BrandBucket Experience

[xtremex]

hello

I am new to BrandBucket. Before getting my hands on this

I wish to experience about brandbucket from my fellow members


Thanks

 

[Recons.Com]

I'm a software engineer that works with big data, but close enough.

Honestly, my answer is closest to ignore. There is a difference between a small data sample and a bad/corrupted data sample. That DOESN'T mean I won't read what he says. But I don't use it in any decisions. Like I said - even with the error % you are suggesting, I would be fired from my job for doing that. Part of the problem is that people are relying on pure metrics to sell brandable domains. But it doesn't work that way. Trust me, I wish it did.

I took LOADS of sales data and ran machine learning algorithms, etc on them last year to look for patterns. What I found? There is no pattern. Or the pattern changes every month or week. What is more important is to understand the pulse of the business world and of linguistics and their interaction. Yes, pay attention to general metrics, but don't place too much faith in them. When I use patterns and metrics I chose MUCH worse domains than when I used linguistic and business knowledge mixed with gut instinct.

Additionally, to be perfectly clearr, if people want to discuss DNBolt's metrics and study them, that's fine. That's not my issue. My issue is when they use false data to make conclusions on BB etc. That's just unfair. For SURE I feel BB has brought this on themselves by not sharing the data themselves, but that doesn't mean we should do it.

Hope this helps!

Let's focus on the specific conclusion on hand:

- Analysis based on the last month numbers show that only 1 out of 80 sales was a brandable that was not based on ANY keyword. Conclusion: don't invest in those names.

Now, to call it CORRUPT, you should be able to demonstrate that the missing 0-16 names were somehow very heavy on NO keyword brands. Do you have such a fact? If you don't, I won't be surprised, if you call polls based on calling 1000 people CORRUPT as well, because that is not any more legit than the above conclusion.

Now, if someone has time and desire, he/she could go over few more months and see if the conclusion holds (it could hold even with 1-5 no kw sales, as it would still mean you are better off buying kw based ones).

 

[equity78]

I'm a software engineer that works with big data, but close enough.

Honestly, my answer is closest to ignore. There is a difference between a small data sample and a bad/corrupted data sample. That DOESN'T mean I won't read what he says. But I don't use it in any decisions. Like I said - even with the error % you are suggesting, I would be fired from my job for doing that. Part of the problem is that people are relying on pure metrics to sell brandable domains. But it doesn't work that way. Trust me, I wish it did.

I took LOADS of sales data and ran machine learning algorithms, etc on them last year to look for patterns. What I found? There is no pattern. Or the pattern changes every month or week. What is more important is to understand the pulse of the business world and of linguistics and their interaction. Yes, pay attention to general metrics, but don't place too much faith in them. When I use patterns and metrics I chose MUCH worse domains than when I used linguistic and business knowledge mixed with gut instinct.

Additionally, to be perfectly clearr, if people want to discuss DNBolt's metrics and study them, that's fine. That's not my issue. My issue is when they use false data to make conclusions on BB etc. That's just unfair. For SURE I feel BB has brought this on themselves by not sharing the data themselves, but that doesn't mean we should do it.

Hope this helps!

Well see that is where the problem lies, we don't know what data is corrupted, I said to Michael I wish BrandBucket could come out and say either:

a) The sales reported are correct but there are more sales missing
b) The sales reported are partially correct
c) The sales data is completely inaccurate

You may get fired from your job Svede but those mistakes would probably screw up everything. With DNBolt data it gives some light to the darkness, a little light is always better than zero light. I wish BB would find a way to take control of their data, why not names that sold without prices ?

Look we can all debate what is and what should never be, but people are always going to look for sales data and sales stories in this business that is not stopping. BB should become the standard bearer for accurate info, to put a modern spin on The Man Who Shot Liberty Valance

Son, this is the Internet, when the legend becomes fact print the legend.

 

[svede]

Let's focus on the specific conclusion on hand:

- Analysis based on the last month analysis show that only 1 out of 80 sales was a brandable that was not based on ANY keyword. Conclusion: don't invest in those names.

Now, to call it CORRUPT, you should be able to demonstrate that the missing 0-16 names were somehow very heavy on NO keyword brands. Do you have such a fact? If you don't, I won't be surprised, if you call polls based on calling 1000 people CORRUPT as well, because that is not any more legit than the above conclusion.

Now, if someone has time and desire, he/she could go over few more months and see if the conclusion holds (it could hold even with 1-5 no kw sales, as it would still mean you are better off buying kw based ones).

When someone presents data, all you need to prove it is corrupt is to present one case (basic boolean logic). I and others have already presented multiple instances in the past. The burden is on HIM to prove it is accurate.

