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Hupu And Toutiao (ByteDance)

Today Toutiao acquired 30% of Hupu for ¥1.26 billion, valuing it at ¥4.2 billion.

Formed in 2004, Hupu provides marketing planning, sports events marketing and management, as well as events management. It also operates businesses such as offline eSports events, e-commerce and gaming co-operation. It owns Hupu.com, the sports site with the most page views in China, a retail site for trending sports gear, and the app for Shihuo.cn. More than 30 million users had registered on its websites and apps as of March. [yicaiglobal]

虎扑

A History

Hupu has been active in the capital market for a while.

It was pursuing an IPO in 2016 on the Chinese stock market with a revenue of ¥200 million in 2015.

[Hupu IPO Prospectus]

Before its IPO efforts, Hupu finished its Series C of ¥100 million in 2014 led by Greenwoods (景林) and Series D of ¥240 million in 2015 led by Guirenniao.

Then in 2017, Hupu’s IPO didn’t go through as planned..

..which led to a round of ¥618 million led by CICC (also the underwriter for Hupu’s IPO).

Toutiao + Hupu

Ways to cooperate:

    1. ads – precisely targeting a community with above-average purchasing power and distinguished tastes & shopping categories/habits
    2. video – Hupu’s sports video capabilities/rights/viewers will have synergies with Toutiao’s video infrastructure and recommendations; plus, Hupu will be one of Toutiao’s efforts to march into sporting business
    3. e-commerce: direct sale, and with the help from ads and video; Douyin’s video can lead to shopping on Hupu’s e-commerce platforms

 

 

「Video of the Week」How deep learning is poised to transform the life sciences and healthcare

Applying deep learning in the life sciences
Deep-learning algorithms have proven to be powerful across many aspects of the life sciences and healthcare. Here are eight examples of how they’re being applied throughout the pipeline:

  1. Deep-learning-powered lead optimization: Lead optimization is a key problem. Once you’ve gotten your lead, how do you explore a 1080 space to find a better molecule based on your lead? According to a recent publication, a type of deep-learning engine called an “encoder” can encode structures with a discrete library into a continuous gradient space. That allows you to explore a much larger area of compound space than you have in your discrete library. You can then drop novel molecules out of the gradient space, design small compounds and test them to see how they perform, compared with all of the molecules in your existing library.
  2. Predicting compound activity: One variant of deep learning is known as “one-shot deep learning,” in which you train the algorithm to identify differences, rather than similarities, in data. That requires a lot less training data, which is a critical advantage. A recent paper shows that one-shot deep-learning approaches excel in predicting compound bioactivity based on training with a small set of data. So, if you’re in a new space and don’t know much about the activity of the compounds you’re using, you can still apply these approaches to get a reading of a novel molecule.
  3. Cell assay imaging analytics: Applying deep learning to cell assay imaging is an obvious path to pursue. All of the papers that have been published in this space so far have shown that deep-learning algorithms can do as well as or better than humans in detecting things like phenotypes. Better yet, they’re more efficient. You still need a human who has to be trained initially and can understand the outcomes. But overall, people are freed up to think about higher-level matters, rather than sitting there looking at images.
  4. Toxicity prediction: Deep learning has been shown to be significantly more effective than existing methods in predicting the toxicity of any given molecule. Over time, it learns to look for the specific elements or substructures that are causing the toxicity.
  5. Counterfeit scanning: Deep-learning systems can be trained to detect counterfeit drugs on the web and other sources by examining the package labeling or the pills themselves. They can pick up on little differences between real and counterfeit with a pretty high degree of accuracy. For example, logos or lettering printed on packaging can be slightly off because the presses aren’t exactly the same as the original.
  6. Electronic health record (EHR) analysis: Deep-learning approaches have been shown to significantly outperform traditional methods in doing things like patient cohort identification, readmissions analysis, clinical trial recruitment and clinical predictive modeling from EHR data stores.
  7. Language translation: Clinical trial protocol translation is a critical issue. If you provide a protocol in one language and then have someone translate it into another language, how do you know if they have translated all of the important phrases accurately? You can use deep learning to translate back into the original language and figure out how to normalize all those key criteria in your clinical trial.
  8. Electronic laboratory notebook (ELN) analysis: Many life sciences companies know they have a huge amount of information in their ELNs, but no good way of getting it out. You can have deep-learning systems go in and pull out this information; they can literally read the text in an ELN and figure out what it means.

