survey Domain Optimal Pricing Research - NP Survey

[Ostrados]

Hi,

I am currently doing a research on optimal domains pricing, the goal of the research is to:

1. Determine sell through rate (STR) for different pricing ranges
2. Derive a formula for the relationship between STR and Domain Price
3. Using formula from #2 we can make simulation for different pricing scenarios to find optimal pricing strategy
4. Ultimately deriving a domain pricing formula (in a separate future study).

This study requires a lot of data, I collected some data using Dofo, Sedo, Namebio.

Here is a sneak peak of what I got so far:

However the results I got are inconclusive, and I need more accurate data.

To get more accurate results I am asking Namepros community to help me collect more data, and for that I have created the following Survey:

https://freeonlinesurveys.com/s/OqGsfT2s

* The survey is totally anonymous there is no way to tell who sent it.

* The survey is for all extensions and not specific to .com

* The results of the study will be published at Namepros, I believe the results will be insightful for all of us.

* Contribution will be greatly appreciated especially from big portfolio sellers and from marketplaces that have enough data.

@Sedo @GoDaddy @DAN.COM @LaszloSchenk @GrantP @James Iles @DaaZ @aoxborrow
@AbdulBasit.com
@bmugford
@Recons.Com
@JudgeMind
@xynames
@twiki
@Acroplex
@Bob Hawkes
@Name Trader
@MadAboutDomains
@tonyk2000
@ResoluteDomains
@Leo Angelo
@Nikul Sanghvi
@TERADOMAIN
@Yusupbabay

...and all others please contribute.

Thanks

 

[AbdulBasit.com]

I've now a little over 8,100 domains portfolio.

I've some 42% of domains priced at $9,888 and above.

Remaining some 58% are priced between $1,988‐$6,888.

My STR in 2022 was around 1.5%

My average sale price last year was over $6,000.

Had the worst year (2022) considering the numbers and quality of domains.

 

[bmugford]

I appreciate the effort to study this, but I think it is going to be hard to read much into the results.

The problem is unlike other products, every domain is one of a kind with highly subjective value.
The quality of the domain really matters when it comes to pricing and STR.

It seems logical that the lower the price, the higher the STR.
The higher the price, the lower the STR.

However, that doesn't tell the full story.

The pool of buyers is naturally smaller in higher price ranges. No matter how good a domain is, most people don't have a spare $50K+ to spend on a domain.

Domains come in so many different types, formats, extensions, etc.

If there was a way to narrow the results down, it would be more useful.

For instance what is the STR for different types of LLLL.com in various price ranges?

Brad

 

[Recons.Com]

Hi,

I am currently doing a research on optimal domains pricing, the goal of the research is to:

1. Determine sell through rate (STR) for different pricing ranges
2. Derive a formula for the relationship between STR and Domain Price
3. Using formula from #2 we can make simulation for different pricing scenarios to find optimal pricing strategy
4. Ultimately deriving a domain pricing formula (in a separate future study).

This study requires a lot of data, I collected some data using Dofo, Sedo, Namebio.

Here is a sneak peak of what I got so far:
Show attachment 230253Show attachment 230254

However the results I got are inconclusive, and I need more accurate data.

To get more accurate results I am asking Namepros community to help me collect more data, and for that I have created the following Survey:

https://freeonlinesurveys.com/s/OqGsfT2s

* The survey is totally anonymous there is no way to tell who sent it.

* The survey is for all extensions and not specific to .com

* The results of the study will be published at Namepros, I believe the results will be insightful for all of us.

* Contribution will be greatly appreciated especially from big portfolio sellers and from marketplaces that have enough data.

@Sedo @GoDaddy @DAN.COM @LaszloSchenk @GrantP @James Iles @DaaZ @aoxborrow
@AbdulBasit.com
@bmugford
@Recons.Com
@JudgeMind
@xynames
@twiki
@Acroplex
@Bob Hawkes
@Name Trader
@MadAboutDomains
@tonyk2000
@ResoluteDomains
@Leo Angelo
@Nikul Sanghvi
@TERADOMAIN
@Yusupbabay

...and all others please contribute.

