Recommendation algorithms work best when they have data to work with. For known returning visitors with browsing or purchase history, Personyze can produce highly personalized recommendations. But what about new subscribers, anonymous traffic, or visitors whose interests don’t yet match any of your products with statistical significance? Without a fallback, those visitors would see empty or arbitrary recommendations — which looks broken.
Fallbacks solve this by defining a secondary algorithm that runs whenever the primary algorithm can’t produce meaningful results.
Setting a fallback
In the algorithm step of any recommendation wizard, look for the Fallbacks area next to the filters — there’s a small + icon. Clicking it opens an additional algorithm picker, identical to the main one.
Select any algorithm to act as the fallback. The most useful fallback choices are typically:
A title per fallback
A fallback changes what the widget shows. Until now it did not change what the widget said — so
“Frequently bought together” could sit over a row that was really a best-sellers fill. Each fallback can
now carry its own heading.
In the template editor, on the Look step, templates that offer it show a Widget
titles entry in the design menu. It opens as:
- Main title — used when the first-choice algorithm serves.
- One row per fallback you have configured, each labelled with that fallback’s own algorithm
name — Bestsellers, and so on — and each with a checkbox. Leave it unticked, which is the default,
and that fallback inherits the main title; tick it and a title field appears for that fallback alone.
The titles are ordinary dynamic text: variables and tokens work in them exactly as they do in any other title, so a
brand token or a visitor’s first name behaves the same way here.
title disappears with the widget rather than floating over an empty box.
titles menu; gallery templates are being updated to carry it, and a template without the entry simply has one
title, as before. It works wherever the template customizer does — on-site widgets, email recommendations and
get-code / external-media widgets — but not in the
Canvas Builder, which is not wired to it.
This supersedes the older email-template pattern of a single “Title (fallback)” field shared by
every fallback.
Best practices
- Always set a fallback for personalized algorithms. “Personalized for this visitor” only works if the visitor has data. Without a fallback, half your audience may see nothing.
- Match the fallback to the surface. A homepage hero deserves a high-quality fallback (Most Popular). A “Frequently Bought Together” widget on a product page should fall back to category-popular items, not random products.
- Avoid arbitrary fallbacks. “Any Products” with no filters can produce strange combinations (out-of-stock items, off-brand products, retired SKUs). Always layer in basic filters like in-stock and active SKUs.
- Test the fallback explicitly. Use the campaign’s QA step with a brand-new email address (no behavioral history). What renders is exactly what new visitors see — make sure it looks great.
When the fallback fires
The fallback activates whenever the primary algorithm can’t produce a statistically meaningful result. Common triggers:
- The visitor has no on-site behavioral history yet (e.g., new subscriber being shown an open-time email recommendation).
- Their behavior history exists but doesn’t intersect with your current catalog (visited a product that’s been removed).
- The algorithm requires a minimum confidence threshold and the available data falls below it.
You don’t need to manually detect these conditions — Personyze runs the primary, evaluates the result quality, and silently swaps in the fallback when needed.