My dear friends,
In the past couple of years I read a lot about AI with JS and some libraries like TensorFlow. I have great interest in the subject but never used it on a serious project. However, after struggling a lot with linear regression to solve an optimization problem I have, I think that finally I will get much better results, with greater performance, using AI. I work for 12 years with web development and lots of server side, but never worked with any AI library, so please, have a little patience with me if I say something stupid!
My problem is this: every user that visits our platform (website) we save the Hour, Day of the week, if the device requesting the page was a smartphone or computer... and such of the FIRST access the user made. If the user keeps visiting other pages, we dont care, we only save the data of the FIRST visit. And if the user anytime does something that we consider a conversion, we assign that conversion to the record of the first access that user made. So we have almost 3 millions of lines like this:
SESSION HOUR DAY_WEEK DEVICE CONVERSION 9847 7 MONDAY SMARTPHONE NO 2233 13 TUESDAY COMPUTER YES 5543 19 SUNDAY COMPUTER YES 3721 8 FRIDAY SMARTPHONE NO 1849 12 SUNDAY COMPUTER NO 6382 0 MONDAY SMARTPHONE YES
What I would like to do is this: next time a user visits our platform, we wanna know the probability of that user making a conversion. If a user access now, our website, depending on their device, day of week, hour... we wanna know the probability of that user making a future conversion. With that, we can show very specific messages to the user while he is using our platform and a different price model according to that probability.
CURRENTLY we are using a liner regression, and it predicts if the user will make a conversion with an accuracy of around 30%. It's pretty low but so far, it's the best we got it, and this linear regression generates almost 18% increase in conversions when we use it to show specific messages/prices to that specific user compaired to when we dont use it. SO, with a 30% accuracy our linear regression already provides 18% better conversions (and with that, higher revenues and so on).
In case you are curious, our linear regression model works like this: we generate a linear equation to every first user access on our system with variables that our system tries to find in order to minimize error
sqr(expected value - value). Using the data above, our model would generate these equations below (SUNDAY = 0, MONDAY = 1...COMPUTER = 0, SMARTPHONE = 1... CONVERSION YES = 1 and NO = 0)
A*7 + B*1 + C*1 = 0 A*13 + B*2 + C*0 = 1 A*19 + B*0 + C*0 = 1 A*8 + B*6 + C*1 = 0 A*12 + B*0 + C*1 = 0 A*0 + B*1 + C*0 = 1
So, our system find the best A, B and C that generates the minimizes error. How can we do that with AI? If possible, it would be nice if we could use TensorFlow or anything with JS! I know there are several AI models, and I have no idea which one would best fit what we need!