Adapted search



what is this about
Present personalised content and adapted search page layouts to support customer's own search intents and shopping missions.

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Challenge
Search engines based on keyword matching can return unexpected results on those sesions looking for inspiration and guidance.

Please, notice we say "unexpected" instead of "wrong".

Goal
To understanding and interpret search intents and customer's shopping missions.

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PROCESS
Translating user behaviours into data dimensions that the algorithm can learn as a way to automise the selection of relevant information.

  1. Discovering opportunities through user behaviors tracking
  2. Triangulasion of qualitative and quantitative techniques for problem understanding
  3. Mapping realtionships between data for initial context and semantics.
  4. Collaborate with data science and engineering to translate semantics into data dimensions.
  5. Build a AI Machine learning Model and tools, creating a search algoritihm's independent learning loop.
  6. Prototype and test SERP layouts and components for each context.
  7. Connect predicted semantics with layouts and components.
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Test results and learnings



6 % conversion increase
in complex purchases.


2 min avrg. decrease in
time to ATC.


6 % conversion increase
in complex purchases.


6 % conversion increase
in complex purchases.






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