PerfectLearn’s beta phase is coming to an end. It has been thoroughly tested (resulting in a substantial amount of bug fixes and several user-facing improvements) and I have a clear understanding of the path ahead of me in terms of the application’s future development. As planned, in April I will make PerfectLearn available to anyone who wants to use it.
Arriving at this stage of PerfectLearn’s development also means that I really need to start thinking about where I want to go from here.
Product development principles
- Don’t build technology for the sake of technology
- Solve for patterns, not for instances
- Always ask, “what is the goal?” and “what are you optimizing for?”
- Look for leverage, but always invest in your core
- Know your core
The above principles should be dear to any developer’s heart. Always, at least, try to keep them in the back of your mind when embarking on a new software-related project. With regards to PerfectLearn, although it is based on the topic maps paradigm1 —one of my favorite meta data models— I definitely did not build it just for the sake of using topic maps. A topic maps-based approach lends itself very well to providing structure, what is for all intents and purposes, unstructured data. In PerfectLearn’s case, the unstructured information is the personal knowledge of an individual.
In addition, topic maps is an enabling technology allowing for the relatively straightforward development of many downstream products. Besides, using topic maps as the core of your software allows you to solve a wide variety of (data-modeling) problems in a standardized way. The side-effect of having to develop a topic map engine for PerfectLearn is that once the engine has been built it becomes possible to solve for data-modeling patterns and not just specific instances of those patterns.
Finally, with regards to the above principles, from the point of view as a software architect and developer, my “core” is semantic technologies in general and the topic maps paradigm, in particular (with the risk of becoming a one-trick pony).
So, what is this all leading up to? Well, as I mentioned above, topic maps is an enabling technology. Topic maps really can be used as the foundation of many software solutions. In that respect, I have been exploring different areas where a topic map-based approach could contribute substantially to a product’s value proposition2 and I think I have identified several interesting options3. So, this is the point where I need to step back and truly consider how I want to proceed.
A fundamental and very powerful concept in microeconomics is opportunity cost. Opportunity cost basically equates to the value of the best alternative that you did not pursue when faced with several mutually exclusive alternatives given limited resources. In my case, the limited resource is time. That is, I can only focus (properly) on one thing at a time. And by doing so, I forgo the other options and will have to pay the accompanying opportunity cost. This means that I need to have some kind of method to determine which alternative really is the best one. So, the method I have devised to provide me with an initial approximation of business model attractiveness revolves around two main variables: potential payoff (a logarithmic scale from 1 to 5, from lowest potential payoff to highest potential payoff, respectively) and probability of success (between 0 and 1, impossibility and certainty, respectively).
Evaluation of business models
When applying the above-mentioned method to some of the (business model) opportunities I have identified for both PerfectLearn (the web application) and the set of technologies I have developed as part of the PerfectLearn offering, we get the following:
- The PerfectLearn web application with a freemium-based SaaS business model: taking into account the feedback from the individual beta users in combination with several companies expressing a desire to explore using PerfectLearn in different scenarios leads me to believe that PerfectLearn can be productized. The real challenge is the execution of an effective SaaS-oriented business model and the accompanying issue of customer churn. In that respect, I score this business model as follows: 0.30/3 probability of success and potential payoff, respectively. Like other SaaS offerings, this specific business model follows the High Consumer Intent for Commercial Transaction/Low Traffic pattern.
- The PerfectLearn online academy/digital content monetization business model: After having researched course design in combination with my own experiments with online teaching, I believe that PerfectLearn’s versatility makes it a viable tool for course instructors to use for planning, building, organizing, and presenting (online) courses in conjunction with the monetization of the course’s digital content in the form of curated topic maps, screen casts, and eBooks. The business model for the monetization of high-quality educational-related digital content is one that I believe that I understand well enough to have a real chance of success. In that respect, I score this business model as follows: 0.60/2 probability of success and potential payoff, respectively. This business model follows the same High Consumer Intent for Commercial Transaction/Low Traffic pattern as the SaaS model outlined above. Finally, an additional advantage of pursuing this business model is that it also provides me with a viable user on-boarding process for the PerfectLearn SaaS offering. That is, some of the pupils would convert to PerfectLearn users because of their exposure to PerfectLearn as a central part of the course offerings which implies that I should probably include the PerfectLearn SaaS offering as part of this business model as a value-added service.
- The PerfectLearn on-device topic map engine business model: As part of building PerfectLearn, I have also developed a native on-device topic map engine for Android (the iOS port is in a very early stage of development). Having an on-device topic map engine opens up numerous possibilities with regards to building compelling and feature-rich mobile apps that can function equally well in both online and offline modes without sacrificing any advanced capabilities4. In many developing countries, intermittent internet access allows people to download your app but not to actually interact with the app’s content and functionality in a consistent manner, resulting in a degraded user experience. Furthermore, when (open) WiFi access is not available, expensive mobile data plans make off-line content delivery platforms attractive. Taking the above into account, I have done extensive research of the mobile space and have concluded that there are several app categories that are perfect targets for topic map-based solutions. In comparison to the other alternatives that I’ve outlined above, this is the outlier business model. A freak. Also, let’s be honest. Any business model targeting the mobile space has to provide a very compelling value proposition in combination with an innovative bring-to-market approach. And, even so … the chance of success if small, to say the least. In that respect, I score this business model as follows: 0.15/5 probability of success and potential payoff, respectively. The reason why I have scored this business model with a relatively high probability of success (0.15) is that I believe that I have genuinely identified an app category that is ripe for (dare I say it, the most over-used word in startup marketing) disruption. Obviously, the potential payoff in the mobile app space is huge if you get it right. That’s why this business model, in comparison to the other two models, has been given the highest potential payoff score. Finally, this business model follows the High Consumer Intent for Commercial Transaction/High Traffic pattern.
It’s possible to develop a myriad of different business models for each of your software products and the above method is only one of many frameworks that you could use when evaluating the different (software) business models.
Software business models allow you to think about your software on a different level. But ultimately, bringing software to the market in a successful manner depends on numerous factors. You need to ensure that you consider all of these aspects in a structured way and then choose the business model that best addresses the challenges that you will face when developing and marketing your software.
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- My other favorite meta data model is The Universal Design Pattern.
- Using topic maps as the underlying data model for a product should be an implementation detail and completely transparent to the user. From a user’s point of view, the superior contextual experience that topic maps make possible should just work as if it were magic.
- No, I don’t think that this is an example of "a solution trying to find a problem". A topic map-based architecture can substantially improve the experience of many software products.
- Revenue forecasts for Augmented Reality (AR) could hit $120 billion by 2020 (VR forecasts at $30 billion). Imagine a hybrid cloud/on-device topic map engine as the Point-of-Interest (POI) database for AR mobile apps. I would be willing to bet the house on this one.