Retail forecast
Below, I have generated an example forecast table that is relevant for retail brands. In the example, I have included 6 days of a promotion for a brand running an Easter promotion from 4/5 to 4/10. The data is just an example of what could be observed (I used Facebook media as a reference point for the metrics listed).
How to use
input amounts for the rows in white (spend, CPA, CPM, AOV, CPC, CTR). A couple things to consider when inputting these metrics:
- Spend: This field should be based on the media plan of the campaign and tied to the budget caps set in platform. As a note - forecasts have round numbers when it comes to spend, but actualized data post campaign flight will often show slightly lower spend due to scale limitations
- AOV: Is there a promotion running (% off or other sale) and how does that change throughout the duration of the campaign? Promotion depth will impact the AOVs (Average Order Values) as the greater the promotion depth, the higher likelihood that AOVs will be lower. In this example, I decided that the promotion depth became greater as the promotion went on, hence the decrease in AOV
- CPM: How competitive is the market during the promotion? Oftentimes when promotions start during the week and go through the weekend, we see higher CPMs during the week as consumers tend to be online more during the week than the weekend and because of this, more advertisers are in market during the week. However, this is just a forecast, so use historical data and platform benchmarks to help inform this metric
- CPC and CTR are largely dependent on historical data, creative efficacy, and promo depth
For your reference, I have also included some calculators and associated definitions of KPIs at the bottom of the canvas as well.