To plan better sales, it is important to monitor the effectiveness of any promotional activity. Here, we analyse the seasonal sale that Zara launched last June as a case study.
Step 1: Identify the discount period
The Calendar module allows you to identify when a retailer launches discounts on a monthly basis.
As seen in the chart above, Zara launched a high number of first-time discounted items (6.11k) in June 2020. We identify this as a seasonal sale, with reference from last year’s discounting cycle.
Compared with Zara’s Calendar chart from last year, we deduce that their seasonal sales happen every June and December.
Step 2: Identify discount depth
The next step is to identify Zara’s discount depth. On the same page, scroll down to the ‘First Discount by Date’ table.
We see here that its sale started on the 18th of June, evidenced by the depth of first-time discounted SKUs. The most common discount range was 30-39%.
Step 3: Identify the discount & price after discount performance
Next, use the Competitor Benchmarking module to identify the discount and pricing performance from the same seasonal sale. For the timeline, we set the date range from the 18th of June, as per when the sale started, until the next two months.
The ‘Retailer Analysis: Discount Distribution’ tab allows you to identify the sell-out performance of each discount range.
In the Discount Breakdown with Sell-Out chart above, the 30-39% off discount range with the highest number of SKUs generated 73.96% in sell-outs, while the lower discounts at the 10-19% range and even the 1-9% discount range saw higher sell-out rates.
At the same time, the deeper discount range from 40% off and above also generated higher sell-outs.
In the chart above, we can see that the highest sell-out was generated by the SGD 0-9 and SGD 10-19 price ranges.
From this exercise, it’s apparent that the discount range has little importance in generating high sell-outs. What’s more crucial is to optimise the promotion or sale activity and to benchmark the price after discount with similar items or categories in the market to be more competitive.
Hope you found this article helpful! If you have any questions or would like to explore the Omnilytics dashboard further, feel free to reach out to your respective Client Success Manager.