How to find what drove last week's non-brand gain, without sorting three tables
Category tab, sort by change, queries tab, sort again, cross-read. A recurring weekly diagnosis, collapsed to a sentence.
Before, the dashboard ritual
9 steps · 3 tabs · 2 sorts
- Open the growth-trends view
- Branded filter: Non-branded
- Dates: last week vs prior week
- Metric: Clicks
- Drill down by Category
- Sort by total change in clicks
- Switch to the Queries tab
- Sort by total change again
- Cross-read the two tables
After, one question
For non-branded organic, what changed last week, and which categories and queries drove the gains?
Paste it into Claude, ChatGPT or Cursor with Quattr MCP connected. No tool names, no field names, routing is the assistant's job.
The answer
For non-branded organic, what changed last week and which categories drove it?
Analysis plan, every step, resolved for you
- Routed to the governed workflow
weekly-search-report - Scope resolved before filtering
segment: Overall Market · Jul 20 to Jul 26, 2026 - 1 analysis queued
gsc_breakdown - Honesty gates armed
scope echo · freshness
One category and two queries carry the week's gain.
- Non-brand clicks
- 46.2K ▲ +12.4%
- Top gaining category
- How-to guides ▲ +1.9K clicks
Jul 20 to Jul 26, 2026 vs Jul 13 to Jul 19organicnon-brandsegment: Overall Market
⚠ Observationalas of Jul 27, 2026IllustrativeOpen in Quattr ↗
Category names are your taxonomy, the same business language in the UI, the card, and the deep-link.
A simulated conversation on fictional data, composed from this workflow's scenario by the same director that renders every demo on this site, scope, freshness and the ⚠ Observational marker are attached automatically, not written by hand.