Do you really think polling and surveys as so accurate? Unfortunately, their inaccuracy is usually for other reasons (small subset or targeting specific people to get specific results). To more accurately compare the two, the comparison would be polling 100 people and then giving the results, but people know that you could have left off any number of people who responded to the poll or added people to it that never responded.

At the end of the day, I'm not going to sit here and argue with you. You are okay with using bad data. Don't ever try to get a job using data, especially in the tech industry and you won't make it. That's not a smart way to operate.

All the best!

 

[svede]

Well see that is where the problem lies, we don't know what data is corrupted, I said to Michael I wish BrandBucket could come out and say either:

a) The sales reported are correct but there are more sales missing
b) The sales reported are partially correct
c) The sales data is completely inaccurate

You may get fired from your job Svede but those mistakes would probably screw up everything. With DNBolt data it gives some light to the darkness, a little light is always better than zero light. I wish BB would find a way to take control of their data, why not names that sold without prices ?

Look we can all debate what is and what should never be, but people are always going to look for sales data and sales stories in this business that is not stopping. BB should become the standard bearer for accurate info, to put a modern spin on The Man Who Shot Liberty Valance

Son, this is the Internet, when the legend becomes fact print the legend.

I totally agree, BB needs to respond with data - no argument with you there. And I understand why people want data as I am right there with you guys. I'm only speaking up to try and give my opinion since it is one of my areas of expertise and I feel a lot of people are jumping to conclusions with bad data. My fear is that we have been going through this tunnel so long that the light we think suggests the end of the tunnel is just a train approaching from the other direction.

I really hope that BB takes these discussions to heart and delivers.

Thanks!

 

[equity78]

When someone presents data, all you need to prove it is corrupt is to present one case (basic boolean logic). I and others have already presented multiple instances in the past. The burden is on HIM to prove it is accurate.

Do you really think polling and surveys as so accurate? Unfortunately, their inaccuracy is usually for other reasons (small subset or targeting specific people to get specific results). To more accurately compare the two, the comparison would be polling 100 people and then giving the results, but people know that you could have left off any number of people who responded to the poll or added people to it that never responded.

At the end of the day, I'm not going to sit here and argue with you. You are okay with using bad data. Don't ever try to get a job using data, especially in the tech industry and you won't make it. That's not a smart way to operate.

All the best!

To your first part, that is true from a scientific or analytical standpoint, but guess what if I am a college football coach in the dark about what my players are doing at night. Then someone sends me an info that 8 players were doing cocaine at a frat house and then after I research it turns out only 7 were, that whole initial email is not corrupted, I am still pissed and worried about the stability of my football team.

 

[svede]

Yeah, right. Tech industry makes bunch of conclusions based on 100% accuracy.

What you are missing is this: without any data, all you can conclude is 50/50. If you can find bunch of "corrupt" data that can let you tilt the scale and get to getting it right 51 out of 100 (51/49), you can become billionaire just off that. I deal with uncertainties, data, probabilities (including subjective ones) on a daily basis. We make billions of investments based on 15% chance of success and any "corrupt" data that can take that to 16% is worth millions.

But you can keep leaving in a perfect world with perfect data. Good luck. I wonder how you buy your domains, if you are always looking for 100% accurate info.

I didn't say 100% accurate data or perfect data and if it sounded like that was what I was saying, I apologize and let me clarify.

Like with the polling data, the data has inaccuracies for other reasons. But you can control and mitigate those risks. Subset size, target audience, etc, you can adjust, especially over time. The inaccuracy is in the result, not the collection of the data. With DNBolt, he is marking items as sold that weren't sold and others as not sold that were sold. The type of inaccuracy you expect to see is that this month our subset had an exaggerated amount of suffix domains sold. But over time, that will level off. If you are outright missing data, it is much harder. IT companies often either collect data into data warehouses or buy data from datawarehouses. If the source of collecting this data was flawed, they would not buy it.

I hope that explains it better.

 

[svede]

To your first part, that is true from a scientific or analytical standpoint, but guess what if I am a college football coach in the dark about what my players are doing at night. Then someone sends me an info that 8 players were doing cocaine at a frat house and then after I research it turns out only 7 were, that whole initial email is not corrupted, I am still pissed and worried about the stability of my football team.

True, but this is a different situation. People are making claims against a company and blackmarking their name over it. That's not fair. I totally thing BB is making a mistake my not defending themselves with data, but this impact a business when we jump to conclusions. Personally, I want BB to make the right decisions and become better. I don't want to hurt them since their health may help my business. When people do that, it looks like they have a vendetta and just want to hurt the business and brings question to their claims to wanting them to do better.

