This is so interesting! I wonder what the reaction from partners or project leaders was as I can imagine that staffing can be a process driven also by qualitative elements, such as “I really enjoy working with x”, “I am already familiar with x style of working and works for me”, “I need exposure to y to turn him into a supporter for my promotion”, etc. Could you help me with a bit of color on this?
Such an interesting company and solution, thank you for bringing it up. You do say in the article “Palantir recognizes these problems and has rejected several prospects such as the Saudi or Chinese government out of concerns about the potential misuse of their technology.” – I wonder what are your thoughts on a non-government person / commercial company /CEO to make a decision of who is the bad guy and who is the good guy. There are multiple conflicts within the world, some at a global scale, some within the borders of the same government (and it is not always very clear who is correct and who is wrong); and we have seen time and again foreign governments trying to profit from such “opportunities” by selling weapons, information or through some other means. We are now looking at a model where private people get to make the same decisions.
Also, looking at their commercial model: they can only scale either by increasing their share of wallet with existing customers, or by increasing the customer base. But by increasing the customer base basically they run a risk of making the solution irrelevant and bringing everyone in conflict on a same playing field (not desirable for anyone who is at war). How would you see them addressing this risk?
interesting application! I am not sure I fully get how it works, but wouldn’t it be similar to the systems police use to recreate faces of people who disappeared / were kidnapped? I am always a bit terrified by these facial recognition softwares as I can easily imagine them being used in a “big-brother” type of world where people on streets would be easily recognized by the government / system, or where AI could analyze your facial reactions and translate them into emotions for other people.. I am curious to hear your thoughts on such applications. I get from the tone of the article that you are a fan of this technology – maybe you will be able to ease my fear a bit 🙂
Thank you for this post, Sultana. Very interesting indeed. I do wonder though if this solves the problem… Are they using AI to bring the gap between demand and supply as well? or just in choosing which designs to produce?
To me it sounds they use AI like a cost saving solution for not having their own designers? They still have quite a bit of variety of models on their site and as you say, the price points are very low ($73 for a halter top, skirt and sweater) so super fast fashion, with a very niche style (by this I mean when the trend is out, if one continues wearing these clothes, they are definitely out of style).
Thank you for this post, Lina. I actually got intrigued by this and installed the app but I have to say that the customer experience is a bit disappointing for me – would love to hear your views on this: inspite of choosing an advance level for English for myself, the exercises I had access to were quite basic (e.g.: pronouncing words like “good morning” and “tupperware”), for words I had issues pronouncing, and I could only do first 2 levels without becoming a paid user. Also, I am not finding Elsa to be offering a very differentiated product compared to duolingo – on the contrary, I think duolingo offers much more flexibility for non-paying users, as well as more variety in terms of languages to be learned and exercises.
have you been a long term user of ELSA? is the value proposition to customers different, after a longer term use? does it become more customized / customer? how do you see them surviving when facing such a strong and well established competitor as duolingo?
why are they all women? white women? by now… nothing shocks me anymore… this tool needs so much more work to keep up with life
I wondered if anything changes with personal searches one does so I typed in vacation into Google as well.. but I got the same pictures of water, beach and sun (even if my perfect vacation and stuff I search for are more linked with mountains and hiking…) wonder if the search is bespoke by location (i.e. US vs Europe vs. Asia)? cannot be such a blank view for everything and everyone… or can it?!
:)) this is so funny and deeply disturbing at the same level. I think the snapshot is trying to tell you that your future career is in the cloud… maybe that is a pre-launch reinterpretation of META? :))
I find it fascinating how we have diversity of color, but not diversity of home type/style… also, these homes seem to be a bit more abandoned than lived it… so might be more houses than homes?! ….
once you get past the shock of the image, it becomes quite interesting… the suit, the age, the sex, the glasses, the power pose somewhat… I am yet to understand why the words you entered created such a horrifying picture. Cannot help but wonder (or hope?!) that maybe the algorithm was created intentionally to shock
thank you for your comment Kate. Seeing your comment I tried to gather some data on the type of customers that use TGTG app but I could not see any split on demographics and/ or income brackets. I would suspect that the trends you noticed are true across different areas.
love your reply, Laura! thank you for this – I did not know but you are raising some very interesting points.
