I fully agree with the comment above re: unprofitable customers. The fact that they even have any given such level of data analysis suggests to me that this is the number one fix they can do to improve their otherwise impressive data management system. Another thing that comes to mind are lessons from dunnhumby and Tesco. Perhaps CVS could learn how to group their customers into specific categories and further tailor the offering based on those? Or maybe it could learn to predict not only what the customer wants and buys right now, but which category they are likely to move to as their life progresses? In Tesco’s case, they would use massive data to draw dynamic (as opposed to static) conclusions: e.g., a customer just purchased their first set of diapers. That likely means they have a baby. From our database we know what purchases usually follow that first purchase for YEARS to come. How do we leverage this knowledge?
Great post! No doubt in my mind that this is hugely value creating. Google is trying out other products leveraging the very same technology of machine learning: Google Inbox for example does exactly the same thing with regular e-mail as it does with spam, recognizing that many automatically generated messages are actually not spam (tickets, boarding passes, purchase confirmations, newsletters etc) and could use some categorization. The more you use Google Inbox, the more accurately it assigns the categories, helping you organize your e-mail content. Your 1-second argument holds!
Great post and a very interesting topic. To me the key question I would think about if I was Fitbit would be: how can I leverage all the data I have gathered from my customers to make my product sticky in the long term? Maybe there is something to be said about long-term data analytics which span over the initial 6 weeks after which attrition becomes high. Could Fitbit launch a very serious study in long-term benefits of tracking and of physical activity itself? Could they refine their value proposition to promise their customers sound insights out of months, if not years, of data?
Great post! I wonder if LEGO indeed has the incentive to review the projects more often than twice a year. 1% of net revenue is a high price to pay and the review process is likely quite costly itself. And the company seems to be doing quite well with its own designs anyway. Another thing I worry about is a free-riding problem: there is a fine line between using the submitted project and sharing revenue with its creator and using the submissions as general inspiration for LEGO’s own design teams. In the end, nothing is stopping the design teams from snooping around the submission website, finding good design ideas, tweaking them far enough from the original submission that the owner cannot reasonably claim it anymore, and retaining the 1% royalty in house.
What a lovely idea! What immediately comes to mind is a very positive side effect: teaching kids from early age how to think in project terms, budget them, and raise support for their ideas. Another positive side effect: finally bringing innovative ideas to education, both in the form of mentioned 3D printers, and in the form of modern ways of engaging the community. I agree with your concern – there are perhaps some ways of incentivizing students to drive the submissions, be it by creating in-school competitions for best projects or by letting the students manage the campaign proceeds themselves (e.g., the student who manages to get the 3D printer sponsored will be a de facto manager of the printer in the school).
Brilliant business and brilliant blog post. Thank you very much! I wonder if some of the challenges you mention are actually real challenges. So what that some of the voices are not heard? In the alternative, so no CrowdMed, NO voices are heard. I agree that the population of medical detectives is likely heavily skewed towards younger, less experienced members. But they’re not there to TREAT the disease (in which case the experience matters a lot), but to SOLVE the issue, right? As soon as they do, the patient in question will likely have no trouble at all finding the few grey-haired specialists that can help with the treatment. The same goes for doctors’ resistance: the beauty (and sometimes the demise) of the crowd lies with its size, and the related ability to vote with its feet. If enough people are on board (and that seems to be the case), doctors can be upset all they want, but CrowdMed will continue to disrupt them.
Interesting take on a product that was initially designed to be very personal (asking you for sensitive data such as your weight or tracking pretty much everything you do day to day). First, I have to disagree slightly with your opening: I don’t think it’s redundant to your phone (after all, you don’t play squash or basketball with your phone on you, and that is exactly when you “clock in” the most steps); in fact, part of its beauty, relies on the fact that it is highly COMPATIBLE with your phone, making tracking of virtually everything so easy (weight, move goals, sleep, calorie balance etc). Second, even though I agree that network effects played a large role in effectively CREATING this market, I would argue they are not company-specific but rather industry-wide. Fitbit created the market for Jawbone and others to enter. Given the number of apps compatible with all available health tracking products, as well as the general ease of use of the software associated with each of them, I think that the switching costs for customers are relatively low. That suggests to me that the initial network effect that perhaps fueled the growth are not strong enough to keep it going in itself.