How deep learning is poised to transform the life sciences and healthcare

 

OYO Countered In China

To be honest, I haven’t tried either brand.

But the game of capital is on.

OYO is grown from India with series B ($100mn), C ($90mn), D ($250mn), E ($1bn) led by SoftBank. Huazhu has participated between D and E; Grab, Didi, Airbnb has participated in Series E separately.

From my understanding, OYO is pursing a model that provides minimum standardization with the least cost while getting data and digitalizing management.

The most valuable thing OYO provides is the traffic (if any), which is where OTA’s profits come from and where hotel chains are good at.

The brand itself tho, doesn’t have much power. China’s overall hospitality standard is higher than India’s I think (with players like Jinjiang, Huazhu, etc.)

OYO’s rapid expansion in China might make it worse.

But it is really big – said to have 10k+ hotels and 450k+ rooms on its website.

It now has a three-tier branding: 轻享，智享，尊享

Branding-up and providing more values is really important. Hotel owners may end up with less profit in the long-run.

It’s like imperialism in the hotel sector.

The traditional hotel sector in China has reacted with their own exploration in “light franchise” (but might be late for this game).

H hotel by Huazhu

轻简 by Botao

轻住 from MeituanDianping

OYU by TongchengYilong

 

 

China’s Fresh Produce E-commerce (2)

previous post – China’s Fresh Produce E-commerce (1)

Second Round

The two words that characterize the second (current) model is “front warehouse” (前置仓).

By managing more distributed front warehouses (mostly in cities), the fresh produces e-commerce companies can usually deliver within 2 hours after an order is placed.

The model could be exemplified by the current focus of Hema (盒马鲜生) and MissFresh (每日优鲜). The difference – Hema’s warehouses are also consumer-facing stores; MissFresh’s warehouses are expanding much faster and many have no “experience store” functions.

Hema is financed within Alibaba (consolidated in earnings reports) and MissFresh has raised several hundred millions from Tencent.

Hema

Hou Yi (侯毅), the CEO and founder of Hema, worked for JD.com and in charge of JD logistics, prior to joining Alibaba. He has rotated to the O2O (online to offline department) and was the founder of the predecessor of JD Daojia (京东到家), JD’s delivery team. It has been rumored that firstly HOU proposed to Richard Liu, the CEO and founder of JD.com, about the idea of Hema; unfortunately, LIU did not approve that idea at that time. Later HOU approached ZHANG You (张勇), the CEO of Alibaba Group, and get offered to join Alibaba and try out his idea. [equalocean]

Since its beginning in 2016, Hema has now expanded into 130 stores in 19 cities as of March 2019.

Tmall’s fresh stores have also been consolidated into Hema’s operations, announced in December 2018. (meanwhile, JD’s fresh produces team was combined with 7-fresh in the same month)

Its operation summary compared with competitors provided by EqualOcean.

MissFresh

Jan 2017, Series C, $100 million led by Lenovo Capital

Sep 2017, Series C+, $230 million led by Tiger Global and Genesis Capital

Dec 2017, Series D, said to be $500 million; another report said $200 million to spin off 便利购 (the unmanned shelves)

Sep 2018, Series E, $450 million led by 高盛（GSIP）、腾讯、时代资本、Davis Selected Advisers

Tencent has invested four times so far.

Its core competitiveness lies in its front warehouse network, inventory management system and local community operation. MissFresh has an average duration of inventory of 2.5 days.

MissFresh is targeting gross margin at ~20% in the long-term while maintaining an operating margin at 10-15%.

So we can see that attempts are made to locate “warehouses” closer to consumers and to shorten the waiting time to ~30min.

