Or it could be people with unusual needs or lifestyles.
Someone observing a kosher diet will buy different food from the mainstream. Someone with limited use of their hands will buy kitchen appliances that most people won't need.
Incidentally, many "As Seen On TV" products were created for people with disabilities. They get marketed to mainstream audiences when the manufacturer realises that there's not a large enough market of disabled people to sustain the product.
Probably the same thing that makes people more likely to root for underdogs.
Avoiding the mainstream, etc.
These people arent as broken as this article may make it seem.
Its interesting how these zip codes are housing bubble resistant for example! Id wager these people arent trying to get rich, just trying to live a decent life and be nice to each other.
I suspect it's some kind of anti-aura effect; those look like the groups that are less likely to be "influencers". The Apple/Tesla strategy also used by lots of fashion products is to sell at high prices to market segments that the rest of the public identify as "cool".
Not only do your numbers not appear in the document you provide, one has to wade through pages and reams of stats ... And your comment still makes no sense to me.
Recall that harbinger zip codes have low average successrates, and so a positive (negative) correlation in Table 3 indi-cates that harbinger zip codes have relatively low (high) valueson that variable.
Effectively what these mean is that, for example, if your product is popular in places where a lot of people are young white people, in a single family household, in the countryside, without a university degree it is not likely to be successful.
If your product is popular in places with a lot of older hispanic people, with a university degree, who live in the city, in an apartment building, it's more likely to be successful
Can't edit it now, but noticed the negative sign was missing off one of them, "single family" should be a negative value.
From the paper:
These values effectively state the correlation between the odds
of the product succeeding, and people who buy the product having
that characteristic.
Age Average age of head of household
Home Value Estimated home value
Income Est. household income in the zip code
Single Family % of households in single family homes
Multi-family % of households in multi-family homes
Distance Distance to nearest MassStore store
Comp. Distance Distance to nearest competitors’ store
Nbr Households Number of households in the zip code
% Urbananized % households classified as “Urbanized”
% Urban Clusters % households in “Urban Clusters”
High School % of households whose highest educational attainment is graduating high sch
Bachelors % of households whose highest educational attainment is a bachelor degree
White % of households that are identified as “White”
African American % of households that are identified as “African American”
Asian % of households that are identified as “Asian”
Hispanic % of households that are identified as “Hispanic or Latino (of any race)”
Whenever I decide to use some software, it vanishes in insignificance. QBasic, Delphi, FreePascal/Lazarus, Micrografx Picture Publisher, Conitec 3D Game Studio, Java Applets, Mercurial hosted on SourceForge or Bitbucket, QCodeEdit, XQuery
Anybody else feel like they are on both sides of this? Do these people REALLY only end up supporting the products that end up failing?
The first time I tried a 1st gen iPod, I was amazed and had to have it. Then bought a Zune HD when it came out, and kept it long into when everyone else had moved on.
Windows Phone, yup, I was a supporter. But was also doing yoga, WHM, intermittent fasting, etc. I was "barefoot" running before Born to Run came out, I rode a single speed mountain bike which never really became a thing.
I didn't read the entire report because I don't have an account, but are the people who are supposedly the "Harbingers of Failure" just more likely to be early adopters who are more likely trying new things and therefore they end up liking and supporting things that end up failing?
I started reading this article, then found myself skimming more and more as it became flakier and flakier. Now, because I just skimmed most of it, I may be missing some important points -- but my impression is that the authors are so bound up in the details & statistical tests that they can't see any big picture.
For example, in discussing household moves they talk about which zipcodes people choose to live in, as if they had perfect freedom of choice. But I don't see where they account for median income. How are we to know if people in a "harbinger" zipcode can even afford to move to a "Group 1" zipcode? Or if it would be a convenient distance from their employment?
I simply can't see putting much or any faith in these "results".
20 comments
[ 2.8 ms ] story [ 57.8 ms ] threadSomeone observing a kosher diet will buy different food from the mainstream. Someone with limited use of their hands will buy kitchen appliances that most people won't need.
Incidentally, many "As Seen On TV" products were created for people with disabilities. They get marketed to mainstream audiences when the manufacturer realises that there's not a large enough market of disabled people to sustain the product.
Avoiding the mainstream, etc.
These people arent as broken as this article may make it seem.
Its interesting how these zip codes are housing bubble resistant for example! Id wager these people arent trying to get rich, just trying to live a decent life and be nice to each other.
Modern Marketing came out of WWII Psychwarfare efforts, gotta keep that in mind.
I suspect it's some kind of anti-aura effect; those look like the groups that are less likely to be "influencers". The Apple/Tesla strategy also used by lots of fashion products is to sell at high prices to market segments that the rest of the public identify as "cool".
Age -.2971
High school -.1710
Home value .2865
Bachelor’s degree .1197
Income .0646
White -.3919
Single family .4047
African American .2232
Multifamily .4132
Asian .3426
Distance -.3740
Hispanic .4854
Comp. distance -.4156
Coupon discount -.2333
Nbr. households .3160
Coupon frequency -.3741
Urban .4190
Unit price paid -.0523
Urban clusters -.1603
Meaning of these variables is here: https://docs.google.com/document/d/1d8O9ja_p08w6cSkOPZ-L1sDZ...
Recall that harbinger zip codes have low average successrates, and so a positive (negative) correlation in Table 3 indi-cates that harbinger zip codes have relatively low (high) valueson that variable.
If your product is popular in places with a lot of older hispanic people, with a university degree, who live in the city, in an apartment building, it's more likely to be successful
From the paper:
Whenever I decide to use some software, it vanishes in insignificance. QBasic, Delphi, FreePascal/Lazarus, Micrografx Picture Publisher, Conitec 3D Game Studio, Java Applets, Mercurial hosted on SourceForge or Bitbucket, QCodeEdit, XQuery
The first time I tried a 1st gen iPod, I was amazed and had to have it. Then bought a Zune HD when it came out, and kept it long into when everyone else had moved on.
Windows Phone, yup, I was a supporter. But was also doing yoga, WHM, intermittent fasting, etc. I was "barefoot" running before Born to Run came out, I rode a single speed mountain bike which never really became a thing.
I didn't read the entire report because I don't have an account, but are the people who are supposedly the "Harbingers of Failure" just more likely to be early adopters who are more likely trying new things and therefore they end up liking and supporting things that end up failing?
For example, in discussing household moves they talk about which zipcodes people choose to live in, as if they had perfect freedom of choice. But I don't see where they account for median income. How are we to know if people in a "harbinger" zipcode can even afford to move to a "Group 1" zipcode? Or if it would be a convenient distance from their employment?
I simply can't see putting much or any faith in these "results".