Thanks

The data from actual sales from open sources won't help.

You are looking for correlation of sales % based on price points. But all you have is ... price.

You don't know how many of the names in the same class and price did the seller hold, hence you cannot deduce %.

That is why the experiment and research really be conducted by a large portfolio holder. And this is one of the biggest motivations for me to collect big portfolio. I could invest the same amount into high cost domains and earn similar returns, but opted for the model with more names as that provides better data set.

So, yes, I will conduct a/b/c test this year with about 2000-3000 domains in each where I will do +20%/0/-20% and see the results. I will be testing for the names currently priced at $2500. The graph should already give some food for thought and might direct me to test lower pricing points to check if there any inflection points there as well.

PS another issue with the charts above is that it is lumping all types of names together. E.g. if you have 1000 LLL.coms and price them $5000 each, your STR would be 100%. But if you take some random 5L.coms and price them $1000, your STR might be 0.1%.

For pure reliable experiment, it has to be fully randomized price change for the baskets of names priced the same prior to experiment. And the data is to be collected at the same long enough time frame for big enough data set.

 

[branding]

Your opening post is confusing... Don't these graphs just show a higher STR for lower priced domains as would be expected?

Bigger pool of buyers = higher STR.

Even so... A low STR doesn't mean you're underperforming if the profit is there. High end sales specifically.

Obviously there's a sweet spot with a correlation between $ and str % but... Str and pricing don't factor in net profit (acquisition, taxes, labour, overhead different for everyone) so...

Really not sure what you're trying to accomplish...

 

[Bob Hawkes]

This is a superb initiative seeking to answer a question of great importance to domain investors - how to optimize their pricing for return.

I encourage all who can to fill out the survey to expand the data. It is pretty fast to complete, and as noted anonymous. It asks how many sales in different price ranges in 2021 and 2022, and your portfolio numbers broken down by BIN.

I look forward to seeing the results.

Thank you for this initiative, @Ostrados.

-Bob

 

[Recons.Com]

I completely agree with both of these points. Any study has caveats, and the important one here is that the quality of the names in the different bins is not the same.

Still, I think it will be interesting to see of those who list names in different price points, what the STR is. So I support the research. While in principle it would be better to take same names and do some A/B/C testing, one needs a huge number of names, and willingness to price what might not be considered optimum, so probably not many test that.

I often wonder what tests the big players, like BD and HD and DM do along these lines.

-Bob

It might be interesting to see, but completely useless ))

Someone like @AbdulBasit.com can achieve 1.5% STR at $5000+ average, while another investor will have 0.8% STR at $1500 average.

So, again, without actually looking at the names and grouping them into separate data sets based on quality, the data will be misleading and will be shaped only by the bias towards one of the subsets in the input. <selfpromotion>Incidentally, just got 0bias.com into my portfolio ))</selfpromotion>

In contrast, compare with this type of data:

6000 domains were priced all at $2500 prior to the experiment. 2000 of them were reduced to $1950 and 2000 of them were raised to $2950 (not quite +/- 20%, but observing the psychological limits as well for my own purposes), and 20% were kept at $2500. After N-months here are STRs for each group: x%, y%, z%.

Information like that could be actionable. I'd pay $1000 right now for info like that, as I am losing way more every month without that either by underpricing or overpricing and hurting STR.

Now I don't know how that randomly lumped data can help anyone with any conclusions about pricing besides "raising prices reduces sales quantity".

 

[Bob Hawkes]

I filled out the survey. Quite apart from the debate on the merits of the proposed research, I found it illuminating to actually think about my own situation as I completed the survey.

It is too sparse data to mean much, but it seemed to show that my really low-priced names were underperforming, and my high-priced names also unperforming. Small number stats though. There does seem to be a sweet spot.

I think the exercise of looking at how many sales and how many are listed at different price BINs is a useful exercise to periodically do.

