Rakuten wesentlich besser als Rocket
vor 5 Tagen
Die von Rakuten betriebene Flohmarkt-App "Rakuten Rakuma" und "Komehyo" (im Folgenden "KOMEHYO" genannt), einer der größten Wiederverwendungsdienste für Markennamen in Japan, bieten einen bemerkenswerten Service "Rakuma Appraisal Service"Dies ist ein Service, der es Benutzern, die Produkte auf "Rakuten Rakuma" gekauft haben, ermöglicht, bei Bedarf eine Produktinspektion (Produktprüfung) anzufordern. Professionelle Gutachter prüfen die Produkte von mehr als 400 Marken, die KOMEHYO einkauft, mittels visueller Inspektion und KI.
Dieser kostenlose Service (Anmerkung 1) mit dem Ziel, den Vertrieb gefälschter Produkte zu unterbinden, wurde am 2023. September 9 in den Probebetrieb aufgenommen. Während wir die Verbesserungen wiederholen, um die Benutzerfreundlichkeit zu verbessern, planen wir, in naher Zukunft auf den tatsächlichen Betrieb umzusteigen.
Die Redaktion von Rakuten Today führte ein Interview über einen solchen "Rakuma-Bewertungsservice". Wir haben Yukihiro Matsunami von KOMEHYO und Ryosuke von Rakuten Rakuma, die für das Geschäft dieses Dienstes verantwortlich sind, über die aktuelle Situation des Marktes für wiederverwendete Waren in den letzten Jahren und Maßnahmen zur Verhinderung des Zustroms von gefälschten Produkten auf den Markt interviewt.
https://rakuten.today/blog-ja/rakuma-komehyo-2023-j.html?lang=ja
https://startup.jobs/@cabify
https://www.intelligenttransport.com/...-demand-shared-mobility-lezs/
November 2, 2023
In the fiercely competitive world of retail and e-commerce, Rakuten Advertising and Cotton On brilliantly disrupted the traditional shopping calendar with this innovative campaign. As consumer habits shifted and competition soared, this strategic partnership saw an opportunity to create a shopping event that would capture attention and drive unprecedented growth.
By leveraging ShopBack's 5th Birthday celebration, they orchestrated a multifaceted campaign that included exclusive cashback deals, viral TikTok content, podcast takeovers, and collaborations with major financial institutions like Westpac. The results proved its success, with ShopBack's Birthday outperforming even the mighty Black Friday in terms of sales and engagement.
This campaign exemplifies how creativity, strategic collaboration, and a deep understanding of consumer behavior can revolutionise the retail landscape. By inventing a new shopping holiday, Rakuten Advertising and Cotton On demonstrated their commitment to innovation and their ability to achieve remarkable results in the affiliate marketing realm.
https://hellopartner.com/2023/11/02/...dvertising-cotton-on-shopback/
SHOPBACK X PUMA
https://ph.puma.com/ph/en/shopbackph
Profit per Share Diluted Profit per Share
Six Months Ended September 30, 2023 JPY 93.26
Six Months Ended September 30, 2022 JPY 77.90
https://contents.xj-storage.jp/xcontents/AS92404/...107123126301s.pdf
PUBLISHED MON, SEP 25 20239:14 PM EDT
HTTPS://WWW.CNBC.COM/2023/09/26/...-SET-TO-REDUCE-LOSSES-IN-2023.HTML
BACKED BY WORLD-CLASS INVESTORS, BOARD MEMBERS AND ADVISORS
INCLUDING TWO NOBEL PRIZE WINNING ECONOMISTS
PAYPAL
BLACKROCK
BAIN CAPITAL
DST GLOBAL
NBCUNIVERSAL
COMCAST VENTURES
CAPITAL GROUP
GREYCROFT
HEADLINE
TPG
RAKUTEN
SOUND VENTURES
HTTPS://WWW.ACORNS.COM/ABOUT/
BACKED BY WORLD-CLASS INVESTORS, BOARD MEMBERS AND ADVISORS
INCLUDING TWO NOBEL PRIZE WINNING ECONOMISTS
PAYPAL
BLACKROCK
BAIN CAPITAL
DST GLOBAL
NBCUNIVERSAL
COMCAST VENTURES
CAPITAL GROUP
GREYCROFT
HEADLINE
TPG
RAKUTEN
SOUND VENTURES
HTTPS://WWW.ACORNS.COM/ABOUT/
Consolidated Revenue 471.0 518.4 +10.1%
Internet Services Segment 264.5 301.2 +13.9%
FinTech Segment 162.5 184.6 +13.6%
Mobile Segment 84.5 88.7 +5.0%
Adjustments -40.5 -56.0 -15.5
Non-GAAP
Operating Income (Losses) -83.0 -41.0 +42.0
(Ref.Excluding Mobile Segment &
Investment Business) 39.5 48.5 +22.8%
Internet Services Segment 16.6 16.6 +0.3%
FinTech Segment 21.1 28.6 +35.8%
Mobile Segment -117.6 -81.2 +36.4
Adjustments -3.1 -5.1 -2.0
IFRS Operating Income (Losses) -94.2 -54.5 +39.7
NOVEMBER 9, 2023
Rakuten Mobile disclosed plans to achieve EBITDA breakeven in 2025, with capex in 2023 forecast to be lower than the original guidance of JPY200 billion ($1.3 billion).
