In both these cases you are making way too many assumptions how a customer will act. You are working under the assumption that all will do as JMich, and we can therefore be modeled on your behaviour. While it can be interesting to see how much the population will vary based on JMich, it do not really confer anything except some (maybe good) guesses. In the second one, people like me would not be captured, as I do not make wishlist entries (never seen the point) or relative new customers. In this case you can only infer some meaning on the people who 1) use the wishlist and 2) use the wishlist in the same way you do. Some may just have the wish list for other to see on GOGWiki, not necessary the game they intend to buy, for example. The subset is becoming meaningless to make any generalisations. The wishlist is not good for this things without more information about each users wishlist behaviour.

The wording on the first one, "irrelevant", is a value and you can never find out without actually asking them this question in some form or other. Value and behavior are linked, yes, but you can never find out value from behavior only as people may act across their values (generally speaking, and especially about perceived values). What one person finds relevant or irrelevant you can only find by directly asking (and questionnaires is difficult for this one also, but possible with some consideration)

edit - basically, all they can find out from this "experiment" is whether people will buy a game when it goes on sale. And lets face it, they do this "experiment" every week. How often can you not find games under $5 here? Right now they are experimenting with Avadon for $3.99. The price point experiment under $5.99 would only be valuable if they had been permanently to distinguish them from normal sales (though granted, it was a sale with many titles)

It's just because it's been out, everywhere, DRM free already. There's no real drive to bring it here.

P.S. This is one of the very few indie games I actually finished and truly enjoyed.

Actually, this is not what I'm saying. What I am saying is that you cannot generalize without checking in more depth. You can say that "Hm, JMich didn't buy any of the experiment games, and neither did Amok. What were their buying habits? Ah, JMich doesn't buy anything if not in promo, and he already had those experiment games that went on promo. Amok on the other hand shows interest only in strategy games, and he already had those in the experiment." So while neither of us bought a game, our bying habits do show why, or at least can help make a guess as to why.


Actually, this is not the same. The experiment you are talking about is whether someone will buy a $40 dollar game at -75%, or the same game at $10 base price. So far, people see the discount percentage, and not the final tally, though I'm not sure if I can find a relevant study. Will try to find one if you wish me to do so though.

P.S. Oh, and the result of "More study needed" or "Results not conclusive" is also a possibility in each and every study. Just remember that they do have a bit more info than just how much those games sold.

(I'll reply tomorrow. I have not slept for 2 nights and you deserve a proper reply)

the soundtrack is awesome.top 5 indie soundtracks imho

This is true, and it is exactly for these reasons that the experiment need more data that straight out numbers from the data warehouse. Reading through your sentence above, the feeling I have is "Yes, and then what?". You are not finding out anything from this experiment that what you find out in a normal promo, i.e. are people more willing to buy a game when it temporarily have a reduced price.

You can off course compare this with the games that person have on a wishlist, if you so want and you outlined a few posts above, but you still need more information about how that person uses the wishlist to make any generalisations. The problem here is that neither of us really have any idea how wishlists are used, how much they are used and why they are used, especially as they are private on GOG. Inferring any meaning on wishlist usage from number-crunching only is problematic for me. How much you can find out through data mining, but not how and why. If so, the only result you get is very obvious and a big so what? again.

In this case it is more interesting as a study in how to manipulate peoples perception then an experiment in new pricing points :)

If this was a genuine pricing experiment, the new price points would have been implemented on a more permanent bases to be able to draw robust comparisons and conclusions. However, what was done here was to temporarily reduce some 5.99 games to 3.99 and some 9.99 to 6.99 (both about -33%?). The 'experiment' only lasted a very short while, and the only value you then get is what happens when a number of games are reduced with -33% for a short while. What would be interesting is to see how many did actually buy while the games where on this reduced price, as for a promo it was not that great (which is why I think is more of a perception study).

There is a possibility of trawling the forum posts to get some perceptions, but this is very time consuming and will be problematic (how do you analyse it?).

re. it takes time going through the data. For the number-crunching bits, it off course depends on structure and resources. But give it to someone doing a little bit of analysis, you can say about one day for data extraction and scrubbing. This involves building a nice little snowflake template and finding the right snapshots. There may be some problems with extracting wishlist data over time, but if the structure in the data warehouse is sound, it is doable. Having clean and ordered data, I would say that running the initial analysis of it for a day is more than enough. To find out your questions, maybe it is enough getting descriptives and a decision tree analysis? Bottom line is that give it a week, and you have a couple of days to spare, this includes writing the report. Given that the experiment was in the end of February, I would say they have had plenty of time going over any possible data if they wanted. They may have done so and kept it secret? I do not know, but if they have I would question the validity of the results because of the above.

I am not saying that there may not be taken some interesting data from looking at the numbers of this price reduction, however i would very much question its validity as an experiment in introducing new price points, especially as the ;experiment' says "we want to see what you guys think of it". Finding out what someone thinks can not be found through number-crunching only. For me the experiment is only valid as a promo with different wording :)

Yes, this is the outcome of every single study made, what is the saying? "The more I know, the less I understand" :)

Doing things the hard way. I finished the game with less than 100 deaths, but by far most of them were for that trinket.