Loved reading about Zara — definitely a great example of just how important data is in developing a competitive advantage in mass retail. Going forward, though, I feel like this is something that all mass retail brands will need to employ — seems like it’s already happening as you mentioned with Uniqlo and others. Given that fashion tastes of consumers change so rapidly, I wonder whether having been first to market in using data will grant Zara a long lasting advantage — aside of course from having developed internal data analysis capabilities. Google, for example, benefits from having collected data far longer than anyone else, making their algorithms impossible to compete with. In Zara’s case, their algorithms are probably more or less created with a new season’s designs. Will be interesting to see how they stay ahead of the competition.
Thanks for this post — I hadn’t heard of Bitscopic but it’s a great example of leveraging big data to try to solve a truly important problem. I have no background in healthcare so this may be far off but in regards to whether hospitals, insurance co’s will / should provide data, I wonder if that’s where legislation could be beneficial. Of course, privacy of individuals should be of highest importance but it seems like this type of information in aggregate anonymized format is beneficial to society as a whole and as such should be shared.
Really enjoyed reading your post! I had no idea that Hubway was using so much data to optimally locate their bikes, though should’ve assumed as much. Thought your ideas on other statistical analyses that Hubway could do were spot on. I wonder if Hubway will ever go a step further and use individual usage patterns to either provide promotions for those users whose usage have lagged or partner with other locations such as movie theaters or restaurants to provide a discount for those who ride a Hubway to those locations.
Thanks for this interesting post! While I had heard of Digg’s fall from grace I had not understood the factors that contributed to it. Digg’s situation showcases perfectly the catch 22 of operating a fully crowdsourced platform. Do you think that allowing users to have followers could have made the system more democratic? Clearly becoming a influencer was a key feature for incentivizing user activity on the site but it also seems like it became the sword upon which it fell. Also, aside from having a more robust community management system, do you think that introducing publisher-curated content alongside crowdsourced content earlier could have extended the life of the product?
Informative post! I didn’t really know that Kiva was a charitable loan platform – thought of it more akin to all the typical lending platforms out there. I was very surprised to see that the Kiva Zip product is resulting in lower repayment rates. The fact that there is more interpersonal communication and the fact that entrepreneurs have to seek out others to validate their creditworthiness should serve to increase repayments. After all, I believe that is the very premise on which CommonBond was founded. What do you think might be the reason? Could it be the nature of the beta groups that they have launched with?
As a power Yelp user, I have noticed that the quality of the rating from the masses have begun falling short in the last couple of years. Your data analysis demonstrates exactly what’s been happening. That being said, I do believe there is additional value in showing the aggregate average rating and quantity of reviewers for the restaurant as it somewhat negates the attempts of many social media-savvy restaurants to plant good reviews to jumpstart their Yelp presence. Your recommendations for their next product iteration is on point. Personalized recommendations would make the dataset much more powerful and relevant, but certainly the large database is a critical moat from competitors like Swarm, whose recommendations just haven’t been as accurate or reliable as Yelp.
Venmo was a great company to write about for network effects. My opinion is that the threat of banks to enter the P2P payment space is low for several reasons. Aside from the obvious fact that banking institutions are slower in embracing innovation, they also do not generally have the know-how of creating an intuitive consumer-facing UI. Moreover, Venmo can be “Switzerland” among all the banking institutions and credit card companies to attract a larger base of users. A single bank may have a harder time trying to integrate with another bank, which reduces the ability for them to take advantage of network effects. My question is: why was Paypal unable to launch a similar app before Venmo? Paypal obviously realized its mistake as it acquired Braintree in 2013, but I thought that Paypal would have had the user base and product capability to create something like this.
Informative post! I’m probably the last millennial to not use Spotify so it was interesting to read about how Spotify has continuously evolved its product to take advantage of network effects. I also recall when Spotify integrated onto Facebook so that every song a user was listening to was put on blast, for better or for worse. Though it was a great user acquisition tool, as you mentioned, it also was a reminder that there are limits to exploiting network effects, and the customer experience must always be considered. I also think the indirect network effect is strongest when it comes to indie artists who now have a centralized place for their music to be discovered and downloaded by a significant pool of users. Do you think there ever will come a time when large record labels will gather together to protest Spotify’s content licensing fees a la Taylor Swift? The impact it could have on Spotify’s ability to benefit from direct network effects could be pretty damaging.
Really enjoyed reading this post! Agree completely about the factors you identified that have led to Twitter’s decline. Ultimately, as you said at the end, Twitter has not been able to iterate on its product to propagate the network effects that were baked into its valuation by investors. It’s interesting to me that Wall Street expected Twitter to grow as large as FB at IPO. From what I know, the engagement, and thus, the content, on Twitter is generated by a very small percentage of the overall user base. I would assume that this concentration of engagement would mean that the direct network effects are impacted strongly by these power users. Twitter’s inability to engage the general user base, unlike FB, has led to a lower direct network effect for the platform.
I totally agree that Walmart’s omnichannel strategy is the right approach in combating Amazon’s dominant retail presence. The main challenge to actually implementing this strategy, imho, is in controlling shipping and fulfillment expenses by (1) finding the optimal inventory allocation, (2) making the correct sourcing decision and (3) retraining or hiring store employees to correctly fulfill e-commerce purchases. This is no small feat and will require heavy investment in both the store and backend software, which may not sit well with the current shareholders who seek capital preservation versus growth. I believe that Walmart should focus its omnichannel strategy on fresh grocery, as this is one category in which it has a large leg up over Amazon given that grocery is over 50% of its revenue and a vast last mile delivery network is crucial for executing an online-offline transaction.
Really enjoyed reading about Instacart and the grocery delivery space. The fresh consumables category is virtually the only one that has not been cracked by Amazon or any other retail giant. As you mentioned, the asset light model for Instacart has allowed them to become a platform for many brick-and-mortar grocery stores. I would label them a clear winner (or en route to being a clear winner) if it weren’t for the ruling in California that came down on Uber this past summer. Uber has until now labeled their drivers as independent contractors instead of employees and have been able to circumvent paying out unemployment and workers’ compensation, among other related costs. In August a California labor board ruled against this categorization and in September, a federal judge in California granted class-action status to a lawsuit by drivers against Uber on this topic. How this ends for Uber will have critical impact on Instacart and other startups in the sharing economy.
While I don’t own a FitBit I have friends who find great value in the device despite what I see as a clunky aesthetic. You make a great point in the fact that the social gamification element of the platform has created a network effect critical in combating substitution threats. Moreover, allowing additional utility apps related to the core metrics that are captured by the device would strengthen the position of FitBit in the market. To the uninformed outsider (such as myself), however, Jawbone appears to offer similar functionality in a similar-looking device. I assume the social component and 3rd party app integration are also available through Jawbone and they launched around the same time. I wonder how FitBit has edged Jawbone out as the clear winner in this industry. I would be also be interested in understanding how you view Apple’s entrant into the wearables space. To be sure, Apple has not found success in its new watch but I certainly believe that Apple will iterate until the right product is created. Will FitBit survive as the lower-priced, fitness-focused wearable device vs. Apple’s premium priced, multi-use device?