Domain name price estimate based on Flippa sales history

Domain name price estimate based on Flippa sales history

Estimating how much domain could potentially sell for on Flippa could be very beneficial for any domain name re-seller or investor.

To help better determine the price and do it quickly, a potential domain investor can use several different options:

  • Automatic evaluation tools available online – some of the tools include…. While they can be sometimes way off, they are good to get the initial price target
  • Ask opinion from others – there is a ton of forums and blogs, where it is possible to post domain and get different opinions about how much it could be worth
  • Using various online guides and tips – there is a ton of information shared online. Everyone with some free time on hand can dip into many informational resources and by clear guidelines determine the value of domains independently

What combines all of the above evaluation methods is the knowledge of what domain names sold for in the past and which factors have possibly influenced the final price. Estimating domain sale price has always been more of an educated guess, than exact science.

However, as with every similar analysis, one way to improve the accuracy of predictions is to consider factors that could lead to higher prices.

In this post, I will analyze 2 of the factors:

  • Domain registration date
  • Initial domain price

To eliminate price outliers from analysis all calculations are done only to the names finished below 25,000$, as in the previous post.

Influence of domain registration date on price estimate

The regression results:

S = 4342,96   R-Sq = 6,9%   R-Sq(adj) = 6,5%

Does that mean, that if you have an old domain name, there is a 6,5% chance that it will sell higher? Not necessarily.

What happens here, is that domains of higher value just tend to be older that other domains, hence the higher premiums.

Influence of initial domain price on final bid

The theory says that lower bids attract more eyeballs and action, which can eventually lead to higher prices.

From the first glance it looks like this is the case – domains with initial price of 1$ on average sell at higher values than domains listed with different initial price.

Below is the comparison of domain auctions started at 1$ and domain auction started at higher prices. The second number is the average number of bids.

average-bid

As it turns out, domain with the initial price of 1$ receive on average a 9,6% premium over domain names initially listed at higher price.

Also, these domains receive almost 6 times more action from participants. More actions mean more eyeballs and eventually higher sales prices for domain name.

However, can the initial price and the number of bids be used as predictors for final bid?

Not really. The regression analysis shows absolutely no correlation between whether the initial price was 1$ and the final bid.

Pearson correlation of First bid 1$ (yes/no) and Price = 0,058

Also, the regression model shows that doing price predictions based only on those two values is not possible. The R-squared found is an abysmal number of 1,6%

S = 4381,18   R-Sq = 1,6%   R-Sq(adj) = 1,1%

The above data clearly shows that making predictions based only on initial bid is not possible.

Conclusion

Unfortunately, bigger domains age and initial bid of 1$ only by themselves can’t help you get higher prices at the auction.

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