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Thanks for a really interesting read! I’m curious how far this platform could extend. Would their service be relevant for other products where information asymmetries exist and users are wary of perverse incentives (e.g., car markets)? I’m also curious how much the ads bias the user experience. Not carrying inventory or pushing their own products is a critical first step in building the trust with consumers, but selling data on the back end or advertising specific retailers may erode some of the credibility if the ads are not very clearly marked as such — almost an implied endorsement.

I’m also curious if there’s a point at which the AI algorithms could leverage computer vision of images of secondhand jewelry and give unbiased appraisals or estimated values based on comps in the database. That seems like it would enhance the value of the marketplace, capture value from sellers with some fixed listing fee, and still maintain the aligned incentives brand image. This may also help expand the range of buyers to include higher end purchases from remote locations in the marketplace.

Thanks for a great article! Really interesting company. I wonder what the limits are for its expansion and applications of Duolingo’s learning algorithms. Could they be used to teach people how to play instruments? Math and coding lessons? Safety trainings for employees in dangerous workplaces? Plays for sports teams? It seems to me that a lot of the techniques leveraged by Duolingo apply to other subjects as well. A partnership with educational platforms could go a long way — especially with remote and distance learning becoming increasingly relevant.

Additionally, the chatbots may be useful in supporting customers of other businesses across languages and may offer an alternative revenue stream for the company. I also wonder if there is a speech to text learning that can be incorporated into the platform in a similar way. It will be interesting to see how competitors like Rosetta Stone respond to Duolingo’s increased market penetration.

Thanks for a great article! I’m also in the market for a new apartment after graduation and have spent a lot of time on Zillow recently. One of the key issues I’m curious how Zillow will tackle is the unknowns in a house that can’t be factored into the algorithm. Did the previous owner remove the appliances? DIY repairs and renovations that may not be captured in housing reports? Is there damage to the foundation / structure? Nuances in HOA agreements that might increase liability on the property? Zoning risks limiting rentals / people allowed in the residence? Tax exemptions relevant to owners not available to rental operators / businesses? Foreclosed properties usually have very little information available, but may be underpriced and disproportionately represented in the algorithm. This requires significant legal and in-person checking which significantly changes the margin and cost-structure for Zillow, potentially shifting its overall core offering.

Also, it seems that much of the input into the algorithm can’t capture the nuances of home buying and that these models are largely based on retrospective information and less forward-looking, predictive data. Furthermore, I can imagine a world where sellers game the system by artificially boosting listing prices, test various offers, etc. Will Zillow be able to filter these corrupted inputs? Even small percent error on housing can add up on thin margins. They will want to be careful to avoid a WeWork scenario.

Overall, an exciting concept, with high risk and high reward!

It is interesting to see AI enter a space like coffee, and I wonder what the implications are for other quick-serve format businesses like fast food. Will McDonald’s, Yum, and others apply similar learnings to their operations? Additionally, does this leave an open space for robotic alignment with Starbucks where the IoT is taken to the next level and Starbucks machines are placed throughout areas where the service / in-person interaction is less relevant? Does this dilute the Starbucks brand? Some start-up coffee companies are experimenting with models that leverage AI to determine optimal store / station placements, and leaner mechanisms can drive a profitability advantage if Starbucks does not address this gap. In the meantime, it will also be interesting to see how AI-training and implementation impact the talent redemption efforts as baristas may require training, and high turnover could break the flywheel. May require some broader cultural shifts at Starbucks to optimize effectiveness.

Thanks for a great article! I wonder what the distribution of prices are on the platform for various artworks sold remotely. I imagine that high-end art would likely be purchased in-person or as an investment and evaluated by art professionals on the buy side — going through traditional art houses or auction processes. For lower-end art, Etsy seems to have a fairly robust offering as well, which further removes the high-volume, low value works from contention. Saatchi seems caught in the middle, so the value-add services specific to its art offerings that others cannot replicate at the same scale for the same low price seem critical to its growth.

Furthermore, you mention the risk of disintermediation. It seems that the calculus of cost of artist acquisition vs take on each sale is critical here as a buyer may quickly connect directly with the artist and only make one or two purchases through the platform. This has significant implications for fee structures and business model design for the platform to ensure long-term sustainability.