Very interesting take on what has become a large part of the life of single 20-somethings (and 30-, and 40-somethings, too). This particular network has some other (negative?) externalities: it perfecetly feeds into the predominant love for optionality among our generation (as in, why keep dating this person, if so many potentially better matches await at the tip of my swiping finger?). In many ways, it commoditizes dating, leading to potential temporary asymmetries in customer satisfaction between e.g., genders. This may indeed endanger the very business model: Tinder may become heavily male skewed, while apps such as IvyLeague (accepting only customers with degrees from top schools) are already heavily skewed towards females. If this imbalance increases, you can imagine hoards of dissatisfied customers (this time on both sides) leaving such platforms.
Very good points overall. I definitely see the possibility of top-performing households leaving the platform (or becoming less active on it) after they realize they can cut out the middleman and advertise online directly to customers. However, this would take coordination between market participants on at least two extra issues: timing of the accommodation (Airbnb solves that problem by only showing accommodation available in the given time frame) and trustworthiness (through its own brand Airbnb does provide extra level of comfort for first-time accommodation users). Before internet search becomes even more efficient than it is today, those two may be worth the extra 3% commission. The latter however indeed becomes an issue if, as you point out, lower quality participants (on both sides of this two-sided network) enter the platform and dilute the value. If any of the sides, or worse yet both, lose faith in the platform, new entrants (with different business model?) may enter the space ending Airbnb’s dominance.
A wonderful service and a wonderful post about it! I am also a big fan of Instacart – I use it as frequently as twice a week. All the features you outline in your post are indeed making the life of a consumer easy (and possibly the life of a shopper a bit more annoying when last minute changes come in to the order). My question for the future success of Instacart is how does it plan to capitalize on the vast amount of data it is collecting? Some companies (such as Haagen Dazs or PepsiCo) are already trying to ride the wave of Instacart’s success by installing online promotions for customers (e.g., PepsiCo sponsors the delivery fee of $3,99 if you order $20 worth of their product). But surely in the world of big data Instacart could go much further than that. Another way to use their insights is or their own benefit: for instance it seems that Instacart’s performance is uneven across cities (e.g., Boston offers truly “Insta” delivery times whereas lead times on Manhattan are often 2+ days) which could be easily mitigated by proper data management (e.g., analyzing incomplete orders based on too long lead times and investing in extra staff to optimize the bottom line).
Great summary of the insanity that WeChat is – although it potentially underestimates the role WeChat plays in the Chinese society. Just as most companies in the Western World have their page on Facebook, virtually ALL players in China kick off their digital strategy with a WeChat plug in. About half of the apps that consumers in the Western World have on their phones as separate icons (the ones you outline but also mobile banking, Venmo, Hinge, stock tracking, Yelp etc) are integrated into WeChat. The benefits of such integration are quite clear and likely if you were to design a perfect one-stop-shop app to have it all from scratch, WeChat would come close (and that’s why it has taken China by storm). However, to your latter point on WeChat’s troubles with winning in other markets, consumers are creatures of habit. And adopting WeChat in its full glory would take not only giving up your favorite messenger but replacing the other 20+ apps you frequently use, which altogether means A LOT of change to your consumption habits.
As a consumer I am absolutely in love with ClassPass – their app resides on the main screen of my phone, I have tried out 30+ different studios over the summer alone, and I have recruited so many of my friends to join that I regret they haven’t introduced a word of mouth reward yet. The value proposition – as you nicely outline – is clear and takes the customer no time to buy into.
As an investor however, I am quite cautious. I am not saying it is a BAD business model, but I want to see it make a real return and survive beyond the lifespan of the GroupOn fad before I join in with the optimistic crowd. I would want to see ClassPass making profit on the sustained operation, not just from growth. I also would be interested in understanding their attrition rates, especially following a recent monthly fee raise, from $99 to $125.