Brands are increasingly facing lawsuits because ‘fair use' doesn't apply to most meme content used in marketing.

Brands don't view social strategies as cohesive packages as much as they used to — they view them as fragmented videos, memes, and photos.

Brands struggle on TikTok due to several key factors: reluctance to embrace unconventional or "ugly" content that resonates with the platform's audience, failure to engage through compelling hooks and in-app styles that disguise branded content, and a lack of strategic posting that prioritizes quality over quantity. Successful TikTok strategies involve leveraging capcut filters, meme-style content, and real-life moments, deviating from traditional brand presentations to capture user attention effectively. Planning content as a social calendar without thoughtful engagement strategies can lead to TikTok penalizing brands by limiting their reach.

“Meme tech” could be poised to become the next big industry, akin to health tech or fintech. Meme Depot is a platform aiming to create a comprehensive archive and community for memes. It's organized in a Pinterest-like interface and there are collections that act like visual subreddits. If you're looking for a Kim Kardashian meme, there'll be a Kim Kardashian collection you can navigate to. Meme Depot's business model incorporates a crypto-based feature called “meme party”, allowing users to buy passes and join communities.

The rise of meme coins in the crypto space has sparked concerns about their negative impact on the industry's credibility and long-term growth. Critics argue that these tokens, which often lack technical innovation and rely on hype-driven speculation, create a predatory environment that disproportionately benefits savvy traders at the expense of less experienced investors.

Most marketing today works by grabbing attention, making you emotional, and turning emotion into action. For this to work, your audience has to trust, like, and relate to you – which is where humor comes into play. One tactic is to make fun of yourself, as IKEA did with a playfully misassembled ad. You can also make extreme and humorous analogies to show how your customer’s life would look without your product. Alternatively, brands can take a bold stance against something in their industry they don’t agree with, as Verizon did with its “one size does not fit all” messaging.

As people are increasingly turning to LLMs to search for product information, companies are becoming more concerned about how these LLMs perceive their brand. While companies can’t change what the models already “know” about the brand, they can put out new content in hopes of ensuring positive associations of their brand names within AI language models. Right now, that exposure happens mainly when a model is trained using a huge compressed version of all the content on the internet.

AI-generated deepfakes are now a reality. There are some state-level laws regulating and limiting deepfakes, but legislation doesn’t often move at the same pace as technology. One way for brands to navigate the ethical complexities of deepfake technology is to declare and disclose all AI content. Without clear labeling, brands, creators, and celebrities alike risk losing audience trust.

Many brands move quickly to protect their copyrighted materials and likenesses. Coca-Cola has recently launched a campaign that does the opposite, celebrating the many interpretations of its logo created worldwide for generations. The ‘Every Coca-Cola is Welcome’ campaign embraces and showcases grassroots interpretations of the company's wordmark created by bodegas, shopkeepers, and local artists instead of slapping these creators with lawsuits.

Baldur Bjarnason, a web developer from Hveragerði, Iceland, recently shared insights on the evolving discourse surrounding fair use in the context of generative AI models. He referenced a paper by Jacqueline Charlesworth, a former general counsel of the U.S. Copyright Office, which critically examines the claims of fair use made by proponents of generative AI. The paper highlights a significant shift in legal scholarship regarding the applicability of fair use to the training of generative models, particularly as a clearer understanding of the technology has emerged. Charlesworth argues that the four factors outlined in Section 107 of the Copyright Act generally weigh against the fair use claims of AI, especially in light of a rapidly changing market for licensed training materials. A key point made in the analysis is that the argument for fair use often relies on a misunderstanding of how AI systems operate. Contrary to the belief that works used for training are discarded post-training, these works are actually integrated into the model and continue to influence its outputs. The process of converting works into tokens and incorporating them into a model does not align with the principles of fair use, as it represents a form of exploitation rather than a transformative use. Charlesworth draws a distinction between the copying of expressive works for functional purposes—such as searching or indexing—and the mass appropriation of creative content for commercial gain. The latter, she argues, lacks precedent in fair use cases and cannot be justified by existing legal frameworks. The paper emphasizes that the act of encoding copyrighted works into a more usable format does not exempt it from being considered infringement. Furthermore, the notion that generative AI's copying should be deemed transformative because it enables generative capabilities is critiqued as a broad and unfounded assertion. This argument essentially posits that the rights of copyright owners should be overridden by the perceived societal benefits of generative AI, which does not hold up as a legal defense in copyright disputes. The narrative pushed by AI companies—that licensing content for training is unfeasible—faces scrutiny, as these companies have shown they can engage in licensing when it serves their interests. This undermines their claims that copyright owners are not losing revenue from the works being appropriated. Overall, Bjarnason encourages readers to explore Charlesworth's paper, noting its accessible language and the importance of understanding the legal implications of generative AI in relation to copyright law.

