At Lux for Predictive Anthropology, we developed a methodology designed to remain effective in the face of digital noise.

Here’s how we filter out the impact of bots, sarcasm, influencer campaigns, astroturfing, and other forms of manipulation:

1. We avoid the biggest sources of noise

We bypass major social media platforms and instead gather data from sources where consumers engage in detailed, meaningful conversations—like forums, blogs, and long-form platforms. These environments are less targeted by bots and manipulators who typically focus on larger, more visible platforms.

Manipulators (bots, spammers, hired influencers, etc.) tend to post low-quality, repetitive content without participating in genuine discussions. Their contributions lack the rich context needed for effective ethnographic research, which focuses on understanding how culture and social factors shape consumer behavior.

By avoiding these shallow interactions and large platforms, we also minimize the bias that can arise from over-reliance on major social media. Our goal is to understand average consumers, not just typical social media users. This targeted approach provides us with high-quality data that has remained reliable despite the shifting digital landscape.

2. Our technology analyzes culture, not just mentions

Unlike many tools that focus on counting mentions or shares, our technology is designed to uncover cultural trends and deep consumer insights. MotivAI, for example, identifies six key themes within a conversation, while our Trends reports look for four distinct microcultures that represent different consumer perspectives.

Manipulators often repeat a single topic to inflate its visibility by boosting mentions or shares. Traditional social media listening tools are particularly vulnerable to this type of manipulation because they rely on these metrics.

Our technology, however, analyzes the role a topic plays within the broader conversation. Artificial mentions and shares from manipulation campaigns don't fit into the rich, connected web of ideas consumers naturally generate. As a result, they don’t appear in our analysis because they aren’t part of an authentic conversation.