Great post! It is clear that this VR use case makes a lot of sense for Lowe’s business and certainly will help drive traffic to stores, yet it will be interesting to know how consumers desire to adopt it – do they prefer to sit at home and experience it and make potential purchases all online, or it is equally important for them to touch and feel the stuff Lowe’s are selling. If the former is true, or partially true, then what Lowe’s is doing is probably not enough. I guess in addition to the challenges you have already mentioned, a overarching question that Lowe’s needs to answer is how omni channel strategy should play out in its specific case.
Nice post Yuval. Vertebrae’s business model is very interesting, as it chose a very specific area to play in VR, a still nascent sector, so early on. I believe its success is highly dependent on the adoption of VR tech as a whole rather than VR ad itself. In this sense, I totally agree with your on your concern of its current addressable market size. Because all advertisers that ever used or want to adopt VR tactics are expecting the format of VR itself is viral enough to attract their consumers’ attention rather than the actual contents. And it will probably take a long time for the VR adoption to be high enough for the advertising industry to be all in.
Nice post Bipul! It’s interesting to know that Unity as a startup has experimented many different value capture models. I wonder which one among them is the major source of revenue for Unity, and if there is any internal tension in business development for different models? Also, it would be interesting to know how Unity’s value creation and capture model differs from its competitor so that it became the share leader, or maybe in this tech sphere really what matters is the quality of platform?
Good questions Bipul.
To your the first question, I do think Legendary needs to make adjustments on both the source of data they collect and the algorithm they developed in order to make this work in different international markets. The data part is easy to understand. For the algorithm part, I guess the good news is that they can leverage machine learning to self adjust based on previous results. And Marolda mentioned that because of the high adaptation rate of advance online ticket purchasing among Chinese consumers, their job, in some sense, is even easier in the China market.
The second question, I guess the answer is that they not only try to leverage historical ticket purchasing data, but also collect more up-to-date data from multiple sources like social media. But you are right, descriptive data (in this case ticket purchasing/movie watching history) should be more relevant, while referential data is an alternative. We can only count on the rich sources of referential data, and according algorithm, to improve its predictive power.
Hope I answered your questions.
Great post! I especially like the points you made in the last sector of this article. I wonder if the existing consumers can get updated reports as the database grows. Apparently the bigger this database is, the more accurate 23andMe’s report will be (presumably). And to some extend the early consumers paid to benefit later comers.
Good question, LiDe. My guesstimate is that though a lot institutional investors showed interest in participating they are not committed but more like ‘let’s see how it plays out’, because equity crowdfunding is even more nascent in China. I learned that when the platform just launched, a lot VCs were very enthusiastic because they wanted to stay relevant if the VC industry would be disrupted by the internet, yet as time goes above mentioned challenges coming out they realized that they were in good positions and could provide some unique value, the willingness to participate cooled down more or less. So to some extent, the platform is also facing VC reverse selection problem, I guess.
Interesting post! I did a bit research when I was interning at JD in the past summer about U.S. equity crowdfunding market, and Angellist and Wefunder stood out at that time as leading players, while Indigogo was more of a benchmark of Kickstarter for financing crowdsourcing, or a new product/idea marketing platform. I wonder if you have any idea regarding the competitive dynamic between Angellist and Indigogo, and why Kickstarter decided to focus on its original territory.
Thanks for the post Anish! There is a copycat of Quora in China (of course), Zhihu (meaning ‘you know?’ in ancient Chinese), and I like it a lot! One major challenge Zhihu right now facing is that it is still a niche market player and even die-heart fan like myself doubt its ability to scale up. The dilemma is that because its user community is highly self-selected and in small size, the overall quality of contents on the platform is extremely high and thus users are very loyal; however, if it manages to attract more mainstream users, which is necessary for meaningful monetization, the core user might be chased out from the platform due to content quality decrease and the lack of sense of exclusiveness. I wonder if Quora is facing the same issue.
Nice post! This article echoes to the discussion we had in class about why so many social media platforms have emerged while Facebook exists. I guess the question posted to Etsy is on expansion, is the ‘niche’ market big enough for its (or its investor’s) appetite? If it has to head-to-head compete with Amazon in some other categories, what would be smart choices that it can replicate its success in the handmade sector?
