Most attribution tools can only see what a customer clicks. But some of the channels that influence a purchase never generate a click at all — a TV spot, a Connected TV (CTV) ad, a podcast read, or a postcard on the kitchen counter.

Polar can ingest view-through and third-party touchpoint data directly from your media providers and weave those impressions into the same customer journey as your Meta, Google, and Polar Pixel data. The result is true multi-touch attribution across your entire marketing stack — click-based and view-based, online and offline.
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In this article, you will learn:

View-through touchpoints are impressions a customer was exposed to but did not click — for example, seeing your ad on a streaming service or hearing it on a podcast. Channels like TV, CTV, print / direct mail, and podcast don't pass a click into your store, so they're invisible to a standard pixel.

With third-party touchpoint injection, your media provider shares impression-level or pre-matched data with Polar. Polar matches that data to your Shopify orders and Polar Pixel data so each exposure becomes part of the customer's marketing journey — exactly like a Google or Meta touchpoint.

Why this matters: once view-through data is in Polar, you can finally see how your upper-funnel and offline channels overlap with paid social and search — and which ones drive first touch, last touch, and everything in between.

Polar has worked with providers across TV, CTV, print, and podcast. Current examples include:

Don't see your provider listed? The process is flexible by design. If a provider can share data and tell us where to pick it up, we can usually work with them — reach out via the in-app chat and we'll scope it.

These channels rarely have a standard API or a consistent data-sharing process, so setup is a light collaboration between you, the provider, and Polar. Together we define three things:

The pattern is the same across providers: the provider deposits files into a shared storage location (such as S3, blob storage, or another data lake), and Polar connects to that location with an ingestion pipeline that picks up new files as they're delivered. The data then typically arrives in one of two formats.

The provider has already matched exposed users or households back to orders and sends Polar the resulting file. This is common for print, where the provider knows which addresses received a mailer and can match those addresses to Shopify orders. Some TV, CTV, and podcast providers also supply matchback files using their own methodology. Polar ingests the matched output and uses it alongside your order and customer data.

Some CTV providers can share raw impression-level data. When that data includes identifiers such as IP address, Polar connects the impressions to its own identity-resolution layer (built from server-side pixel and clickstream data) and combines view-through touchpoints with your clickstream, pixel, and order data for a more complete journey.

Once the data is ingested, Polar connects it back to the customer journey using the strongest available matching key. The method depends on the format provided.

Matchback files usually already include an order ID or another order-level identifier. Polar uses that order ID as the join key to place the view-through touchpoint into the right journey and conversion. In effect, the provider has already identified the order tied to the exposure, and Polar slots the touchpoint into that journey.

Raw impression data is resolved using the identifiers in the file — IP address, email, or other fields the provider can share. Polar matches those identifiers against its identity-resolution layer to connect the impression to a Polar Lifetime ID, then uses the timestamp of the view event to decide whether it should be associated with a later conversion.

So matching is based on both:

Good to know: raw impression matching relies on the same Lifetime ID that powers the Polar Pixel. A healthy pixel install with strong identity resolution means more view-through impressions can be tied to a real customer journey.

Once matched, view-through touchpoints behave just like clickstream events. They become part of the customer journey alongside the events collected by Polar's server-side pixel, which means your attribution models — first-click, last-click, linear, and multi-touch — can credit view-through interactions together with click-based ones.

For example: a customer sees your CTV ad on Sunday, clicks a Google ad on Wednesday, and buys on Friday. With view-through data ingested, a first-click model can credit the CTV exposure, while last-click still credits Google — and a linear or multi-touch model shows the full path.

Linear TV is usually handled differently. The data available for linear TV is often closer to spend, airing, or placement-level data rather than user-level impression or matchback data. For that reason, linear TV is not always integrated into attribution the same way as CTV or print — it can still be used for reporting, but the level of attribution detail depends on what the provider is able to share.

View-through ingestion is configured with help from our team. To get started:

View-through ingestion closes the gap between the channels customers click and the ones they only see. By bringing TV, CTV, podcast, and direct mail into the same customer journey as your pixel and ad data, Polar gives you one unbiased view of what's really driving purchases across your whole stack.

Running TV, CTV, podcast, or direct mail and want to bring it into attribution? Reach out to our team via the in-app chat and we'll help you scope it.