Alongside the 1st and the 2nd rounds, there is another attempt – not necessarily new but will take some time to stabilize, if possible) – to combine 1) mainline logistics, 2) city delivery networks, 3) front-warehouses + community stores, all facilitated by digitalized and AI-driven systems.

 

China’s Fresh Produce E-commerce (1)

Overall Market Size And Online Percentage

Fresh produce has long been seen as an undeveloped area within e-commerce.

The penetration rate of e-commerce in the Chines apparel market is ~35% in 2017, while the fresh produce category’s is only in the single-digit range (but growing fast!).

The overall size of fresh produce market in China is around 5,000 billion RMB. So the online sales is ~1% in 2015 and ~4% in 2018.

First Round

The first wave of exploration is an extension of traditional e-commerce platform + specialized logistics (cold chain).

Miao Fresh (by Tmall, Alibaba) and JD Fresh (by JD) are the two examples (and first movers) in this round.

Self-built logistics has been one of JD’s core capabilities for a long time. And the war in fresh produces, requiring an upgrade in cold chain, has made JD Fresh a very competent player in this field (besides the upgraded potential in logistics-as-a-service) .

JD Cold Chain Logistics | Source: JD Fresh Presentation

Tmall seems to have a better position in recruiting overseas/premium sellers (cherries, lobsters, crawfish, etc.)

Meanwhile, Alibaba (Tmall) has been investing in Yiguo continuously. In March 2016, Yiguo raised ~$250 million Series C from Alibaba and KKR.

Yiguo’s subsidiary ExFresh (安鲜达), China’s largest cold-chain company established to serve the fresh food via e-commerce, according to a new release from KKR in 2016.

Source: exfresh.com.cn

And Suning, a strategic partner with Alibaba and a very strong player in 3C retailing, led a round of $200 million (Series C+) for Yiguo in Dec 2016.

Then in Aug 2017, Yiguo finished its Series D of $300 million from Tmall (Alibaba).

But the battle in fresh produces is more than the battle in cold chain + traditional e-commerce. It involves exploring the new format of retail.

And so comes the Second Round…

How Do E-commerces Generate Revenue? (3)

(1) and (2) in this series can be seen as a large category, where the companies are not holding inventories.

So the other category of e-commerce companies (e.g. JD.com) or the original Amazon model – is to hold inventories and to profit from the differences between retail and wholesale prices.

The goods will appear both in top-line revenues and in COGS – where as the marketplace model doesn’t include any value of goods sold on its platform.

For 2016, 2017 and 2018, over 90% of JD’s revenue comes from online direct sales or net product revenues.

net product revenues (¥, millions): 237,944 | 331,824 | 416,109

Usually they

    1. start with one or a few categories of goods (e.g. books for Amazon and electronics for JD)
    2. they could expand into other categories to be an “everything’s store”; or stay within their specialized categories and grow into highly related services (to better serve their distinct customers).
    3. have lots of investments in their infrastructures; then it becomes natural that they could only provide the logistics, marketing and other services instead of purchasing everything first. The packaged services are then accounted as revenues for JD/Amazon.

Because the fees are usually based on total value of goods (commissions), the services revenues are also related to GMV.

net service revenues (¥, millions): 20,346 | 30,508 | 45,911

Meanwhile, for 2016, 2017 and 2018,

JD’s total GMV (¥, billions): 939.2 | 1,294.5 | 1,676.9

After deducting the direct sales figures, we could see the revenue take-rate for pure services are 2.9% 3.2% 3.6%

JD’s discussed its business model in its F-20 for 2018

Since founding our company, we have focused on developing our online direct sales business as well as building our own fulfillment infrastructure, including last mile delivery capability, all based on our proprietary technology platform to support our operations. As our online direct sales business grew substantially in size, we launched our online marketplace to complement it and expand our product offerings, leverage our established fulfillment infrastructure and technology platform and ensure a superior customer experience. The combination of our online direct sales and online marketplace, and our own nationwide fulfillment infrastructure and technology platform, make us a uniquely strong player in China’s online retail industry in terms of providing superior customer experience.

Leveraging the significant scale of our business, cutting-edge technologies, and our well-established retail infrastructure, we have also begun to offer comprehensive services that complement our core business and create significant value for a wide range of business partners. Ultimately this will boost business development and the overall customer experience.

