Great business idea and impressive growth! I think that the move to support community development through APIs is very smart. That is basically a first step to create a whole ecosystem around Patreon core product and business model. I agree that the best long-term strategy for Patreon is to go towards consolidation and improvement of content creation, distribution and delivery within the platform.
To answer your question, I definitely would expect to get some sense of content before committing. In this case free trials and previews certainly come in handy. I perceive subscription-based services as not being cost effective. There are so many times when you become locked down in a subscription while not actually having time or/and desire to use the content. I generally prefer on-demand one-off targeted purchases of the content that I’ve tried and liked.
I thought that crowdsourcing ideas for expanding the product portfolio is pretty smart. In a matter of fact it fulfills two tasks – idea generation and market research. You can consider a product recommended by and voted for by a huge number of people to automatically appeal to that group of people and convert them into actual consumers. The question here is would people put their money where their word is. People might find an idea interesting and vote for it, despite being reluctant to consume that actual product in case it materializes. Another risk would be that a crowdsourced product might become a victim of a hype wave. Consumers might lose interest quickly and in this case all the funds spent on launching a product to the market would become a loss. I think that the most effective approach would be to use some combination of crowdsourcing and traditional research and development to maximize the potential for market traction and financial success of a new product.
I was pleasantly surprised that BMW has already incorporated additive manufacturing into production process. I was under the impression that 3D printing technology is currently at an experimentation state rather than ready for high-scale production application. I also liked the fact that one of the two current production applications of 3D printing is BMW i8 – the most innovative and cutting-edge models in BMW’s lineup.
The idea about using 3D printers in dealerships to print a needed part in a just-in-time fashion rather than holding an inventory is appealing. However, I would like to do a deeper cost analysis. It’s not immediately obvious that deploying and maintaining complex industrial-grade 3D printers as well as keeping highly-qualified staff in dealerships would actually be cheaper than just keeping an inventory of parts.
I also agree with the intellectual property concerns. Having people downloading and printing parts without paying a cent to BMW would be a nightmare for the company. However, I think there are ways to address that. BMW could use some type of electronic chip labeling and tracking the parts, possibly based on blockchain technology.
It was very interesting to learn about 3D printing in food industry. That is one of the applications of 3D printing that I’ve never thought of. I was also impressed with 38,5% CAGR. A few thoughts on possible applications and areas to improve. First area that Hershey should look into, in my opinion, is printing time. Right now the technology is great as a proof of concept, however it’s hard to imagine a real-world production application with such a long production time. As far as market positioning goes, it’s currently hard for me to imagine how it could be marketed to a retail customer. However, where I see it being in demand, are smaller artisan bakeries and chocolateries. Those businesses typically create luxury chocolate products, selling them at a high margin. The ability to create complex 3D edible shapes will allow them to attract customer’s interest and will generally be a solid value add.
As a consumer, I can attest that decision fatigue is very real. With abundance of goods and services in any given category, even the most basic task such as shopping for let’s say sour cream becomes exhausting, not to mention vacation planning which is rather expensive and significant for majority of people. Any technological advancement that would help to optimize that decision process would be a huge hit. However, it’s important to note that decision fatigue is driven for high extent by fear of making a sub-optimal decision that will result in attaining lower value. Recommendation engines were among the first real-world applications of machine learning, dating back to when Amazon was shaping its first online bookstore platform. The question is – how comfortable is the customer with actually trusting synthesized recommendations? Would there be a concern that recommendation engine results are skewed, either intentionally to promote a certain product, or unintentionally due to inefficiencies in training data. I think that Tripadvisor should look for ways to organically embed the results of machine learning algorithm outputs into different aspects of user experience.
It was really interesting to read about the way BHGE structures its machine learning initiative. Having access to new and unconventional data sources like drones and IoT devices would definitely provide competitive advantage. One thing I would be interested to learn more in BHGE case is its market strategy for machine learning products. What kind of value proposition are they going to come up with, which customers to sell to, and how are they planning to compete in already oversaturated machine learning and AI market?