Optimization of ads, based on time of week and day

Awareness of the most popular times to buy is also crucial for a successful marketing strategy.


The trend towards online shopping continues unabated even after the lockdown and is boosting the e-commerce business. In many cases, however, the talk here is often only about how merchants can optimize their marketing activities. In the process, however, the aspect that consumers shop differently at different times is lost sight of. We try to show which times of day and days of the week consumers prefer when shopping online. For merchants, this can be quite valuable information. The results of the payment provider can be considered representative of the German population, as the payment processing provider is integrated with many merchants in Germany and processes millions of transactions every day.

Popularity of other days of the week varies depending on the product

Products from the Automotive and Erotic categories are preferably purchased at the beginning of the week: On Mondays, these two product categories record the highest sales. In the Automotive category, Mondays at 7 p.m. are the most popular time - compared to the average volume per hour, this corresponds to an increase in sales of 152%. In the Erotics category, on the other hand, shopping is most popular at 8 p.m., with a 162% increase in sales.For products in the Entertainment and Intangible Products categories, Tuesday is the favorite day for German consumers.

Compared to the previous year 2019, the times at which Germans prefer to shop online in 2020 have shifted for many product categories. Products in the Children Products and Clothing & Shoes categories were still most preferred to be ordered at 9 p.m. on Sundays in 2019, while these products were preferred to be shopped for two hours earlier, at 7 p.m., in 2020.

These are the preferences among women & men

Female shoppers prefer to shop online on Sundays. This is where most categories have their sales peak. Across all categories, the peak shopping days for women are between Sunday and Monday, and none of the product categories surveyed have their peak on a day between Tuesday and Saturday.

The situation is similar for male online shoppers, who also prefer Sunday as their shopping day: nine of the twelve product categories have record sales on Sunday. When shopping for erotic products, men and women like to order at different days and times. Men prefer to store for erotic products on Mondays, at 5 p.m., while women prefer to order them at 8 p.m. on Sundays.

Other preferences when shopping from a mobile device

When consumers shop from their mobile devices, they prefer the evening hours: across all product categories, the most popular time of day is 6 p.m., 7 p.m. or 8 p.m. What is particularly exciting is that entertainment products are most popular with mobile devices on Sundays at 7 p.m., while the favorite time for all devices is Tuesday, at 6 p.m. In the automotive product category, too, the favorite shopping day and time differ in the comparison of mobile devices vs. all devices: instead of the actual peak day, Monday, mobile devices prefer to order these products on Sundays.

What does this mean for retailers?

Especially in times when people spend more time at home, the e-commerce sector holds great potential for retailers. An awareness of the most popular times for customers to buy can be crucial for successful marketing. If retailers manage to pick up their target groups and adapt their targeting specifically to individual points in time, they have a clear advantage. In particular, they should be aware of the different purchase times for different products and take these into account in their marketing strategy.


  • Sunday is the most popular day for the German population for online shopping.
  • However, the popularity of other days of the week varies depending on the product type.
  • If shopping is done via a mobile device, the most popular days for online shopping change to some extent.
  • If the targeting of target groups can also be adapted to individual points in time, increases in conversions can be expected.
Klaus Wegener