How does OrderAhead delivery compare to DoorDash
Nexus 10: Amazon, Zalando, findings from a16z “Marketplace 100”, Bird Pay
good news, bad news. Bad news first: it looks like the end of Nokia (or the rest of Nokia) may soon be around the corner. Good news: the internet is finally back in my office.
And another breaking news: After the MWC, Facebook has now also canceled its F8 developer conference, which should take place from May 5th to 6th. You won't be the last.
We may have more time for other things in the conference season this year.
Let's get this remote party started.
In this issue among others:
- Many platform / marketplace topics, but no European segment.
- Amazon relies on one-tap reviews against fake reviews.
- a16z has identified emerging marketplaces.
- Bird Pay shows where the platforms are likely to be in the mobility sector.
Steven Levy - Facebook: The Inside Story
Levy is one of the best tech journalists, and at the same time is perhaps the tech journalist with the best contacts and sources. His new book on Facebook hits the headlines almost immediately as soon as it is published. This thread from Casey Newton of The Verge on the book gives a good taste of the book, I think. The book has already landed on my Kindle.
David Kirkapatrick's “The Facebook Effect” helped me a lot back then to classify Facebook and Zuckerberg. The book ended with Kirkpatrick's breathless hint that Facebook already has 400 million active users. So it's not that fresh anymore.
Levy comes at the right time.
Amazon and fake reviews
Product reviews are a very important asset to Amazon's growing role as a product search engine.
Vox.com/Recode reports on Amazon's latest measure to combat fake reviews, which at the same time increases the number of customer feedback:
The online retailer quietly introduced one-tap ratings for product reviews late last year, making it possible for shoppers to provide a star rating without needing to write a review to accompany it.
The change has already led to an increase in overall customer feedback, a competitive advantage that Amazon has over many of its biggest brick-and-mortar competitors. And new products are generating feedback on Amazon sooner, the company says, which could be a boon for new brands and sellers. But some industry observers believe another indirect impact of the change will be a significant increase in authentic ratings that will make it harder for fake reviews to break through the noise.
Less friction (Star rating without text), which is only available to "verified" buyers, i.e. actual product buyers:
The new one-tap feature asks customers to select from one to five stars for a product. It's only available to customers who have actually purchased the item from Amazon - “verified” buyers. That barrier alone creates one hurdle that will make the new rating system harder to game, since Amazon does allow written reviews from non-verified buyers. And as the new rating feature attracts more and more feedback from verified buyers, it'll get more expensive for schemers to buy enough phony reviews to try to break through the noise.
This strengthens positive network effects and reduces negative ones. The abuse has become more expensive because if in doubt it is drowned out by the flood of legitimate one-tap reviews.
Of course, ratings aren't just counted and then the star average calculated. As with Google's PageRank, Facebook's newsfeed and other weighting algorithms, as many criteria as possible play a role here, the weighting of which is not disclosed:
Amazon does not provide many specifics about how a product's overall star rating is calculated, other than stating that it is not a simple average but instead uses “machine-learned models” that take into account factors such as how recent the rating or review is and whether it was a verified purchase or not. It's not clear whether one-tap ratings will carry as much weight in these models as written reviews.
These quick assessments will not play a role here individually, but as a group: What trend do you also see for product X in terms of time? Also: what percentage of buyers rate the product? How soon after delivery is the rating? etc.
One can assume that the mass of reviews on Amazon will increase.
The question remains, why is Amazon only doing this now (many online rating systems have been offering this for a long time) and, in addition, when all reviews will only be possible for "verified" buyers. It is quite possible that the two are related. If the faster, text-free reviews deliver enough mass, Amazon can switch all reviews to purchase-linked.
Findings from the "Marketplace 100" by a16z
The VC company Andreessen Horowitz presents the "a16z Marketplace 100". The emerging marketplaces in the US market, both startups and private companies, are weighted according to size.
They used anonymized credit card data for this:
In this case, anonymized, aggregated US consumer spending data captured via credit cards, debit cards, and bank transfers, which has become a popular tool for analyzing high-growth startups. For the Marketplace 100, we use data from a company called Second Measure, a firm that analyzes billions of purchases to track real-time consumer behavior and relative sales across 4,500 merchants. (See the methodology below for more details.) We collected this anonymized data from millions of consumers and analyzed their spending. This data lets us see which marketplaces are capturing the most dollars, what's trending up and down, and which categories are growing fastest. The companies on this list were then ranked using a common industry metric, Gross Merchandise Value (GMV), which is extrapolated from how many total dollars consumers are spending against each company. This provides an approximate measure of a marketplace’s scale and its importance in the economy, based on how much revenue is trading hands between buyers and sellers.
The database is therefore relatively good. In other words: You will not find a better database for classifying new marketplaces.
Power law dominates not only on platforms but, understandably, also between platforms themselves: 76 percent of the tracked turnover falls on only four of the marketplaces. (Airbnb, Doordash, Instacart, Postmates)
Hence the following are the largest marketplace categories of course, travel (AirBnB) and food & grocery shopping (Doordash, Instacart, Postmates).