Now the next part, on a personal level, is to ask why certain names are underperforming. Is it because the low-priced names have no audience really at any price? For some of mine, yes.

For the higher-priced names, is it because I have them over-priced, or inherently the STR is just lower for these names, because audience pool lower, or maybe I have them for sale at the wrong place? All possible.

Anyway, just say I found worth completing it, personally.

-Bob

 

[bmugford]

• The only known STR for us is for Tier 4 & 5, and we only have an approximate STR range.
• Unkowns: STR for Tiers 1,2 and 3.

Lets say I want to build strong portfolio with only Tier-1 domains where I will pay $10k+ on each domain acquisition. I want to make a feasibility study, and know expected ROI in next 5 years. I can't do that without knowing the excpeted STR, if you ask anyone how much STR for selling $50k+ domains nobody will give you an answer.

The STR for domains priced well into 5 or 6 figures is going to be extremely low.

It is largely because a bunch of garbage domains are priced in that range, but also because not many buyers have that much money.

However, when you start playing in higher ranges I would argue STR doesn't matter as much. Then you start to factor in things like upside, downside, wholesale value, etc.

If I buy a LLL.com for $15K I know I can always sell it around there. The downside is limited.

If I find an end user to pay $75K great, but it doesn't matter that much as the renewal fee of $10 is such a low cost compared to the value of the domain.

Also, these higher end domains tend to appreciate in value over time far more than lower end domains.

I think the STR matters much more towards the low to mid tier, where holding costs (renewal fees) make up a much larger portion of the domain value.

Brad

 

[bmugford]

I filled out the survey. Quite apart from the debate on the merits of the proposed research, I found it illuminating to actually think about my own situation as I completed the survey.

It is too sparse data to mean much, but it seemed to show that my really low-priced names were underperforming, and my high-priced names also unperforming. Small number stats though. There does seem to be a sweet spot.

I think the exercise of looking at how many sales and how many are listed at different price BINs is a useful exercise to periodically do.

Now the next part, on a personal level, is to ask why certain names are underperforming. Is it because the low-priced names have no audience really at any price? For some of mine, yes.

For the higher-priced names, is it because I have them over-priced, or inherently the STR is just lower for these names, because audience pool lower, or maybe I have them for sale at the wrong place? All possible.

Anyway, just say I found worth completing it, personally.

-Bob

I think most domain investors would come to a similar conclusion if they did a deep dive.

Lower priced domains underperform in general because they are lower quality. Even for low prices, they are not that likely to sell if the pool of potential buyers is small (or non-existent).

Higher priced domains underperform for one of two reasons -

1.) The domain is overpriced and not worth the asking price.
2.) The domain is priced well, but you hit budgetary restraints of potential buyers.

Even for the best domain, not many people have tens of thousands of dollars or more available.
Even with a large pool of potential buyers, the actual pool of serious potential buyers would be much smaller.

I think the sweet spot is around $2K - $5K, at least for domains that are are priced relative to the quality.

Brad

 

[Bob Hawkes]

But... If an investor reports data for names priced at $900 and $2500, he is basically reporting data for different quality of names. So it is not apples to apples and STR reflects not only change in price but in quality as well.

Again, the true accurate result can be obtained only by randomly changing prices for the names currently priced at $X price point.

I completely agree with both of these points. Any study has caveats, and the important one here is that the quality of the names in the different bins is not the same.

Still, I think it will be interesting to see of those who list names in different price points, what the STR is. So I support the research. While in principle it would be better to take same names and do some A/B/C testing, one needs a huge number of names, and willingness to price what might not be considered optimum, so probably not many test that.

I often wonder what tests the big players, like BD and HD and DM do along these lines.

-Bob

 

[Recons.Com]

I appreciate the effort to study this, but I think it is going to be hard to read much into the results.

The problem is unlike other products, every domain is one of a kind with highly subjective value.
The quality of the domain really matters when it comes to pricing and STR.

It seems logical that the lower the price, the higher the STR.
The higher the price, the lower the STR.

