My take is, you need to continue creating helpful, original, human-finessed content. AI tools can (should) get you partway there, but they've yet to master brand voice/tone and product/specs accuracy. A human touch is still the requisite final "layer" before publishing.
I would also suggest that content be written for the cross-section of (merely) organic search volume...and purchase intent.
For example, consider the intent behind the query/article of
"Best Gym Equipment To Use"
vs.
"How To Build A Custom Gym"
One attracts traffic. The other attracts traffic with a higher likelihood of converting (sign up, purchase).
@ron_ecomm@TaylorHoliday@DaveRekuc@ron_ecomm we use a blend of GSC + GA4 data. It's not perfect, but it's the best way to merge query level data and organic revenue.
https://t.co/w7RfeUvvSZ
@therealkieran, a few ways to accomplish this. We know GSC is devoid of revenue & GA4 is missing query-level insights, so there is some data stitching required.
We look only at non-brand queries in GSC + the traffic lift on pages *beyond* the HP, advertising LPs, and functional LPs.
From here, we can directionally apply a revenue lift % to the organic traffic that flows through these pages as landing pages.
@therealkieran, a few ways to accomplish this. We know GSC is devoid of revenue & GA4 is missing query-level insights, so there is some data stitching required.
We look only at non-brand queries in GSC + the traffic lift on pages *beyond* the HP, advertising LPs, and functional LPs.
From here, we can directionally apply a revenue lift % to the organic traffic that flows through these pages as landing pages.
@therealkieran, a few ways to accomplish this. We know GSC is devoid of revenue & GA4 is missing query-level insights, so there is some data stitching required.
We look only at non-brand queries in GSC + the traffic lift on pages *beyond* the HP, advertising LPs, and functional LPs.
From here, we can directionally apply a revenue lift % to the organic traffic that flows through these pages as landing pages.