Why did Peel focus on first touch when we built the attribution on first touch attribution when GA is all last touch attribution?
We focused on first touch because all of our cohort analyses are focused on first orders. We also added “last touch before the first order” for that reason. It is available in the attribution segmentation.
We will be adding last touch attribution soon.
How robust is the data that comes from Shopify's attribution model?
Landing page session tracking is what Google Analytics also uses for attribution and it should be fairly accurate although we’ve seen some checkout implementations break it without saving any data. The most robust approach is always a holistic combination of all tracking combined with modeling that takes into account multi-touch (i.e ads then email then ads, etc.) attribution.
What does Other mean? What does Shopify say about it?
Other is unknown. Shopify blames it on ads blockers:
The takeaway is there just may be to many factors on a software (browser) level to obtain this info on every order. There is some insight found in this forum post here: https://community.shopify.com/c/Shopify-APIs-SDKs/Why-is-the-CustomerJourney-null/m-p/952347/highlight/true#M58807 - JB from our Developer Support team provides some insight on pain points for customer journey (adblockers, caching, etc).
What channels are best with first time customers?
While each brand is different, first time customers are often acquired through social, and paid search channels and you can use the attribution segmentation to find it on LTV metrics.
What channels are best with returning customers??
Returning customers tend to be attributed to email channels (SMS too but that can’t be tracked and they will appear as “Direct”).
Can the Instagram and Facebook attribution be split by organic vs paid?
It is blended.
There is no way to tell the difference other than by using custom campaigns UTM codes in the ads links. At this point we do not have an option to define a model for each client to describe how their ads look like.
Updated about 2 months ago