Product SKUs (Stock Keeping Unit) are the identification numbers that are used to track inventory. Sometimes, a product might be same, however having different variants within them. For example, a T-Shirt can come in different sizes and different colours. Each of the combinations of variants will be allocated with a unique SKU number. So, this is highly important to differentiate a product with different variant and to track inventory for each of the product variant.
They are important for eCommerce, as for any business, SKU allows them to manage inventory - track items as they are bought, shipped and delivered, as well as their placement in warehouses.
Companies need a unique product ID so that they ship the right product, and have an easier inventory tracking method. Also, if there are multiple Vendors selling the same kind of product, it is obvious that multiple products (from different Vendors) to have this same name, for example "red shirt", or "black iPhone case". Here’s where the SKU plays a significant role. It distinguishes even the same product with same attributes and defines exactly which product is from which supplier or manufacturer.
How are eCommerce systems configured for allocating SKU numbers for each of their product
As the thumb rule, the SKUs should include the key information that are based on the features of the product and that may include – style, brand, colour, type or size. In case of laptops, it can be based on memory space, operating system and so on. The SKUs can also different for the same product, but sold by different Suppliers or Vendors on the same eCommerce platform.
Let us study the allotting of SKU for a product type, based on characteristics, with an example.
Let’s say, the product is a T-Shirt. And, this T-Shirt is available in different sizes and colours.
So, let’s say the T-Shirts are available in sizes – Extra Small, Small, Medium, Large and Extra Large and colours – Red, Blue, Green, Orange and Yellow.
Then, the SKUs will be like this:
·Red T-Shirt and Extra Small Size – TS01-R-ES
·Blue T-Shirt and Large Size – TS02-B-L
·Green T-Shirt and Medium Size – TS03-G-M
·Green T-Shirt and Extra Large – TS04-G-EL
And so on….
Let’s now also bring another key piece of information for the same set of T-shirts. And, that is going to be the style – V-Neck and Polo-Neck
So, for the same set of SKUs as mentioned above, the SKUs change like this:
·Red T-Shirt and Extra Small Size – TS01-R-ES-V
·Blue T-Shirt and Large Size – TS02-B-L-P
·Green T-Shirt and Medium Size – TS03-G-M-V
·Green T-Shirt and Extra Large – TS04-G-EL-P
Further, let’s assume if the same Red-T-Shirt of Extra Small Size and V-Neck style is also sold by another Vendor:
Then, the SKU can be like this
Vendor # 1
Red T-Shirt and Extra Small Size – TS01-R-ES-V
Vendor # 2
Red T-Shirt and Extra Small Size – TS02-R-ES-V
To learn the flow of SKU Configuration in Spurtcommerce, watch this YouTube Video:
How does SKU vitally help your eCommerce business
Maintaining Stock and adjusting supply/demand: Let’s say if Red T-Shirt is moving faster, than the Green one, or if the Medium Sized T-Shirts or moving faster than the others, the supply can be adjusted accordingly. The inventory stock can be re-filled as per the demand only for those particular SKUs that are fast moving.
Discounts and Offers only on particular SKUs: Let’s say, Polo-Neck T-shirts are moving faster and V-Neck is hardly preferred by any Customer, you can plan a clarence sale and offer the V-Neck based SKUs alone at half price. After the clearance sale, you can decide if you should even have those V-Neck SKUs anymore on your eCommerce store.
Generate Key Performance Indicator (KYI) Reports: The KYI reports can be generated for each SKU to analyse the trend on faster moving SKUs and not so much in demand SKUs. This will help the eCommerce business Owners in analysing and adjusting the inventory stock accordingly.
Data Analytics for re-filling stock: You can also use the data from the KYI Reports and plan and fill the inventory stock in advance, so that the SKU do not run out of stock, when actually the demand for it is very high.
Data Analytics for offering personalized experience to Customers: You can also analyse the data based on Customer demographics. Say for example, V-Neck based SKUs might be more popular and preferred by the Ladies, while the Polo-Neck SKUs might be more preferred by Men. Similarly, Pink colour might be fast moving among Girls aged between 20 and 25 and Black might fast move among Men aged between 40 and 50 and so on. And, with the available data of each Customer – their age, gender and other information, the ecommerce system can suggest certain SKUs – ‘You may like this one’.
We have now understood what are SKUs, how are they allotted to each product depending on their key characteristics and how they can boost your eCommerce business.
This way, you can plan and adjust stock based on supply/demand and also plan discount and clarence sale, only for a particular SKU, if not all. So, even if it is same product, within the variants available under that product, the preferences of Customers and buying trends can be observed and the stock and the discount sale can be planned accordingly.
In addition, you can study the KYIs individually for each SKU and also use the available data for offering personalized customer experience.
There’s more to come on the same topic of SKU. Stay tuned for more informative articles on SKUs.