Thank you for this post, Elizabeth! it’s been interesting to read it and find out more about the app I absolutely had to download to be socially accepted here :)) In terms of threat to users and therefore threat to scalability (especially internationally, but also locally within the US), I think Revolut represents a major one: they have a very strong position in Europe, they entered the US as well, and while it allows for easy transfers between people (very similar to Venmo), it also has additional features, such as stock & crypto investing, breakdown of expenses, currency exchange, etc. Would be interesting to see if Revolut eats into Venmo’s market share, or will pose a threat for other fintech apps.
I agree, a time frame of 30 mins is too short; from how I see their business, I think TGTG is more of an enabler so from this perspective, I think restaurants have the freedom of mixing or matching dietary options in their bags. I know the food they select is basically left overs from the day (when they decide not to sell products from one day to the next) and the quantity is based on not discounted pricing, number of bags the restaurant wants to make available and overall quantity of food available for TGTG.
So excited you decided to download the app! Let me know how your experience goes 🙂
I cannot tell you how excited I am for receiving the first comment on my post!
You are making some very fair points, Elizabeth. I will try to address them all properly. Their revenues are coming from an annual fee + share of revenues from each surprise bag sold (the figures published suggest they charge $1.79 / transaction, representing 30-45% of the value of each surprise bag sold). So their unit economics would be fairly healthy once they reach a critical volume that covers app development, customer support and overall SG&A costs. For their partners is actually a good opportunity as well, as they would not have to throw away that food, but get to make some modest revenues out of it too. Nor TGTG nor the partners incur any delivery expenses as customers need to go in their locations and pick up their surprise bags. Also, TGTG does not target necessarily customers with lower income level (I actually believe it to be a bit tricky to make an eating plan out of TGTG, precisely because you do not know what you will get. But it is a fun way to shop from your favorite places when you don’t have any preference as to what you will be getting. And you get rewarded by paying a fraction of what the contents of the box are. Regulations are indeed a fair point of concern and I know they do take them into consideration when expanding to other countries (but I do not have the detail of what specifically they are considering from this spectrum).
Re quality of meals: they do end partnerships if customers are raising concerns over both the quality of the food and the value of the bag (the 1:3 ratio is something TGTG team cares very much). From some of the articles I have read it seemed they have a zero tolerance for quality and value. I always used them with places I liked and places I used within normal times as well, so I always had a stellar experience with them.
thank you for this post, Patric. Very interesting read. The idea is fascinating, but I do wonder on the quality of data this app collects. I can see it integrates information from other apps such as Strava, Fitbit, AppleHealth and others : how is this point addressed by the big Pharma companies and the health NGOs that Evidation partners with?
I still struggle to understand the value of GoodReads (to be read, I use it, but I would not pay for using the app). I use it as a way of keeping track of the books I read and more importantly the books I want to read + to quickly find reviews for books I hear of or that are recommended to me. I am curious, given the introduction of your blog, are you using it for book recommendations as well? Also, I wonder how Amazon is using all the data GoodReads is generating for them – could put them at a huge advantage with publishing houses…
funny insights. thank you for the article. I wonder if they did any A/B testing on the logo (or other data research) and what the results were. Are you aware of any other uses of data apart from discovering when the users were dropping off their shopping carts and buying behavior? and did they do anything with these insights apart from pulling everything together under one brand? in other order of ideas, I think Zara is an amazing example of data collection and usage in the space of retail stores / fast fashion. Falabella could learn a trick or two from them
Loved the article! I was surprised to see this initiative from Bayer as I have heard about the technology times before, more from startups who are entering the industry and disrupting the way farming is done, in a more climate friendly and sustainable way. And this is somehow hurting Bayer’s business who is also selling insecticides and by using AI and drone assisted technology for farming, the use of such chemicals would be reduced. Do you have any insights in their thinking and approach? Also, was this technology developed inside, or are they acquiring innovative start-ups? And how are they planning to compete against them going forward?
Thank you for your post. I wonder if you could maybe give some more flavor into data sourcing as I see that the most sensitive element of the entire data infrastructure and use cases they might have. Amazon not only has their online portal but also the Goodreads app; the number of users on both those platforms, interacting with books from all over the world, irrespective of language, topic and publishing house is enormous and therefore the level of insights Amazon can generate (even for making recommendations) is much more accurate. I wonder in the case of PRH: 1. reliability of data sources and 2. data size as well. And I worry of a vicious circle called “garbage in , garbage out” which might lead to hurting their business even more, if they end up being the victims of their own bias. Would love to get your thoughts on the matter.