has captured 5.7% of restaurant related domain names

I recently decided to compile a very large list of domain names for the German country code top-level domain .de. I did this with the help of the Common Crawl project which provides a free, open repository of web crawl data and web graphs for the last years.

A few command line commands and a small bash shell script was all it took to compile a nice list of roughly 9 million .de domain names.

If you want to know more about how exactly I compiled the domain name list, just let me know and I might write about it in another blog post.

The resulting list is by no means complete and also not up-to-date, but it can be a nice starting point for further analysis and investigations. One of which I am going to write about in this post.

Enter the restaurant world

I was interested in domain names that belonged to restaurants and eating places in general. A simple but quite effective way to achieve this was to filter the domain names by German words that indicate such eating places:

  • Restaurant
  • Gasthaus
  • Gasthof
  • Gaststätte
  • Wirtshaus
  • Gastwirtschaft
  • Schänke
  • Speisewirtschaft
  • Speiselokal
  • Speisehaus
  • Speiserestaurant
  • Speisegaststätte
  • Gastlokal
  • Kneipe
  • Pizzaria

Since I was running this analysis on my windows desktop, grep was not directly available. So I used the findstr PowerScript command instead to do this filtering:

findstr /I "Restaurant Gasthaus Gasthof Gaststaette Wirtshaus ..." huge-domain-list.txt

This yielded a still impressive list of about 31.000 domain names related to German restaurants.

Who's still alive?

Since I knew that the original list is outdated by definition, I had to check which domain names were still active. My first attempt to do this was also with a PowerShell script. This worked in principle and I was somewhat impressed by the capabilities that PowerShell provided, but at the same time the unfamiliar syntax turned me off and most importantly the speed was not great. So I created a small Golang program to get this job done, which worked great due Golang's concurrency features.

  • 63% of the domain names were still active (roughly 20.000 domains)
  • 49% of the domains had redirects (mostly from http:// to https://)
  • 14% of the domains still serve http://
  • 37% of the domains did not exist anymore or returned other errors

Let's do some manual spot checks...

I was happy to have a list of 20.000 restaurant domain names to work with and started some manual spot checks. After looking at 20 randomly selected websites from the list, I made two observations:

  1. Domain Parking was another group of domain names to filter out
  2. had captured a significant number of domain names

I was not surprised about the first observation, because I had noticed already quite often that many good domain names are "parked". But that thing caught my attention. The domains that were captured by did not redirect to, but instead showed their logo and a link to their website.

How many of them?

With just a small extension to my Golang program I could find all the domain names form the initial list, that were captured by

5.7% of the active domains from the restaurant domain list belong to

That is 1101 domain names. Here are some random examples:


The numbers are of course only estimates, since the initial domain list is not complete, but it provides some impression for the size of the topic.

When did it start?

I have not yet done a systematic analysis, but it seems (based on WHOIS entries for some domain names) that this "capturing" of restaurant domain names has started already before the COVID-19 pandemic in 2019 and continued at least until 2022 and potentially still continues.

(Preliminary) Conclusions

  1. The number of "lost" domain names provides evidence that German restaurants have been struggling in the 2019-2023 time frame. It would be interesting to revisit this analysis in one or two years to see who many more domain names have become inactive or taken over by lieferando.
  2. Lieferando is using aggressive tactics to drive traffic to their site. Maybe this can be described as growth hacking or a way of SEO. It is apparently not even new.
  3. The extend to which lieferando is using this method suggest that it is at least somewhat effective and probably quite cheap to implement.
What are your thoughts on this topic? When you sign-in, you can let me know in the comments.