Product Cognitive Evolution: Large data age you're not alone.

Sendhil Mullainathan, a professor of economics at Harvard University, Sendechir Moulenassan in the New York Times online edition that whenever Apple's new iphone was sold, it felt that the old iphone was slowing down. 20 years ago, if you wanted to know what most people knew about products, you had to do expensive research, and now people just need a simple search to know that they are not alone.

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The advantage of being a professor is that you can talk to a group of loyal listeners about your strange theories. For example, I often think of my graduate students complaining that the iphone on my hand seems to be running at a slower pace every time the new iphone goes on the market. This is really good, I might think: is not many companies like in the release of new products to belittle their previous product? If you are not only selling the equipment but also having control over the system, then this is a choice.

Although this theory is very insidious, it does have a strong conviction. But for an economist, this is a bizarre theory, because economics argues that this type of strategy is better than singing to the bottom line of business.

Apple will not comment on such theories. It takes two simple reasons to prove that a person's scrap may not achieve maximum profit. First, legal risk. Second, competition and consumer rationality will boycott the theory. What rivals need to do is to launch a smartphone product that is not going to be outdated and cheaper.

But these are just theoretical aspects, and I'm just a experience.

Usually, my students know not to take my complaints seriously. But this time, Laura Trucco, a Ph. D. in economics at Harvard University, seriously Laura Trouck. She wanted to know if anyone had a similar experience with me. But how do you know what other people think? She reasoned that when people began to struggle with the slow pace of their phones, they would go to Google (Weibo) to find a solution. So, in theory, it is possible to predict the extent to which older devices will be entangled when new products are released by Google Trends (Google Trends), the "iphone runs slow" search frequency data.

As Google Trends updates the data on a weekly basis, Truk will be able to use this to cross-reference the release time of the new phone with related search results. It turns out that I'm not the only one with a similar experience. With the increase in the number of software and the user's expectation that the mobile phone is running faster, the speed of the mobile phone is slow. But the comparison results show that the feeling is not growing, but a few days after the launch of the new phone.

What this data reveals is that people suddenly ' feel ' the phone slows down, but that doesn't mean the iphone is slowing down. Imagine someone telling you there's a buzz in the office, and you didn't notice it before, but now you're buzzing all over your ears. For digital products, the truth is the same. The introduction of new products will make you want to have a faster new mobile phone, but also will make you suddenly find that your mobile phone running speed is how slow.

To test this inference, we can compare the main differences between Apple and Google Android. In the case of Apple, the company not only sells products but also develops systems. In principle, Apple's characteristics create the incentive to (sell more devices), and the approach it takes is to slow down the speed of older models (to control the operating system).

Google has its own approach (which controls the Android operating system), but Google has no incentive because it does not sell its new hardware products directly to revenue. Samsung and other Android device makers, in contrast, have a motive but no way.

The extent to which a mobile phone slows down is due to the psychological effects of a new product release, a psychological effect that can make sense for Android and the iphone. Whether it's a new Android device, or an iphone, it gives users a focus on their existing devices. But the truth is that this "conspiracy theory" applies only to one platform.

Another search term for Truk is "Samsung Galaxy Slow". In this contrast, the Galaxy's new mobile phone after the release of the relevant search data, not the iphone as a big gap. In addition, the results of other brand Android devices are similar to those of Samsung, and there is no such a spurt of search data. This suggests that Apple's release of the new product, compared with other handsets, has certainly attracted more media attention.

But if the focus on new products causes users to feel that their old phones are slowing down, why is the relevant search data Apple announcing an increase on the day of the Apple product release, rather than the date of the new product launch? In 2008, for example, IPHONE3G's release and launch time differed by one months, while the relevant search data surged on the day the product was sold, but did not change when Apple announced the launch.

The data even has a kinder explanation. The new operating system will be released with the new iphone each time. While there is no comment on the issue, one possibility is that the new operating system (optimized for the new iphone) will slow down the old device.

The difference between Samsung and the iphone can also be seen: only 18% of Android device users use the latest operating system, and Apple's new system's user adoption rate is as high as 90%, for the iphone, the new operating system slows down events.

The most obvious difference between Android and iOS is intent. In the mild version, the slowing down of older handsets is not an attribute goal, but a side effect of the operating system's optimization for the new hardware. The search frequency data does not ultimately determine if my phone is actually running slow and why.

In this way, this whole contrast process is a perfect generalization of the advantages and limitations of "big data". First, 20 years ago, a very expensive survey was needed to make sure that many people found that their equipment was running at a slower pace. And now, with the correct use of the data provided by Google Trends, we will be able to know the search content of hundreds of millions of users and, theoretically, their feelings and ideas. Twitter, Instagram and Facebook created "digital emissions" (digital exhaust) to uncover similar macro data for users.

Second, these new data have created a sense of intimacy between individuals and groups. Even for our most peculiar feelings, such data can tell us that we are not alone. It only takes a few minutes for me to know that a lot of people are as entangled as I am. Even if you have never done data collection yourself, you can also use Google's auto complement to see the words you want to enter, and you'll find that "many people want to know this stuff." ”

Finally, we see one of the biggest limitations of large data, which is that the data shows only relevance, not conclusions. There are at least two different interpretations of the search frequency in the keyword search results of "slow iphone running", namely conspiracy theory and benign theory. Relevance is the driving force that gives us a further boost. If what the big data does is just to point out the interesting interplay between the things we're studying, it's also a huge value. And if those correlations make conspiracy theorists more smug, that's a little bit of a price to pay.

(Responsible editor: Mengyishan)