Overview
Direct Mail is one of the custom and non-conforming marketing sources Provalytics can ingest when there is no native platform connector. This is a strong fit for:- national direct mail programs
- regional or local mail drops
- prospecting and retention mail programs
- vendor-managed direct mail reporting files
Recommended data structure
Best practice is to send Direct Mail data in a consistent hierarchy:ChannelCampaign NameCreative
Audience SegmentGeographyVendor
DateImpressionsor the closest available exposure metric such as mailed piecesChannelCampaign NameCreative
SpendAudience SegmentMarketVendorResponse Metric
Why this structure matters
This structure gives Provalytics enough detail to:- separate Direct Mail from the rest of the media mix
- preserve campaign-level reporting where it exists
- distinguish creative-level performance when available
- analyze how Direct Mail contributes alongside search, social, video, and offline channels
Historical backfill and cadence
If historical data is available, best practice is to backfill it before the feed goes live in production. That allows the model to train on the data before it begins appearing in the live dashboard. After setup, the data should continue arriving on the same cadence as the rest of your reporting inputs so the dashboard and model outputs stay current.How teams usually send it
Direct Mail data can be delivered through any of Provalytics’ custom-data intake methods, including:- recurring email feeds
- Google Sheets
- SharePoint
- S3 bucket delivery
- Snowflake delivery
- manual uploads
- BigQuery delivery