When Influence Became Harder to Measure
Years ago, when we organized the DigitalFilipino Web Awards, the challenge of identifying excellence online felt far more straightforward.
We were not judging personalities. We were assessing web properties.
Using platforms such as Alexa, SEMrush, and other third-party tools, we examined traffic, visibility, consistency, and discoverability across clearly defined categories. The methodology was not perfect, but it was externally observable and explainable. The signals were visible. The criteria could be articulated.
That experience shaped how I think about influence to this day.
Why Measuring Websites Was Easier Than Measuring People
Websites behave in predictable ways.
They leave data trails.
They aggregate intent.
They can be evaluated without asking the owner to nominate themselves.
When the conversation shifted from top websites to top individuals, things became more complicated.
What changed over time was not the intention to recognize excellence, but the environment in which influence operates. Influence today moves across platforms, communities, offline decisions, and private networks. It is shaped not only by content, but by trust, access, timing, and context—making it harder to capture using any single set of signals.
This shift affects everyone trying to make sense of credibility online: those building rankings, those seeking experts, and those simply deciding who to trust.
An Early Experiment in Community-Led Recognition
This challenge was something we encountered early on.
After the Web Awards, we also ran a “Top 10 Emerging Influential Blogs” writing project. Instead of appointing judges or publishing a ranked list, we designed it as a community activity.
Bloggers were invited to write a post citing their own top 10 influential blogs, guided by minimum criteria—such as how long the blogs had been active, and whether both the cited blogs and the participating blog had an established publishing history. The emphasis was on reflection, attribution, and peer recognition, not competition.
Importantly, we were careful not to frame it as an award.
The goal was to surface emerging voices through participation, not to declare winners. Blog owners whose sites were cited were invited to our Digital Influencer Marketing Summit, where their blogs were recognized through their writers or owners. For those who joined the writing project itself, we ran a raffle draw, with ten participants receiving US$100 each—not as a prize for “being top,” but as encouragement for contributing to the community.
Looking back, this approach already reflected a discomfort with rigid rankings. It acknowledged influence as something relational and contextual, not absolute.
Why Measuring Individuals Remains Difficult
Today, when I’m asked who the “top influencers” are, I often hesitate—not because influence doesn’t exist, but because the way we try to observe it has changed.
Followers, likes, comments, views, and even search visibility can now be manufactured, purchased, or algorithmically amplified. Metrics that once served as useful proxies no longer consistently reflect trust, decision-making power, or lasting impact.
This is also why, when I’ve been invited to fill out forms to be ranked or included in “top” lists, I’ve chosen not to participate. The hesitation is not about disagreement, but about clarity. When criteria are unclear or heavily reliant on signals that are easy to manipulate, participation becomes difficult to assess.
Different Tools Answer Different Questions
Lists and rankings often serve an important purpose: they help people discover voices they may not have encountered otherwise. Visibility-based approaches are useful for understanding reach and discoverability.
They become less reliable, however, when the question shifts from who is visible to who influences decisions, behavior, or outcomes over time.
This perspective does not replace rankings or lists; it simply addresses a different question—not who is visible, but how influence translates into real-world change.
Rather than treating influence as a single score or leaderboard, I’ve found it more useful to change the question itself.
A Shift in the Question
Instead of asking who is most visible, I now ask:
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Who shapes decisions?
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Whose ideas are adopted by others?
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Who mobilizes people or institutions into action?
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What outcomes persist after the spotlight fades?
Influence, in this sense, is less about attention and more about translation—the ability to move ideas into decisions, and decisions into durable outcomes.
A Framework That Works Across Categories
To make this practical, I developed a simple framework for thinking about influence without relying on vanity metrics. It applies across domains, whether we are talking about:
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business leaders
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policy advocates
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educators
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creators
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consultants
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researchers
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MSME ecosystem builders
The framework looks at four domains:
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Knowledge Production – Are original ideas, practices, or insights being created and adopted by others?
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Decision Impact – Do those ideas influence real choices, whether in organizations, markets, platforms, or communities?
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Network Activation – Can people or stakeholders be mobilized into collaboration or collective action?
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Outcome Traceability – Are there observable, sustained results that can be reasonably traced back to that influence?
Surrounding these is an authenticity filter—a check to ensure that visibility is proportionate to contribution, not inflated by platforms, popularity loops, or manufactured engagement.
The framework does not rank people against one another. Influence is contextual, not universal.
Does This Also Apply to Celebrities, Creators, and Online Personalities?
Influence shows up differently across domains, but it is not confined to any one profession or industry.
Yes, the framework also applies to celebrities, beauty bloggers, gamers, streamers, and other online personalities—with an important distinction.
What changes is how influence shows up, not whether it exists.
For these groups:
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Knowledge production may take the form of techniques, styles, routines, formats, or cultural norms rather than formal frameworks.
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Decision impact often appears in consumer choices, gameplay strategies, brand positioning, or platform behavior.
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Network activation may be seen in community mobilization, collaborations, charity drives, or coordinated fan actions.
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Outcome traceability becomes visible when behaviors, routines, norms, or platform dynamics persist beyond a single post or viral moment.
In these contexts, visibility alone is still not enough. The core question remains the same:
What changed because of this person’s influence—and did that change last?
Why This Perspective Matters
In an environment where attention is increasingly easy to buy, borrow, or game, credibility has become harder to earn—and easier to lose.
That does not mean we should abandon efforts to surface voices or guide audiences. It suggests we may need to use different lenses for different questions, especially in decision-making contexts where trust, adoption, and outcomes matter more than reach.
This perspective is especially useful for organizations, institutions, and communities that need to make decisions—not just discover content.
When I’m asked today who the influencers are, I don’t offer a list. I offer questions. I offer signals. I offer a way of thinking that reflects how influence actually operates in a digital, hybrid, and often opaque world.
Visibility can open doors.
Influence is proven by what happens after.
And sometimes, the most influential work is the quiet kind—embedded in systems, carried forward by others, and visible only if you know where to look.
