Consumer Data, (De)Coded.

Harnessing Collective Intelligence

Have you ever come across a new word while reading a book and been able to determine its meaning from context alone? When children are learning their first language, they do this by listening, even though they still have little awareness of contextual factors in conversations. Scientists marvel at how they are able to form associations, seemingly in a vacuum and with relative ease, given that relationships between words are complex, variable, and often multifaceted. Adults, on the other hand, have a solid framework for expanding their vocabulary, and can reference dictionaries to fill in gaps. While this is a useful exercise, dictionaries only illuminate the meaning of individual words — they do not explain how words interact, or what else comes to mind when heard — one does not learn to speak a language by reading the dictionary.

A similar issue exists when it comes to the perception of brands. It is notoriously difficult to pin down what exactly defines any given brand — the term itself has multiple definitions and is somewhat disputed. In any case, brands are not defined by how they present themselves, but how people perceive them. How does Coca-Cola compare to Pepsi, excluding taste and packaging? This may depend upon an audience's perception of the words 'pep' and 'coca', whether there are pre-existing products with similar names, or if soda has any cultural stigmas in a particular market. There are a number of factors that impact popular comprehension, so no matter how much marketing goes into establishing an image, it ultimately depends upon the consumer. Being a question of subjectivity, how would a collective definition of a brand or product be calculated?

Imagine this: an encyclopedia for brands and products, not written by any one authority but composed of the collective perception of millions of social media users. With dynamic definitions that change according to popular opinion, such a resource would let analysts tap into consumers’ minds for live insights, effectively crowdsourcing market research.

Topic Example 1: What brands do eco-conscious consumers associate with sustainability?

Topic Example 2: Are sheet masks more associated with acne than clay masks?

To answer such questions, such data points would be made available by systematizing language, cataloguing relations, and tracking connotations: a task that would be impossible without vast numbers of social media users engaging in constant discourse. In other words, insights like these are made possible by the collective intelligence of the online community.

Collective intelligence is a process where the combined actions and thought processes of a group of people amounts to a sum greater than its parts. Essentially, humans are notoriously unpredictable, and yet patterns of behavior emerge organically when considering aggregates. Social media provides a expansive forum for extremely diverse discourse regarding all aspects of life, so its analysis requires a delicate approach that retains contextual elements. Consider the aforementioned ‘ brand encyclopedia’: its insights would not be very helpful if cross-sections of culture and society were not accounted for. Just as a normal dictionary includes multiple definitions to handle the richness of language, an encyclopedia of social media conversation topics would need to cluster meaningful relations in order for analysts to approach their questions from various angles.

This ‘brand encyclopedia' really exists, and it can help brands better understand themselves through the eyes of the consumer. Social Standards is a consumer insights platform backed by a nontraditional approach to social media analytics: instead of relying upon quantitative analysis — which largely eliminates valuable contextual information — we prioritize qualitative relational data that preserves connections between topics and lets users explore how and why consumers engage with different brands. Through discourse, social media users establish intricate relationships across topics: when someone mentions that they are lactose-intolerant in a post about baking with a specific brand of milk substitute, that becomes a data point that can be found in Social Standards under any of the topics or brands mentioned in that post.

Entries in the Social Standards system begin with the usual information like social media statistics, demographics, potential competitors, market share, and other data pertinent to brand analysis. But by tapping into collective intelligence, we are able to provide truly distinguishing features such as the ability to benchmark conversation data across other brands and industries, uncover relative penetration levels of other topics, and investigate relational data spanning myriad contexts. Now, you may be asking: what does this mean exactly and how does it work?

Social Standards not only covers all brands and products within a market, but also tracks key product claims that contribute towards consumer decision-making: qualities such as paraben-free or plant-based stand beside ingredients and concerns like quinoa and GMOs. Our descriptive space taps into foremost consumer concerns, tracking them across conversations in order to reveal their associations to brands and products. Finding out what brands or traits consumers think of when considering vegetarian meals is as easy as turning to the page that contains words Ve-Vi. While a dictionary doesn’t make for good casual reading, Social Standards allow for exploratory investigations of relational data that can unveil valuable insights without any plan in place. A hierarchical and web-like organizational schema links concepts to their constituent elements, which helps retain structural integrity and enables analysis of topics on multiple levels of granularity.

In the same way a normal dictionary includes multiple definitions to handle the richness of language, the Social Standards system clusters meaningful relations and contextualizes them with regards to one another, retaining the multiplicity of collective intelligence for analysts to approach from various angles. Even without an agenda, analysts can explore our relational data to uncover constituent parts of aggregates that usually present as a consistent whole. Whether the goal is to uncover popular products or ingredients, to investigate relevant topics and trends, to scope out competition, or even to conduct diligence on your own brand, Social Standards will help you contextualize your concerns by harnessing the power of collective intelligence, one voice at a time.