Ranking, grouping, and correction - in one configuration
Every sort configuration is built from three parts: what ranks, how it's grouped, and when it re-runs.
Revenue per impression ranking
Products are ranked by the revenue they return for the shelf space they occupy, calculated separately for every collection they appear in.
Groups and conditional logic
Split a collection into ordered buckets and apply a different ranking rule to each, with tiebreakers to resolve ties.
Ordering that corrects itself
As demand, stock levels and seasonality change, sort order updates on schedule - without a merchandiser catching each change by hand.
How Every Possible Collection Sort Works
From default sorting to performance-based merchandising
Install, set your ranking rules once, and let performance data automatically reorder collections. Full visibility into every sort.
Install and enable tracking
Install Every Possible Sort from the Shopify App Store and enable the tracking extension. It records product-card impressions, clicks and revenue with the collection context attached, so every metric can be traced back to the page it happened on.
Configure your first collection
Define groups, data points and tiebreakers for one collection. Choose revenue per impression or conversion rate as the primary ranking metric, and set conditional rules for stock levels where needed.
Preview and schedule
Review the resulting order before it goes live. Once confirmed, schedule the sort to run automatically at the frequency you choose, and the collection will keep reordering itself as the underlying data changes.
Monitor and refine
Track collection performance, revenue per impression and conversion rate over time, and adjust the configuration as needed. Every sort run is logged, so the reasoning behind any ordering is easy to trace.
Features of Every Possible Collection Sort
A sort configuration built for how merchandising actually works
Performance metrics
Rank by revenue per impression, conversion rate, sales velocity, or a combination of these. Every metric is calculated per product, per collection - not as a blended, store-wide average that describes a different context than the one being sorted.
Conditional groups
Split a collection into ordered buckets, each with its own ranking rule: fully in-stock products ranked by revenue, partially stocked products ranked by velocity, and out-of-stock items pinned to the bottom. Full merchandising logic covered.
Variant availability
Set conditional rules based on inventory levels, such as requiring core sizes to be in stock. Products missing key variants move down automatically, and dead stock no longer occupies a position it cannot convert.
Tiebreakers
Use a secondary data point when the primary metric is equal or deliberately coarse; for example, rank by edition year, then by sales velocity within each year. Merchandising intent is preserved while the fine ordering is still earned.
Allocate shelf space by performance, not guesswork
Let revenue per impression and conversion rate automatically drive collection ranking, and let a collection that used to need weekly attention run on its own.
Install Now