My Items

I'm a title. ​Click here to edit me.

Report: Integrity in personal care

What drives believability and the feeling of value and efficacy in personal care? It's all about integrity. Integrity has emerged as one of the single most important factors helping consumers in their decision making process. [We discovered integrity and its importance to personal care through our Signals platform where we track the development of early signals of opportunities and threats in the context of various industries and categories.] In this 12 minute video (with 6 additional minutes of Q&A), we provide a summary of a detailed ethnographic analysis of integrity in the context of personal care. The analysis was conducted by our PhD Concierge over the course of one business week, using our AI Anthropology engine, MotivBase Trends. The analysis answers the following key questions - What does integrity/believability mean to consumers in the context of personal care? What are consumers' motivations, attitudes, values, and fears in the culture of personal care products and integrity/believability? What are the opportunities in this culture? You can watch the video below and also explore the full report by subscribing to our blog.

How we differ from other data science and trend prediction providers

One of the first things I learned when we launched MotivBase is that it's a lot easier to explain what we do to someone who already has a background in anthropology, semiology or linguistics. Now the challenge of course is that, there aren't many people in corporate research with that kind of a background. Which means that I can't simply say - we're the only company that uses a deep cultural anthropology and post-structuralist model of analyzing consumer language. Instead I have to recognize that most people would evaluate us in the same way that they'd evaluate any other type of technology-enabled research or analytics provider. And there are a lot of them! So this post is dedicated to the task of explaining the difference between any other form of data science and trend prediction, and an anthropological approach that is grounded in the decoding of meaning from language. I'm going to begin with a simple chart that highlights the key differences. In this chart, I have included some ideas and topics that I'd like to define further: Implicit meaning - here's an article that explains the importance of implicit meaning. Decoding implicit meaning also requires contextual intelligence. This article will provide some background around the notion of context. Culture - before we talk about sizing a culture, it's important to define a culture. A culture is made up of shared meanings and assumptions. These meanings are of course created through a combination of sense experience as well as one's own internal belief and value systems. But what makes a culture unique is the fact that within it, people hold a set of shared beliefs, meanings, and myths (assumptions and ideas that appear real and truthful to those within that culture). Ethnography - The study of a culture. Typically you can look at ethnography through its two component parts. The first being the study of meaning, and the second, being the study of related behavior. Our technology focuses on the first and often overlooked, yet most critical part. Consumer-led vs. industry-led thinking is really the distinction between how an organization looks at markets versus how those within the markets (consumers) look at and examine it from within. Ultimately, no one else can do the following: Search a topic like "intuitive eating" instantly, on-demand. Study the meanings around it immediately. Quantify its relevancy to a population, calculate maturity, predict growth (with 80.4% accuracy), and provide invaluable information on timing - showing when something is ready for mainstream acceptance. Plus, decode the intrinsic motivations, attitudes, fears, and values of the consumer within the culture. All this is possible because of the incredibly rich and complex foundation in cultural anthropology and semiology that MotivBase is built upon. Analytics and behavioral science cannot solve a problem that is not always obviously observable to the senses. Meaning is mostly symbolic. It is perceptual. And it is incredibly difficult to pin down unless one takes an approach created by some of the most famous and reputed philosophers in the field of anthropology, semiology, and linguistics. That is what sets MotivBase apart.

