Introducing MotivBase 2.0
In June 2018, we launched MotivBase - the world's first and only research tool that instantly decodes the hidden meanings behind consumer interactions. Our technology instantly enables the discovery of ethnographic insight, using big data (millions of consumer interactions online) and allows our clients to solve complex business problems in a matter of minutes and hours, rather than weeks and months.
When we first launched MotivBase, we were proud of what we had achieved, but we were also very aware of the areas where our technology needed improvement. There were two areas in particular where we sought significant gains in the short term.
The first was our technology's ability to track the volatility of trends and predict, with greater accuracy (>80%) the future of a trend or idea.
The second was MotivBase's ability to capture the nuanced changes in the hidden meanings behind trends over time.
I'm proud to say that we've achieved both these objectives in just 7 months since first launching MotivBase. On January 3, 2019, we will launch MotivBase 2.0, which now leverages a vector database instead of a traditional relational topic database in order to convert social science knowledge into mathematical data - a point in multi-dimensional space (this is explained below).
The advantage of this is that we can make social science data (the meanings behind topics/trends) measurable and comparable over time, allowing us to not only improve the accuracy of our predictions, but also capture nuanced changes in cultures and subcultures that otherwise might have been missed. For example, our technology can see that the culture of yogurt is moving slowly away from the digestive health universe and into the avoid sugars and processed sugars universe (i.e. increased worry of sugars in yogurt). This sort of movement can be detected very early and can make a huge difference in our ability to understand where trends or topics or even industries are headed, what impact they'll have on the market size/potential, and over what kind of time frame? This is the power of MotivBase, and our latest improvements add significant value to the innovation and trend analysis process.
To learn more about our vector database, continue reading below or watch this 15 minute that explains what it is and why it's so powerful in the context of big data ethnography.
In order to understand the power of our vector database, we must begin with some basic theory.
Every trend or idea in culture is impacted by two types of factors - economic and cultural. Economic Factors usually involve the spending of money in order to popularize new ideas, while Cultural Factors involve the creation of new norms or ways of doing things (usually driven by the creative classes).
Of course, where things get complicated is that there isn't just one cultural or economic factor affecting trends in our society, there are thousands.
To truly understand a trend, we must first identify the right mix (and relative strength) of all the cultural and economic factors affecting that trend, and then track the changes undergone by the makeup of these factors over time.
This is key and our vector database gives us to ability to do this extremely efficiently.
Let's begin with a simple example. Let's say for argument's sake that we live in a world where consumer culture is driven by just one cultural factor, and one economic factor.
Example of a Cultural Factor:
Feeling a sense of control over one's own health and longevity.
Example of an Economic Factor:
Only buying certain types of natural, less processed foods as a symbol of one's prosperity.
In essence, in such a world (made up of only two factors), a particular topic or trend would be represented in two dimensional space - with let's say the economic factor on the x-axis, and the cultural factor on the y-axis.
In this two dimensional place, each topic will carry with it, the coordinates of its position. Using these coordinates, we can calculate the distances between topics (as there are millions of them in culture) using basic high school mathematics - i.e. Pythagoras Theorem.
With distance, we can now begin to create a genuine model with which to track the evolution of a topic or trend over time.
First, we can examine changes in the position (coordinates) of a trend over time in this 2D space, to project where it will be in the future.
Second, by examining each topic's position relative to millions of other topics in culture, we can not only capture the nuances of meanings that surround specific trends and topics, but can also examine the changes in these nuances over time. After all, the study of something in culture is nothing but a study of that something in context - i.e. relative to its surroundings, and its history (as well as the history of its surroundings).
Consider for example, the case of Gut Health. Just a year ago, this trend used to be about taking supplements or supplementing one's diet with missing nutrients, along with also considering changes in one's diet. But supplements played a big role.
Today, it has become mainly about changing one's diet to fit in natural products that are good for one's gut (the role of supplements has diminished significantly).
The vector database is constantly performing this kind of "universe" or contextual analysis by plotting topics/trends at any given time and calculating the distance between that topic and millions of other topics surrounding it. Doing so allows MotivBase to fully understand the cultural context that surrounds a particular topic (at a given time) and deliver (as well as enable) a truly ethnographic analysis in only a matter of seconds to the user.
Now here's where it gets interesting and the power of technology and big data truly begins to shine through. The example I shared with you earlier was in two dimensional space, where we assumed that our world was impacted by merely one economic and one cultural factor. The reality is that our world (or our culture) is impacted by thousands of such economic and cultural factors. Which means, within our vector database, each topic actually sits in space made up of thousands of dimensions. That is, each topic is represented by thousands of coordinates that identifies its position in space at any given time.
In this way, MotivBase 2.0 has taken social sciences data (i.e. the meanings that exist in culture around a particular topic) and translated it into geometric data, making it highly measurable and opening the door to not only numerous other forms of analysis, but also improving the accuracy of our maturity analysis and trend predictions.
We are excited to show you what MotivBase 2.0 can do.