I run aihello.com that uses predictive analysis to predict which of your inventory is going to sell where and how much. We use this stock up appropriately in re

I run aihello.com that uses predictive analysis to predict which of your inventory is going to sell where and how much. We use this stock up appropriately in recommended geographic area. (for example 30% more organic products in the east coast vs west coast etc) We use sklearn, facebook prophet and apache spark ML Here is a screenshot of the dashboard of one of our customer : https://screenshots.firefox.com/hO1TIVsQWoNolqLj/www.aihello.com https://screenshots.firefox.com/hO1TIVsQWoNolqLj/www.aihello... >3.How much data do you need to have until your predictive analytics gets smart enough to predict things accurately? Depends. We have roughly 4.5 million data points for each month and the results are practically usable (Customer has no issues with the error margin in predictions) >4. What are the typical "triggers?" Don't understand this. > Anyone think predictive analytics is BS? If so, why? This is like asking if anyone thinks trigonometry is bullshit.