Dream: Corporate VP of Junk

I dreamt I was called into a meeting without knowing why I was there. (That is typical.) The meeting was about a company VP being in the hospital with a heart attack so they were going to make me the acting. Which was confusing because I have no idea who that guy was, what was his portfolio, or even how things are done there.

I leave the meeting and learn he sells junk on eBay and Amazon. Literal junk. The company’s other areas hand over broken or unusable objects. We list and sell them and write off the loss.

Goodreads Imports Amazon Purchases

When Amazon bought Goodreads, the main hope for me was a tighter integration.

Many of the books I read have a variety of editions, so I have to figure out which one to select on Goodreads. Different editions might even have the same cover, so it can be a challenge. If the book is an ebook, then the ASIN is definitive.

Importing my purchases into Goodreads would be easier on me. So I do love the new Add Your Amazon Books to Goodreads. It only shows those books I’ve purchased on Amazon but not added to Goodreads, so I do not have to scroll through hundreds of books to find the new purchases. They are also organized so the newest purchase sits first. Finally, it does not automatically add books which means I have to mark them as to-read, currently-reading, or read one-by-one. That is fine, as I have some sets I bought on Amazon that I list individually on Goodreads.

Overall, I am pretty pleased and caught up on some listings I missed.

A listing of oddities…

  • If Goodreads librarians did not add books correctly, then the there might be a mismatch in editions.

Accounting Predictions

In my Prediction Accountability, I ranted on how no one really knows whether predictions are accurate and ended with it really does not matter because no one is going to really stop using these services because they are usually wrong. Basically, I thought it futile to even try. In retrospect that is probably the perfect reason to do it.

So I came up with a scoring system:

    • Good Recommendation= 3 points
    • Not interested= -1 points
    • Wishlist/Queue= -2 points
    • Dislike= -3 points

Would you score these differently? Why?

My reasoning goes something like this. Something I agree I should watch should equal the inverse number of points of something I know I will dislike from previous experience. Anything I am not really interested in definitely is not a win, so it should be a negative, but not too close to a dislike. Suggesting something already on that company’s records that I am interested in wastes my time because they already know I am interested in it, so lose two points.

First pass, Amazon sent me an email today saying,

Are you looking for something in our <x> department? If so, you might be interested in these items.

One item I have thought I should watch based on TV ads but not put on my wishlist yet, so I agree with Amazon, I might be interested in it. It gets three points. (3) Five items already were in my wishlist so that is negative two points each. (3 -10= -7) One item is the 6th season of a television series I have only seen part of the first season and not gotten around to completing even that so not interested and negative one point. (-7 -1= -8) Another item is the 3rd season of a TV series I where I have not watched even the first yet. If the recommendation had been the first, then I would count it as a good one so instead I’ll award halfway between good and not interested (-8 + 1 = -7) Out of eight items in the email, the score is a -7. That is just one email. I track this for a couple months and see where it goes. And do the same for Netflix.

I think this exercise points out the possibility that these “predictions” are basically nudges more to buy something.

If your Learning Management System vendor claimed they have a 90% plus correct prediction rate for whether students will fail a class, then how would you assess it? The obvious start would be track the predictions for classes but do not provide the predictions to instructors. Compare the predictions to actual results. Of course, these things are designed around looking at past results. What is the investment company statement they have to put in so they do not get sued for fraud? Oh, right, “Past success does not guarantee future performance.” So I would not rely too much on just historical data. I would want a real world test the system is accurately working.

Prediction Accountability

The technology buzzword standard for prediction appears to be Netflix and Amazon. Everyone wants to get to where they make recommendations customers will buy. But are these predictions any good?

Out of the slew of emails you get from Amazon, how percentage do you actually buy? How many do you sneer at it and hit delete in disgust that they could get it that wrong? For me, the latter is more common than the former. Certainly it is not from a lack of data, I buy more off that site than I do all bricks and mortar stores excepting groceries combined. (And that makes me re-think how I buy groceries.) Maybe Amazon has too much data that confuses it mixed with correct data. I look things I have no interest in buying such as someone mentioned having problems with a product. Though I have to question Amazon recommending I buy the camera I bought from them a couple months prior.

Netflix really is not any better. Their top 10 recommendations change weekly for me. In my current top 10, one was already rated 5 stars. Another four were already in my queue. The remaining five predicted I would like them between about 3.0 and 3.3 stars. That is out of five. There are 27 items in my queue with higher predictions than these.

Before I start tracking these predictions to gauge how effectiveness, do I even really care? Am I going to stop consuming from companies that overstate their claims? Or should I close my ears when clueless people spout the prediction buzzword? Not really. No. Guess that is what I am left doing.

I think the standard comes not from them being any good. Instead decision makers are aware of them, so they understand wanting to emulate them.

