Trends Month: Are we forecasting trends or forecasting algorithms?

Trends have become a core input to strategy. Brands track cultural signals, insight teams analyse emerging conversations, and foresight specialists attempt to anticipate what will matter next.

But there’s a growing question behind all of this work.

What if the signals we’re interpreting are not purely cultural signals at all?

Social media feeds shape visibility, and algorithms amplify some things while suppressing others. Emotional intensity, repeatability, and engagement-friendly formats often travel further than nuance or complexity. Over time, these dynamics don’t just influence what people see online; they shape how culture itself is expressed.

For teams responsible for identifying trends, this creates a difficult problem.

If algorithms influence what becomes visible in the first place, how confident can we be that we’re forecasting culture rather than forecasting the outputs of ranking systems?

This opening panel explores how algorithmic infrastructure shapes the signals analysts and strategists rely on, and what this means for the practice of trend forecasting.

Rather than rejecting social data, the discussion asks a deeper question: how should insight teams interpret signals when visibility itself is engineered?

In this session, we will explore:

• How algorithms shape the signals that analysts interpret as trends
• Why visibility and cultural significance don’t always align
• How engagement incentives influence the kinds of cultural expressions that spread online
• How insight teams can account for algorithmic distortion when analysing cultural change
• What responsible trend forecasting looks like in platform-shaped environments

This conversation sets the stage for the rest of Trends Month to challenge assumptions about how cultural momentum forms and how strategy should respond.

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