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Technological evolution as function of demand – Part II

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In part I we’ve already seen several technologies at various stages with saturated/declined demands and in this part I will bring more examples such as Facebook, Dropbox, gaming market and Crocs.

Sum table:


Intro (can skip if you have seen part I)
Stages of technological evolution are inevitable as they are driven by those who are created by evolution by themselves. Demand for higher efficiency, demand for higher excitements, demand for communication, demand for very existence, DEMAND is a smoking locomotive of exponential evolution. We can accept it, we can follow up, we can drive it, but it is extremely hard to ignore it. I will examine trends of tech evolution by great tool of demand analysis – Google Trends.
In consumer market, the demand-S-curve is following the technology-S-curve at the beginning and changing the phase at some point, so it is hard to see the breakthrough of technology from demand, but “easy” to see the coming saturation or decline of technology by looking at the demand for variety of products (not a single one) or for representing segment as a whole.

Part II:
Communication driven by web evolved into form of permanent social sharing information under dominated Facebook. Taking demand for Facebook on a worldwide scale would be a tricky part.

One of indicators for demand might be amount of users. Thanks IPO we know well numbers, while even if we would not know that, we have Google Trends to help us as well (not straight forward though as users once registered are not searching for it, but going directly there, so there is a need to perform a cumulative function and reduce from it weighted “leave Facebook” index).
So this is how we are getting # of users (in Millions) based on Facebook Timeline (or taken from quarterly earnings reports) versus cumulative “Service Interest Rate” for Facebook (no drop off as it is negligible comparing to growth):


You can see that linear regression from 2004 is 0.992 and from 2009 0.996!

The drop off rate might be important indicator of decline and we see that it has stabilized and not growing (and relatively small as mentioned).

Same way we can see anther exponentially rising services e.g. Dropbox:


And the same data, but Google Trends Cumulative versus Actual published data:


Games as something that has to survive in a very competitive and low-entrance-barriers market has to be extremely creative and push limits. That is why it is easy to study the relatively short-lived evolutional cycle. You can see that there are two main types of behaviors:

Long&Low (World of Warcraft, Angry Birds) and Peak-based (Half Life, Starcraft, Diablo)
It would be interesting to drill down into differences in market strategies for those two types.
Same thing we see for Facebook Games:
Generally, about gaming platforms, there are clear trends of growth, saturation and decline (bad news for Zynga):
Another good example of technology cycle is Crocs:
You can see a seasonally aligned perfect S-curve

We’ve seen more examples of demand-driven technology evolution cycles in various diverse fields. We’ve seen that it is possible to get a high-precision diagnostic data of evolutional stage for specific product or entire technology by use of Google Trends.


Author: Andrey Gabdulin Product Development

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