Probably Alex's Profile

So this article is very interesting as I am an avid purchaser of Glossier products, but had no idea that they use crowdsourcing. To me, their success is more about being a very cool brand that understood the instragrammability of marketing/packaging, and who also embraced diversity in a way that feels very authentic. I think their best bet to continuing their success would be to crowdsource from people who aren’t Glossier users, to gain an understanding of what they aren’t currently offering that customers want from them and convert them to brand loyalists.

I think your question hit the nail on the head – how does the company protect itself from competitors when it is using an open innovation format? I think it is good that the internal team uses these ideas as a source of inspiration rather than taking them literally. It allows them to put their own spin on the ideas, while also showing the customers that they are listening to them and that their ideas are valued. I would take it one step further and also crowdsource from the sales reps – they should have some ideas of what the company is missing out on since they are working directly with customers.

This was a really interesting read – thank you! My question for Organovo and their future is really regarding the presence of alternatives. The current organ transplant industry is unsustainable, with demand far out-numbering supply, and I think it’s fantastic that companies are experimenting with different ways to solve this problem. Due to the ethics question that you bring up at the end, and the amount of time it will take for this product to have the possibility of hitting the market, I would be concerned that there will be other medical breakthroughs that will render Organovo obsolete before they are able to reach the market. I am not aware of what those potential competitors could be, but to me that is what potential investors would be weighing when looking at investing in the company.

This article was super interesting! I think one of the pain points for customers is finding what they like and knowing which items to choose out of all options, so Choosy learning what a customer likes and then giving them that is an interesting proposition. However, it seems like the recommendations are relevant at a user-specific level, which makes me hesitant about whether they can turn this concept into a store. Just-in-time production for Zara still means that clothes are taking weeks to get to the store, so if Choosy is creating recommendations based on one person’s browsing, and then extrapolating those preferences to large orders of product, I am not sure that the recommendations will be as spot-on as the direct-to-consumer model. In addition, an in-store experience requires cohesion of message, as customers don’t want to walk in to a store filled with a chaos of color, print, and garment type. Because of these things, I think Choosy’s business model would have to be drastically altered to adapt to a store format, and which could result in the loss of their value proposition.

This article brought to my attention data capabilities regarding investing that I didn’t know existed, so thank you. The biggest challenge that I see with shifting from manual to algorithmic investing is that investors want to be ahead of the curve, not just getting the same information that all others are getting. Once there is enough data about a company for Helios to form an opinion, will it already be too late? To answer your second question, the networking aspect of investing cannot be replicated, and serves the purpose of assuring an investor of their belief in the leadership team. Because the success of small companies is so dependent on their leadership, I think CircleUp would need to be a tool for investors to use, rather than a replacement for the current process.

This was an interesting read! I have heard about exceptional grocery business in the past (Wegmans, Whole Foods), but as you point out in the article, never thought about Kroger as an innovator. I think the major challenge in the grocery business is that you are essentially selling the same thing as your competitors, with a fairly predictable amount of demand across the country as a whole (ie without a population change, food sales can’t spontaneously increase or decrease). With a fairly standard product, grocery businesses have to set themselves apart by going after what the customer wants – price, experience, convenience being a few ways to differentiate. Kroger investing in convenience in an exciting, innovative way, is how they will attract talent, similar to how Wegmans has attracted talent by creating the best customer experience.

This was an interesting look at what I believe to be the best application of machine learning for retail – using for the purpose of customer conversion and retention. Regarding the question of privacy, it seems like consumers at this point are used to semi-invasive collection of data, and while they may not love it, they are used to it and don’t fight against it. For example, people have various examples of times that they received targeted advertisements shortly after having a conversation about a brand, which indicates that their phone listened to the conversation. People share plenty of experiences like this, but don’t seem to care about stopping it.
Regarding in-store technology, I think Farfetch’s approach in creating a store of the future is great, but its success seems contingent on having a consumer who is already quite involved in Farfetch’s platform, and also having a larger number of customers so that you can aggregate the data and actually learn something that can turn into a prediction. With just one store and 1 million users, and with a high price point indicating that purchase frequency may not be very high, I am not sure that Farfetch can gather enough data to get a great return on their investment.

This article was an interesting take on the use of data in retail, since it is looking at the application of predictive technology in a section of the retail industry that is unpredictable. Unfortunately, I have to disagree that there is any possibility that technology will be able to predict trends and eliminate the creative process. The difference between Gucci and retailers who are currently using machine learning is that Gucci is setting trends, whereas other companies are learning to get as good at possible at knowing when customers will adopt trends. Amazon, Gap, and Stitch Fix’s success in the apparel industry is contingent on luxury brands like Gucci creating new trends that drive customers to buy more, even when their closets are full. To consider whether machine learning could replace the creative process in retail, I look other artistic industries (art, food, entertainment) and ask if could have their creative process replaced solely by data. Will artists, chefs, and movie producers become irrelevant in the future? I don’t think so.

It is interesting that IKEA is experimenting with 3D printing while it is still in a fairly non-commercial stage as a technology. On one hand, IKEA is known for being innovative, but on the other hand, I think of IKEA as a company whose success has been driven by their ability to mass produce in a very affordable way, so introducing a technology focuses on customization is a step outside of their wheelhouse. Because 3D printing is still a fairly young technology, and has high costs that go along with that, I think IKEA should continue to outsource this work to existing 3D printing companies. It seems that they are trying out different approaches to 3D printing (customization, intricate designs, prototyping), and by outsourcing they can continue to experiment with ways to implement without committing to building capabilities catered to one approach. Regarding whether they should charge more – to me it depends on whether they want to make this a core part of their product line and sell high volumes, or use 3D printing as a way to expand their price range upwards with a higher-end line of customized, highly designed items. However they intend to sell this in the long-term, they should focus on building credibility at that price.