If you need to zero out your inventory for just a few different product types, then batch updating is the fastest way to do that. Since quantity adjustments are variant specific, you do have to do each product type separately. What you'll need to do is:
On the Inventory > Products page, select the product type from the dropdown menu
Under the variant specific filters, check the box for each condition (and language, if applicable)
Still under the variant specific filters, use the filter for "quantity between 1 and __" (note that this is different than the "total qty between" filter under the product specific filters)
Under batch update, check the top box under the "Variants" tab. Select "Set qty to" "0"
Batch update!
Using the "quantity between 1 and __" filter is a very important step that we sometimes see get skipped. It makes sure that the batch update only goes after the conditions you have in stock, since those are the only ones that need to be set to 0 anyway. Otherwise, it will go through all of your conditions, which takes a very long time.
As an example, this is what it would look like to set all Magic Singles to zero:
If you have products spread out across multiple product types, then mass create may be the best option. Here's how to zero out your inventory via mass create:
On your Inventory > Products page, only use the "quantity between 1 and __" filter under the variant specific filters. (don't select any product types or categories)
Export to CSV
Go to your Notifications > Generated reports page and download the inventory export when it completes.
Open the file in excel, and remove all columns except for the following: Product Name, Category, Condition, Language, Qty
Set the numbers under the Qty column to 0 and save.
Go to the Inventory > Mass Create page in your admin.
Check the box for "this import contains multiple categories"
In step 3, keep it on the default settings and upload the file you saved. Click "Mass Create" to upload it, and it will set your quantities to zero.
Here is an example of what one of these csvs might look like:
