Bringing the new PDP IA concept to life and aiding design team adoption to deliver most relevant experience for the user.
Design team worked on the new IA for our PDP (Product Description Page). However there were multiple issues with the IA adoption. Some concepts identified in the IA did not exist yet as well as multiple product teams creating their own interprations of what the new IA means for them.
I worked with designers from product teams and design ops team to create an extension framework to the new IA concept. I've also worked in two product teams to bring some newly identified concepts from the IA to life.
I created an extension framework to the new IA that facilitated clear alignment between teams on what the new IA means and further clarified concepts in the IA. I've also worked within product teams to create two new features to bring the new IA to life and deliver most relevant experience to the user.
To kick this project off I reviewed the new IA for the page and worked with design team to identify any missing gaps to aid adoption. Even though I was working to bring the new IA to life, the overarching concept needed to be scalable for any designer in the team to pick it up. Through meeting with different designers I identified two main areas for improvement - more clarity on the new IA sections and guidance on design patterns.
To identify possible solutions to these two gaps I again reviewed existing foundational research on the new IA and reviewed related research to the top of the PDP. In the research I found more evidence to extend the IA with clearer section definitions as well as some indication on what design patterns create best experience to the user.
These insights set the foundation for the extension framework to the new IA. The framework had a few objectives in mind to aid the new IA adoption. First of all, it needed to clarify how much information there should be at the top of the PDP and what are the considerations when choosing different levels of information. Secondly, it needed to have information on the appropriate design patterns for different levels of information. Lastly, it needed to clarify the new sections in the IA and provide more detail on what kind of content should go in them.
Creating a framework
After spending some time drafting the extension framework, I then started sharing the draft for feedback to see if what I'm going after will actually aid the adoption of the new IA. First thing I did was share it the design team to see if there are any incoming features in this space that this framework could influence. I then shared with other business units, to see if there's anything that they're planning in similar space to seek alignment.
The framework was well received. And there was a lot of excitement, especially on the thinking behind how much information to show in each of the IA sections and how it links to existing design patterns in our design system. In addition, the framework considered how this IA could translate to machine learning driven page where all of the IA sections are contextual to the user.
Bringing new IA to life
Having finished the framework and aligning with all teams, I then start working on the actual features to bring this IA to life and to our users. I worked in two product teams simultaneously to do that. First team I worked in a was the relevant amenity team, which based on the new IA aimed to bring most relevant machine learning driven amenities to the users. The second team aimed to introduce a new section from the IA called property highlights, which would show the best and most unique features of the property to the user.
Each of these work streams required different levels of effort and different types of design exercises to deliver the end product. For the amenities. I mostly worked on data signal capture and aligning with data science to gather as much data as we can to show most relevant amenities to the user. It also included testing some of the patterns that I identified in the extension framework to the new IA. The property highlight work stream was a bit more complicated as it was a completely new section identified in the new IA.
I kicked off the property highlight work stream with a two day design workshops. The two days included workshops to reviewing existing data, qualitative research and working stakeholders and subject matter experts to define HMW statements on what a property highlight might be. With a number of potential options identifies I ran a workshop with our product team to create some design concepts.
I then turned those design concepts into prototypes and decided to do user research to evaluate them and guide our direction. This was a self serve research project, so I led most of it included drafting the test plan, brief and setting up an unmoderated study online. The study identified a number of interesting findings and helped us narrow down our focus on what a highlight could be. The most conclusive finding was that the location is the most important aspect when differentiating one property from another
We then work with external teams to align on possible data sources and content sources that we could use to create highlights for our users. After many conversations, we decided that showing most popular and most positive mentions about properties location is the biggest opportunity for us. I then worked with the development team to align on the API responses and created design options for our fist test on property highlights.
After completing the work for the relevant amenity work stream, as well as having the first test ready for the property highlights. I initiated another research project to both test these new feature concepts, and to test some of the principles from the extension framework that I created. This research in practice validated some of the principles I outlined in the extension framework and gave us a further steer on amenities and property highlights.
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