The video filters
These rank by attention:
Views (all time, 24h, 7d): ranks videos by views or view growth, so the top result is the most viewed or fastest-growing video. Use it to find viral formats and study the hooks, angles and editing styles working right now.
Date posted (last 24 hours, 3, 7, 14 or 30 days, all time): filters videos by when they were posted, so you stay on recent trends instead of outdated content.
Sort by view growth (24h or 7d, low to high or high to low): surfaces the videos currently gaining traction.
The product filters
These rank by money:
Product units sold (all time, 24h, 3d, 7d): ranks products by total sales volume in that window. The video shown is one example linked to that product, not its top video; tap the product to see more of its videos.
Product sales growth % (24h, 3d, 7d): ranks products by how fast sales are increasing. 3 sales growing to 28 shows as +900%: it measures speed, not volume, so it spots trends before they peak.
GMV MAX Only: shows only videos running ads, which is how you see the products brands are scaling with paid traffic.
Category filter: keeps results inside your niche (Beauty, Fashion, Home and the rest).
Minimum product review score: screens out low-rated products.
Additional filters: all-time views, product total sold count, and product in stock, for volume thresholds and skipping sold-out products.
A workflow that uses both
The two filter families work best in sequence:
Start with product data, units sold or growth, to find what's trending or already selling.
Apply category, review and stock filters to narrow to quality.
Open the product and study several of its videos and angles.
Finish with views and view growth to see which content styles pull attention.
What to remember
Views are attention; product data is sales and demand. Under a product filter, the video on screen is an example rather than the top performer, and product numbers reflect results across creators, ads and regions, not one video's doing.
Next steps
The neighbouring reads: