Very well-written and insightful post! It is interesting to think how this pivot was possible thanks to a digital initiative (F1 video game) that was already existing and so provided the tool to temporary self-disrupt the business model. What would be interesting to explore more is how sponsors and advertisers reacted to this choice i.e. whether they were perfectly OK to keep their deals even with virtual audiences or if they wanted to adjust deals in any specific ways. In fact, while viewership may have stayed high (it’d be interesting to compare also vs. real-life races, to understand if/how much viewership declined), the interesting thing to analyze is whether audience composition is the same (this is the most important criteria for sponsors and overall advertisers, after the numbers on reach). Curious to see if this new set up actually will have a post COVID-19 future too!
Nice analysis on Shopify and the risks it bears re. concentration of the customer base (not in terms of few big customers, but in terms of mostly SMBs in non-essential industries), that is exposed to liquidity crunch. One point I’d explore more is the one related to logistics, as in a period of uncertainty I would prioritize flexibility and working with 3PL exactly to have a variable cost (since demand will be uncertain). Going forward, Shopify should anyway be well positioned to support eCommerce companies and compete with Amazon, especially if it could add extra services like an advertising targeting capability (Amazon Advertising is growing 30% YoY, exactly as they can leverage purchase data). Shopify could have a service where sellers that opt-in could both receive / give data (non-PII) from / to other sellers, so that advertising could be targeted to people with highest purchases likelihood (based on purchases of complementary processes or overall purchase behavior of look-alike consumers).
A very nice example of a digitally-native company that is shining throughout the current pandemic. As the business was already digitized before the pandemic, they could experience significant growth in the last couple of months. At the same time, going forward, it would be interesting to understand how costs should be managed, in order to sustain growth, in a profitable way. I think the big uncertainty right now is if the pandemic will also change consumer habits and so how many consumers will keep ordering their grocery online. In case there will be significant drops or even just fluctuations in volumes, GoPuff will need to build a variable cost structure, that can be scaled up and down with agility. Logistic is a good example, where they should invest in 3PL relationship vs. internal capacity (fixed cost).
The thought on the trade-off between a ‘lean’ or ‘robust’ supply chain is spot-on. In fact, with companies trying to continuously reduce working capital and investments in capacity (to maximize asset utilization), very lean supply chains are also very prone to disruptions. The absence of ‘buffers’ increases the fragility of supply chains. Software that increase visibility, transparency and ability to predict issues in any of the nodes of a supply chain can be very useful. The challenge will be to help supply chain companies ‘justify’ such investments, as the cost-benefit analysis is not very immediate. Many insights triggered by BlueYonder may result in false positives, at least until the AI will learn on real data (that are specific to the supply chain), so organizations will need to carefully track costs incurred and costs avoided, to define how much value BlueYonder can deliver.
Very compelling article, as AI and chat-bots are destined to change our lives forever. Besides the use-cases mentioned in the article, it could be interesting to explore the impact of these technology on advertising. In fact, while today consumers still ‘decide’ what to buy, in the future they may completely outsource this task to recommendation engines integrated with a chat-bot that collects our interests or requirements. In this case, machines will collect data and make decisions on our behalf – in the long term this could bring ‘branding’ to an end, by making purchase much more rational and timely. This could be a very interesting application to explore, both for advertisers and for AI/chat-bot companies.
Interesting post, especially in a moment where advertising technology is going through a big revolution. On top of Safari ITP and Chrome Privacy Sandbox (both preventing cross-site cookie tracking), there are also regulatory changes (GDPR in Europe, CCPA in the US) that could push out of business many of today’s AdTech companies, whose business is based on cookies. Criteo will need to find (or help build) a new source of data, to be able to re-target and survive in a cookie-less world.
In this very dynamic environment, it will be also important to explore potential partnerships that can deliver innovation to advertisers and retailers. While Criteo has the advantage of having relationships and access to e-retailers’ purchase data, it would be interesting to explore if/how it could partner with other technologies e.g. to help assess how effective advertising was.
Very thoughtful and detailed description of how Zoom managed to achieve such high market share!
Product superiority definitely helped, as well as the freemium model.
For the monetization strategy and the sustainability, it may be important to assess the situation by segment. Specifically, for private users, it may be challenging to move to a subscription model, since there are many alternative free services (and product superiority may not justify the cost to users). For enterprise clients instead, it will be important to understand if/how Zoom will integrate to adjacent services – in fact, Microsoft Teams, as an example, has already integrated its video-conferencing tool with its chat and its digital collaboration platform. Such synergies, in the long term, may make a big difference for monetization and market share.
Very much needed platform, that can actually help “create” a market vs. simply facilitating transactions. In the article, I liked the perspective on network effects, as well as the thoughts on (1) the low disintermediation risk, given the specific customers provenance i.e. mostly travelers, (2) mitigating multihoming (low) costs, for example by offering services that can simplify the end-to-end experience. I agree setting up partnership with other service providers (e.g. AirBnB) could help expand user base as well as increase entry barriers for other players. Back to the initial point on “creating” a market, it could be interesting to understand what kind of partnerships (and potentially also advertising strategies) can help target the right audience and scale the platform.
Very interesting article and compelling platform – second-hand car transactions are exposed to information asymmetry that leads to overall opacity in the system, so this platform can bring a lot of value. With strong network effects but also low entry barriers and multihoming cost, competition is very high. It would be interesting to explore more the actions CarGurus can take to influence multihoming costs, in order to improve loyalty of users (car buyers). As an example, a strong offering on complementary services (e.g. maintenance, insurance, etc.) may be helpful. Lastly, another area that could be explored is the advertising stream – advertising revenues were mentioned and represent 11% of total revenues; it could also be powerful to explore how advertising investments (from CarGurus) could help increase traffic and so boost both transactions as well as advertising revenues.
Very clear and articulate description of the digital offering from Mercado Libre! Understanding the different services, with high degree of complementarity, helps realize why Mercado Libre is so successful. The founders could ride the wave of e-Commerce, as they believed in the opportunity well ahead all of possible competitors (e.g. existing offline retailers).
One thing that could be interesting to understand – it looks like the competitive advantage of Mercado Libre connects only to timing (i.e. they were among the first companies to leverage the power of digital in the retail industry). It would be important to define what the long term competitive advantage is (e.g. any tech advantage?) and if/how Mercado Libre could resist vs. new players (e.g. Amazon) which may enter the space.
The three reasons presented are compelling for this case – consumers’ trust (based on the overall Amazon brand), target audience (with a good product fit) and existing infrastructure (leveraging last mile delivery). More specifically, I fully agree that the existing relationship Amazon already has with many consumers can give incentives for people to try the solution. Similarly, the superlative efficiency focus of Amazon is what is required to crack online grocery. While all the reasons above position Amazon to be possibly the best player to disrupt this space, it will be interesting to understand if this space will actually be disrupted. In fact, there are still profitability questions that may not be overcome despite the great digital solutions Amazon is leveraging.
This case is absolutely interesting – specifically, I like how it described the different digital initiatives that were able to lower entry barriers in the space. Re. Digital Community and Digital Content, I agree these are dynamics that helped the brand grow in a very efficient way. One thought that could be interesting to explore in this case – what is the actual balance of inbound/organic digital marketing activities (i.e. the ones above) vs. paid digital marketing activities? In fact, several studies confirm that inbound/organic (free) activities have a very high ROI in the first stages of brand growth. Afterwards, paid activities are required, so it would be interesting to understand if/how they leveraged the opportunities of digital media also in this space.