Chairman Mickey Mikitani said on an earnings call the company is progressively worked to reduce expenses, primarily network-related costs and used new roaming contracts as an opportunity to control capex.
Mikitani explained the company is transitioning from its build phase to one focused on lean and solid management, cost reductions and customer acquisition.
Rakuten Mobile is also looking to improve coverage by expanding existing bandwidth including 700MHz spectrum early in 2024 and optimising its network, he said.
https://www.mobileworldlive.com/rakuten/...akuten-capex-below-target/
Mizuho Financial Group Inc. plans to increase its investment in Rakuten Group Inc.’s online securities arm, which isn’t proceeding with an initial public offering for now.
Japan’s third-largest banking group will raise its shareholding in Rakuten Securities Inc. to 49%, slightly more than a year after it bought about 20% of the firm and formed a business alliance. The deal is valued at 87 billion yen ($576 million) and scheduled to close on Dec. 15 subject to regulatory approval, according to a joint statement on Thursday by Mizuho and Rakuten.
https://finance.yahoo.com/news/...e-rakuten-securities-072815436.html
FY2024: Aiming to Establish Self-Funding through
1. Significant improvement in Mobile
Segment FCF
EBITDA to improve materially
Significantly reduced Capex after FY2024
2. Growing Internet Services FCF
EBITDA to continue to improve
Cash conversion cycle to shorten
3. Growing CF from FinTech
Dividends, Management fee, etc.
(FY2022: approx. JPY 70bn)
CF from equity-related financings if necessary
23Q3CEOPPT_E.pdf
https://global.rakuten.com/corp/investors/
By Juan Pedro Tomás
November 9, 2023
Rakuten Mobile said it attracted 192,000 new mobile customers only in October
Japanese operator Rakuten Mobile expects to reach 8-10 million mobile subscribers by the end of 2024, the telco said in its earnings statement.
The telco added a total of 400,000 subscribers since August, ending October with 5.4 million, the company said in its earning statement.
In October alone, the telco said it attracted 192,000 new mobile customers.
https://www.rcrwireless.com/20231109/carriers/...-million-subscribers
17 hours ago
An e-commerce platform lives or dies by its ability to connect customers with the products they need. For decades, this task has been largely accomplished by the humble search bar – input a keyword or two, and be rewarded with a list of items with matching terms.
But the world of tech never stands still – especially in the age of AI. As a company with e-commerce close to its heart, Rakuten’s talented engineers have embarked on a mission to take search to the next level. Lee Xiong leads the deep learning initiatives at Rakuten Group, aiming to infuse Rakuten’s search and recommendation technology with the latest AI technology. Xiong is a pioneer in applying deep learning technology at a large scale and had worked on Bing at Microsoft before joining Rakuten. Today, Xiong’s work span an even grander scope, covering a broad portfolio of Rakuten products across multiple industries.
“RAKUTEN GROUP IS A FANTASTIC PLAYGROUND FOR ENGINEERS AS IT HAS ONE OF THE WORLD’S MOST DIVERSE PORTFOLIO OF PRODUCTS, RICH AND HIGH-QUALITY DATA AS WELL AS AMPLE COMPUTING POWER. ENGINEERS HAVE THE OPPORTUNITY TO AMPLIFY THEIR IMPACT BY APPLYING STATE-OF-ART TECHNOLOGIES TO CREATE VALUE FOR OUR CUSTOMERS IN JAPAN AND WORLDWIDE.”
-TING CAI, CHIEF DATA OFFICER OF RAKUTEN GROUP, INC.
What’s new in search?
