Understand value, movement and relationships
without losing the evidence.
See eligible customer and journey signals in context, keep observed behaviour separate from inferred preference and use supported patterns in responsible store decisions.
A connected view of behaviour, intent and commercial context without reducing a person to a single segment label.
Illustrative interface - actual results depend on your store data
Relevance begins with understanding,
not assumption.
Customer Intelligence brings behavioural signals into the same context as products, orders and store performance. It supports useful personalisation while keeping the difference between observation and inference visible.
See meaningful actions in context.
Use the same context across Liva 7.
Inference and confidence stay visible.
Understand meaningful behaviour
Bring browsing, purchase and engagement signals together without treating any single action as the whole customer story.
ObservedRecognise useful relationships
Identify repeated interests, affinities and journeys that can inform a better store decision.
ConnectedKeep the commercial question visible
Use customer understanding because it helps answer a store question, not because more segmentation is always better.
PurposefulCarry understanding into the experience
Support recommendations, content and storefront placement with the same customer context.
ActionableObserve the signal.
Use it with a clear purpose.
Liva 7 connects customer understanding to the decision it is intended to support, whether that is a recommendation, a message, a product relationship or a storefront experience.
- 01ObserveRead the behaviour
Relevant customer and session signals are connected.
- 02DistinguishLabel the evidence type
Observed and inferred information remain separate.
- 03UnderstandIdentify the pattern
Behaviour is considered with product and store context.
- 04ApplySupport a decision
The insight informs a relevant recommendation or experience.
- 05LearnMeasure what followed
The outcome adds context to future decisions.
Useful context should not
become unexplained surveillance.
Signal origin, confidence and intended use remain visible. Customer context supports a relevant experience rather than becoming a claim about a person that the evidence cannot support.
The system does not present interpretation as observed fact.
Personalisation remains connected to a useful store goal.
You decide how customer context is used in your store.
Make the next store decision more relevant to the people it should help.
Connect customer signals to practical, reviewable store action.