Thanks for the article! One issue with exercise equipment is always “is this a fad?” Having a subscription insulates Peloton from a lot of these challenges as leaderboards lock in users and spur engagement, but in an economic downturn when users are cutting their subscriptions, is the sunk cost of the bike enough to keep them engaged and paying monthly subscription costs?

Similarly, this works in cities where outdoor access is less readily available, but I wonder how long Barry’s and SoulCycle will lag before their offerings are more robust, tied to brick and mortar offerings, or other products are introduced. You mention that multi-homing would be limited as the bikes are so expensive, but if the true value is in the subscription, it seems that content can be easily displaced for cheaper alternatives (imagine Netflix entering the workout video space).

Will Peloton be able to continue innovating with new machines and new classes or will media players be a bigger threat than traditional competitors? Will the fad die out? Will an economic downturn be enough to halt new sales? Can growth expand to rural areas beyond the current user base, or is growth capped?

Thanks for an interesting article! One interesting piece here is the disintermediation potential which would cut Patreon out of the mix. I’ve seen several YouTube channels which publish their content, get a cut of YouTube ad revenue, and can scale their fanbase very rapidly on that channel. With increasing ease of building your own website, what stops a YouTuber from directing fans to their own site and simply setting up a paywall to access exclusive content there? Or what stops YouTube from displacing Patreon and charging lower fees across more artists since the content is largely hosted on the platform already? Seems like Patreon may be facing significant challenges as technology becomes increasingly accessible. One potential solution is connecting fans of one artist / creator to similar artists as a referral platform, though I imagine the margins would be smaller and again, YouTube may be able to displace this service with at-scale machine learning.

Really interesting article! Thanks for sharing! One piece of this that jumps out to me is the focus on marketing and customer engagement. I wonder, in a world where other apparel retailers offer similar omni experiences, does Burberry successfully differentiate itself through these digital initiatives, or are the digital efforts the new table stakes for competing in the space?

Additionally, where can Burberry go from here? Players like Amazon are entering full force in the space and developing their own private labels using many of the techniques described here with the backing of a strong tech foundation.

Will the brand image be able to prevail? How will the brick-and-mortar footprint adapt to adjust to the dynamic retail marketplace as the industry shifts to embrace digital over time? As a premium brand, how will Burberry balance the old-school, traditional history with the need to attract younger customer segments used to digital-first strategies?

Clearly, the company has navigated the transition well and is implementing unique and creative digital solutions. It will be interesting to see how these offerings continue to evolve as competitors catch up.

Great article! Thanks for sharing! I wonder how Coursera and similar platforms will change the nature of higher education. I know institutions such as MIT are already posting all lectures for some courses on public forums for individuals to have greater access to quality education.

While it may be difficult to have MOOCs fully replace universities on their own, there are significant implications for public education, the rise of flipped classrooms, and the need to fundamentally rethink what it means to have higher education. Will employers begin recruiting individuals with certifications that never attended class in a physical university? Will these certificates carry the same weight as a diploma?

Furthermore, this could have major implications for the issue of student debt in America. With so many young people accruing loans which take decades to pay off for their higher education, something like Coursera’s offering becomes increasingly attractive.

Of course, this also leads to tradeoffs related to the university experience. Are there ways to mirror or replicate the social experience of college which enables personal growth? Is there a difference between liberal arts and STEM degrees on these platforms? How does performance change the nature of recruiting for employers? These questions highlight the disruptive nature of Coursera’s offering which may change education worldwide in the years to come.

Thanks for a great article! Another wrinkle to consider here is how the privacy rights extend across geographies and regulatory environments. I imagine that each country of operation has varying levels of privacy requirements and restrictions. Compliance can be costly for a company with already high variable costs such as 23andMe.

Furthermore, the healthcare and genetic information nature of this offering subjects it to even more restrictive policies. While much of the value can come from unlocking the genetic information and data users provide, there may be direct tradeoffs and competing incentives for customer satisfaction with privacy standards, political regulation of similar products and companies, and VC or other investor incentives.

Working in the healthcare space, I know how cumbersome it can be to overcome legal regulations intended to protect consumers. Together, legal challenges, lawsuits, compliance monitoring, and even lobbying may increase the company’s risk profile significantly in the years to come, independent of customers’ reactions to privacy issues.