Skip to main content
The Personal Recommendation Preset is a machine-learning preset that predicts which product a customer is most likely to buy next. It leans on each customer’s own behavior, the behavior of similar shoppers, and the catalog itself to surface the most relevant items for every person. Maestra Platform offers two variations — a standard version that refreshes once a day, and an event-based version that recalculates in real time. Pick the one that matches the placement.

Personal Recommendation Preset

Refreshes once a day. Best for email placements.

Event-based Personal Recommendation Preset

Refreshes in real time as customers browse. Best for on-site placements.

​
Personal Recommendation Preset

This preset only generates recommendations for customers with activity in the last 90 days. Everyone else will see either recommendations calculated earlier (if the preset is more than 90 days old) or a fallback to the Bestsellers preset.
Predicts which product a customer is most likely to buy next.
  • Best used for “Next order suggestion” flows and win-back mechanics — placements that don’t need an in-session reaction.
  • Identified customers only.
  • Available through the API (recommendation widget) and email.
Good to know:
  • Signals used: the customer’s views, orders, and list activity, plus behavior from similar customers (Look-A-Like).
  • Refresh: once a day.
  • Limit: up to 5 instances per project.
  • Segment: can be limited to a product segment.
  • Auto-filters: checks the product’s area and brand (multi-brand projects); excludes items the customer has already bought.

​
Event-based Personal Recommendation Preset

This preset only generates recommendations for customers with activity in the last 90 days. Everyone else will see either recommendations calculated earlier (if the preset is more than 90 days old) or a fallback to the Bestsellers preset.
Works just like the standard Personal Recommendation Preset, but recalculates in real time as customers browse, add to cart, or take other actions on your site. Also supports anonymous customers.
  • Best used for the homepage, account page, 404 pages, and search results.
  • Works for identified and anonymous customers.
  • Available through the API (recommendation widget) and email.
Good to know:
  • Refresh: real time.
  • Limit: up to 1 instance per project.
  • Auto-filters: checks the product’s area and brand (multi-brand projects); excludes items the customer has already bought.

​
How to set it up

1

Open Product recommendations

Go to Content → Product recommendations and click Add mechanic.
2

Choose the preset

Pick Personal Recommendation Preset or Event-based Personal Recommendation Preset, depending on the placement.
3

Name the preset

Give it a clear name so you can find it later in widgets, emails, and reports. Click Continue.
4

Configure general settings

To draw recommendations from a specific slice of your catalog, choose a scheduled segment of products. Leave it empty to recommend from the full catalog.
5

Launch the preset

Activate it. The Product recommendations page shows the preset’s status and the timestamp of its last update.
Pair the Personal Recommendation Preset with a fallback (like the Bestsellers preset) so customers with too little behavioral data still see a relevant set of products.