However, that doesn't tell the full story.

The pool of buyers is naturally smaller in higher price ranges. No matter how good a domain is, most people don't have a spare $50K+ to spend on a domain.

Domains come in so many different types, formats, extensions, etc.

If there was a way to narrow the results down, it would be more useful.

For instance what is the STR for different types of LLLL.com in various price ranges?

Brad

I am glad someone gets what I have been trying to explain.

We want to find the relation between STR and Price by:

1. Finding STR for each price group separately (ex: for different domains qualities)
2. Assuming that all domains were priced correctly

Finally! Here is the thing though. You CAN'T with any level of accuracy or confidence assume that, even if you would manage to define what is CORRECT pricing.

 

[bmugford]

An STR for a specific price range, does not mean you can raise your prices to that range!

For example: @AbdulBasit.com reported an STR of 1.5% for $6000 Average sale price on 2022, that does not mean to go crazy and raise your hand reg domains to around $6000 and hope that you will achieve same STR as his, you will end up with STR close to 0.01% and you will lose moeney. Do your homework and price your domains correctly.

I agree. You need the domain quality to support it.

Just randomly raising prices is not going to magically yield better results, in fact it is likely to yield far worse results.

Brad

 

[Recons.Com]

BTW:

@Recons.Com said in another thread



Me explained in this thread:


Spot the difference!

But negativity must exist

Not sure what you mean here by "negativity must exist".

I kind of given up here, because I believe the problem lies in you not understanding correctly what price elasticity means, while that is what you are trying to measure...

You don't measure price elasticity of ALL cars together, as different cars are priced differently and they differ way too much and serve different audiences and markets.

You can measure price elasticity of THE car, buy doing a/b/c/d... tests for the SAME car at the SAME time to see how change in price (delta price) influences change in demand (delta demand). Based on this, you determine the optimal price that maximizes your revenue.

In case of someone's specific portfolio that is large enough (many many thousands), you can take all domains CURRENTLY priced the same and treat them as homogeneous. Then you can do delta price to check delta demand simultaneously and over long enough time. You can't replace this by treating current price levels as change.

Again, IT HAS TO BE THE ACTUAL CHANGE IN PRICE UP AND DOWN OVER N NUMBER OF MONTH.

There is no substitute or shortcut here. You will be just cooking numbers to suit your original hypothesis.

That is not how research works.

 

[Ostrados]

@Recons.Com

First I would like to issue this statement: This study is for educational purposes only, and this subject will continue to be an ongoing research after publishing results.

As I mentioned in my first post there are 4 objectives in this study, the first objective is to find the relationship between price and STR. We do that by dividing domains in subsets of prices ranges and we find the STR for each subset.

You raised valid concerns:

1. Not enough data from open sources like Dofo & Namebio
2. Data noise from underpriced & overpriced domains
3. No point in determining STR for price range
4. You need testing to find better price
5. Each domains portfolio has unique qualities

There are many details but I will try to explain as much as I can.

1. Not enough data:

While I admit that the results I have so far are far from being conclusive, but what I wanted to see when I started researching this topic is a non-linear relationship between STR & Price (I would be surprised if it was linear). And I got same non-linear curve shape regardless of source of data! which indicates that I might be in the right direction.

* Regarding the data I got from Dofo, I compared listed BIN domains at Dofo with sales at Namebio, first results showed same curve relation as in my first post, but the results were off by big margin, for example $1000-$2000 price range had 10% STR. I fixed this by:

• I found an STR points from my own sales data, I picked STR=3% point and corresponding average selling price as a reference
• I did a linear transformation by simple shifting the curve until the 3% STR touched at same price.
• All the STR values shifted and were very reasonable after the shift.

* Similarly I repeated the same for only Sedo and the curve shape also matched Dofo but with different mathematical equation.

* I repeated with my own portfolio data and the results was very close to Sedo!