 

[frank-germany]

My interest is not in discrediting DNBolt, but to get people to use logic. I am neither on DNBolt's side or BB's side. I use BB. I use other platforms. I like things about BB. I dislike things about BB. But I refuse to use bad data to make arguments for or against them. If data is not valid, you can't use it (or shouldn't use it). People are making claims using data that is false. It would be better to not use any data that to use it. I am not offering an alternative, because there isn't one. I want one! But using bad data because there isn't an alternative is a HORRIBLE decision.

like they say in germany:
don't trust any statistical data you didn't fake yourself !!!

 

[equity78]

I didn't say 100% accurate data or perfect data and if it sounded like that was what I was saying, I apologize and let me clarify.

Like with the polling data, the data has inaccuracies for other reasons. But you can control and mitigate those risks. Subset size, target audience, etc, you can adjust, especially over time. The inaccuracy is in the result, not the collection of the data. With DNBolt, he is marking items as sold that weren't sold and others as not sold that were sold. The type of inaccuracy you expect to see is that this month our subset had an exaggerated amount of suffix domains sold. But over time, that will level off. If you are outright missing data, it is much harder. IT companies often either collect data into data warehouses or buy data from datawarehouses. If the source of collecting this data was flawed, they would not buy it.

I hope that explains it better.

Svede I think you would agree that if I have been selling domains on your platform Svede.com for two years, you never gave me any sales data. One day you say I am not going to give you all the data but here you go, here are 80 of the 100 sales that took place on Svede.com this year. That has value, it is not complete but still valuable.

Now I agree with you 100% if DNBolt is saying names sold that didn't then that is a major problem.

 

[svede]

Svede I think you would agree that if I have been selling domains on your platform Svede.com for two years, you never gave me any sales data. One day you say I am not going to give you all the data but here you go, here are 80 of the 100 sales that took place on Svede.com this year. That has value, it is not complete but still valuable.

Now I agree with you 100% if DNBolt is saying names sold that didn't then that is a major problem.

Yes, if I was sure that was the only error, I would be more open to that. However, IIRC, there were already NP members that came forward and said some of their domains were listed as sold that weren't (upset due to being Google indexed on his site) - not sure if those posts still exist as much of that got deleted.

The problem I have is that when I see 1 data inaccuracy it suggests any sort of data inaccuracy. Add in the "technology" he is using to do it, and I know from my experience it tends to err on both sides.

The problem is that there is no confidence in his data due to bad data already identified and his method of collecting it.

EDIT: You aren't selling Svede.com are you??

 

[frank-germany]

a little light is always better than zero light

I can't agree here

this will most probably get you even more confused/ misguided

 

[frank-germany]

But you can keep living in a perfect world with perfect data. .

a german is a german is a german ..

 

[Recons.Com]

a german is a german is a german ..

Oh, if you knew how much geologists are paid for slight refinement in their guestimates ))

 

[equity78]

I can't agree here

this will most probably get you even more confused/ misguided

Not really with a litlle light you can make your way out of the maze, I was making an over arching statement, not just focused on sales data, I never depended on anyone else's research to make any decisions.

But to keep it on the domaining topic, no sales reported is darkness, 30% is some light and that should never confuse anyone. It is a data point to give a little insight. The subjectivity of brandable domains is unlike any other niche. The majority of people I have spoken to about brandables all had the same line, Their names were great everybody else's names sucked.

I used to talk to Zane Gocha and he thought BB names were inferior to Namerific and while I never asked her I would be willing to bet Margot would say the opposite.

 

[frank-germany]

decision based on incorrect / incomplete data are as good as decision made out of gut feeling

you may be lucky or not

in the end there is only trial and error

which is absolutely good enough for me personnaly

 

[svede]

removing, because I think I misread/misunderstood the original statement.

 

[svede]

Look, I am not into broad academic discussion with "BB experience" thread.

I am discussing practical and tangible conclusions. For myself, personally, I have decided that no-kw-brands are not going to be more than 1-5% of my total .com portfolio based on the above, until I see data, corrupt or not, telling me otherwise.

And, accordingly, my thanks go to @hookbox and @Dnbolt for spotting out something that could save me a lot of money over the time.

See my above edited post, I misread your original post - sorry.

In any case, to speak to that, the problem is that there is such a large range in what we mean by "kw" and "non-kw". A lot of non-kw domains accepted on BB, I wouldn't handreg. On the other hand, I personally sold one for $5k on BB last year. There is a lot more to whether it is KW-based or not that goes into that discussion.

 

[frank-germany]

If someone here would say "data is corrupt, because I have sold personally few non-kw-brands in last month or two" that would also tip the scales towards "it is corrupt" camp...

I have sold personally few non-kw-brands in last month or two

 

[svede]

I have sold personally few non-kw-brands in last month or two

Personally, they sell better for me, but I am also pickier than most on the ones I select, so that could be part of it.

 

[Recons.Com]

I have sold personally few non-kw-brands in last month or two

on BB? ) We are still on whether 80 BB sales are missing any non-kw-brands )