The easiest way to enable the product recommendation section is to use one of the official…
We have recently completed a major migration of our database technology from Hbase (part of the Hadoop stack) to Apache Cassandra.
One of the original appeals for selecting Cassandra is AWS Keyspace since Siggy runs entirely on AWS infrastructure.
However, after testing our Siggy on AWS keyspace, we discovered the…
With the launch of Siggy, our AI-based product recommendation app for Shopify. I thought it would be a good time to share the product journey from the background motivation to any of the future plans.
I was working on Trakr, a visual QA automation product where we were running into…
As our product recommendation engine (Siggy) matures, we are starting to look at areas that can improve its performance. The two areas of performance we are looking at improving are:
Siggy uses a “content-based” recommendation algorithm. This means that we only need “content data” for the algorithm to work.
In the context of a product recommender, we only need product attributes such as (Product name, description, images, tags) to generate effective recommendations for the user.
There are three primary reasons…
This is the classic dilemma of building digital products from experience and proven technology vs. trying new things.
We are almost 3-months into the venture of building a functional prototype for our recommendation engine and we are almost there!
Our goals for the functional prototype are still:
One of the keys to an effective working day or week is to group related tasks together where you can concentrate and make great in-roads. Last week was not one of those weeks.
For example, we had planned various types of tasks: