Fresenius Seeks €1.1 Billion for Stake in Dialysis Company
The German group is offering 10.5 million shares in Fresenius Medical Care to raise around €500 million, and about €600 million worth of three-year zero-coupon exchangeable bonds, according to terms of the deal seen by Bloomberg News.
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San Francisco Chronicle
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Fresenius: Q2 Earnings Snapshot
BAD HOMBURG, Germany (AP) — BAD HOMBURG, Germany (AP) — Fresenius Medical Care AG (FMS) on Tuesday reported earnings of $255.3 million in its second quarter. The Bad Homburg, Germany-based company said it had profit of 44 cents per share. Earnings, adjusted for non-recurring costs, were 52 cents per share. The dialysis services provider posted revenue of $5.44 billion in the period.
Wall Street Journal
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Fresenius Medical Care Confirms Guidance After Sales, Profit Rise
Fresenius Medical Care FME 0.07%increase; green up pointing triangle said it is on track to deliver its full-year targets after it posted an increase in both revenue and profit for the second quarter. The German dialysis group on Tuesday booked revenue of 4.79 billion euros ($5.54 billion) for the second quarter, 7% higher organically than in the prior-year period and against analysts' forecasts of 4.75 billion euros, according to consensus estimates compiled by Vara Research.
Business of Fashion
12 hours ago
- Business of Fashion
Unpacking Fashion's New AI Marketing Toolkit
Ever since Mango started to use Smartly, an AI-driven performance marketing tool, for social media ads, its revenue generated by these ads has quadrupled. Using the platform, Mango's design team is able create brand templates that can be easily toggled between different versions of a photo of a dress, for example. Whereas before, creating different images required taking photos of different outfits in multiple settings. The womenswear brand is far from the only fashion player to have figured out how to use artificial intelligence to optimise and boost the efficiency of advertising. Companies including sneaker retailer Foot Locker and German e-commerce giant Zalando are using AI for everything from product image backgrounds to quick-turnaround campaigns that align with social media microtrends. Consumers go through content — and trends — so quickly today that advertisers struggle to keep up with analog creative production alone. AI's rapid generation capabilities help marketers produce more varied ads so viewers are less likely to tire of them as they scroll social media's endless feeds. But figuring out the right formula to use AI is no small feat. New tools seem to pop up weekly and while some platforms excel at automatically generating images, they may lack the editing tools marketers need to ensure visuals stay on-brand. Brands must consider their unique needs — which can range from visualising creative ideas for a campaign and enhancing their product imagery with dynamic backgrounds to automatically targeting different audiences with different versions of the same ad — in order to determine the ways in which AI could amplify their creative production. The most accessible AI tools are ChatGPT and Adobe's Firefly, which many agencies already use for easy image generation. Others favour more advanced platforms like Midjourney and Leonardo AI for greater creative control and experimentation. Meanwhile, AI agency Maison Meta and Zalando aggregate multiple AI technologies into their own platforms, curating the best tools for specific tasks like background generation and editing under one interface — Maison Meta also hosts workshops for clients like Mango to teach them how to use its toolkit. More advanced tools are able to connect the dots between image generation and ad optimisation on social media. Meta, for instance, has its own suite of AI tools called Advantage+, which includes creative enhancements that allow brands to customise their ads by animating imagery, adding music or enhancing copy. Platforms like Smartly and Pixis are also dedicated to optimising the creative content in ads, allowing marketers to create visual templates that can be automatically updated to cater to different customers across platforms like Meta, TikTok, Amazon and more. Footwear retailer JustFab, for example, was able to create a template for its broad product catalog by removing the backgrounds across all images and generating new seasonal scenes across using Smartly. 'It's the consumption happening now through social media that requires a volume that the marketing industry wasn't prepared for,' said PJ Pereira, creative chairman of advertising agency Pereira O'Dell. Lead With Human Creativity Regardless of the AI tools, human creativity and artistic direction must come first. 'This is not the end of the creative director or the creative teams,' said Jason Widup, senior vice president of marketing at AI advertising company Pixis. 