Closing the loop: performance data back into the warehouse so the next generation run is informed by the last. Scoped as a standalone workstream or folded into a full data scientists build.
from $2,700 as a standalone workstream · included in the Data Scientists Build tier
Most publishing pipelines are one-directional. The interesting gains come from feeding performance back into generation decisions. We run this as a fixed-scope workstream: 4 defined deliverables, one named approver, and a written handover at the end. It attaches to an existing data scientists engagement or stands alone if that is the only piece you are missing.
Search Console and GA4 into the warehouse at URL granularity
Joining performance to template version and data version
Feature importance analysis on what predicts an indexed, converting page
Feeding those signals back into the eligibility gate
We look at what data scientists already hold — systems, exports, APIs — and score each axis for demand and defensibility.
The data contract is written and the first template is designed against real rows, not placeholders.
4,500–10,500 URLs published with schema, internal links, sitemap entries and IndexNow.
Indexation and impression data decides what widens and what gets cut. Templates, gates and runbook transfer to you.
Roughly 2,000 indexed URLs with 90 days of history; below that the signal is mostly noise.
We'll audit the data source, size the first batch, set the performance budget and tell you honestly if programmatic is the wrong tool for your category.