How startups can use nostalgia marketing to build trust, spark loyalty and stand out with storytelling, vintage design and emotional connections.
Updated
January 8, 2026 6:35 PM
Vintage beer pong posters showcasing colorful, diverse designs from different eras in one collection. PHOTO: FREEPIK
Turning the subtle power of nostalgia into meaningful marketing.
Think of nostalgia as a time machine for brands—it doesn’t just take people back; it brings their emotions forward. And emotions sell. For those who are unfamiliar, nostalgia marketing is a strategy where brands use elements from the past—like familiar sights, sounds, or stories—to evoke warm memories and emotional connections with their audience.
This emotional pull isn’t just anecdotal—research shows its real impact: according to The Team and Forbes via The Drum, 80% of millennials and Gen Z are drawn to brands tapping into nostalgia, while 92% of consumers say nostalgic ads feel more relatable. And for startups competing in noisy markets, this is a goldmine.
In this article, we’ll explore why nostalgia marketing can be a game-changing strategy for your company.
Out of all the popular marketing methods—like influencer partnerships or attention-grabbing ad campaigns—nostalgia is unique because its impact starts intrinsically, in the brain. By triggering the release of dopamine, a reward-system neurotransmitter, Nostalgia evokes feelings of warmth, happiness and comfort. Consequently, people don’t just remember a moment—they relive it. Take, for instance, your favorite cereal brand bringing back childhood cartoon characters or using retro fonts and colors. You might choose it over a healthier breakfast option simply because it reminds you of the mornings you enjoyed as a kid. Similarly, speaking of stirring fond memories, Coca-Cola has mastered this effect, using classic holiday ads, vintage packaging, and iconic imagery. Those associations make people see Coke as more than a drink—it’s a familiar feeling they’re willing to pay extra for.
New marketing campaigns can spark curiosity but often trigger skepticism—especially when audiences lack prior connection to the brand. Nostalgia marketing breaks down this barrier by tapping into familiarity, using retro jingles, vintage fonts, pastel colors, or familiar packaging that immediately resonate. This recognition builds an emotional connection and trust with the brand. More importantly, it fosters social connectedness by making consumers feel part of a larger community—giving that reassuring “others remember this too” feeling. As a result, this sense of belonging reduces loneliness, strengthens warmth and trust, and encourages word-of-mouth sharing, naturally amplifying the campaign’s reach and impact.
While luxury brands can afford massive campaigns, startups and small businesses can tap into nostalgia as a cost-effective storytelling tool. In a world where marketing often chases the “next big thing”—from AI to futuristic tech—nostalgia offers the opposite: a chance to revisit the past. More importantly, nostalgia allows brands to stand out in a crowded, fast-scrolling feed by delivering something comfortingly familiar with a fresh twist. Think of Polaroid: in an age where smartphones boast crystal-clear cameras, it wins hearts with pastel hues, a vintage lens, and the tactile charm of instant prints—selling not just images, but a moment that feels straight out of the past.
The same principle worked brilliantly for Tiffany & Co., whose 185-year-old brand refresh featured Jay-Z and Beyoncé in a Breakfast at Tiffany’s-inspired campaign, blending timeless charm with contemporary star power and racking up millions of views. In essence, when done right, nostalgia doesn’t just market a product—it invites people to relive a story they already love.
Nostalgia resonates across generations speaking to diverse audiences. For Millennials, it’s a chance to relive the cultural touchpoints of their youth, while Gen Z approaches it with curiosity, eager to explore eras they never experienced firsthand. This crossover creates a unique marketing sweet spot: one group is driven by memory, the other by discovery. Pokémon proves this power by keeping lifelong fans engaged through retro trading cards while introducing younger audiences to its history. Similarly, Nike used nostalgia to bridge two different generations by reissuing retro classics, keeping both longtime fans and new sneakerheads excited. By appealing to both memory and curiosity, brands can create lasting connections that keep different generations engaged at once.
Nostalgia can be your startup’s non-cliché marketing mantra. Imagine a small bookstore that offers handwritten recommendation cards designed like vintage library checkout slips. This simple touch invites customers to slow down and rediscover the joy of reading. Or picture a local coffee shop serving drinks in mugs inspired by classic diner ware, evoking comforting memories of simpler times. Overall, the lesson is clear: combining nostalgic design with stories that connect people to shared moments creates emotional warmth and trust. Thoughtful nostalgia turns everyday products into meaningful experiences—building loyal communities eager to return.
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Sonilo and Shutterstock are betting that licensed training data could define the future of AI music.
Updated
May 13, 2026 3:39 PM
A human operating a digital turntable. PHOTO: UNSPLASH
As copyright disputes continue to grow around AI-generated music, Sonilo, the world’s first professionally licensed video-to-music AI platform, has partnered with Shutterstock to train its models on licensed music catalogs.
The agreement gives Sonilo access to Shutterstock’s music library for AI model training. According to the companies, it is Shutterstock’s first partnership with a video-to-music AI platform and the timing is significant. AI music companies are facing growing pressure over how their systems are trained. Artists and record labels have increasingly challenged the use of copyrighted music in AI datasets, especially when licensing agreements or compensation structures are unclear.
That tension has created a divide across the industry. Some companies have continued building models around scraped or disputed data. Others are trying to position licensing as part of the product itself.
Sonilo falls into the second group. The company says its models are trained only on licensed material where artists and rights holders have agreed to participate and receive compensation. The Shutterstock partnership strengthens that position while giving Sonilo access to a larger pool of commercially cleared music.
The collaboration also points to a broader change happening inside generative AI. As AI tools move into commercial production, companies are being pushed to show not just what their models can generate, but also where their training data comes from.
Sonilo’s platform is built around video rather than text prompts. The system analyses footage directly, studies pacing and emotional tone, then generates an original soundtrack to match the content. The company says this removes the need for manual music searches, syncing or editing workflows. The generated tracks are cleared for commercial use across social media, branded content and broadcast production.
Shawn Song, CEO of Sonilo, said: "Music has always been the last unsolved layer of video creation, and video has always carried its own soundtrack. We built Sonilo to hear it and compose from it, without a single text prompt. But how we build matters as much as what we build. While others have chosen to take artists' work without permission and charge creators for the privilege, we've chosen a different path—one where artists are compensated from day one. Partnering with Shutterstock reflects that standard. Every model we train meets a bar the music industry can stand behind, because the most innovative AI platforms don't have to come at the expense of the artists who make all of these possible."
For Shutterstock, the deal expands the company’s growing role in generative AI infrastructure. The company has increasingly focused on licensing content for AI systems across images, video and music.
Jessica April, Vice President of Data Licensing & AI Services at Shutterstock, said: "AI innovation depends on access to high-quality, rights-cleared content and trusted licensing partnerships. Sonilo's approach reflects the growing demand for responsibly sourced training data and commercially safe AI workflows. We're pleased to support companies building generative AI products with licensed content and scalable data solutions that help accelerate innovation while respecting creators and rights holders."
The partnership also comes as Sonilo expands into creator and developer ecosystems. Earlier this month, the company launched as a native node inside ComfyUI, an open-source AI workflow platform used by millions of creators. Sonilo also offers API access for integration into creator tools, video platforms, game engines and other AI systems.
As AI-generated music becomes more common across advertising, creator platforms and digital media, the industry’s focus is shifting beyond generation alone. Questions around licensing, ownership and compensation are increasingly shaping how AI music companies position themselves and build trust with creators.