Editor’s Note:
This article is part of a Digital Summit Collective series where we’re turning standout live sessions from recent Digital Summit events into actionable, on-demand insights for our community. Each piece is adapted from a real stage presentation—capturing the ideas, examples, and strategic thinking that resonated most with attendees.
Meredith Howard opened her session with a moment that felt instantly familiar.
On August 26, 2025, social media became completely consumed by the engagement of Taylor Swift and Travis Kelce. Feeds were flooded with memes, reactions, commentary, and coverage, regardless of whether people actively followed either of them.
Howard admitted that she is not a Swiftie. She does not follow the NFL. And yet her entire feed transformed into a stream of Taylor and Travis content almost overnight.
That, she explained, is the algorithm at work.
This is simply not the version marketers talked about ten years ago, where feeds were driven mostly by follower counts and posting cadence. The algorithm now is something far more behavior-driven, powered by interest graphs, AI recommendations, and predictive systems designed to keep people on platforms for as long as possible.
And for brands still relying on a 2020-era social strategy, that shift changes almost everything.
Social Media Is No Longer Built Around Followers
One of the biggest misconceptions Howard challenged is the idea that social feeds are still primarily follower-based.
They are not.
Today’s platforms prioritize interests over networks. The algorithm surfaces content based on what it believes a user is likely to engage with, even if they have never followed the account before.
That means brands are no longer competing only for the attention of their existing audience. They are competing for discoverability within broader interest ecosystems.
Howard described this as the move from follower graphs to interest graphs. Instead of asking, “Who follows us?” marketers need to start asking, “What content clusters are we associated with?”
It is a subtle shift, but an important one. Because once content becomes interest-based rather than relationship-based, the role of social media changes entirely.
Your content is no longer speaking primarily to people who already know your brand. In many cases, it is reaching people who are encountering you for the very first time.
Discovery Matters More Than Loyalty on the Feed
That reality changes how content should be created.
Howard encouraged marketers to stop designing posts exclusively for existing followers and instead assume every post is someone’s first interaction with the brand.
That means content has to work harder and faster. It needs to capture attention immediately, communicate value without requiring additional clicks, and feel complete within the platform itself.
This is where many brands still struggle. Social strategies often prioritize traffic-driving tactics that pull users away from the platform. But the platforms themselves are optimized for the opposite. Algorithms reward content that keeps people engaged without leaving the app.
As Howard put it, brands need to stop assuming users will click through.
Instead, the content itself needs to carry the full experience.
Interest Clusters Are Replacing Broad Audience Targeting
Another major shift Howard outlined is the move away from broad demographic targeting and toward interest-based clustering.
Platforms are trying to understand what categories of content a brand consistently belongs to. If your messaging is too broad or inconsistent, it becomes harder for the algorithm to understand where your content belongs and who should see it.
That is why Howard encouraged brands to narrow their focus and become more recognizable within specific content ecosystems.
Instead of speaking generally about “marketing,” for example, a brand might consistently create content around AI workflows for marketers, demand generation strategy, or common misconceptions in B2B growth.
The goal is not just consistency, it’s clarity.
When platforms can confidently associate your content with a defined interest category, discoverability improves.
Cultural Relevance Still Matters
While consistency is important, Howard also emphasized the value of participating in cultural moments when they align naturally with the brand.
She pointed to examples like the Coldplay concert meme cycle and the way brands quickly adapted trending moments into social-first content.
The key, however, is intentionality.
Not every trend needs a brand response. Forced participation is easy to spot and rarely performs well. But when a trend overlaps naturally with a brand’s tone or audience interests, it can create highly shareable content that expands reach quickly.
Howard recommended creating internal “trend playbooks” ahead of time so teams can move quickly without scrambling to decide whether something is worth participating in.
Because in social media, timing matters almost as much as creativity.
Community Management Is No Longer Optional
One of the strongest sections of the session focused on something many brands still underestimate: the comments section.
Howard argued that social teams should spend just as much time engaging with communities as they do creating content.
That includes responding to comments on brand posts, but it also means participating in conversations happening elsewhere within the same interest ecosystem.
This is where discoverability becomes especially interesting.
Howard shared the example of Miro, a SaaS company that actively comments on posts related to AI workflows and project management. She discovered the brand not through advertising or direct promotion, but because they consistently showed up in relevant conversations.
In other words, community participation itself became a discovery strategy.
That matters because comments are increasingly weighted as high-value engagement signals, especially when they contain meaningful conversation rather than passive reactions.
Metrics Need to Change Too
Another important point Howard made is that many brands are still measuring success using outdated signals.
Follower growth and likes are no longer the strongest indicators of performance. Platforms now place more value on metrics tied to depth and intent.
That includes:
These are signals that tell the algorithm content is worth surfacing more broadly.
Howard pointed to Gap’s highly viral “Better Than Jeans” campaign as an example of content designed specifically for shareability and participation. The campaign extended far beyond Gap’s own channels because users recreated, remixed, and circulated the content themselves.
That kind of engagement carries more weight than passive visibility.
AI Should Support the Process, Not Replace It
Howard also addressed the growing role of AI within social workflows.
Her perspective was practical. AI is most valuable when it helps scale and repurpose strong human-created content, not when it replaces original thinking altogether.
That might mean using AI to:
But the underlying strategy and voice still need to come from the brand itself.
As Howard emphasized, consistency matters to the algorithm, and AI can help teams maintain that consistency more efficiently.
What to Do Right Now
The Bottom Line
The social algorithm is no longer simply deciding what people see.
It is shaping how brands get discovered in the first place.
And in that environment, the brands that succeed will not necessarily be the ones with the largest audiences. They will be the ones that understand how to create recognizable, interest-driven content that feels native to the way people already consume social media today.
Watch the Full Session
This article was adapted from the live session Today’s Social Strategy 3.0: Winning in the Age of Algorithm-Driven Attention presented by Meredith Howard at Digital Summit Dallas 2025.
Watch the full video: https://resource.digitalsummit.com/resources/material/todays-social-strategy-3-0-dal25/