The secret to some of last year’s most successful CPG innovations

Some of the largest CPG brands in the world are turning to a new philosophy when it comes to consumer research. It’s agile. It’s iterative. And it is helping them innovate more effectively. It’s the study of meaning. Why? Some say there is one universal truth - the only constant is change. Take culture. It is in a constant state of flux. And as culture changes, so do the buying and consumption patterns of our consumers. So, if you want to predict consumption, one must be able to predict what is happening in culture. And if you want to understand what is happening in culture, you have to look at the dominant meanings that consumers are using to understand the world (and where your product fits in it). This is one of the most common problems MotivBase is asked to solve because our AI Anthropological approach allows us to map meanings as they are manipulated by consumers over time. It’s really the only way to accurately predict if a cultural shift is occurring. And we are seeing more and more large retailers and CPG companies embrace it. Why? Because the world is complex. Sure, if you went back twenty years, most major CPGs could and would look to past behavior to predict future behavior. Consumer habits were more easily tracked, charted and acted upon. But the world changed. Today: The Internet made information more accessible. The smartphone made it instantaneous. New nimble CPGs made the market more fragmented. As a result, a tremendous amount of pressure has been placed on the consumer. Because more information and more choice doesn’t just require more thought and more time. It requires more justification for why a choice is made. The need to better justify one’s choice has led to the meanings associated with a purchase becoming deeper, and more emotional than ever before. In fact, in most instances the emotional underpinning that is driving a purchase is subconscious. The reason for believing in a purchase is so deep, the consumer could never articulate what is drawing their hand towards that box of cereal, that carton of milk or that bar of soap. This poses a big problem for research, innovation and R&D teams at CPGs. Because they can’t use their standard or traditional tool box to study, understand, or plot the needs of the consumer. Because: You can’t ask a consumer where culture is heading. You can’t ask a consumer to describe something about themselves they don’t understand. You can’t look at one, two or three hundred consumers and assume this is relevant to the masses. So what do you do? You study meaning and you do it at big-data-scale. Predicting the relevance and growth of a trend Before we begin. Let’s talk about what a trend is and what a trend isn’t. An ingredient is not a trend. A diet is not a trend. A product category that starts to grow is not a trend. If someone is telling you that “mango” is the big thing this year, your immediate question needs to be “why”? Too many organizations want a simple answer to a complex question. Too many suppliers are oversimplifying what is happening in the marketplace. Those simple answers, will not yield the desired results. For a more detailed explanation check out this article by our CEO. For your innovation to thrive you need to understand: Why are consumers moving towards a certain ingredient? What are the consumer-led associations that are making one diet more relevant than another? What checklist is an old product all of sudden satisfying that is making it culturally viable again? For this, you need to study meaning. When MotivBase engages with over 130 clients, we are almost always brought in to identify emerging trends. But, trend identification is just the tip of the iceberg. In order to truly help an innovation or R&D team prioritize opportunities and build an effective pipeline, we need to understand the size of the population that will be interested in or engage with an idea, and what the growth trajectory is to pinpoint the exact right time to bring something to market. Launch something too early, and it will not yield the return the organization requires. Launch something too late, and you will lose out to your competition. Let's look at a short use case. Understanding consumer expectations for mineral supplements in the context of mood. Over the last 12 months one of our large CPG clients has worked with MotivBase across their innovation process. The goal? To identify early signals and validate the legitimacy of trends. This assures the foresight and innovation teams are moving in the right direction. Our AI Anthropologist helped the client to strip away their industry lens, and take a more pure and consumer-led approach to understanding the unmet needs of the consumer. And because our system can map, and quantify shifts in meaning, the client was able to better understand, quantify and prioritize the “why” behind changes in consumer expectations and behavior. This “why” is critical. Because while there were a number of social media analytics companies and research firms that specialize in pattern recognition that were seeing strange fluctuation (around a topic like magnesium), they could not actually pinpoint or share cultural “why” this was happening. That is where we stepped in. By leveraging our AI Anthropologist, we were able to quickly see that there was a whole culture of consumers looking to enhance mood via increasing the intake of mineral supplements.

Within this macroculture were 3 dominant microcultures. Improve Sleep. Improve and Boost Energy. Supplement for loss of nutrients during dieting. Magnesium presented itself in all 3 microcultures. For sleep, consumers were looking to some mineral supplements (like magnesium) and natural supplements (like psyllium) to aid in slow digestion. Improving digestion improves the ability to digest fatty foods, and prevents heartburn and stomach discomfort that can prevent proper sleep. For boosting energy, consumers were looking to magnesium to help them boost energy as one part of a healthy lifestyle. Magnesium was being used in conjunction with consumers looking to increase energy levels with high intensity exercise, a more diligent approach to managing water intake, and avoiding dehydration and countering electrolyte imbalances. But while these microcultures validated what our client knew, there was something more important holding magnesium back. While many consumers were looking to supplements to help replace nutrients that were being denied during a diet or fast, magnesium posed an issue. Namely, ‘fasters’ believed magnesium was problematic because magnesium supplements can increase appetite, making fasting even more difficult. The culture of fasting diets is having an impact on the culture of magnesium supplementation. You can not identify or discover this type of cultural collision by analyzing mentions. Because it is not enough to simply study and unlock social data. You need to apply an anthropological lens that allows us to understand secondary, and tertiary meanings that are the root cause for the cultural shift. As you can imagine, this insight provides both opportunities for product innovation, as well as communication opportunities to teach consumers who are looking to complement a fasting diet, but the most important discovery was that one could not simply bet on magnesium because there is a lot of chatter. This is the difference between studying meaning, and studying conversation. It is the nuance, that truly goes beyond what people are saying, to decode the why. How AI Anthropology can help your business grow MotivBase combines our always-on cultural trend prediction software solution, with two additional solutions. The first is an early-warning detection tool designed to look at emerging trends before they hit the mainstream.