And again the above results are not reliable and I need more data, that's why this survey will greatly help getting more conclusive answers

2. Data noise from underpriced & overpriced domains:

There is ofcourse the problem of overpriced & underpriced domains, but if we apply a Gaussian distribution then we can hypothesize that there are equal number of underpriced domains and overpriced domains, and so they will cancel out in the output result if we take enough big data.

Example: Let's say for the range [1000-2000] there is 20% overpriced domains that reduced average STR, then there is also 20% underpriced domains that increased the STR, so they will cancel each other in final STR.

3. No point in determining STR for price range

Domain prices are elastic, unlike cars where you can simply find exact comparable prices for example 2020 Toyota civic, in domains each domain is unique and there is no exact comparables. In the case of cars you can sell +10% max of the market value, while in domaining you can sell at -/+ 100% or more of the market value.

When we appraise domains we usually refer to ranges, so we say this domain is a low x,xxx, what does that mean? Some domainers will list that domain at $1000 while other may list it $3000. Because of that I believe that it is very useful to find STR for each price range.

In general their is an optimum price range for any domain (regardless of it is value) where ROI is maximized. If we go far above that range then domain STR will drop significantly, if we go too low then we lose revenue.

Please note that we need also to define STR cutoff limit (under study in my research), which is the limit after which STR drops very low, for example if we take a domain that has a value of $1000-$3000 and increase it's price to $10,000 then we reduce selling chance to near 0.

4. You need testing to find better price

I can't agree any more, and I repeat please do your own test, don't rely on my data or anybody else data.

The important thing from the results that I hope to get from this study, is not static STR values but the relative ones. For example you said you want to do +/- 20% test for domains priced at $2500, I don't know your STR but according to my "draft" formula your STR will:

Increase by 9% at $2000 (ex: for 2% STR => 2*1.09 = 2.18%)
Reduce by 7% at $2500 (ex: for 2% STR => 2*0.93 = 1.86%)

Ofcourse that can be totally wrong, so it is better to test yourself, and I highly encourage you to do that.

5. Each domains portfolio has unique qualities

True. Each domain portfolio is different, but on average most domain portfolios are of relatively similar quality. Some unique portfolios have different STR profile, but such portfolios are rare. So the idea of this Study is to find General STR formula, not specific formula for a specific portfolio.

In the final study results I can post an Excel template that you can use to derive STR formula for your own portfolio data.

Finally, this survey is to derive STR data only, we are still still far from talking about pricing strategy, we will use this formula to make simulation of different pricing strategies, which should be only educational and informational, you should do your own test, it is your portfolio and you know it better than anyone else.

 

[Ostrados]

Update:

I got 7 responses so far on the survey. Thanks a lot for the participants your contribution is appreciated.

But we still need lot more data, I hope more will contribute.

11 days left for the survey so there is still plenty of time.

It takes less than 10 minutes to complete the survey. The only question that is time consuming is this:

But it can be done in less than 5 minutes, here is how:

> IF you have your domains in an excel sheet then from your price column you can use filter->Numbers Filter->Between:

> Then enter the price range (ex: $500 to $1000):

> Now select the entire column and read "count" from Excel bottom right bar.

Thanks for your time

 

[Ostrados]

BTW @Recons.Com raised a very important point in his previous posts regarding of his concerns of using any STR formula for blind pricing, so I have to strongly assure the following especially for new domainers:

IMPORTANT:

An STR for a specific price range, does not mean you can raise your prices to that range!

For example: @AbdulBasit.com reported an STR of 1.5% for $6000 Average sale price on 2022, that does not mean to go crazy and raise your hand reg domains to around $6000 and hope that you will achieve same STR as his, you will end up with STR close to 0.01% and you will lose moeney. Do your homework and price your domains correctly.

