How to improve AI gender identification accuracy?

I’m trying to crack my head around another key challenge at the moment. That is to Increase
AI’s accuracy to be able to identify demographic gender groups from 70% to 80%.
Currently accuracy of the information is at 70%.

I’m running a Data Management Platform (DMP) which collects demographic tag
information and these information are saved in Treasure Data.

I’m thinking of setting some rules in AI to be able to better
differentiate gender. For example, E-commerce data parameters that tells AI that
visitors who have viewed cosmetics have a higher chance of being female while
gadget viewers would have a higher chance of being male.

Do you think these are good ideas/methods? If yes, why. If no, any better
suggestions please?

The Data I have at the moment is not very large, average database of 100,000
users. I’m not able to increase this number any bigger at the moment.

Would be great if anyone could also advise or share on how best to
approach the challenges above and help shed some light on the challenges faced.

Many thanks in advance!
JM LeongAspiring Data AnalystAsked:
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Shaun VermaakTechnical SpecialistCommented:
I believe it is far better to have historical data that includes those behaviours in addition to the gender. You can then use machine learning to guestimate the gender.
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