Spaceship

analysis 17 Proven Tips for Better Domain Sell-Through Rates

Spaceship Spaceship
Many members in the Atom thread are discussing their dashboard stats that have yet to be shown by Atom to correlate to a higher sell-through rate ("STR"). Thus, I thought it helpful to compile the data shared by Atom that does correlate to STR. This adds to a helpful article written by another NamePros blogger, @Bob Hawkes, in 2022 re: Atom, including analytics that could be used to help a seller increase their STR.

Here's a list of 17 items where @Atom.com showed data with STR correlation.

1 - Root words

Obviously the data on Root Words is not exhaustive, e.g., more root words sell than those they show in the image, but this data highlights the importance of choosing proper root words. Use this Atom tool to find more root words that are correlated with high STRs. In my opinion, search for words that have a greater than 6% STR.

Root words and STR.png


2 - Root word sequence (left vs. right)​

This is ignored by many Atom sellers resulting in low to non-existent STRs. Use this Atom tool to find which placement has a higher STR.

Root word placement left.png


Root word placement right.png


For example, here is the importance of root word placement for the keyword "AI" (front vs. back). Sequence matters (and not just for the "AI" keyword). Don't be an Atom rookie - placement matters.

Ai word placement.png


3 - AI appraisal domain score

STR by ranking.png


4 - TLDs Taken

If you can find or acquire domains with them, STRs rise exponentially as TLDs taken rise (exceptions apply).

Atom TLDs taken.png


5 - TLD type

If you're going to play in the non-.com world, choose wisely. Atom's Sapphire Marketplace may change this data going forward.

STR by non com.png


6 - Non-.com TLDs taken

If you're going to play in non-.com TLDs, be sure to follow this rule and/or make sure the SLD is incredibly synergistic with the TLD. Atom's Sapphire Marketplace may change this data going forward.

Atom TLD taken by extension for sold.png


7 - Domain age

STD by domain age.png


8 - Type of name

Name types include Made Up Words, This & That (T&T), One Word, Compound, Alliteration, etc.

STR by type of name.png


9 - Price changes

Scheduled price increase, price drop, and/or price increase.

price change vs STR.png


10 - Name quality

The point here shows higher quality names, with corresponding higher prices, have higher STR. Higher quality names are in our control.

Higher prices have higher STR.png


11 - Pricing

BIN vs. Make Offer STR. Always choose BIN on Atom, in my opinion.

BIN vs MO.png


Adding a Make Offer ("MO") option next to a BIN price leads to an immediate dilution of domain value (by almost 40%). NEVER add MO next to BIN, in my opinion.

Bin plus mo lowers price.png


MO discount.png


12 - BIN and/or LTO

For names priced higher than $3.5k, LTO may increase sales price and STR. The data shown doesn't prove causality, but I'm extrapolating/assuming.

Avg Sales price BIN vs LTO.png


13 - Pricing by use case

Pricing differs by the end user who buys the name. Price appropriately.

Pricing by use case.png


14 - Pricing levels

Be sure to price just below psychological thresholds.

Pricing levels.png


15 - Length matters

Be careful with names that are 10 letter (10L) or longer, unless there is strong word synergy. Choose shorter unless you know what you're doing.

Domain length STR.png


This is a graph of Atom Premium .com acceptance rates for my personal NameGroove portfolio. You will see Premium acceptance rates dropped dramatically for my submissions as the name increased in length. Length matters not only to buyers but also to Atom.

NG folio acceptance by length.png


16 - Syllable count

Similar to length, the easier the name is to say, the higher the STR. Be careful with 4+ syllables.

Syllable count.png


17 - Repeat Visits

While you cannot directly effect repeat visits, Repeat Visits are highly correlated to STR. Thus, if you see repeat visits, you may want to renew, enhance, or schedule a discount or price increase, etc.

Sourced from Bob Hawkes' 2022 analysis:

Screenshot 2025-03-28 at 9.00.55 AM.png



* All of these charts have been shared by Darpan on his X profile or on @Atom.com blogs.
 
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The views expressed on this page by users and staff are their own, not those of NamePros.
#18. Luck
 
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Fantastic compilation with great insights based on data. Thanks so much for doing this, @NameGroove!
-Bob
 
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Fantastic compilation with great insights based on data. Thanks so much for doing this, @NameGroove!
-Bob

Thanks Bob. I learn a lot from your posts and this community so this was a way to pay it forward.
 
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Super!
 
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Thanks Bob
 
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:xf.grin: definitely, used the thank you button, thanks @NameGroove
 
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Will chk my repeat visits domains, thanks! :unsure:
 
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nice thread shane (;
 
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Thanks for putting this together. I had them bookmarked on several places, now I can easily find all important metrics at one place.
 
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Thanks for sharing, very interesting details!
 
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Perfect timing, this is excellent :xf.smile:
 
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Bob is just an observer in this thread.

Just noticed that, the @ mention at the beginning and Bob's comment through me off. Also the fact this is very detailed and thorough, something I've grown to expect mostly from Bob. :xf.smile:
 
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Just a little funny observation - Today's most popular thread warns against funky spelling in your domain name, but at Atom they are the fifth best selling names - Thanks for the blog

https://www.namepros.com/articles/dont-use-a-funky-spelling-in-your-domain-name.1349420/

That's a great observation. Although you mean 5th highest STR (STR doesn't mean 5th best selling). But it does mean whatever amount of misspellings on their platform that exist, sell well.

People who argue against misspellings will argue they succeed in spite of the name. Of course that is conjecture on their part. The facts are companies with unique spellings succeed - and these sorts of names sell.
 
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Thanks, Bob, priceless (y)
 
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Hey folks just to make sure credit goes to right place @NameGroove put together this excellent article. And as noted, thanks to Darpan @Atom.com for regularly sharing data.

-Bob
 
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The number of people thanking @Bob Hawkes on this thread is a testament to his great contributions to the forum.

And it's funny too.
 
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Thank you Bob, for recognizing NameGroove's contribution.
 
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Despicable Me Kevin GIF by Nashville Tour Stop
 
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Can you elaborate on root words?

e.g

(my understanding)

airplane

1st root - air
2nd root - plane
3rd root - none

Going by your graph it looks like the category the word falls in is the root word.

1st root - gas
2nd root - flat surface / level of existence
3rd root - none

----------------------------------------------------------------

Second question

Does STR conversion depend on using Atom nameservers?


Thanks for the breakdown analysis.
 
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Can you elaborate on root words?

e.g

(my understanding)

airplane

1st root - air
2nd root - plane
3rd root - none

Going by your graph it looks like the category the word falls in is the root word.

1st root - gas
2nd root - flat surface / level of existence
3rd root - none

----------------------------------------------------------------

Second question

Does STR conversion depend on using Atom nameservers?


Thanks for the breakdown analysis.

You're welcome. It should be noted all the stats come from Atom so my answers are my take on the info they provided.

Root Word are whatever words are inside the name. So HealthNest contains "health" and "nest". If a blend like Healthex (a blend of "Health" and "Exchange") the root word would be "health". And so on.

Since these stats are from Atom sales and Atom sales are primarily Premium - it would make sense most sales use Atom NS. I am unclear if Atom included Standard sales in its data sharing.

It should be noted STR data could skew on a brandable marketplace and may differ for non-brandables on alternate marketplaces, However, I think these stats are relevant to all naming, whether on platform or off.
 
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1743347006831.png


Nice article overall, but as the actual STR numbers on the left are missing, this translates into a totally useless chart, as it could be a difference of 0.01% for all we know.
 
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