The second is an anthropological tool designed to take consumer review data, and then isolate and quantify the size of jobs-to-be-done. This allows us to select the right tool for the right use case, or to perform a comprehensive 360 degree examination of a category and follow the breadcrumbs being revealed by the consumer and start with early trends, compare them to mainstream meanings that are shaping the culture and dig into the nuanced, and tangible actions the consumer is taking to solve for their unmet needs. Conclusion: The beauty of studying meaning, is that we can also look at where both meaning and cultures collide. The net result is the ability to look at: Social Cultures (like the culture of racial injustice) Cultures Around Trends (like a new diet) Category Culture (like yogurt) And our tool is built to allow you to look at them individually, or to identify the intersection of these different cultures. For an example of that, please see this sample report on the intersection of the social justice movement and how it is reshaping the food industry. You can view that report here. The goal is to provide an organization with the ability to inform Corporate strategy Category Strategy Validate Innovation Pipelines Validate Communication Objectives Better understand your consumers in general. To find out more about how we apply AI Anthropology to drive business growth and use the study of meaning to drive more meaningful innovation please contact our team today.

Relativism vs. Realism: Why things aren't as they seem

More than a century ago, the Swiss linguist Ferdinand De Saussure made some critical observations that still to this day hold great significance in the context of modern day research. Saussure noted that we live in a world of linguistic relativism, not realism. That is, nothing is real in and of itself. Nothing has meaning in and of itself. Everything has meaning in a context, and relative to other things going on around it. The moment the context and the surrounding ideas change, the thing and what it means also changes. The reason why this is so significant a finding is that one of the most common mistakes researchers make when studying ideas, trends, objects, and issues in culture is to assume that the thing they are studying has a fixed and unshakable essence. That is, it has meaning in and of itself - by virtue of just being a thing. Take sugar as an example. It is seen as a thing in and of itself and is commonly assumed to have a fixed meaning behind it. It sweetens things. It tastes a certain way. It is unhealthy in large quantities, etc. What most researchers do not realize is that what sugar means in culture is actually a moving target, more so than one might imagine. This is because the contexts it gets placed into, as well as the culture around it, are constantly evolving. In fact, sugar was on a downward trajectory for a good five or six years - assumed to be responsible for all ills in the modern world. In the last two years, this has started to change. Why? The surrounding context is changing. There's a greater conversation about moderation. There's discussion of different forms and types of sugars and the health benefits they can bring with them (e.g. honey). There's narratives around the impact of the right amount of sugar on our mental well-being and joy. New innovations in the area of fermented sugars are opening doors to new applications that reduce the negative health impacts of traditional sugars. And so on… Because the context and meanings around sugar are evolving, so is the purpose and meaning of sugar itself. Sugar does not have an unshakable essence or fixed meaning in culture. Sugar isn't one real thing. It's existence is relative to the things it is surrounded by. That is what I mean by relativism. Why linguistic relativism? Well, words and language is the easiest and most effective way for us to understand the context and meanings sugar is surrounded by. That is why the idea of linguistic relativism is so powerful. Which is also why we practice it with big data, at MotivBase.

What are implicit meanings?