Keyword matching has long been a staple of any website or app with a search bar, but it is defined by its limitations. A user searching for a specific keyword will typically only be presented with products that contain that exact keyword, leaving out words that might be synonyms or slightly different phrasing.
Xiong’s team is looking to improve this by adopting something called semantic search, which does exactly as the name suggests: It conducts searches based not just on the words searched, but what they mean.
“Traditionally, users have needed to synthesize their query into a few keywords, maybe [T-shirt, cotton]. Now, they can search for a [cotton T-shirt for kids with animal patterns] – complicated queries that go beyond three or four words – and they will still get relevant results.”
The team began trialing the tech at Rakuten’s apparel e-commerce platform, Rakuten Fashion. With its diverse array of fashion products, the site proved the perfect test ground for revolutionizing search.
“This is a disruptive technology that advances the paradigm of search, so we need to be careful not to surprise merchants who might not be used to it,” Xiong says. “We decided to start with Rakuten Fashion, and we received a lot of support from them. They were very brave in trying it out!”
Xiong gave another example of a search query in Japanese along the lines of [casual socks that aren’t too thick made from comfortable cotton]. On Rakuten Fashion, the query produces a selection of closely matching items while a leading competitor’s site returns no results for the same query.
“The only limit is whether or not the platform carries it in their inventory with an accurate description,” he says. “Phrases that on other platforms will land you zero results; this system will always give you something.”
Semantic search: How does it work?
Xiong explains that the system is much more than a conversion layer that translates complex queries into simple keywords.
“The secret behind it is an academic term called dense retrieval,” he explains. “On a high level, what it does is it vectorizes natural language so that it can represent a search query or an inventory item in a vector.”
In a machine learning context, vectors are simply a way to represent a word or an item as a list of numerical values. Words or items with similar meaning will be close in the vector space. “It’s like neurons firing signals – a kind of representation that’s understandable by deep learning models.”
When input data is ‘vectorized’ in this way, it can be processed mathematically, and machine learning can take place.
“So these vectors have hundreds of dimensions, including all kinds of semantic meaning, ranging from categories and colors to age and more,” Xiong continues. “The magical part is that we don’t have to manually specify all these dimensions. The deep learning model identifies the most important dimensions by itself.”
Because everything is in a vector space, any search query will always be able to find the closest match in a given inventory. “It eliminates zero-hit scenarios.”
Vectorizing Rakuten’s high-quality e-commerce data
“For any embedding of the vectorization models, the key is to find pairs,” Xiong reveals. “For example, given [A], we want [B], and not [C]. So we just need to find [A], [B] and [C].”
Xiong’s team can utilize Rakuten’s wealth of search and purchase data to find these pairs and train the model.
“In the context of search, [A] would be the query. Given this query, which item does the user want [B]? Which item do they not want [C]? Which item the user wants is easy, if you know what item the user ends up purchasing from among the search results. “
Now, the model has worked out [A] and [B]. “Which item this user doesn’t want – you can, for example, start with randomly picking an item from the inventory that the user didn’t purchase,” he explains. “With that information, the model will learn: Given this, I should be looking for this type of item.”
A major benefit of using deep learning is that this entire process happens autonomously.
“With classic search technologies, you would need to find out all the terms that match and write many rules for ranking. But with deep learning, you throw all of these problems to the model, and it figures out how it should match all the terms by itself. Sometimes the user might have a typo or a different way of describing an item, but the model will still understand.”
The key to making this process a success lies in the quality of the training data.
“One of the biggest challenges for any deep learning work is creating very high-quality training data for the model that we want to build,” he reveals. “In this case, we need to create a set of very high-quality Japanese user e-commerce purchase behavior data, together with catalog data containing item details such as the title, description, reviews, price and more.”
It’s here that access to Rakuten’s powerful e-commerce data reveals its true potential: “While it’s challenging, I actually think Rakuten is in the best position to solve that challenge. Other companies will find it even more difficult, if not impossible.”
Letting the results speak for themselves
Initial results from the team’s experiments show promise: Rakuten Fashion enjoyed a 5% jump in GMS from search.
“It’s because we have a deeper understanding of both our users and our inventory,” Xiong explains. “Now that our results have become a lot more relevant to what users want, they are able to find what they need and make the order.”
Another important area of e-commerce that Xiong and his fellow research scientists are also working on are product recommendations. The team has shipped deep learning-driven recommendations on Rakuma, Rakuten’s second-hand goods marketplace.