Nice post Libby. I especially like that True & Co designed the process for customers to try out different products and then feedback size information to the firm’s database – a win-win move! I guess another future use case/ expansion of True & Co’s data and analytics strategy could be tailor making bras and other apparel pieces for customers who are willing to pay more.
Interesting post, thanks! I think what makes Netflix stand out among all the Hollywood players who claim using big data is that it integrated the approach in content production. I wonder if you know any ‘inside information’ regarding the detailed mechanism. I guess to help pick up leading actor is a low hanging fruit, would be great to hear more about other specific samples for big data tactic application in production.
Nice post Amy. I’m very much interested in what the core alternative credit assessment variables are, and how ZestFinance team interpretate the correlations between them and loan performance outcomes. Also, I wonder if more data collected in the China market will help ZestFinance to predict risks in the US market, i.e. how transferable data and according algorithm is across markets.
Very interesting post! Thanks Yezi. One question I’m interested is that if this costly data collection task can be done in a crowd sourcing way? Like you mentioned that taxi and rideshare apps can provide data regarding how citizens travel, probably insurance companies can provide more information regarding car accident in Chicago to help improve city planning, for instance? It’s very clear how value should be created and captured in this AoT project, yet crowd sourcing in data collection might be helpful to improve ROI? Of course there will be other challenges associated, to name a few, collaboration between public and private sectors, privacy, and data compatibility. But it will be interesting to know if Chicago or any other city thought about this approach as an alternative.
Thanks for the post! Last week I learned about L&F in two other classes, Strategic IQ and Business Analysis and Valuation, as well. Your story definitely provided another piece to form a more complete story about this company. I believe the biggest challenge L&F faced – the reduction in information asymmetry – is essentially the challenge for a lot traditional 2C businesses when new online players join the competition. L&F actually tried to vertically integrate the value chain, such as providing logistic services, and acquiring manufactures with brand names that end consumers would recognize. Yet it seems that their efforts didn’t pay out. I guess this also posts a question for other traditional/offline businesses that what is the way out to survive and transform in today’s digital world.
Nice post Kathy. A few months ago Wechat went beyond “official account” and launched a Mini Program initiative, which essentially is building an app store on this platform and, arguably, an operation system. My post is actually about its new initiative: https://d3.harvard.edu/platform-digit/submission/wechat-mini-program-one-step-further-evolving-into-a-one-stop-solution-platform-from-a-messaging-product/?notice=success¬ice_message=Your%20submission%20has%20been%20published%20successfully.
What I found interesting is the question you raised about Wechat’s oversea expansion. I kept thinking why in the states the messaging and social media markets are so fragmented, why there is no such a player like Wechat being a one-stop shop, and why it is difficult for Wechat to take off in Southeast Asia market. Your thoughts are welcome:)
Nice post, thank you for sharing. Value for money is for sure an important, perhaps the most critical, consideration for mass market to adopt a new product. It’s not only a question for Nest, like you said, all smart home devices will need to answer the same question: how much do my target customers value the delta between their smart and stupid home brought by the device. In addition, we see different players are betting on different devices to function as a hub to connect the device system at home, and I don’t think thermostat is a good choice in that sense due to the fact that it is not a necessity and has a long replacement cycle.
Great post, thanks for sharing! I found the theater attendance graph particularly interesting, as it seems that actually more people went to movie theater after 2010 than before yet frequency dropped, assuming average ticket price held still, as per capita admissions decreased by a larger proportion than total admissions did. I wonder if this is also driven by movie theater’s strategy shift as you mentioned that AMC favored larger tent-pole movies. Another interesting question would be if the size of total entertainment industry (includes every choice you mentioned) actually grew while each type of player grabbed a smaller slice of pie. If yes, every player needs to think about adjusting its operation strategy then.
Great post! Such successful adaptations of digital marketing by a traditional offline retailer are indeed rare to find. Sephora does a great job in driving traffic and trial, guess the challenge lies in deal closing. It is simply too convenient for a customer to find the product she likes in Sephora and then buy it at which ever e-commerce website offering the best price. And online retailers become free riders that don’t need to bare the high brick and mortar, and technology cost. Thus the question goes back to how Sephora can close the deal in its own online and offline eco-system even if it may not be able to offer competitive prices, and if the target customer is willing to pay a premium for the experience she enjoys at Sephora.