Everything around us has meaning. Sometimes meaning is very personal to us, like something someone might have done for us at some point in our lives. But most of the time, these meanings are shared in our culture and society. It is these shared meanings that interest us because they teach us about the reasons why we do the things we do and hold the opinions we do. We all partake in the process of creating and assigning meaning to the world around us. We do this simply through the natural interactions we have with the people around us be it physically or virtually. In the process of trying to make sense of things or take an opportunity to explain something to somebody, we create and assign meaning. What specifically is meaning? It refers to the words we use when we are trying to explain or make sense of something in the world around us. These words we use in the context of something gives meaning to that something. For example, the way we talk about a topic like “chemicals in skincare products” assigns a set of meanings to the topic. Over time, certain meanings become more dominant while others take on a more repressed position in the context of that topic. What is most interesting perhaps is the fact that in this constellation of meaning, even among the most dominant, a lot of the meanings are quite subtle and implicit. In the sense that if you asked someone, they would find it very difficult to reflect upon their position and talk about those meanings. Let me give you an example. When consumers think about chemicals in skincare, in addition to the obvious – i.e. worrying about the presence of so-called toxic chemicals, they link the issue to an interest in pre- and pro-biotic rich products. In fact, they are so keen on pre- and pro-biotic rich ingredients that they worry about using natural products (as a simple alternative to chemicals) because many have naturally occurring anti-bacterial properties that could harm their skin’s flora. It will be impossible to get to an insight like this by interviewing consumers. In fact, our client did just that in this case only to discover the expected. Consumers worry about toxic chemicals in products and think they could be either harming their skin in the short term (causing, rather than eliminating blemishes) or worse yet, making themselves susceptible to cancer in the long run. No one discussed the connection between chemicals in skincare and the desire for pre- and probiotic skincare. That is simply the power of studying meaning in the context of [something]. Consumers just do not make these linkages overtly yet. Examining the broader context of discussions around the topic of "chemicals in skincare" allows us to identify and quantify the dominant meanings – many of which are implicit and often indirectly linked to the culture, yet are in context and therefore give it meaning and shape its future. Why can't we just study meaning by asking people the right questions? The work of the famous philosopher Jacques Derrida teaches us something very relevant and important about decoding meaning. Human beings, when asked a question, work hard to provide answers that are concise, logically structured, and relevant. This process our brains go through in answering a question is also a process where our brains eliminate a lot of the meanings that are nonetheless shaping our thoughts and opinions, but are difficult to explain or just don't fit a logical framework with which we need to answer a question. Which is to say that when put on the spot, we all often eliminate meanings rather than articulate and consider them. That is just the limitation of human interaction, one that we can overcome by decoding extremely large samples of data from the natural and organic conversations millions of consumers have on the internet every single day. By examining the meanings shaping the broader context around a topic, we get to capture all those implicit perceptions and assumptions that consumers make in the normal course of their lives, but that will rarely get communicated in framed discussion. Studying meaning is a way for us to force ourselves outside the logical paradigm of Q&A. It enables us to see the things that aren't common knowledge just yet or even fully logical, but are still affecting the future outcomes of our businesses. Does that mean modern data sciences and analytics engines can better capture meaning? Yes, but not without an understanding of context. Which is exactly where these engines fail the goal of studying and decoding implicit meaning. Every engine out there studies the "mentions" of a topic. Through "mentions", they grab data, then analyze patterns in that data-set to report on relationships. This is fine for the purpose of analytics, social media listening, and such tactical exercises. But it fails in the goal of studying meaning, because more than 70% of the meanings associated with a topic are indirectly established. That is, they rarely exist in the same sentence or "online post" as the mentioned topic. Take the example of "gut health". If you examine the direct mentions of "gut health" you will see the meanings that are the most explicit or direct. Such as the connection to weight loss or food. The problem is this presents an incomplete picture of what is really going on in this culture. When you examine the broader context of meanings created around "Gut Health", you realize that there is so much more going on that was simply hiding in plain sight. It requires contextual intelligence to unearth. In fact, in the macroculture of "Gut Health", the microculture of "Nutrient Absorption" and "Vitamin Deficiency" is not only one of the most lucrative spaces at the moment, but it is also quietly shaping the future of what makes something legitimate in the context of one's gut. If we didn't have the ability to tap into (and quantify) the meanings shaping the broader context of the culture, we would never have identified any such groundbreaking ideas. Instead, we would have kept surfacing the same insights as everyone else and missed a majority of the forces that are quietly brewing in the backdrop. That is why the study of meaning requires greater thought and attention to how culture gets created, how it proliferates, grows, or becomes volatile.

