Search and Discovery
technology that engages
Traverz humanises the Product Search Experience by using preference-based interactions, resulting in unparalleled insight into users’ commercial intent
A whole new paradigm
for online product search
Traverz is a UX and Search layer that encourages users to explicitly indicate their needs and wants. This provides powerful first-hand information on their commercial intent, allowing platforms to generate truly personalised recommendations.
Product search is failing users - and platforms
“Frustration with the overall product search experience is responsible for 68 percent of consumer churn and burn today.” - Forrester
Hard Filters
A generation of users has learned not to use ‘hard’ filters and search bars, for fear of zero results or simply missing out on that product that is not quite meeting every criteria. So they scroll and scroll, until finally they give up.
Passive Recommendations
Collaborative recommendation technology provides a ‘push’ of suggestions from platform to the user – they do not enable users to express intent. Hence recommendation quality is low and personalization is limited.
Frustrated users express no clear intent, leaving platforms with limited data and rudimentary recommendations. See how Traverz changes this with a whole new product search experience.
“The technology that Traverz has developed is an important step towards commoditising conversational AI and allowing e-commerce players, big and small, to take personalisation to the next level”
Barry Smyth
ProfessorTraverz Conversational Recommendation
Customer Experience
Traverz provides a modern, productive experience that generates user confidence and loyalty.
Users smoothly move from the discovery phase to search and purchase on the same platform.
Sales and Conversion
Confident, engaged users are more likely to convert.
Greater engagement in the search process organically broadens user consideration, and encourages upsell.
User Insights
Traverz encourages users to explicitly share their needs and wants, rather than aimlessly browsing.
Preference-based search unlocks user dialogue and enables a two-way communication.
Data Requirements
Traverz is robust in the face of imperfect data, through preference- based recommendation and AI-driven data analysis.
Product attributes are expanded well beyond the original filter data.
An independent UX study found Traverz to outperform traditional filters
Seamless integration
Traverz Conversational Recommendation Technology is designed as a plug-in UX and Search layer, replacing or supplementing existing search and recommendation tools.