'What we're seeing is the creative teams want to create new, interesting, fun concepts. They want to be pushing the envelope. And AI still doesn't have human taste.' What this looks like in practice is using traditional brainpower to come up with core campaign concepts, and then using AI to see how far the idea can be pushed — testing out how an image would look on Mars, for instance, or with a giraffe alongside a model, said Pereira. 'You can think and see in real time,' he said. While in the past, campaign generation could be costly, AI enables marketers to test multiple ideas at one time and see what works best. 'The biggest leap currently as a creative industry is the fact that the risk of trying something is infinitely smaller,' said Pereira. Turn One Asset into Countless Variations Proponents of the technology still don't trust AI to fully take over ad production, said Pixis's Widup. Instead, many feed product assets and brand guidelines into tools like Smartly and Pixis, and then use the platforms to iterate on existing ideas and imagery to change backgrounds, colours or placement to create different versions of an ad that can be personalised and targeted across audiences. For Zalando, using its own AI tools to showcase products in a relevant context — like a hiking boot on a mountain, or even to turn static imagery into video — makes all the difference in driving customer engagement. This, in turn, helps them better understand what their customers want to see, which leads to fewer returns and triple the conversions. 'We do not have endless hands, and we do not have endless time and endless budget,' said Matthias Haase, vice president of content solutions at Zalando. Localise in Real Time Beyond creative content, AI can be leveraged to reach the right users at the right time. Whereas in the analog days of digital acquisition, consumers were repeatedly served the same ads, brands can now automate when viewers are served a piece of content — whether for a complementary product to one they already own or a specific handbag colour they've been searching for. Most of Zalando's AI-generated content is market-specific to cater to local moments like Oktoberfest in Germany or regional running events, for example. These quick-turnaround, targeted campaigns typically take four days to produce, compared to six to eight weeks for traditional ad campaigns, and made up 40 percent of Zalando's campaigns in 2025. Its product description pages will eventually be customised to each geographical market using AI, showing different outfit combinations for French versus Polish shoppers, for example, and swapping out models that are recognised in different regions using digital twins. Build Content that Responds to Context For platforms that connect AI image generation with targeting such as Smartly, brands can reach customers even more dynamically by making each element of an image changeable depending on the customer who is interfacing with it. 'Every element can effectively change based on the time of day, [and the] specific audience that is being targeted,' said Oliver Marlow-Thomas, chief innovation officer at Smartly. 'We can dynamically map specific audiences to show specific variants … The dress the model is wearing, the shoe that's in the image, the colour of the background, or the colour of the hat, all of that is mapped and changeable.' Pixis, on its end, draws on data sources from Shopify to Google to macroeconomic data and weather channels to inform its decisions around which ad imagery is shown to who and when, said Widup. The platform has tested these dynamic ads for fashion brands on Meta, tailoring visuals and messaging to current weather patterns to make them feel relevant — showing rain jackets during storms or breezy outfits during heatwaves, for example — and boosting engagement and conversion rates. Optimise Targeting with Platform Data Brands that advertise on Meta can use its native AI tools to enhance existing content and optimise targeting. After Meta's targeting capabilities were reduced with Apple iOS changes in 2021, the platform began to build out Advantage+ in order to enhance advertising effectiveness on the platform by testing different ad types across users — and the more versions of creative content it has to test on customers, the better. 'Platforms like Meta are now saying, 'We've reduced your targeting capabilities, but just give us a lot of creative ads to use, and we'll refine it,'' said Widup. Meta's own targeting only goes so far, however, because it solely relies on data from its own ecosystem of platforms and first-party customer data provided by advertisers. Tools like Pixis and Smartly, which are integrated across social, search engines and shopping platforms including TikTok, YouTube, Google and Amazon, can use data from various sources to expand their targeting capabilities. Regardless of the optimisation tool used, the creative idea at the root of any campaign — and the creativity that underlies the different AI-made iterations — ultimately remains the most important piece of the puzzle. 'The original thought is the thing that will capture the human,' said Smartly's Marlow-Thomas. 'The artificial thought is the thing that will scale it and create lots of different iterations.'
