Stock planning is important for retailers. Overestimating stock wants may be pricey. However underestimating might be pricey, too — hurting income and revenue. Simply-in-time stock preserves money, reduces storage wants, and lowers the danger of loss.
It's important, subsequently, to precisely predict stock necessities. Google Analytics and Knowledge Studio can help by offering historic gross sales and developments.
Historic Gross sales, Developments
Assuming Ecommerce reporting has been arrange (Conversions > Ecommerce), Google Analytics supplies historic gross sales knowledge general and by product identify, SKU, and class. For gross sales by product, go to Conversions > Ecommerce > Product Efficiency.
To report by SKU, add a secondary dimension by “Product SKU.”
The “Amount” column exhibits the variety of models bought within the timeframe chosen.
To forecast demand for an SKU:
- Click on “superior” above the desk of knowledge. Then arrange an embrace filter to report on a selected SKU.
- Choose an prolonged historic interval, comparable to two years
The report will present two years of gross sales for a single SKU. Within the instance under, the SKU has a number of entries based mostly on the gross sales channel – website, Amazon, eBay.
To report amount within the graph as an alternative of income, choose “Amount” within the drop-down menu.
Lastly, report month-to-month knowledge by altering choices from “Day” to “Month.”
The ensuing output is 2 years of gross sales by amount for the SKU. Use this knowledge to know seasonality influence on gross sales and to spotlight general tendencies.
Used collectively, the two-yr gross sales graph and the amount bought desk, under, may help you estimate future gross sales and stock wants every month.
If the info is inconclusive, examine gross sales yr-over-yr. Within the screenshot, under, I’ve chosen the 12 months ended April 30, 2018, versus the identical interval ended April 30, 2017.
Then analyze the graph and desk for modifications in gross sales. Within the instance under, amount gross sales of the SKU elevated 10.5 %. This means a better demand, probably, within the coming yr.
When analyzing historic knowledge, contemplate modifications in pricing, promoting, promotion, and competitor actions that will not have an effect on future gross sales. Report gross sales by product class — a dimension in Google Analytics — to watch modifications over time. This will present a much bigger image of stock demand on the class degree.
Combining Gross sales Channels
If a product is bought in a number of channels, similar to on a service provider’s website, Amazon, and eBay, aggregating gross sales by SKU is tougher.
Within the occasion the gross sales can't be aggregated within the purchasing cart, Google Knowledge Studio could possibly be useful. Knowledge Studio’s “group connectors” studies gross sales by numerous channels. These connectors mixed gross sales knowledge from Google Analytics and a service provider’s purchasing cart (if the cart has a connector) into one report in Knowledge Studio to combination gross sales by a single SKU.
The pattern Knowledge Studio report under combines a number of gross sales channels for one product and compares yr-over-yr gross sales. I added a pattern annotation for future planning — “Easter was 2 weeks earlier…”