{"id":6804,"date":"2022-09-04T09:16:49","date_gmt":"2022-09-04T14:16:49","guid":{"rendered":"https:\/\/www.atom.com\/blog\/?p=6804"},"modified":"2026-01-27T08:36:24","modified_gmt":"2026-01-27T14:36:24","slug":"a-new-framework-to-measure-domain-name-interest","status":"publish","type":"post","link":"https:\/\/www.atom.com\/blog\/a-new-framework-to-measure-domain-name-interest\/","title":{"rendered":"A New Framework To Measure Domain Name Interest"},"content":{"rendered":"\n

Traditionally, broad metrics such as traffic or number of visits to a landing page have often been used to determine the potential value or buyer interest in a domain. While these metrics can be helpful for traffic focused or SEO focused domains, they typically do not work well in case of brandable domains. <\/p>\n\n\n\n

Number of visits to a domain landing page can often give a false sense of optimism about the potential buyer interest in that domain. As with anything, context is extremely important when evaluating such metrics. For example there are certain type of visits that can create a significant noise in this data: <\/p>\n\n\n\n

Bots<\/h3>\n\n\n\n

There are all kinds of bots and crawlers that visit domain landing pages every day. If you use Google Analytics, it tries to exclude known bots and crawlers when counting visits. Similarly, many Marketplaces attempt to remove visits from bots. However the truth is that not all bots can be excluded by any reporting tool. More and more scraping tools<\/a> are being added which try to evade bot detection and scrape different marketplaces every day.\u00a0\u00a0<\/p>\n\n\n\n

Previous users of the website or misdirected searches<\/h3>\n\n\n\n

If you bought a domain in an expired auction, it is possible that there was a website previously built on that domain. We get quite a few visits and inquiries from customers of that previous website who are asking to return a dress that they bought or asking to refund the service fee they paid to that website. Clearly these are not end users who are interested in buying the domain, but these visits typically get lumped together in the overall stat.<\/p>\n\n\n\n

Other Sellers<\/h3>\n\n\n\n

Sellers often browse Marketplaces to check for other names for sales, and it is possible to get their visits counted in the overall metric as well. <\/p>\n\n\n\n

Bottomline is that we don’t see any direct correlation between number of visits a domain receives and its expected sell-through rate<\/strong>. We have seen domains sell with less than 10 visits, while we still have many domains that remain unsold after thousands of visits. <\/p>\n\n\n\n

So what is an appropriate indicator of serious buyer interest?<\/h2>\n\n\n\n

One clear indicator of end user interest is the number of offers or inquiries received on that domain. However the challenge with this metric is that only a small percent of brandable domains receive ongoing offers and inquiries, therefore this metric can only be used for a small % of portfolio.<\/p>\n\n\n\n

As a result, we started looking for other metrics that can be indicative of end user interest. We analyzed all our past sales along with the buyer browsing behavior leading up to that purchase. One interesting pattern we saw in more than 70% of transactions was that the buyers typically visit the landing page multiple times during the last 7 days before making the purchase. This is logical and expected for any high value purchase. If you are buying an expensive suit or a dress online, it is very likely you will visit that page few times before pulling the trigger. Domains are one of the foundational aspects of a startup, and entrepreneurs typically go through an extensive research (which often involves multiple visits to the landers of their shortlisted domains) before settling on a domain. <\/p>\n\n\n\n

So while it was clear from our analysis that most buyers of the domains typically visit a landing page multiple times before purchase, does the reverse also hold true? Are multiple visits to a landing page by the same user a strong indicator that a sale is more likely to happen?<\/p>\n\n\n\n

We back-tested this data to see if we can find a correlation between repeat landing page views and expected sell-through rates. We tested this hypothesis by keeping track of IP addresses as well as additional fingerprints that can identify the same users even if they are not logged into Atom. We then excluded all the visitors who are known to be sellers on the platform. <\/p>\n\n\n\n

The results were quite interesting<\/strong>:<\/p>\n\n\n\n