 

[Eric Lyon]

I just finished doing the survey, however, after doing professional appraisals for the last couple decades (More so in the last 6 years), it's become clear that STR and Sales Reports are not as reliable as they used to be. Especially since many sales reports stick, that actually fell through (E.g. buyer failed to pay at the venue the purchase was reported from or The sales report was falsified unethically in an attempt to leverage the report to sell the domain later referencing the falsified sale). I'm sure your survey will also get data input that isn't accurate from some claiming more sales than actually transpired for higher amounts than they actually sold for (The human condition of embellishing is as natural as that Big 5 pound Fish your buddy said they caught the other day at the lake, that was actually a tiny 1/2 pounder)

It's unfortunate that sales reports can not be counted on as much these days. I find that in as high as 95% of all the evaluations I do, that the majority of sales reports (Even those decades old) have never been developed by an end user and remain parked, landed, or do not resolve. Which questions the very essence of accuracy when it comes to "Genuine use case" examples of domains that resold to an end user (These are the most accurate STR's/Sales reports one should be leveraging when considering a domain assets value) - Investor/Reseller to End User and not Investor/Reseller to Investor/Reseller.

Even then, one can not use a single or even 2 variables (STR + Sales Reports) as a definitive or even remotely accurate way to establish a domain names value. A single variable change in a combination (E.g. adding or removing an "S", singular vs plural) can sometimes sway value on the scale greatly.

It is not advised to register or invest into a bunch of variant domains based on a single domain evaluation or variable source. Each variant change may or may not decrease or eliminate value completely.

Value can never be determined from a single point of research or variable. It's also important to understand the potential use of a domain asset in terms of monetization and revenue structure. This gives an inside look at what such an asset may be worth in a particular niche industry.

If you are dealing with a Brand asset of companies that may have been established prior to asset acquisition, you may want to consult with an IP/TM attorney in the country you reside. Most have 1 free consultation. Just to be sure, if you haven't yet.

Remember, at the end of the day, a domain name is truly only worth what a buyer and seller agree on.

In my opinion anyways. Everyone's different.

 

[AbdulBasit.com]

Thanks for sharing, Abdul.

This confirms my point that STR/price correlation is heavily dependent on the quality and no conclusions can be drawn just by bulking all the numbers together.

Btw, what portfolio size did you use for STR calculation: beginning of year size, mid year size, end of year size, weighted average?

Mid year size.
Thanks!

 

[Ostrados]

I don't want to go in circles, but if you are serious about the analysis,, I would recommend the books in the attachment. Or there newer version. These are my keepers from my MBA.

I would also recommend taking college or grad level classes on the subject.

Show attachment 230299

I have Master's degree in engineering

 

[Recons.Com]

I have Master's degree in engineering

Then, assuming Masters in Engineering entails studying statistics in depth, you should realize that the input you are seeking won't let you get even remotely accurate output.

I am surprised I have to explain all this.

I checked out your survey. It askes for the number of names priced at each price point and sales. Again, this doesn't consider differences in quality of names. So by definition, any conclusion would be misleading, as you are throwing in together apples and oranges.

If you are proficient with stats, maybe where the problem arises is the science of economics. Please read about price elasticity. Again, you can't get price elasticity for all watches. A luxury watch will have different one at different price level, casio might get another one at another price level and a cheap vanilla-brand one will get completely different one at the lowest price levels.

 

[Ostrados]

The problem is unlike other products, every domain is one of a kind with highly subjective value.
The quality of the domain really matters when it comes to pricing and STR.

It seems logical that the lower the price, the higher the STR.
The higher the price, the lower the STR.

It seems my opening post is confusing? I didn't say we will blindly change prices of all domains and see what happens

We want to find the relation between STR and Price by:

1. Finding STR for each price group separately (ex: for different domains qualities)
2. Assuming that all domains were priced correctly

Price groups can be imagined as baskets containing different quality/tld/LLLL objects (you name them). Or we can recall them tiers like tier1, tier2, tier3...etc.


After we find STR formula then we can move to pricing part in which we:

• Find optimal price range (lets say +/- 50% of domain value)
• Do several simulations using STR formula to see what happens

For example:
If you have a domain with fair retail value of $20k,
Lets say optimal price range for this domain is $15k to $25k
What is the price that will give highest ROI?

I talked before about cutoff STR limit after which domain STR will drop to 0.