What conditions must be met for an innovation to succeed?

In every microculture, consumers have requirements that must be met in order for a product to be considered a ‘real’ solution. The field of phenomenology [the study of structures of experience and consciousness] distinguishes itself from the field of psychology by asking one really important question — What conditions must something satisfy in order to count as ‘real’ in the mind of a human being? That is exactly our preoccupation at MotivBase. We ask the same question every time we run an analysis, just in a slightly altered format to make it more relevant to corporate innovation. What conditions must [something] satisfy in order to count as ‘real’ within a [cultural or marketplace context]? Let us make this tangible with an example. If you explore the macroculture of plant protein today in the almost post-pandemic world, you'll find that a major microculture shaping plant protein is one of nutrition. Specifically, the desire to reduce nutritional deficiencies across one's diet with the consumption of the right type of proteins that ensure that our bodies get access to essential nutrients. When we see a microculture such as this, especially one that offers growth potential in the culture of plant protein (which otherwise is going through a lot of volatility), the key question we ask is what will make a solution 'real' to the consumer in the context of this microculture. To put it another way, what requirements does the consumer naturally and inadvertently outline for us to deliver against? What are the must-haves? Some of those requirements include - Minimizing the use of processed and refined sugars in plant proteins. Reducing the fat content of plant proteins. Ensuring the prevalence or inclusion of essential amino acids. Only will the satisfaction of these requirements make [something] relevant in the context of this microculture. This isn't a question of following shiny 'trends' but rather the task of understanding a bundle of related tactical requirements that, when met, become 'real' in the mind of the consumer and take the macroculture of plant protein and make it relevant to a broader audience. Let's take another example - In the area of 'natural' personal care. If you explore the macroculture of natural personal care today, you'll find that a major microculture revolving around the use of plant-derived ingredients. Specifically, the desire to include natural ingredients in the mind of the consumer relates to the inclusion of ingredients derived naturally from plants and plant-extracts. This microculture offers growth and innovation opportunity, being in the Early Consensus Stage of maturity. However, for a solution to appear 'real' in the mind of the consumer in the context of plant-derived ingredients, it must satisfy certain requirements or conditions. Let us examine what they are - Rich in Vitamin E, Completely free of any unnatural fragrances (no added fragrance). Offer natural moisture benefits. Be guaranteed not to trigger allergies. Begin with a line of Shampoos before expanding to other personal care products. Only will the satisfaction of these requirements make [something - a brand or a product line] relevant or believable to the consumer in the context of this microculture (plant-based ingredients). Here again we notice that it isn't about any particular isolated tactical 'trend' but rather about the bundle of requirements that, when met, become 'real' in the mind of the consumer - solving their implicit needs and desires. Why are these conditions so important? An understanding of human motivation isn't enough if our goal is to uncover opportunities for revenue growth. While an understanding of the consumer's psychology and motivation is valuable in allowing us to build empathy for the human condition, it's not sufficient in helping us figure out the implicit requirements that need to be met in order to create a natural cultural fit within a microculture. This is where it becomes so valuable to take the approach of examining the implicit meanings shaping a culture and identifying the specific conditions that show up in the mind of the consumer often in a way that they themselves may not realize. Taking such an approach of examining meanings to decode the conditions for success also has an important side effect. It helps prevent "shiny object syndrome" and allows us to realize what is truly an opportunity shaping culture rather than a tactical blip on the radar that will not yield long-term top or bottom line growth.

