Measure the real-world impact of your audio campaigns
Podscribe’s Offline Conversion Tracking enables advertisers to connect podcast ad exposure to real-world outcomes—including in-store purchases, retail sales, and CRM-driven conversions. By leveraging 1st and 3rd party data sources and partnerships, Podscribe provides a unified view of online + offline performance.
1. Shopify S2S (Offline Purchases)
Shopify Server-to-Server (S2S) tracking captures both online and offline purchases (including POS) directly from Shopify. The advertiser must use Shopify’s POS system at their physical store locations in order to measure.
Who will the Shopify S2S work for?
Ideal Customer Profile: Think, ‘Does the client sell in a physical location with Shopify POS?’
- DTC brands using Shopify (online + retail/POS)
Example Use Case
A podcast listener hears an ad, later visits a physical store, and purchases via Shopify POS. Podscribe attributes that sale back to the ad exposure.
How to Enable
- Install the Podscribe Shopify App
- Enter your Advertiser ID + User ID
- Enable S2S tracking
- Map purchase events to Offline Purchase in Podscribe
- Launch attribution in the dashboard
2. Ibotta (CPG Purchase Data)
Ibotta provides verified, first-party retail purchase data across 80+ retailers using receipt uploads and rewards programs. Podscribe matches this data to ad exposure using HEMs, MAIDs, and IP signals.
Who will iBotta CPG work for?
Ideal Customer Profile: Think, ‘Does this product get sold in a retail location?’
- CPG brands selling through retailers
- Brands that can be found within the shopping cart of a consumer.
- Brands without direct access to POS or transaction data
Example Use Case
A user hears a podcast ad for a razor brand, then buys it at Target. Ibotta captures the purchase, and Podscribe attributes it to the campaign.
How to Enable
- Email Partnerships@podscribe.com
- Request Ibotta integration access
- Confirm brand/product mapping
- Enable offline purchase reporting in dashboard
- Launch attribution in the dashboard
3. Affinity Solutions(Retail Sales Data)
Affinity Solutions datasets (credit card transaction data) allow Podscribe to measure in-store purchases at scale, using anonymized transaction panels (billions of transactions).
Who will the Affinity Solutions data work for?
Ideal Customer Profile: Think, ‘Is the Brand’s logo on the building?’
- Retail brands with physical store presence (i.e. Macy’s, Target, Dick’s Sporting Goods)
- Enterprise advertisers seeking broad market coverage
Example Use Case
A listener hears an ad for a retailer, visits a store, and pays with a credit card. The transaction is captured and attributed back to the campaign.
How to Enable
- Work with Podscribe to enable transaction data partnerships
- Define brand/store mapping rules
- Configure reporting windows (lookback + attribution)
- Monitor results in offline conversion dashboards
4. Foot Traffic Measurement (Coming Soon)
Foot traffic measurement links ad exposure to physical store visits, using location signals and device graphs to understand visitation lift.
→Podscribe: Foot Traffic Measurement 1-Sheet (Coming Soon)
Who will Foot Traffic Measurement work for?
Ideal Customer Profile
- Retailers with brick-and-mortar locations
- QSR, grocery, and multi-location brands
- Advertisers optimizing for store visitation vs purchases
Example Use Case
A user hears a podcast ad and later visits a nearby store location. Podscribe measures the lift in store visits compared to exposed vs control groups.
How to Enable
- Upload or confirm store location list
- Enable foot traffic measurement in campaign setup
- Define geographic and attribution windows
- Analyze visitation lift + incremental impact
5. Sending CRM Data: Raw HEMs (Hashed Emails)
Podscribe supports ingestion of raw hashed emails (HEMs) from your CRM, CDP, or data warehouse to enable deterministic matching against exposed audiences.
Who will sending CRM Data work for?
Ideal Customer Profile
- Brands with strong first-party data (CRM, subscriptions)
- Subscription, fintech, healthcare, or high-LTV brands
- Advertisers needing deterministic attribution
Example Use Case
A listener signs up or purchases using their email after hearing an ad. The hashed email is matched to Podscribe’s exposure graph to attribute the conversion.
How to Enable
- Export hashed emails (SHA256 format recommended)
- Send via secure ingestion (SFTP/API)
- Map events (e.g., purchase, signup)
- Enable attribution and validate match rates
Putting It All Together
Podscribe’s Offline Conversion Tracking allows you to mix and match data sources depending on your business model:
- Shopify S2S → Best for owned commerce data
- Ibotta → Best for retail/CPG visibility
- Affinity → Best for scale across transactions
- Foot Traffic → Best for visitation-based KPIs
- HEMs → Best for deterministic CRM matching
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