We’ve created the world's only AI Anthropologist that can predict the trends that will shape consumer culture.
Every day, consumers leave billions of clues online about how you can future proof your business. We’ve created an AI Anthropologist that can perform a big data ethnographic analysis on consumer conversations online, on any topic or trend.
To do this, we built an AI platform that uses Cultural Context Graphing technology. It's a mouthful, we know. What is that you ask? It is the culmination of decades of social science theory married with the latest in NLP technology. And it allows our machine to perform a full, contextual analysis of millions of consumer conversations.
This is what allows MotivBase to perform an authentic, observational, big data ethnographic analysis of a culture in seconds. It allows you to search for insight on demand. Or have our team deliver in-depth ethnographic research in as little as 3 days.
Self serve, yet comes with a Ph.D. Concierge.
When you acquire a Motivbase license, you get to choose the level of support you'd require. We know you're busy. So you can either self-serve with limited support or go all the way to acquire a fully supported license for your team or even organization.
The key benefit is that our Ph.D. Concierge (team of anthropologists) is able to run in-depth custom ethnographic analyses for you that typically require 3-5 business days of work. In the process, they can answer complex business problems for your teams in a matter of days, track demand spaces on an ongoing basis and even identify net new product and brand development opportunities.
Stop identifying new trends and start measuring their impact and value to your business
White Paper:
How to model the future impact of significant events in culture.
How to add much needed rigor to the scenario planning work that futurists often do.
Whenever something significant happens in culture, be it the last recession, the 2016 American election or even the coronavirus pandemic, organizations flock to consulting companies to try and make sense of future scenarios. Most often, these scenarios are created by "futurists" who tout their ability to apply a framework to outline four (everyone like a grid) possible scenarios - from best case to worst...for the business.
While this may serve as a helpful thought experiment, it rarely prepares an organization for the tangible elements of change that might affect their business. This is where MotivBase's contextual intelligence comes in handy. By understanding the broader context of discussions happening naturally and organically among consumers, it is able to tap into those signals that might not be obvious or directly related, but is in fact crossing the contextual boundary and growing in relevance. The whitepaper outlines this very model with tangible examples and visuals to provide a framework for action.
How we created the world’s first
Ethnographic Insights Discovery tool with big data
Almost 10 years ago, our CEO and Cultural Anthropologist Ujwal Arkalgud asked a question – is it possible to take the models and theories that make social science research so powerful and scale them with big data? In 2015, he launched MotivIndex, which became the first company to offer big data ethnographic research to Fortune 500 companies around the world. But with recent advances in Natural Language Processing and Machine Learning, the question of “can we access consumer motivations and values online” quickly became “can we build a machine to do it at a larger scale, with greater accuracy?”
Teaming with some of the most talented developers in North America we began work in 2016 to see if this could be achieved. After almost a decade of theoretical development and more than 2 years of product development and testing, MotivBase is ready for the world.
It performs on-demand big data ethnographies. Simply search a topic, and it will reveal the cultural forces at play.
But how?
Just like the English language where a mere 3000 words is all we need for over 95% of communication, we discovered early on that making sense of consumer culture also required a finite library.
This library, made up of just a few thousand factors (motivations, attitudes, values, and fears), unlocks the meaning behind 95% of the topics that consumers discuss every single day across the social web.
It took us eight years and studying over 1.5 million consumers
to identify and build this finite yet vast library of factors.
Once we did that, the next task was the figure out how we could teach a system to understand these factors by understanding the millions of ways in which people naturally talk about these factors.
So we created recipes for each factor. Made up of an intricate web of topics and relationships that millions of people across the web associate with each factor, these recipes provide our system a blueprint of each and every factor in our library and teach it to identify these factors when it examines millions of consumer conversations on a day to day basis.
The outcome is a Natural Language Processing engine that constantly identifies the meanings behind the people, places, and things consumers talk about every day across the social web. Which makes our technology the only self-serve research tool in the world that can not just tell you what people care about in relation to a trend or topic, but can also tell you why.