The new emerging marketplace categories show that marketplaces can meet a wide variety of needs:
Several emerging categories are intriguing, including local indie brands, celebrity shout-outs, streetwear, fitness memberships, and even car washes
The fastest growing marketplaces are growing really fast — 3x to 5x year-over-year
The top 4 may not yet be listed on the stock exchange, but they are anything but small, young companies:
The top 4 companies on this ranking were started between 2008 and 2013, making them 7 to 12 years old as private companies, with billions in revenue and thousands of employees.
Of course, the question is particularly interesting how marketplaces compete with each other:
While celebrity engagement and streetwear are emergent marketplace categories, food & beverage continues to grow rapidly, despite its already massive scale. DoorDash (# 2) continues to take market share from the likes of Grubhub, UberEats, and Postmates (# 4) in the massive $ 22 billion food delivery market. (As public companies, the latter aren't included in the Marketplace 100.) In the adjacent order-ahead takeout space, emergent platforms like Ritual (# 32) and Snackpass (# 81) are acquiring large swaths of urban professionals and college students with clever social features like food-gifting and group ordering.
Like all platform types, marketplaces grow according to the typical S-curve to saturation:
The typical lifecycle of a marketplace is that startups grow quickly in the early years — often> 3-5x year-over-year. In later years, their growth rate usually slows into a more comfortable range. We see this borne out in the data, where the top 10 fastest-growing companies are growing at a top rate of 5x year over year.
The fastest growing US marketplaces:
The four fastest-growing companies (by year-over-year relative growth)
Faire (# 53) is a wholesale marketplace for boutique retailers to find and purchase unique merchandise from local indie brands.
Cameo (# 67) is a video-sharing marketplace where fans can book personalized shoutouts from their favorite celebrities.
GOAT (# 16) is a peer-to-peer marketplace for buying and selling authenticated streetwear and sneakers.
EverWash (# 66), the most surprising company of the top five fastest-growers, offers car owners access to a members-only network of car washes. Similar to the Masterclass model, EverWash customers have access to unlimited car washes for a flat monthly membership fee.
With the exception of EverWash, whose success I don't really understand, all of these companies make a lot of sense. They serve needs that can only be met by marketplaces and also fit into the current social context.
Of course, the distribution of the marketplace activities according to categories, i.e. how many marketplaces are in the same segment, is exciting:
When grouping startups into their respective categories — tickets, transportation, education, and so on — we see a highly concentrated sector, as well. Twenty-one of the Marketplace 100 belong to either the travel industry or the food & beverage industry, which together account for 63 percent of the list’s total GMV. A closer look at the GMV breakdown within those categories reveals two completely different market dynamics. Within the travel segment, Airbnb (# 1) is the runaway leader, accounting for 95 percent of the GMV segment — of course, these days, Airbnb’s primary competitive set includes large, public companies focused on travel, as opposed to other startups.
On the other hand, the food & beverage category is much more fragmented, with multiple startups vying for leadership: Doordash (# 2) and Postmates (# 4) have all gained material GMV share, accounting for 72 percent and 23 percent of their segment’s GMV, respectively. Similar to Airbnb, Postmates and Doordash’s largest competitors are public incumbents, like Grubhub and UberEats.
The reason for the different concentrations in the markets of course lies in the underlying network effects. AirBnB aggregates global offerings, food deliveries are aggregations on a regional level.
a16z also comes to this logical conclusion:
In comparing the two categories, our theory is simple: There’s a big difference between network effects that span global and continental regions, as opposed to city-by-city networks. Airbnb’s global network effect spans regions, since potential guests book lodging outside their home base and hosts expect to receive visitors from all over the world. It is a single, global network, which provides a strong defensible moat that, thus far, competitors have struggled to copy. On the other hand, Doordash and Postmates both have local networks effects, meaning that transactions within their 2-sided networks exist within specific cities, not across them. Consequently, winning in one geography, like Los Angeles, doesn't confer an advantage in another location. City-by-city network effects are naturally more fragmented and suffer from more severe competition. In other words, winner-take-all-dynamics are nonexistent.
For food delivery and other marketplaces where fragmentation is the norm, competition is severe. There is little to no cost for users — both restaurants and consumers — to join a new platform. Restaurants are incentivized to join multiple platforms to tap into more potential demand, meaning no platform’s supply is unique. When consumers can order the same meal from multiple platforms, the providers then compete on price and experience (most notably delivery time).
Conversely, this means that an industry like the travel industry will always be dominated by a few providers, while food delivery or comparable categories will see ever increasing competition at the level of the marketplace provider.
Unless, of course, a provider finds an asymmetrical way to develop global or at least supra-regional network effects.
Keyword: bundling of offers.
(We will look more closely at network effects soon.)
Zalando: Business figures 2019
Jochen Krisch on Exciting Commerce about Zalando's business figures:
Accordingly, Zalando was able to increase by a further 1.1 billion euros in 2019 to total sales of 6.5 billion euros (+ 20%). DACH sales rose by 16.6% to 2.9 billion euros. [...]
