisions
Once impact is measured and validated, Provalytics helps teams act on it through:- report interpretation
- budget recommendations
- scenario planning
- budget guardrails
- recurring exports and downstream access