Big Data Ethnography
MotivBase is the world's only AI Anthropologist that decodes the hidden meanings behind millions of consumer interactions online.
In 2015, we created and pioneered the art and science of ethnography at big data scale. In 2018, we launched MotivBase to make this form of research faster and more agile to support innovation efforts across the organization.
Self serve, yet comes with a Ph.D. Concierge.
When you acquire a Motivbase license, you get access to unlimited searches. You also get the ability to commission custom ethnography reports from our team of Ph.D. social scientists, who will leverage our technology to answer complex business questions in 3 business days.
Motivbase gets to the unspoken motivations because it doesn't just identify patterns in WHAT people are saying, but understands the whole context around a topic to decode the WHY.
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One Tool. Limitless Potential.
Discover and compare broad trends and identify their future market potential. Determine business fit by exploring the underlying motivations, attitudes, and socio-demographics behind these trends. Even examine the existing products consumers relate to the trends. Prioritize the right areas for investment in innovation.
Explore unmet consumer needs and pain points around specific types of products and solutions, identify the motivations and values that drive these needs, pinpoint underlying trends, size the current and future potential of these trends and unmet needs to build the most effective innovation pipeline.
How MotivBase can truly personalize
your digital customer experience.
MotivBase's Natural Language Processing algorithm can analyze any text and identify the hidden meanings and patterns in culture. Which means, MotivBase can identify and cluster users, based on what they read, say, or even buy. All in a matter of seconds.
These days every organization has an online presence, if not an Ecommerce offering. Which means, finding ways to personalize a consumer's experience through one's online presence is a top priority for every organization, big or small. In the past, this has not been an easy task. It often requires the creation of rules in a CMS system, driven by manually created personas, and estimated content needs of these personas.
MotivBase is going to change all that, and reduce the hassle and inaccuracy in the personalization of digital experience. This white paper will shed some light on the power of MotivBase in transforming and automating the process of personalization.
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.
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.