One Billion Ideas… One Big Question
Diving into data to learn how people REALLY use mind mapping
Our friends over at MeisterLabs recently published an interesting article to mark an incredible milestone on the MindMeister journey as they celebrated over one billion ideas being generated using their online mind mapping application!
Read the MeisterLabs article: World’s largest online collection of creative ideas?
First and foremost, we congratulate the MindMeister team for creating a tool that makes it so easy and appealing to generate, capture and organise ideas! Beyond that however, we found ourselves considering what those BILLION ideas could potentially tell us about how people are really using MindMeister and mind mapping tools in general…
A billion data points… now what?
With a billion ideas, comes one big question: Now what? What could we learn from one billion ideas that are saved (and still developing) in MindMeister? What insights could we extract from over one billion data points? And how could the mind mapping community use that information to our collective advantage?
Well, in this particular case, a large percentage of the billion ideas reside in private mind maps within the MindMeister system, and so the data is not actually viewable or usable, even to the MindMeister guys themselves, who take the security of your ideas pretty seriously… and rightly so! (Read more about MindMeister security). But still… taking just the publicly shared mind maps from the MindMeister library and digging into the contents would surely tell us something interesting about how people are using mind mapping? As MindMeister founder Michael Hollauf notes:
“The MindMeister public mind map library contains hundreds of thousands of maps, whose topics range from the best productivity hacks to effective learning strategies and from book summaries to business plan templates. Public maps are often used as collections of thoughts, as knowledge pools, guides or even presentations.”
Given the size and richness of the MindMeister public map library, it is amazing to think what we could learn about the topics that people and teams are exploring through mind maps. Michael shares a mind map image within his article with a few of the topics that people have mapped, but it would be fantastic to see more in depth analysis, or infographics showing (for example) the most common words used across all of the public mind maps. Maybe the team can share some more information/analysis with us soon!
However, in reality, the MeisterLabs article got us thinking about a bigger trend, opportunity, and challenge than just the MindMeister map library data… and this is what we’ve been looking at in our Biggerplate planning sessions too…
Diving into data
The world of data, and the particularly buzz-wordy domain of “BIG Data” is all the rage. We’re all supposed to care more about our data, but not many of us really know what that means. We know that websites gather and use our data somehow, but we’re not really sure what ‘data’ they’re capturing, or whether we should really care. And most of us don’t know what companies actually use our data for, although we all suspect it’s something to do with those annoying adverts that follow us around the internet trying to sell us a pair of shoes that we looked at momentarily 3 weeks ago... and nobody likes to be stalked by footwear, it’s too ironic.
To a certain extent, the same is true for many businesses on the other side of the equation; we know we’re supposed to be doing something clever with data, but we’re not always sure what, and the realities of trying to do “something clever” when you don’t have an army of data analysts and experts at your disposal is quite different to the idealist data wonderlands outlined by the experts! To put it bluntly, you can dive into data and drown pretty quickly.
A well-used data quote you’ll see at any tech conference is from Psychology and Behavioural Economics Professor Dan Ariely who famously said:
“Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it…”
Within the mind mapping sector, it’s fair to say that collective (or BIG) data is still lacking, and I don’t think any companies within the sector would be publicly claiming that they’re “doing it” at this stage. In general terms there is a distinct lack of overall ‘market insight’ around mind mapping, and we may therefore be missing a key insights to inform decision-making for individuals and organisations on both the supply and demand side of the equation.
The Biggerplate Annual Mind Map Survey & Report are the closest things to independent industry insights at present, but the report would certainly not constitute the volume of data that could justifiably be called ‘BIG’ by any stretch of the imagination, although it is certainly very rich!
What we need is BIGGER and better data in order to better understand the trends, preferences, and direction of the mind mapping sector. In an ideal world, this would come from multiple sources (including software vendors) to help build a coherent total picture. However, that may be a harder thing to pull together, so in the meantime, we’re looking into what we could do at Biggerplate to further develop the data story for the mind mapping sector…
As we continue working on our new website (due for launch in Q4 this year) we are increasingly excited about the data insights that the platform could provide. Obviously this is not data insights in a creepy “we know everything you have ever done on the internet” kind of way, but instead focused on building up a more complete understanding of how people are using mind maps, and building a strong evidence base to illustrate the uses and benefits of mind mapping to a wider audience.
The most logical starting point for us is of course, the map files in our mind map library. Obviously all mind maps on Biggerplate are public, meaning the data is already public, and we can therefore readily dive into the map contents to see what we can learn. So, what could we do, and what could we learn?
Let’s start simple: What if we took every mind map from Biggerplate.com, and analysed every single word, within every single mind map. We could then add up which words were used the most often within mind maps, and create a visual to represent this, like the one below from our Annual Report 2017, showing which words were used most often to describe the benefits of mind mapping…
However, while a visual showing word use from the whole map library may be interesting, will it tell us anything useful? The library contains a mix of Business, Education, and many other maps, and so the cumulative word use may actually be a bit mixed between the domains… so why not break it out further?
What if we could see the words most used in Business mind maps, and separately see the words most used in the Education maps that have been shared? Then we start to get a little clearer on the topics and information that people are actually mind mapping within each of these domains.
Or perhaps, going a level deeper, we could see the words used most often within mind maps from certain specific categories, like Project Management, or Productivity… and now this starts to get very interesting. This level of detail could tell us topics to explore in training courses, keywords to target in advertising campaigns, or long tail topics that may be currently underserved by the map content currently available.
But are all words in a mind map created equal? Well, the answer is no. The very structure of a mind map actually gives you further data signals to consider, based on how far out from the central topic a particular word is. For example, if one of your main branch headings is REQUIREMENTS, then that surely indicates that this word has more importance (or weight) in your mind map than if the same word was 4 or 5 levels further out in the mind map.
So, what if we consider not only the total number of times that a particular word is used in a certain selection of mind maps, but also look at the cumulative weight that the word is being given in maps? Well, it’s complex, but surely going to yield something pretty insightful!
Beyond that, you could compare by topics, and by software. For example, do MindMeister users map the same productivity topics and keywords as iMindMap users? Do MindManager users give the same weighting to the same words as XMind users when mapping out projects? In theory, the data would tell us, or at least give us some helpful hints!
For Biggerplate users, the more immediate benefit to this use of data would be improving the relevance of search results that the website is able to serve up. At present, the search engine on Biggerplate relies on the map titles and tags provided by members, which are very hit and miss (hint: Please title and tag your maps properly… it makes everyone’s life easier!) What if we could find you better search results from our mind map library by analysing every word within each individual mind map file (and ranking their importance based on the branch hierarchy) to show you relevant mind maps even if the author has created a title and description that is… shall we say… less helpful! That’s a big potential gain for members.
Further to that, what if we could use this same data to show you which members were publishing the most relevant content for you, based on the word usage and word hierarchy within their mind maps? This would help you find mind map contributors who are most relevant to your areas of interest. All of this, simply by digging into the words people are using in their mind maps!
Ok, so maybe “simply” is not quite correct, but as our team designs and builds the new Biggerplate website, we want to put data at the core of the user experience, and enable members to benefit from the powerful data architecture and infrastructure that can now be leveraged. This will not only help to improve the experience on Biggerplate, but could also help to build more of the independent industry insight that can support our collective goals, whether you’re a mind map user, software developer or, well, us!