Online Direct Sales

In our online direct sales business, we acquire products from suppliers and sell them directly to customers. We started selling computer products online in 2004 and introduced mobile handsets, consumer electronics products and auto parts and accessories by 2007. We significantly expanded our product offerings in 2008 with home appliances and a wide array of general merchandise product categories, and have been continually adding new products and categories since then. As we now offer a wide range of categories through our online direct sales business model, net revenues from electronics products, which include computers, mobile handsets and other mobile digital products, and home appliances, have declined as a percentage of our total net revenues.

Retail Infrastructure

Online Marketplace. In our online marketplace business, third-party sellers offer products to customers on our online marketplace and pay us commissions on their sales. We launched our online marketplace in October 2010, and have been adding new products and services since then. As of December 31, 2018, there were more than 210,000 third-party sellers on our online marketplace. We provide transaction processing and billing services on all orders placed on our online marketplace and require third-party sellers to meet our strict standards for authenticity and reliability. We tag certain top stores on our platform as “JD Haodian ( 京东好店 ),” based on third-party merchants’ quality of service during the entire purchase process. Such certification can help our top merchants improve their sales volumes on the platform. Furthermore, it sets a benchmark to encourage other merchants to improve their quality of service. We aim to offer customers the same high-quality customer experience regardless of the source of the products they choose.

Marketing Services. Leveraging our AI capabilities and the comprehensive dataset accumulated from a wide range of business scenarios along the entire value chain, we provide a variety of marketing services to suppliers, merchants and other partners in the ecosystem through our proprietary advertisement technology platform.

In 2017, we started to offer our suppliers and merchants a new fully-automated marketing platform that can make targeted product recommendations to users on www.jd.com and our mobile apps, and across our content partnership network, driving new customers and repeat purchases for advertisers automatically. Powered by AI, the platform only requires advertisers to input total budget, unit bid price and optimization goals to market to their targeted audiences, which enables advertisers to lower their operating costs and increase their returns.

In order to provide our partners with better targeted marketing and broader access to advertisement resources, in addition to our successful partnership with Tencent, Baidu and ByteDance, we also formed strategic partnerships with other leading mobile internet companies such as Qutoutiao and iQIYI, with an aim to leverage these companies’ powerful big data resources, massive user bases and AI-driven technologies to strengthen collaboration in precision marketing, user access points and content-driven marketing.

JD Logistics Services. In April 2017, leveraging our advanced technology and logistics expertise, we established JD Logistics, a business group under JD.com, to provide logistics services to businesses across a wide range of industries including those beyond e-commerce. We have opened up our technology-driven fulfillment infrastructure by offering comprehensive supply chain solutions to third-party sellers on our marketplace and to merchants that do not sell products on our online marketplace, including warehousing management, transportation, delivery, after-sale services, and logistics technology solutions, including cloud-based service and data analytics, or a combination of these services. Our logistics services to third parties have experienced rapid growth and have been well received by major clients such as Nestle, NetEase, Gree, and others. We are dedicated to developing an effective, environmental-friendly, innovative and smart “green logistics system” through developing and promoting the use of innovative and environmental-friendly materials and a series of technological innovations.

In the second quarter of 2018, to reduce product-to-customer distance and provide customers with innovative delivery options, JD Logistics launched the “Flash Delivery” initiative, offering delivery times ranging from several minutes to about one hour for selected merchandise in certain areas through optimally allocating merchandise across its distribution network, including front-line metropolitan distribution centers, delivery stations and partners’ offline stores, based on its analysis of customer demands. Moreover, in October 2018, JD Logistics opened up its leading logistics network to consumers, offering parcel delivery service to users in certain regions. Leveraging JD Logistics’s extensive delivery network, users in these areas can conveniently send items intra-city and throughout most of mainland China with JD Logistics’s same fast and reliable delivery service.