Best Sellers

Several friends mentioned reading the Hunger Games over the past few months. The movie opened last night. (No, I have little interest in either seeing the movie or reading the book. But then I was late to jump on the Harry Potter bandwagon plus have not yet jumped on the Twilght or Sookie Stackhouse bandwagons.) Presumably people were reading the book because of the movie. That should mean book sales increased, right? UPDATE 2012-MAR-18: Oh, right, in the NovelRank graph below and others, the trend appears to be sales decrease in the months before the movie release. I probably should check again on April 1st to see if March stays low. Maybe Jan/Feb buyers delayed for March? /UPDATE

So I went looking for information on sales.

My first mistake was thinking to look at best seller lists. The New York Times, Amazon, and Barnes & Noble lists all provide ranks. NYT bases its on numbers reported from various book stores. Amazon and B&N base theirs on their own sales. Ranks do not equate to sales volume. The difference between any two ranks could be 1 unit or 1,000. All three lists only provide rank. Only the NYT provides old lists. It would be really cool for Amazon or B&N to make available a chart showing the popularity over time. Though, because it is just rank, I could see some obsessive types worrying about dropping from #1 to #2 when sales stayed the same.

Strangely Amazon and B&N both ranked the Hunger Games paperback #1 with other editions and sequels also show up in the top 100. NYT did not have it. Depending on the kinds of stores used by the NYT, I could see this being true.

I did run across an interesting site called NovelRank. It purports to provide exactly what I want: sales numbers over time.

NovelRank Hunger Games
NovelRank Hunger Games

Then the numbers seemed absurdly small. Over the past year, Amazon sold less than 28,000 copies of the Hunger Games paperback? Hardbacks added another 10,000 and Kindle editions another 11,000? All combined less than 50,000 copies over the past year?

According to the NovelRank FAQ:

Are sales estimates 100% accurate? Book sales estimates are still estimates, and for books selling a low volume ( less than 100 copies a month for instance ) the estimates are most likely accurate within 1%. In the end, it is all based on sales rank changes rather than sales numbers, and NovelRank should not be used to dispute hard sales figures from publishers or Amazon.

Again, these are sales ranks used to imply unit sales volume. That could explain why the numbers seem too small.

Ah, well. Hopefully the information exists somewhere and my short adventure looking for it just needed a few more hours.

Pneumatic tubes

According to Dan Pink, John Elfreth Watkins, Jr. predicted several things:

Among his calls: Americans will be taller. (True) There will be no C, X, or Q in the alphabet. (False) Photographs will be telegraphed from large distances. (True) Rats and mice will be gone. (False). Pneumatic tubes, instead of store wagons, will deliver packages and bundles. (False, but Amazon is working on it.)

The pneumatic tube one was interesting. Packages and bundles would have included memos, correspondence, and perhaps even books or games. The Internet was so “eloquently” described by Senator Ted Stevens, “The Internet is not something you just dump something on. It is not a truck. It is a series of tubes.” Most memos, and correspondence these days is carried over the Internet. Books are getting there. So maybe this should be a partial?

Am I too generous?

Library Netflix Model

I tend to buy books. As Heather pointed out on Flickr, I could save lots of money by checking books out from the library. I don’t for one big reason. I am lazy. Most of my purchases fall within a sweet spot of wanting to read more about something because I heard about it on the radio, saw a television episode on a topic, read something in another book, or talked to someone about it. My memory is poor so I only buy a book if I happen to hit the bookstore prior to forgetting. For most of these that means Amazon. To get a book from a library would be mean remembering to go there AND the book I wanted which is unlikely.

However, books sit on my shelf for sometimes years before I get around to reading them. I also tend to read several at a time which slows my pace on any particular book to about 250 pages a month unless I devote more time to it.

Netflix works similarly for me. I add things to the queue and maybe eventually get around to getting the disk. I’ll watch a disk a week maybe. Netflix’s Watch Instantly is much better for me as I can pick whatever I want off the list and see it then. Even then I might watch half and watch the rest later. I’m watching 3x more with the Watch Instantly model than I did off the DVD model.

While I would like an eBook Reader, I don’t find the purchase model compelling.  Take the Netflix concepts of:

  • A watch instantly queue (more a list of everything I am interested in watching)
  • When I am ready to read it downloads to my device.
  • When I am finished, I no longer have access.
  • Do not limit me to one out at a time.
  • A monthly charge for the privilege of all of the above.

With that kind of model, I would be willing to buy a Kindle, Nook, Kobo, or whatever for anytime access to an enormous library of books. They could even charge me $10-15 depending on how many I can have out a time.

New DVDs

Hmmmmmmm… got some new DVDs to watch. Stuff I already had on VHS already: 5th ElementTombstone, and Wrath of Khan. This brings my DVD collection to 61 titles.

Have never thought of myself as a PC repair person. I have done some stuff on my own home and office computers. Assisted Andrew Otapski with some stuff. He really wants me to go to grad school and get a Masters of Education in Instructional Technology and later an Education Specialist in Instructional Techology.