PasseiDireto 2019

A new search intelligence and experience on web and mobile app

TEAM | Laurence Alves (Product designer) and Mariana Nobre (UX Researcher)

MY ROLE | Discovery, product strategy, visual and interaction design, prototyping & testing, metrics and iteration 

Problem scope

We wanted to increase study material consumption (% engagement view).

However, users couldn't find the material they needed and existed within the platform.

Process

  • Research

    CSAT, In-depth interview with engaged users (Search patrons) and data analysis of use of the filters

  • Design Sprint

    Collaborative team immersion, benchmark analysis, sketching, prototyping and validading

  • Validading

    Usability tests with high fidelity prototype with Search patrons and iterations

  • Performance

    AB testing, performance analysis and post production iterations

goal

Guarantee a great search experience by delivering high quality results intuitively

πŸ‘‰ Make a smooth and easy to use experience

πŸ‘‰ Implement some level of personalization in search

πŸ‘‰ Focus on the search engine (recommendation logic) and its delivery

Deliverables

Phased out into smaller deliveries, rollout out, AB tested and CSAT survey to track performance

Autocomplete

πŸ‘‰
Best matches to input (using Elasticsearch)

πŸ‘‰ Smart filters: Suggestion of filters in accordance to input typed by user

Filters

πŸ‘‰ Dynamic and contextual to the input searched

Listing page

πŸ‘‰ Intelligence: Direct results to a single type of content (depending of the search input)

πŸ‘‰ Other types of content offered in sections mixed with the main result

Usability test phase

  • Analyse comprehension on the new search recommendation engine; findability; and overall experience (focus on mobile)

  • 17 users tested between mobile and web rounds. 3 users from Search Patrons.

  • RITE method. 5 rounds of test with iteration in between.

Micro interactions

Microinteractions are trigger-feedback pairs in which (1) the trigger can be a user action or an alteration in the system’s state; (2) the feedback is a narrowly targeted response to the trigger and is communicated through small, highly contextual (usually visual) changes in the user interface. – Nielsen Norman Group

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