Marketers should reconsider posting campaign assets on Instagram, as overuse often causes significant drops in reach and engagement that take months to recover. They should instead assess Instagram performance before, during, and after a campaign to understand the impact. Prioritizing aesthetics over performance can lead to diminished visibility and less interaction. Thoughtful upper-funnel marketing is important. Social teams should gather data to avoid these issues.

The marketing industry is grappling with the rise of "made for advertising" (MFA) websites, which lure visitors in with clickbait headlines and then inundate them with ads. Despite industry warnings and efforts to block MFA sites, they continue to prevail, underscoring the challenges of defining and mitigating such platforms' impact. Marketers must weigh the risks of poor user experience and inflated ad costs against the potential benefits of wide-reaching ad placements.

Companies are leveraging memecoins, or tokens associated with internet memes, in their go-to-market strategies. These companies are taking advantage of memecoins' established communities by integrating popular memecoins into new products or projects. Examples include the BONKbot trading bot using the $BONK token and $SHIB incorporating its token into an Ethereum L2 called Shibarium. This approach can tap into the established userbase and liquidity of memecoin communities, providing a potential solution to getting initial momentum in a project.

As AI-powered chat programs like ChatGPT and others become prominent, marketers need to prepare for negative brand mentions in search queries. Tracking how large language models perceive brands and measuring "share of model" will become crucial. Marketers will need to optimize content to align with model preferences and establish metrics comparable to traditional marketing indicators.

Buzzfeed issued a cease and desist notice to Trending Now, an AI news aggregator, over a logo design that Buzzfeed claims is too similar. The logo features an ascending arrow and a Google Trends emblem motif. Trending Now's director acknowledges the resemblance but considers the dispute a positive sign for the site's future.

Social media marketing has evolved to prioritize entertainment over interaction. This was heavily influenced by TikTok's emphasis on public posting and content consumption time. Today's social media algorithms also prioritize entertaining content over divisive or argumentative posts. This shift has led to a decline in engagement and interaction on platforms like FB and IG, despite increased time spent on AI-commended content.

Meta and Universal Music Group have renewed their multi-year licensing agreement to expand monetization and evolve creative possibilities for UMG's artists on platforms including Facebook, Instagram, and now WhatsApp, focusing on fair compensation and addressing unauthorized AI content issues.

With over 74,500 posts on TikTok under the #demure hashtag, brands like Ssense and Anthropologie have rapidly incorporated the viral phrase into their marketing. While quick adoption can boost relevance, strategists warn that misalignment with brand identity can lead to missteps. The emphasis should be on understanding the deeper cultural meaning behind trends rather than just capitalizing on their popularity.

Regulators argue Meta's new ad model fails to offer a less personalized alternative as required by the Digital Markets Act.

Small businesses are worried about losing a vital marketing channel if TikTok faces a ban. Bigger brands appear less concerned, but some have started planning alternative promotional strategies. Marketing agencies are advising clients to diversify their influencer spending across platforms like Instagram and YouTube.

Harley Davidson is suing UK retailer Next over a children's t-shirt design that allegedly copies its logo, claiming it could cause consumer confusion. The disputed t-shirt features a winged badge motif with flames, which Harley Davidson argues “essentially replicates” its motorcycle branding. The case is currently in the High Court, with Harley Davidson demanding the removal and destruction of all infringing materials.

Nathan Jun Poekert, former Head of Social at American Eagle, says that campaign assets often underperform due to rigid playbooks, misguided trend-chasing, and the misuse of content creators. Brands frequently fail by not adapting to the ever-evolving social media landscape and by neglecting audience-driven strategies. Poekert advises marketers to prioritize data-backed content that resonates with audiences over traditional campaign footage.

Major brands are wasting ad dollars on Made for Advertising (MFA) sites. MFA sites prioritize profit through advertising, resulting in subpar user experiences with low-quality content and excessive ads. Brands like Procter & Gamble and Pfizer have inadvertently had their ads placed on these sites, emphasizing the importance of thorough ad spend monitoring.

Microsoft is defending OpenAI against The New York Times' copyright infringement lawsuit, arguing the case is based on unfounded claims and comparing the dispute to past technological advancements like the VCR.

The social media marketing landscape is evolving as platforms adjust their algorithms. Meta has shifted away from news content, impacting publishers' strategies. Reddit's organic referral traffic has surged sevenfold due to its partnership with Google. LinkedIn is seeing higher engagement through newsletters, while Meta and X penalize link posts, leading publishers to explore new opportunities. Ad budgets are shifting from X to Snapchat and Reddit, with notable increases in spending from small and medium-sized businesses.

This article examines the impact of social media saturation, where over 5 billion users and constant content production create a chaotic landscape for brands. Audiences struggle to engage with the overwhelming amount of content, so brands should focus on originality, understand their audience's preferences, and set new success metrics. It is important to think creatively and have a flexible strategy when navigating the complexities of modern social media.