A few weeks ago, we launched a new tool, the Topics Matrix. The Topics Matrix lets you generate growth-share matrices automatically. We described in a previous blog post how it works. As we said in this previous blog post, when people saw the Topics Matrix, they usually asked:
“Interesting! I can do this for any of my topics on-the-fly, and the data will always be real-time. But can I also see how the data points have evolved over time?”
Yes, now you can!
We just released an update to the Topics Matrix. This update lets you see, for any topic, how the topic’s growth and share developed over the recent past. For example, consider ‘cloud computing’ vs. ‘edge computing’. A little while ago, we published a blog post arguing that edge computing looks like an emerging topic. We looked at edge computing because Peter Levine at a16z very convincingly argued that (decentralized) edge computing will replace (centralized) cloud computing.
Let’s come back to this and directly compare edge computing to cloud computing in our newly enhanced Topics Matrix:
For “perspective”, we also added blockchain as another topic. For each topic, the matrix shows growth and share across three time windows (2012-2013; 2014-2015; 2016-2017). You can see the differences between topics:
- Cloud computing is very big but its growth has declined.
- Blockchain is quite big already and continues to grow a lot (although the growth has slowed down a bit in the most recent time window).
- Edge computing is the smallest topic yet but its growth has really picked up.
So this appears to confirm Peter Levine’s arguments.
In the matrix above, the fastest-growing topic is blockchain (we wrote about blockchain in more detail in a previous blog post). Its size is approaching that of cloud computing. Let’s look at this in more detail. You can do this in the Topics Matrix by right-clicking on a topic’s time trail:
This view shows how size and growth of blockchain are distributed across different types of information (VC investments; patents; science and technology publications; patents; industry news; technology blogs). This view shows that VC investments are the biggest drivers behind share and growth of blockchain.
The chart below shows blockchain VC investments identified by Mergeflow. The spikes are individual investments, and the line is the running sum of the investments. For some of the bigger investment events, we added the company names as labels:
Aside from VC investments, look at how science and technology publications are picking up. The screenshot below shows the same zoom-in view on blockchain as the screenshot above. Only this time the mouse was hovering over the SciTech Publications line. The matrix is interactive; it blends out the other data lines so that the SciTech Publications line is easier to see:
Notice that the temporal pattern here is interesting: We see that VC investments pick up in size and in growth before the scientific publications start growing. This seems to go against traditional assumptions of how technologies or innovations develop. Following theories such as Schumpeter‘s, many people expect technologies to go from basic research to applied research; from applied research to prototypes; and from prototypes to full-scale commercialization. In other words, scientific publications should have started growing before the VC investments. In our data, we observe the opposite. Why is that? Well, we could dig deeper now in Mergeflow and look directly at the underlying information (i.e. the scientific papers and their topics over time). But this is something for another day, for another blog post.
Also published on Medium.