Steph Denoyer's Profile
This is a truly inspiring application of AI — thank you for sharing, Aditya! This reminds me somewhat of the mission Ovia Health (original an iPhone app) had at the outset, which was to help women through the fertility journey and identify “high-risk” cases to suggest medical (or other) intervention, thereby improving health outcomes for mother and baby. However, I can’t imagine the challenges ARMMAN faced in implementing a similar mission in populations where access to internet/apps — and the education / literacy required to use them — is not always reliable or consistent. It’s cool to see how a seemingly un-solvable problem (re-engaging the women who have dropped out, prioritizing those who are high risk, with limited human bandwidth) can be unlocked using AI and provide incredible insights to the team, and health outcomes for the women.
Very interesting post, Carlos — thanks for sharing! A few thoughts:
– When I wrote about Grammarly in my first blog post for this class, I pondered whether Grammarly is truly a whole product or just a feature. Copy.ai’s application of NLP/GPT-3 takes what Grammarly is doing a step further in a way that provides a ton of immediately-visible value for users, which is very impressive
– However, the ethical concerns are real, as having a paid service could provide some individuals (students, applicants…) an advantage in creating content more efficiently and exclude those who do not have the access/resources to pay
– In terms of our class discussion today, I think Copy.ai is creating system-wide change, as content-focused roles/teams (e.g., content marketers, ghost writers, etc.) no longer have to be centered around the drafting process and can re-organize their time towards cutting-edge research or other creative (vs. mechanical) exercises
Isabella, really interesting post! Though I had heard of Rappi before, I was surprised when I visited Argentina last year to see just how ubiquitous the platform is — nearly every food establishment had the Rappi logo posted outside, and there were delivery people everywhere. It’s interesting to me how regionalized food delivery startups are (i.e., US = DoorDash, Europe = Deliveroo, LATAM = Rappi… etc.), given that they all seem to replicate a similar business model. However it was interesting to read in your post that Rappi has differentiated itself immensely on the level of talent it brought and graduated from its organization. This is a cool metric to look at and think about when building disruptive platforms.
This is really interesting, Kaitlyn, and I want to use this service next time I travel abroad! I know anecdotally that consumers (especially millennials and Gen Z) are shifting their spending more towards experiences, so it seems like a worthy business opportunity. Piggy-backing on what Karthik mentioned, I think they are probably feeling significant pressure from competitors like Airbnb who offer similar experiences. However, I am optimistic that TBL is able to differentiate on (a) quality, (b) variety, and (c) specificity/expertise.
One way that they could continue to differentiate and generate an even more sticky customer base would be to create a “traveler portal” where individuals can see their past experiences, record memories, and share their travel log with others. This social aspect is something that Airbnb lacks, but TBL could easily add. They could even position themselves for an Airbnb acquisition if it is so desired by the founders, if they are able to prove true value beyond simply the first iteration of their marketplace.
Great post, Amy, and you inspired me to write my blog post about a similar fitness marketplace (Gympass, like Classpass but for the B2B market). I find it interesting that there is such a push around bundling disparate fitness and wellness experiences, given consumers already do this in their everyday lives (e.g., SoulCycle class on Sunday, Barry’s on Wednesday, yoga and skincare on Thursday…). But, this becomes really hard to replicate unless EVERYONE participates from a partner perspective, as consumers have high discretion on which brands they want to use and when. So, I think you hit the nail on the head in mentioning that their success relies on signing up more high-quality partners.
I, for one, used ClassPass in SF to go to the Crunch gym without having to pay a monthly membership fee since I was only there for a short time. However, when I moved to LA, I churned from the platform due to extreme scarcity of gyms or classes I was interested in. So, I think density of studios/services offered is also important.
Yannik — thanks for the post, it was both hilariously written AND interesting. It was thought-provoking to read about how Uber is able to adjust its services in real-time, versus using big data as an input to make its product better in the long-term. Even though Uber and Lyft have achieved mass scale, I do wonder if they will continue to be competitive with rising prices and the increased ubiquity of big data as a business asset.
Interesting post — thanks for sharing, Patric. This reminds me of a case we read in Launching Tech Ventures (LTV) class about a similar company, Ovia Health. This company focuses more on family planning/maternal health, but also covers the whole female health journey. It was interesting that Flo also took the approach of pursuing the B2B channel through working with employers/corporations to offer their services as a benefit, rather than insurance companies. I believe the mission alignment between FemTechemployers (vs. FemTechinsurers) makes the most sense, even though the data asset would be incredibly valuable to insurers and the sales process would potentially be less cumbersome. I hope this means Flo & Ovia continue to prioritize women’s actual health outcomes vs only doing what insurance companies perceive to reduce their costs.
Really interesting post, Isha! Your submission made me reflect on parallels in other industries, where deeply-entrenched traditions or ways of working (often based on bias) can quickly become dismantled through the use of big data. I wonder if the fashion, art or other creative industries have experienced (or will experience) something similar? Is this unique to digitally-consumed products, or can we use data similarly for physical ones?