JD Property Management Group. In 2018, we established our property management group, JDPM, which owns, develops and manages our logistics facilities and other real estate properties, to support JD Logistics and third parties. JDPM has unique advantages to secure scarce land resources as we continue to help boost economies across China through creating employment opportunities and contributing tax, among others. JDPM aims to develop its logistics assets portfolios while maintaining strong capital discipline. With the expansion of asset portfolios, we will adopt a capital recycling strategy through our fund management platform and other partnerships, such as our partnership with GIC, Singapore’s sovereign wealth fund. See “Item 5.B. Operating and Financial Review and Prospects—Liquidity and Capital Resources.” We believe this strategy will help further expand our asset portfolios, minimize our related future capital expenditures and enhance our returns.

Omni-channel Initiatives. To achieve our “Boundaryless Retail” vision, we are exploring a variety of omni-channel integration opportunities and innovative business models. Leveraging our well-established retail infrastructure, we believe we are well-positioned to create an enhanced shopping experience for consumers and improve efficiency for our business partners.

We believe we are well-positioned to provide omni-channel solutions to customers and offline retailers in select locations in China by capitalizing on our strong online presence and leveraging Dada’s crowdsourced delivery system. Dada is one of our equity investees and its online-to-offline supermarket platform JD Daojia, which was JD’s asset before our transaction with Dada in April 2016, leverages the expanded delivery network, focuses on the location-based mobile commerce sector and collaborates with offline supermarkets, convenience stores and other local businesses to provide consumers with a speedy premium shopping experience. As of December 31, 2018, our joint venture, Dada-JD Daojia, had partnered with more than 100,000 stores from leading supermarket brands, including Walmart, Yonghui, Carrefour and CR Vanguard, by leveraging Dada’s crowd-sourcing delivery network. Dada-JD Daojia is China’s leading on-demand logistics and omni-channel e-commerce platform.

In June 2016, we entered into a series of agreements in relation to our strategic alliance with Walmart. We have collaborated with Walmart on e-commerce, including launching a Sam’s Club Flagship Store and Walmart China Flagship Store on JD.com, Sam’s Club Global Flagship Store, Walmart Global Flagship Store, and ASDA Flagship Store on JD Worldwide, and a one-hour delivery service from Walmart Stores in select cities through the JD Daojia app, as well as leveraging each other’s supply chain to enhance product selection for customers across China. We also experimented on other omni-channel opportunities, aiming at offering shoppers across China faster and more convenient access to high-quality products through multiple channels.

To provide customers with a more dynamic and interactive integrated omni-channel shopping experience, we have enabled some of our offline partners with a variety of the latest technologies such as facial recognition, product recognition, tracking system for customers’ in-store activities to name just a few. We have established a closed loop to accumulate a large volume of offline shopping data, and through further analysis of the integrated online and offline dataset, we can offer differentiated products in each offline franchise store that best suit potential customer demands. For instance, in August 2018, we launched a cooperation with China-based home furnishing retailer Qumei. Leveraging our extensive product selection, Qumei expanded its offering from furniture to a wide range of home products. Our ability to use big data to build accurate customer profiles has enabled Qumei to more effectively match its product selection with consumer demand. With the help of our cutting-edge technologies such as AI-based facial recognition and AR features, the cooperation enables Qumei to deliver a fully-interactive shopping experience in its traditional offline stores.

7FRESH, our offline fresh food market brand, is an example of a real-world trial of our “Boundaryless Retail” vision, the idea of enabling consumers to buy whatever they want, wherever and whenever they want it. In December 2017, we opened our first 7FRESH store in Beijing’s Yizhuang suburban area. Integrating advanced supply chain management know-how and cutting-edge storage technologies, our 7FRESH store is able to deliver a unique shopping experience by offering many fresh products (including fruit, flowers, vegetables and quality fresh seafood), providing food preparation and catering services, and making available a 30-minute delivery service for customers within three kilometers of the store. As of March 31, 2019, we opened 13 7FRESH stores in 8 cities.

We believe our 7FRESH business model will continue to evolve as we strive to pursue an enhanced shopping experience for our consumers and partners by exploring a variety of omni-channel opportunities, integrating quality products with superior services and providing fresh produce supply chain solutions to our partners.