Once sorting is automatic, the next question is how often it should run. "As often as possible" sounds safe and is rarely right. The useful answer depends on the category, and working it out takes three questions.
What changes between two sorts?
An order goes stale because the things it was based on change. There are three of them, and they move at different speeds.
Stock changes fastest. A product can sell out, or lose its popular sizes, in an afternoon. If the sort uses availability, as it should, a new sort moves that product down as soon as the data shows it.
Demand changes more slowly. Signals like weekly sales and weekly views are sums over days, so one more hour of data moves them only a little. A weekend, a campaign or a change in the weather shifts them over days.
The catalog changes in steps. New products arrive when a delivery is put online, and prices change when someone changes them.
So the question "how often?" is mostly the question "how fast does stock move in this category?"
Which signals does the rule use?
A rule built on monthly sales is not going to give a different order an hour later. A rule built on daily sales and current stock might.
Look at the periods in the rule. Performance signals come for the last day, the last week and the last month. The shorter the period the rule leans on, the more a frequent sort can show. If the rule is all weekly and monthly numbers, daily sorting is plenty.
How fresh is the data?
A sort can only be as current as its inputs. If product data arrives once a day, sorting every hour repeats the same calculation on the same numbers twenty-three times.
Find out how often your product feed and your performance data are refreshed, and treat that as the ceiling. This is also why the freshness of the feed is worth watching: a sort that runs on time over data that stopped arriving is confidently wrong.
A way to decide
| Category | What moves | Reasonable frequency |
|---|---|---|
| Campaign and sale pages during the campaign | Stock, within hours | Every hour to every few hours |
| Large core categories with steady traffic | Stock daily, demand over days | Several times a day to daily |
| New arrivals | The catalog, when deliveries go online | Daily |
| Brand pages and the long tail of small categories | Little | Daily to weekly |
| Evergreen categories with stable stock | Very little | Weekly or less often |
These are starting points. The check is simple: if two sorts in a row give nearly the same order, the interval can be longer. If products that sold out are still near the top when you look, it should be shorter.
Do not treat every category alike
A single frequency for the whole store is either too slow for the busy categories or wasted on the rest. Most stores have a few dozen collections that carry most of the traffic and hundreds that carry little.
Give the busy ones a short interval and the rest a long one, and review the split now and then, because which categories are busy changes with the season.
In Merchandiser each collection has its own sort frequency, from every hour to once a month, and it can be changed for many collections in one step. The shortest interval depends on your plan; the plans list it.
What faster sorting cannot fix
Frequency is the last thing to tune. It does not help when:
- The rule ignores availability. Then a sold-out product stays on top no matter how often you sort. Fix the rule first; see Size-Broken Products.
- Pins hold the top positions. A pinned product does not move on any schedule. See Pinned Products: When to Pin and When to Let Go.
- The data is stale. Then every sort repeats yesterday.
Keep an eye on it
A schedule can fail without anyone noticing: the page still shows an order, only an old one. The Collection Health Score includes Sort Freshness, which compares the time since a collection was last sorted with its own frequency. A collection that is overdue shows up there before a customer notices.