Author: Oriol Salvador

The sources that defined referral traffic online used to be clearer just a few months ago. Search brought people looking for something specific, either evergreen or breaking; successful social media posts could determine clear boosts in page views and direct traffic was a sign of brand recognition, even better when it was regular and loyal visitors.

Artificial intelligence and other algorithmic changes from tech companies have messed with the way we discover and consume content, with some sources of external traffic heavily hit while others have managed to survive or even thrive.

People are still consuming content, probably more than ever, but the way they get to it is less linear and, in many cases, harder to track.

As the “Ask Google” habit shapeshifts to “Ask the Chat” (ChatGPT), how much has AI changed how we distribute and discover content online?

In digital news media, success is often defined by the newsrooms that published accurate information first. Platforms also reward immediacy and audiences scroll through an endless stream of updates that can feel obsolete within days.

But a more durable truth persists: Evergreen content grows over time, answers relevant questions, surfaces in search results, supports ongoing reporting and strengthens a newsroom’s credibility long after the initial spike in traffic fades after breaking news.

For video, that idea is a structural choice that shapes how stories are conceived, reported, edited and distributed.

In today’s digital landscape, audiences encounter stories and information in dozens of places: websites, YouTube channels, social media accounts, email newsletters, messaging apps, and each comes with different expectations, attention spans, and ways of engaging.

Adapting ideas for multi‑platform storytelling means making editorial choices that preserve your original intent while reshaping tone, structure, and delivery to match the platforms where your audience lives and interacts.

This article offers an editorial perspective with practical approaches that extend beyond simple repurposing.

Video has lived on social platforms for decades now, but the dominant mode of consumption has shifted in recent years.

Discovery increasingly happens through algorithmic feeds rather than search or deliberate selection.

At the same time, vertical formats have become the default, rather than the exception, as mobile consumption takes the lead.

These changes are subtle but consequential.

They influence not only how video looks, but also how editorial decisions are made and how production workflows are implemented.

Designing content around audience needs is one of the most reliable ways to create stories that work across platforms, build loyalty and reach people who may not yet be familiar with your work.

This goes beyond questions about format or platform.

It asks content producers to understand what people are trying to accomplish when they open an article, watch a video or search for context on a topic that affects their lives.

When you identify those needs early, every editorial and production choice has a purpose and you gain a clearer sense of what the audience is looking for, what the story must deliver and how it should live across platforms.

We are bombarded with notifications, social media snippets, and breaking headlines. The 24/7 news cycle can feel overwhelming.

Without context, news feels like noise, facts float in isolation, and stories lose meaning. Clear background and framing show audiences why events matter and how they connect to their lives.

It is what makes audiences understand, remember, and care.

Social media was meant to be a space for people to connect, share ideas, build communities, and participate in public life, a digital agora.

But what once brought us closer is now being overrun by automation.

Instead of amplifying real voices, algorithms are increasingly pushing artificial interaction.

If you have been on social media lately consuming content originally produced in languages other than your own, you’re familiar with the push for dubbed audio, produced using artificial intelligence (AI). This is not a minor shift.

Meta and YouTube are doubling down on AI translation features that aim to increase reach and attract a broader audience.

And while their goal is similar, they have made design choices to implement this technology that produce very different outcomes.

On Jan. 19 2025, TikTok was banned in the United States for a few hours.*

The latest resolution from the U.S. Supreme Court, issued on Jan. 17, made it “unlawful for companies in the United States to provide services to distribute, maintain or update the social media platform TikTok, unless U.S. operation of the platform is severed from Chinese control.”

The internet did what it does best, and many U.S.-based TikTok users protest the ban by moving to the app 小红书国际版 (“Xiaohongshu”), also known as REDnote. Ironically, this app is entirely Chinese-owned and operated from mainland China, unlike TikTok.

This digital migration sparkled both an unexpected cultural and language exchange and raised concerns about freedom of speech on the new platform.

If you struggled to keep track of everything happening, this TikTok ban is just the latest shakeup in the ever-evolving—and let’s face it, exhausting—social media landscape.