The trading volume (GMV) grew to 8.2 billion euros in 2019. This means that the 10 billion euros targeted for 2020 can still be easily achieved; in 2023/24 it should be another 20 billion euros. Zalando wants to increase sales to at least EUR 7.5 billion this year.
He puts it this way on Twitter:
Zalando grew by 2 About You in 2019
Zalando now has 31 million customers. The average shopping cart value fell slightly from 57.1 to 56.6 euros.
The app sales are interesting:
According to this, 48% of the trading volume at Zalando takes place via the mobile apps - after 31% and 38% in 2017 and 2018.
In 2019, of the 8.2 billion euros GMV (+ 24%), 3.9 billion euros (+ 56%) were achieved in the apps.
The mobile traffic, on the other hand, is even at 84%. Every time I see numbers from online retailers where the share of mobile traffic is much higher than the share of sales from mobile offerings, I have to say: this is a sign that, for whatever reason, customers are not ready to really make full use of the mobile offer. To put it more clearly: Such a large discrepancy indicates a malfunction in the mobile app. Without a grievance, the numbers would not be the same either, because the context is too different (and therefore the browsing behavior on mobile vs. desktop is different), but they would be much closer to each other.
But like this: Almost half of the retail turnover is via the mobile apps, although almost all of the browsing (84%!) Takes place via them.
The difference in the proportions is astonishing because, unlike many other online retailers, Zalando is not in a bad position per se when it comes to the mobile app. There is a lot to be done in this area.
The e-scooter pioneer Bird equips its app with a payment feature, as reported by Protocol:
Bird is announcing a test of Bird Pay, a new feature that lets people buy smoothies and açaí bowls from local businesses by scanning a QR code with the Bird app. The company says it's already testing it in Los Angeles and Santa Monica (the latter city being notorious as a testing ground in the scooter wars).
Anyone who is surprised by this has not paid attention in recent years. Every provider of an end-customer-oriented mobile app with great ambitions thinks at some point about whether one can take the super app route. Grab is so much more successful than Protocol shows here:
Expanding into payments is also increasingly part of a mobility company’s playbook, despite how seemingly unrelated they may sound. Southeast Asia’s Grab has made a push into fintech, as have other mostly Asian transportation companies. Grab’s financial services arm does everything from payments and rewards to money-lending and insurance.
Micromobility is predestined to go in this direction because the customer contact with active (!) Users is higher than with other Mobility offers.
At the same time, something like this only makes sense with a corresponding flight altitude. This is where Bird's franchise platform model comes into play: This can not only bring the flight altitude (because the local franchisees take over the fleet management) but also in connection with payment and other additional services (which can also be used / integrated by the local partners ..) become a flywheel.
Admittedly, that is a long way off. The main point, however, is that in the mobility sector it is only the micromobility providers and the large ridehailing services that can seriously consider such software platforms. This is another reason why I see more potential in micromobility than, for example, in car sharing.
The question is always: which approach has platform potential.
ADAC and data
The ADAC demands the right for drivers or car owners to pass on all data that manufacturers can use remotely to independent service providers. Only certain data sets should be excluded from this, such as the automatic emergency call system eCall or software updates for the IT security of the car.
Fundamentally comprehensible requirement. But if the end users / end customers / private customers are left with the decision-making authority, which private customer-centric giants will benefit disproportionately from this?
The longer I think about it, the more I think about data portability and which asymmetries it favors (instead of alleviating) a very complex topic.
Media change and networked public
heise on the distribution of sales in the German music industry:
Classic sound carriers such as CD and vinyl continue to fall behind purely digital audio offerings. In 2019, 64.4 percent of sales were achieved in the digital sector. This corresponds to an increase of 20.8 percent. 55.1 percent of sales are accounted for by audio streaming, which has increased by 27 percent. Downloads make up 6.2 percent.
The most amazing thing for many is that the CD still accounts for 29 percent of sales.
One almost always underestimates how long even mutually exclusive developments can run parallel to one another, because they each lie in their own value creation systems and social and personal contexts. The world is big. At the same time, the resilience of the shrinking, old processes naturally weighs the institutions that benefit from them with a false sense of security.
This is why this quote from William Gibson has graced the nineetz.com sidebar since 2006:
The future is here. It's just not evenly distributed yet.
Kuaishou (KWHY-shoh) has built a social network of more than 300 million daily active users in China — an audience three-quarters the size of that for its archenemy Douyin, ByteDance’s domestic version of TikTok. While Douyin has grown by feeding funny videos to bored urbanites, Kuaishou has instead fostered a devoted fan base in smaller cities and countryside with an emphasis on building an online community.
300 million daily active users and in this country one has in fact not heard of it. How many daily users does such a challenger in China become dangerous for the market leader?
And, related to that, what role (strong, weak) does multihoming play for these mobile short video services?
Kuaishou still had 200 million daily active users in May 2019. (See Nexus 3 about Bytedance)
Don't forget: Tencent's WeChat also wants to make TikTok dangerous. (See Nexus 6 about Bytedance vs. Tencent)
Filed Under: Nexus
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