Personalized Shopping Experience using Watson

Watson Analytics is a smart data discovery service available on the cloud that guides data exploration, automates predictive analytics and enables effortless dashboard and infographic creation. Using the data served by this intelligent tool, we are better able to make confident decisons regarding a set of data.

My Role

With a team of 6 members, we were tasked to design an application that presents useful information driven by the Watson Analytics API. We tackled the problem by presenting an online shopping experience that uniquely tailors to the user based on their observed interests. The team was composed of front end developers, back end developers, business oriented members, and two UI/UX designers including myself. My contribution was mainly the user experience and design of the mobile application which serves to satisfy the requirements discussed by the whole team collaboratively.

Problem Space

Shopping becomes super frusturating when you've scanned through 20 pages of an online store and you haven't come across a single product that tickles your interest. After that, the only thing that might be felt if regret, especially when you probabaly should've been getting other important work done in this time and online shopping was only suppose to be a quick source of happiness!

Research

With online shoppers within our project team itself, the research subjects were easy to obtain. We analyzed team members as they searched their favourite online stores with a "think aloud" approach. As a result, we were able to identify the pain points during the process:

On average, user was interested in a product after searching three pages of items.

User feel that majority of the products perform poorly at aiming to their unique personalities.

Time taken to find a product exceeds the time that the user allocated for their shopping visit.

Some users never even found a prodct that they liked during their recorded shopping trip.

Solution

A store just for the user.

We presented a shopping application that performs deep learning on each unique user. By collecting data from certain activities in the user's social media, Watson Analytics is able to analyze this data and determine the user's interests in a few different categories: Sports, Movies, Health, and Education. More specificly, each of these categories can be taken a step deeper by the user to see which of their activties in the past have impacted their persoanlity results. The result of this is an online store that collects catered products from multiple vendors into one place. This saves time from browsing through countless pages, and highly improves the success of the mobile shopping visit.