So for our $20k domain example the STR should look like this:

This chart is not to be confused with the general STR chart in first post, this is the STR cutoff region for one price range.

If you notice, if the price is increased too much outside the optimal range, STR will drop fast to 0.

To sum things up:

1. We price domain at fair market value
2. We define optimal price range (ex: +/- 50%)
3. We use STR formula to predict which price within our optimal range will give best ROI

 

[Ostrados]

Your opening post is confusing... Don't these graphs just show a higher STR for lower priced domains as would be expected?

Bigger pool of buyers = higher STR.

Even so... A low STR doesn't mean you're underperforming if the profit is there. High end sales specifically.

Obviously there's a sweet spot with a correlation between $ and str % but... Str and pricing don't factor in net profit (acquisition, taxes, labour, overhead different for everyone) so...

Really not sure what you're trying to accomplish...

Yes I know my first post was confusing, I explained in details in replies after that.

The objective of this study is to compare real life sales with portfolio pricing, to derive STR values for different price groups.

I will give simple example:

Lets say your portfolio consists of the following domains (numbers are just for illustration):

Groups	Type of Domains	Selling Price Range	STR
Tier 1	* Premium domains * One word domains ...etc	$30,000 to $100,000	??
Tier 2	* High value keywords * EMD domains .. etc	$15,000 to $30,000	??
Tier 3	* Strong value domains * Pronounceable LLLL ...etc	$5000 - $15,000	??
Tier 4	* Average value domains * GD Closeouts ...etc	$2000 - $5000	Maybe 1% to 2%
Tier 5	* Hand Reg domains * Obscure TLDs ...etc	$500 - $2000	Maybe 2% to 4%

What we know:

• The only known STR for us is for Tier 4 & 5, and we only have an approximate STR range.
• Unkowns: STR for Tiers 1,2 and 3.

Lets say I want to build strong portfolio with only Tier-1 domains where I will pay $10k+ on each domain acquisition. I want to make a feasibility study and find expected ROI in next 5 years. I can't do that without knowing the expected STR, if you ask anyone how much STR for selling $50k+ domains nobody will give you an answer.

 

[tonyk2000]

Optimal pricing? It strongly depends on portfolio imho. What works for one portfolio would not necessary work for another portfolio. One example. Buydomains .com has a large portfolio and they maintain "Just missed them" (recent sales) list right on their homepage. It shows that buydomains prefers to sell in low 4 figures range. It is their preference today, 01/21. They may well add extra zero tomorrow and will still sell some. They may set 50% discount next week and will definitely report more sales. Whatever their current preference is, imho it has little or nothing to do with other portfolios...

 

[Ostrados]

I would like to share this excellent eye opening info from Namebio (@Michael)

https://twitter.com/x/status/1621065221212368897

Here is the twitter thread in one text block:

If you're a domain investor you're definitely leaving money on the table. A story about price sensitivity...

For those of you who don't know, NameBio's sister company owns more than 70k domains. We BIN price all of them, and to do this initially we grouped them into seven price buckets based on GoValue, DotDB, and other metrics.

The bottom 30% of the portfolio was priced into three buckets: $1795 (20%), $1295 (5%), and $995 (5%). After three months of testing, this group of names was contributing 14% to our total sales by quantity.

As an experiment, for the next three months we combined those buckets into a single price point: $2195. Logically we were expecting fewer sales, but we wanted to see if the higher price could more than offset the decrease in STR.

But something shocking happened... the number of sales didn't decrease. The bucket was still contributing 14% to our total sales by quantity, except now it was contributing 38% more to our gross revenue.

Darpan noticed the same thing a few months later, that there is almost zero price elasticity at <$2k

That means a name priced at $500 has basically the same chance of selling if priced at $2,000. If you're pricing names below $2k - $2.5k, raise your prices up to that level. You shouldn't experience a meaningful drop in STR and you'll make more money.

Topics of pricing sensitivity, price elasticity and STR need more research and some generous publicity from big marketplaces like Afternic and Sedo.