By Ronnie Jansson, Director of Data Science at Investopedia / Keynote
Data science is fundamentally about understanding your user
base to offer insights you can’t ask your business intelligence
team to pull out for you.
A helpful use for data science is to create algorithms for
recirculation. It allows you to provide users with content
links relevant to what they are already reading. This keeps
users “circulating” your site longer. It can also identify gaps in
content, which is no small task for companies like Investopedia,
whose site already has over 100,000 articles on finance and
economics.
Analyzing user interest can help drive sales or inform new
products. For example, it can identify a co-occurrence
between users reading on multiple different topics, meaning
if a person is interested in topic x, they’ll also be interested in
topic y. This allows publishers to create content for an intent-driven
audience.
Many insights gained from data science can benefit online brokerage firms, such as how market performance affects content consumption. For example, in a low-interest-rate environment, tutorials demonstrating how to invest in stocks became much more popular compared to those about bonds.
Location and reader demographics have an effect on content consumption as well. For example, New York-based consumers read more content on advanced topics- such as structured products, while North American tech centers can be identified by looking at where those interested in stock options are...
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