@denizdoingstuff@interaction@linear Itβs honestly super simple, intentionally
Issues = individual tasks I need to do
Projects = one-off things I need done with multiple tasks
Initiatives = βlargeβ projects/categories with multiple projects within them
Morning brief + multiple check-ins from @interaction
@EcomRedneck Easiest move is campaigns per style/sku with your setup
Alternative:
Have been scaling hard with ABO, highest volume testing for the same reasons
Adset = βSKU/Collectionβ x βAngle/Batchβ
Then scaling campaign per sku/collection, but creative testing usually outspends them
Have been focusing hard on finding & systemizing the best setup for *smaller* brands on meta
Across a large variety of brands spending <4k/day, I am scaling very fast with:
1. CBO βMainβ - adset per concept/angle/batch.
2. CBO βScalingβ top ads duplicated here
@ron_ecomm Really same thought work got us there, backing out against site + MTA #βs
The brand Iβm referencing spends a lot on influencer so (as always) this stuff just depends on a combo of things
@ron_ecomm 7DC based on your 3rd party callout, especially if it wins out when you compare to the site
Not sure your full structure but then you could also test this for different objectives
(Ie one of my brands runs 7DC prospecting campaigns, then IA for retention)
Introducing ChatGPT Images 2.0
A state-of-the-art image model that can take on complex visual tasks and produce precise, immediately usable visuals, with sharper editing, richer layouts, and thinking-level intelligence.
Video made with ChatGPT Images
Since the big Meta update, across 30+ brands Iβm seeing;
1. Much cheaper impressions (CPMr + FTIR moving in positive directions)
2. Higher cost per conversion events (ATC, IC, Purchase)
3. Relatively flat (or improved) site wide + MTA KPIs
@herrmanndigital +1
Top spender for one of my brands by far L7D is a flex
CPA is up >500% in platform DoD
MTA (TW) CPA is only up ~1% π§π½ββοΈ