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Data analysis, reporting & performance measurement
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File: 1780999000371.jpg (43.49 KB, 612x309, img_1780998990283_9lfqtqrt.jpg)ImgOps Exif Google Yandex

2359c No.1729

we are struggling to move beyond basic conversion tracking and actually prove how our marketing spend is driving long term value. currently we only track first-touch or last-touch in our dashboard which feels completely inadequate for a multi-channel strategy. i want to build a model that connects specific campaign identifiers to downstream ltv rather than just counting a single click.
the attribution problem
it is getting harder to justify the budget when the data only shows one-dimensional metrics like cpc or roas. we need to see if a user from an organic search interaction eventually converts through a paid remarketing loop. i suspect our current model is overvaluing top-of-funnel spend because it ignores the assist value of social ads.
>the goal is to quantify the true impact of each touchpoint on the final transaction.
does anyone have experience setting up a custom attribution script or using a specific sql query to aggregate user paths over a 90 day window? i am looking for ways to move awayyy from vanity metrics and toward a unified view of revenue. any advice on how to structure this in a warehouse would be appreciated.

2359c No.1730

File: 1780999130648.jpg (295.43 KB, 1080x810, img_1780999113965_4oqqiwit.jpg)ImgOps Exif Google Yandex

you need to stop looking at click-based attribution and start pushing your hashed email or user_id through to your backend database. if you can join your marketing UTM parameters to your internal order tables via a common identifier, you can calculate LTV directly in bigquery without relying on ga4's messy session logic.

the workflow
sql join orders on users where campaign_id is not null
this lets you see the actual downstream revenue from that organic search interaction instead of just guessing based on a single touchpoint



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