A Search Algorithm that gives relevant data to the customer upon a specific search key ("12MP Phone", "IPhone X", "Black color phone", "Blue color watch" etc..)
What’s your project called?
Sia (why we named it Sia… is because Sia is the Greek god known as personification of knowledge) we want this search engine to develop further and become a virtual interactive bot that Rogers can deploy at their stores to give an amazing experience to the customers.
Elevator pitch (short tag line)
Giving the power of useful knowledge to the customer to enhance their website experience.
It’s built with (language, API, hardware, hosts,UI kits…)
AWS cloud, Java, NodeJS, Sql, springboot,
Whole Story
a. Inspiration, what it does, how I built it, challenges I ran into, accomplishments that I’m proud of, what I learned, what’s next for this project…
Our inspiration came from a problem that we faced when searching for products on Rogers website. We noticed that the search results didn’t generated more value to us and we spent more time to find the product and services we were searching for. Consequently, we decided to focus on this problem and build a small application that will enhance a user experience and make the website more intuitive. We took an approach of incremental innovation that will allow the company to capitalize on the technology blueprint they already have and improve it.
We started analyzing the given data set and the current search screen to make a search result layout that will help customer look at the data and make a decision quicker. It will reduce the number of clicks a user has to do in order to buy a product. When we started building the application, we got into many issue with connectivity as it was taking a lot of time to load the project components. This delayed our timelines a lot and we had to rush to build without end to end regression testing.
We are very proud of our team as we all came together from different paths of career and tired our best to deliver a product that Rogers can use readily in their existing website.
We see many future applications on focusing on the search and search patterns. i.e.
1) Analyzing the search history of the website users who bought a product or bought a service, using those data points or click pattern to provide the search results for the next user who is searching for a product with similar search words. This is a machine learning use case of building on search functionality.
2) Building a virtual interactive bot with use of hologram technology that gives the results on the predictive search/sell pattern and user input. This can be used at rogers stores.
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