Black Friday for online stores: what to measure before, during and after

1. Set a goal and a comparison period.

Before you prepare the creatives, write down what the promotion is supposed to deliver: more orders, new customers, clearing stock or a higher profit after costs. Each goal needs a different metric. You'll judge a stock clearance by units sold of selected products, and customer acquisition by the number of first orders and the later purchases of those people.

Also decide which period you're comparing. Black Friday 2026 falls on November 27, Cyber Monday on November 30, and many stores run their sale for the whole week. Compare the entire promotion period with typical weeks before it and with the same period of the previous year, keeping in mind that Black Friday 2025 fell on November 28. Matching day of week to day of week is more reliable than comparing calendar dates.

2. Before the promotion: record a baseline and check your measurement.

A few weeks before launch, prepare a baseline card from typical weeks: sessions, conversion, average order value, share of phones, ad spend and profit after costs. Also note which products will be on sale, at what discount and how many you have in stock. After the sale, these notes let you separate the effect of the discount from regular sales.

Check your measurement while traffic is still normal. Complete a test purchase on a phone, make sure orders show up in reports, and check that campaign links have consistent UTM tags. Check prices too: when advertising a price reduction, a store in Poland must show the lowest price from the 30 days before the reduction next to the current price. Price changes in the weeks before the promotion therefore affect both your messaging and the later comparison of results.

• A test purchase on a phone and a desktop, using a payment method your customers use.
• The test order is visible in the sales report.
• Campaign links with UTMs that match the naming dictionary.
• A list of sale products with the discount, the pre-reduction price and stock levels.

3. During the sale: watch a few signals and react to failures.

On sale day, you don't need a full report every hour. You need a few signals that tell you something has stopped working: traffic is rising but orders have stalled; one payment method stops appearing in orders; a bestseller is out of stock but ads still point to it; ad spend is growing faster than sales. For each signal, decide in advance who reacts and what they check.

Set alert thresholds for sale days, not for a regular Tuesday, because during a promotion every number looks different. In Flowpeek, you can set an alert on a chosen metric, e.g. conversion below a threshold, and choose the interval between notifications. A shorter interval helps on sale days, a longer one in a regular week. Log every change to campaigns and prices with the time, so you can connect it with the result after the sale.

4. After the promotion: calculate the result after discounts, returns and ads.

Revenue from the sale days is only the starting point. Subtract the cost of goods, shipping, payments and ads related to the promotion. Make the final assessment after returns. Under Polish consumer law, online shoppers have 14 days to withdraw from the contract, and for a single item the period runs from the day it's received, so Black Friday returns keep arriving well into December. Record two assessments: a preliminary one right after the sale and a final one once returns have come in.

Compare the sales mix as well. If the products with the deepest discounts sold best, the profit per order may be lower than in a regular week despite higher revenue. Check the share of new and returning customers, and whether loyal customers bought on sale what they would have bought at full price anyway. For ads, record the attribution model and window, so the result can be compared with the next promotion.

5. Check whether the promotion just shifted sales in time.

Some customers hold off on purchases while waiting for a promotion and then take a break after it. In that case, the sale days look great, but the month as a whole doesn't. That's why, besides the sale days, you should compare a few weeks before and after with your normal sales level. If the dip before and after the sale is similar to the spike during it, the promotion mostly shifted sales in time, and the store paid for that with the discount.

Follow customers acquired during the promotion for longer. Check how many of them placed another order within two or three months and whether they bought at full price. Compare this with customers acquired in a regular period. Only then do you know whether Black Friday brought in valuable customers or mostly one-off discounted purchases.

6. Worked example: more revenue, lower profit.

Let's assume a regular week: 200 orders at PLN 250, or PLN 50,000 in revenue. Variable costs other than ads, i.e. goods, shipping and payments, amount to PLN 150 per order, and ads cost PLN 6,000. Profit before fixed costs is PLN 14,000. In Black Friday week, the store gets 400 orders, but with a 20% discount, so at PLN 200 each. Revenue rises to PLN 80,000.

The cost of goods and shipping doesn't drop along with the price. For simplicity, let's assume variable costs other than ads are still PLN 150 per order. With a doubled ad budget of PLN 12,000, profit before fixed costs falls to PLN 8,000. Revenue grew by 60%, while profit fell by PLN 6,000. This is a worked example using made-up numbers. It shows why a promotion is judged after costs, not by revenue.