“Because we can vectorize all the inventory, we can find similar inventory items. We can also take into account the purchase or browsing history of the user and represent the user as a vector, and find which items are most likely to be purchased next using dense retrieval.”
These experiments have also yielded impressive results, with Rakuma seeing a 30% improvement in conversion through the home page user feeds.
Xiong is excited to see where the technology could be applied next.
“Similar technology can be shared between different services, so we can develop once, and use it many times. It’s pretty economical in that sense,” he reasons. “I think many Rakuten services will benefit, as long as they have some kind of search or recommendation function. Rakuten Ichiba, Rakuten Books, Taiwan Rakuten Ichiba, and even Rakuten Music – we can support them.”
Pioneers of Japanese AI
One concern often raised in the field of AI is the dominance of English-based training data, and how other languages could be left behind. Xiong’s work bucks that trend: “Here, because I get most of the data in Japanese, the model actually works much better in Japanese.”
But the team’s ambitions don’t stop with Japanese market.
“Our next goal is to make the model multilingual. We want to support searches so that even if our inventory is fully in Japanese, you can still search in English and other languages,” he says. “I don’t think a translation layer for search is necessary. The multilingual vectors are the most scalable representation of information.”
Competing on the world stage
Xiong believes that Rakuten has the right ingredients to drive AI tech on a global level.
“First of all, you need a strong team of people who know how to develop this technology,” Xiong explains. “Subsequently, the training data is key – and Rakuten really has an advantage in that area because of our extensive e-commerce data – we could construct the most comprehensive e-commerce Japanese training data for any such deep learning model. I don’t think even other major tech companies could build such a strong e-commerce dense retrieval search engine as Rakuten, because they lack the kind of training data that Rakuten has.”
Xiong isn’t shy about his team’s ambitions.
“The goal of my team is to deploy cutting-edge deep learning technology for search, recommendations and other applications, with the aspiration of being on par with major tech giants like Google, Microsoft, and Meta,” Xiong declares. “We have already achieved impressive results and are actively transitioning Rakuten into a leading tech company.”
https://rakuten.today/blog/...-transforming-how-we-find-products.html
Nov 9, 2023
Tokyo, Japan – Rakuten Symphony, Inc, today announced the integration of Rakuten Symphony Symcloud Storage – its enterprise-grade, highest-performing storage for Kubernetes – as a foundational software-defined storage (SDS) in Google’s Distributed Cloud Edge. This development further enhances the process of running Google Kubernetes Engine (GKE) clusters on the dedicated edge hardware provided and maintained by Google Cloud. It also represents a significant advancement in delivering sophisticated and integrated cloud services to businesses globally.
Commenting on this collaboration, Partha Seetala, President, Cloud Business Unit for Rakuten Symphony, said, “This is a step forward in our commitment to technological excellence and innovation. Rakuten Symphony Cloud Native Storage – a pre-certified solution for Google Distributed Cloud Edge – acts as a local storage abstraction layer on each Distributed Cloud Edge node, making its local storage available to workloads running on other Distributed Cloud Edge nodes. The integration ensures businesses the ability to effortlessly roll out the solution across multiple locations, removing the necessity for manual intervention across various sites, and allowing for a more streamlined and cohesive deployment experience.”
https://www.telecomtv.com/content/...le-distributed-cloud-edge-48923/
https://www.jiji.com/jc/article?k=000000104.000035783&g=prt
https://dealflow.es/issue/382/...-iesa-acquired-jme-prepares-new-fund
August 2, 2023
https://www.eu-startups.com/2023/08/...onized-fleet-by-2025-in-spain/
Rakuten Viber unveils first Filipino brand Ambassador, Gabbi Garcia, in line with its Superapp vision
The multifaceted star shares how the app is helping her connect, inspire, and do more
November 10, 2023
Rakuten Viber has handpicked multifaceted star and Sparkle artist Gabbi Garcia as its first-ever brand ambassador in the Philippines, which is one of the leading communications app’s key growth markets.
“We are excited to be working with Gabbi to represent Rakuten Viber in one of our most dynamic markets in the world. With millions of active users daily, we see the Philippines as a crucial driver of connections and conversations. Gabbi couldn’t be any more perfect for the role as her on-the-go lifestyle didn’t stop her from strengthening her relationships with those who matter most. She has also served as an inspiration to many young Filipinos who look up to her on how she carries herself with authenticity and creative spirit,” shares David Tse, Senior Director for APAC at Rakuten Viber.
https://orangemagazine.ph/2023/...ia-in-line-with-its-superapp-vision