Great post Peter. The sequence in which Junhong Yao developed the business model is as impressive as the business model itself. It seems to me that identifying the social networking nature of the offline dealers to share inventory and better serve the varying customer needs was a key entry point to gain 60% penetration. They were able to get a lot of cost out of the system because they can leverage the data on consumer preferences to guide inventory purchases and shorten the time cars are kept as inventory. I wonder how they are dealing with the quality issues and whether scams are less likely to happen on cars purchased through Souche. Are they demanding guarantees from the dealers to ensure quality?
Thanks for the post M! It’s interesting to see how technology is disrupting the banking industry. I agree that given the cannibalization risk to existing business lines and the high costs required to change their legacy systems, banks should focus on expanding their services to better serve their client’s needs while outsourcing R&D by investing in fintech startups.
However, banks don’t seem to be pursuing this strategy. The following report from CBinsights shows that Corporate VC investments as a percentage of overall fintech investments have remained flat at approximately 25% since early 2016.
Great post Austin! To your point about the implementation challenge under the franchise model, I agree that initially McD might have to fund the required Capex but as they validate that the data-deiven approach yields better performance franchisees will be more open to adopt the model and fund the additional expenses. Ideally, McDonalds should have objective metrics such as sales per sq foot and use those them as a selling point.
Interesting post Nandx. I wonder if Nielsen is looking into artificial intelligence applications for satellites to better assess demand in real-time. For instance, data analytics companies are using satellite surveillance of parking lots to determine current and future demand based on the number of cars in the parking lots of malls and supermarkets.
Great read Ting. I agree with you in that one of the main challenges will be getting the right level of accuracy in the system. If ZSL requires the system to simply identify species then I can see how this approach would work. However, if ZSL needs to be able to identify individual animals and not just species (i.e. endangered species with very low population numbers) I don’t see how this approach would work. For the latter case I think that tagging will still be a better solution.
Great post KZ! I agree with you that one of the biggest challenges they will face as they acquire demanding clients is translation quality. It seems that the users that get the most value out of the product are those with limited mastery of the language. Those users that learn the language leave the platform or switch to more sophisticated learning methods such as hiring a tutor. To improve translation quality they would either need to retain advanced users, increase the number of translation attempts per word (play the numbers game) or invest in the software to improve its accuracy.
Great post Eliza! The value of having a crowd-sourced encyclopedia is undeniable but I wonder how their non-profit entity status and being over-funded affects their drive to innovate. I would think that the use of machine-learning technologies could help the platform scale and cross-check articles at a much lower cost than $42 million per year. I wonder if they are already doing this.
Taka, I had the same thought as I was reading the post. I would think that there is a high overlap in type of concerns and documents. Implementing things like tutorial videos or chatbots for the most frequent topics would help the platform scale. However, given that there seems to be an oversupply of volunteers I don’t think that this will be an issue in the short-term.
Great post Taka! Just like Hans I was also thinking about the issue of limited complementarity between the payments and the ride-hailing products as I read your post. It seems that Grab intends to leverage its already large user base to accelerate the adoption of the payment product. However, there might be some complementarity if they intend to use the same e-wallet for both products because it eliminates the need to build trust with consumers who are already using the ride-hailing app.
Additionally, I wonder how the payments space will be affected by the blockchain. The adoption of cryptocurrencies by the unbanked in emerging economies is on the rise and cryptos are being used for a wide variety of financial transactions. For instance, Bitso is a cryptocurrency exchange platform based in Mexico and almost 30% of users are unbanked using cash to open accounts.
Great Post! I agree that price transparency across madis should make the value chain more efficient and farmers should improve their bargaining position. I think that using algorythms that are fed by supply and demand data to help farmers forecast what crops to grow would result in a lot of value transfered to them. I assume that farmers bear all the spoilage costs.
Great Post! Local and global network effects seem to play a key role here. Local from the driver’s perspective because you care about having charging stations along your most frequent routes and not necessarily three towns away.
Global from the perspective of the EV OEM who has to make their cars compatible with different charging systems. This will be particularly true for fleet owners.
Awesome post Brittany! While it may be too early to call roboadvisors “winners” in the wealth management space (particularly considering the high customer acquisition costs) the trends mentioned in your post make a strong argument for roboadvisors going forward. The partnership approach with large financial institutions makes a lot of sense given that incumbents have large customer bases as well as brand recognition, thereby increasing the platform adoption rate while keeping acquisition costs low. For traditional banks, roboadvisors act as new net-positive acquisition funnel because they are targeting younger less wealthy individuals which probably didn’t have access to wealth management services. As these individuals increase their wealth they can be converted into clients of traditional wealth management services at higher margins.
Thanks for the post Hans! This would be a really cool problem to solve. I think that we shouldn’t just think about this issue from a cost perspective but also from a productivity standpoint. For instance, if the Census Bureau was able to provide accurate real-time data, businesses across all industries would be able to forecast demand better and entire supply chains would become more efficient. I think the U.S. Census Bureau should think of themselves as a key enabler of economic progress via the provision of high quality information to society.
Awesome post! I think that the applications for real-time, high quality imaging combined with AI are infinite and that we are barely starting to understand the full potential of the technology. However, I wonder about the sustainability of launching thousands of small low-cost satellites into orbit. These satellites eventually will become “space junk” orbiting earth at extremely high speeds and possibly complicate the launch of space craft or next generation satellites for space exploration.