Fallback behaviour and when it applies
How Liva 7 fills gaps when rules or limits restrict the product pool
Overview
Fallback behaviour is the safety net inside the Liva 7 Personalisation Engine. It ensures that recommendation blocks never appear empty, even when rules, limits or shopper behaviour reduce the number of eligible products.
This article explains when fallback activates, how it interacts with rules and algorithms and when merchants should allow or restrict it.
What fallback behaviour is
Fallback behaviour is the engine’s final step when selecting products. If the eligible product pool becomes too small because of exclusions, strict limits or weak behavioural signals, fallback ensures the system can still generate a complete recommendation block.
Fallback exists to:
- prevent empty or broken layouts
- maintain a consistent storefront experience
- support discovery when signals are weak
- ensure widgets and Smart Content always have enough items to display
Fallback activates only when the engine cannot fill a block using eligible products.
When fallback activates
Fallback behaviour triggers in predictable situations where the engine cannot meet the minimum number of recommendations required by a widget, Smart Content block or bundle.
Fallback activates when:
- too many products are excluded
- strict rules reduce the eligible pool
- a shopper has very weak or no behavioural signals
- a page context has limited product relationships
- minimum recommendation limits cannot be met
Fallback ensures the system can still produce a complete, stable output.
Fallback is a last resort, not a primary strategy.
How fallback interacts with rules
Rules always take priority over fallback.
Fallback can never override exclusions or force pinned items to appear.
The hierarchy remains:
- Exclusion removes items from the pool
- Pinning elevates items within the pool
- Algorithms rank the remaining eligible items
- Fallback fills gaps only if needed
Fallback respects all rule boundaries and never introduces items that rules have removed.
Fallback cannot break rules, it only fills gaps within them.
How fallback interacts with algorithms
Algorithms determine relevance.
Fallback determines completeness.
When fallback activates, the engine:
- uses broader product relationships
- expands category relevance
- relaxes behavioural thresholds
- prioritises general popularity signals
This ensures the recommendations remain sensible, even when the shopper’s behaviour provides little guidance.
Algorithms optimise relevance, fallback ensures stability.
How fallback affects widgets
Widgets rely on fallback to avoid empty or incomplete layouts. If a widget requires a minimum number of items and the eligible pool is too small, fallback fills the remaining slots.
Fallback helps widgets:
- maintain consistent layout structure
- avoid gaps or empty rows
- support early session shoppers
- ensure homepage widgets always feel full
Widgets use fallback to protect layout quality.
How fallback affects Smart Content
Smart Content blocks that include product lists also rely on fallback when rules or signals reduce the eligible pool.
Fallback ensures Smart Content can:
- display complete product lists
- support targeted messages without empty spaces
- maintain consistency across different audience types
Smart Content uses fallback to keep product lists complete.
How fallback affects Smart Bundles
Bundles use fallback more sparingly because bundle logic is more specific. However, fallback still plays a role when:
- excluded items remove key bundle components
- product relationships are too narrow
- the shopper’s behaviour provides limited context
Fallback ensures bundles remain functional even when constraints are tight.
Bundles use fallback only when essential to complete the bundle.
When merchants typically disable fallback
Some merchants prefer strict control and choose to disable fallback entirely. This is useful when you want:
- highly curated recommendations
- strict brand or category boundaries
- no broad or generalised suggestions
- recommendations to disappear when rules restrict the pool
Disabling fallback increases precision but reduces coverage.
Disabling fallback increases control but may reduce visibility.
When merchants typically allow fallback
Most merchants keep fallback enabled because it ensures:
- widgets never appear empty
- Smart Content always displays complete lists
- new shoppers receive helpful suggestions
- the storefront feels consistent and stable
Fallback is especially valuable on high traffic pages like the homepage and product pages.
Allow fallback when consistency matters more than strict curation.
How fallback supports long term personalisation
Fallback ensures the engine remains reliable across all shopper types and page contexts. It protects the storefront from empty states and ensures that personalisation remains functional even when signals are weak or rules are strict.
Fallback supports long term personalisation by:
- maintaining layout stability
- supporting early session and anonymous shoppers
- ensuring recommendations always feel complete
- balancing strict rules with adaptive behaviour
Fallback keeps personalisation stable, even under tight constraints.
