“How much I’m gonna sell of it?” is the question that every retailer has in mind when they are thinking about adding a new material into their stores and e-commerce.
We usually have a lot of techniques to help us with forecasting and prevision, but when we talk about new products we face a little big problem that is the fact if we don’t have sales data for the new product to use in regression or in a time series algorithm.
So… how can we forecast it?
One way to work around this lack of data is finding a product that is similar to the new one and copying a percentage of its historical sales data, and with it, you can now apply your preferred forecasting technique.
Basically, you can compare the products in several different ways and besides that each business will have to define what are the ideal features to use in this analysis.
After having the features defined, which is the most difficult and important step of the process, you will follow a simple step-by-step to achieve your goal:
1. Apply one-hot encoding to categorical data
Applying one hot encoding we go from comparing distances between the categories names/texts, to comparing whether or not the product is in the same category as the old one.
2. Apply a scaler technique to numerical data
When we talk about distances it’s always something like A-B=C, but now we are discussing about the distance of several characteristics and the result sounds like the sum of all Cs created by all As minus all Bs.
There would be no problem with that, only if the range of values from columns is all the same, and I’m quite sure that this is very, very rare to occur.
Let’s say that we have 3 columns, one has a range of values from 200 to 400, another column is something like 15k to 78k, and a third one is from 1 to 10.
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Oh…I am so sleepy…because I launched AskMakers 2.0 on Product Hunt and I have been monitoring it almost without sleeping😪
The first version of it was launched about 10 months ago.
I worked so hard on it and it got over 100 upvotes within 24 hours for the first time🤩To make an app useful, I sent emails to ask successful makers to join AskMakers.
I am nobody, just a software developer from Tokyo (currently in Vancouver), however, some of them signed up on and support it!! Unbelievable🤯
After that, it took 10 months until the launch of 2.0…
I always thought like I need to add more features to launch, and I felt like I can never launch it…I should not try to be perfect.
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