Job alert: Digital Architect (Canada)

We are looking for a digital architect in Canada to join our growing research technology company. At MotivBase, our specialty is market research; specifically, in a niche that informs the front-end of innovation. By 'front-end' we're not talking about single-page-apps. Rather the big strategic moves that our clients make in order to compete in their industries. When decisions are informed by our research, with our home-grown methodologies and technologies, good things happen. We are now in our 6th year of operation. Our business is growing faster than ever, and we need a hardened professional to take ownership of some of our strategic moves. In the role, you will work with our founders to build an information system that will solve a well-understood problem. It is a greenfield project and an opportunity for us to create new technology. It is also an opportunity to expand the reach of our existing IP. The architect will own all stages of development, in the code and out, and be granted the necessary resources to see the project to completion and beyond. As the project unfolds and the architect becomes familiar with all the systems we've built, we expect new ideas and thought leadership where it's needed. From day one, you'll be part of a daily scrum with a good group of people that will make sure you're 'getting it' and getting what you need. We expect the candidate to be strong in several of the following areas. Where strength is lacking, there is an ability to learn quickly by doing: Microsoft Web Tech (MVC, ASP.Net, IIS) API Development: implement new features, instrument, and automate quality control. (C#, Web tech) Natural Language Processing: can represent qualitative data quantitatively and create data visualizations (Python, Spacy, word vectors) Content Management Systems: building tools for non-technical users (Umbraco) Front-End Development: (Angular, SPAs, Highcharts) Cloud and Dev Ops: provision infrastructure, deploy and monitor systems, improve development process. (VSTS, Azure, Git) Machine Learning: you know when to use ML and can set realistic expectations. (Azure ML, Tensorflow, Others) 2D Graphics: can implement visualizations that run in a browser( SVG, <canvas>). Big Data ETL: transform data on a schedule and process streams of user generated content. (Azure Data Lake Analytics, Powershell, USQL) Resource Management: you could hire, onboard and manage contractors to implement your design. (TopTal, Upwork) Product Management: agile by nature, not agile by choice. (Basecamp) Information Security: once you understand our system, you could answer an industry standard info-sec questionnaire (Auth0, PII, SSL) Apply to

The anatomy of a trend

Contrary to popular perception, a trend isn’t something that’s getting a lot of mentions at a point in time. There’s a broad misconception about what makes something a trend and it often sends corporate innovation on a wild goose chase. Over the course of the last ten years, we’ve all grown to accept the idea that a trend is something that is being talked about a lot (let’s thank Twitter for that, shall we?). How many mentions is something getting? Have the mentions grown significantly over the last little while? These are the types of questions we find ourselves asking when we are trying to determine if something is trending. As I am sure you’ve guessed from the title of this article, this method of defining trends is inherently inaccurate. There are two main reasons why – The first is the fact that such a definition makes no acknowledgment of the underlying context within which a trend is being examined. For example, the flavor ‘cranberry’ might be getting a ton of mentions online (for whatever reason…maybe people love the Cranberries again!) but when examined in the context of a healthy beverage, it may not in fact be a trend worthy of mainstream acceptance. Context is everything and adding the lens of context requires the framework of ‘meaning’. But more on this later. The second reason is that such a definition completely ignores the fact that language is never truly black and white. Just because the word ‘cranberry’ is getting a lot of mentions does not necessarily mean that ‘cranberry’ is in fact a trending flavor. We have made far too much progress as a society over the last hundred years especially in the fields of linguistics and the Social Sciences to turn a blind eye to the fact that language, the words we use in everyday conversation, is nothing but a set of pointers. Words point to things. They point to larger sets or themes of meaning that are being inadvertently and often subconsciously communicated by people (consumers) in culture. ‘Cranberry’ in most cases isn’t actually about the fruit or the flavor, it’s about something else altogether. For example, it could be referring to a renewed interest in preventative health practices or the use of food and beverage to improve mental focus or energy. How should one go about identifying ‘real’ trends? There are some fundamental requirements to identify trends in context. To start, as you might have already guessed, we need to develop the ability to understand context. If we’re trying to look for trends within the context of, let’s say, sustainable personal care, the first task is to examine the broader context of conversations that consumers are having around sustainable personal care. That is, we need to get beyond examining the direct mentions of sustainable personal care or its related synonyms but rather examine the full range of natural conversations that consumers end up having within its broader context. Even when they’re not specifically using the words “sustainable personal care” they may be clearly responding to someone who has instigated the topic and thereby engaging on the broader subject matter. Next, we need to explore the themes of meaning emerging, from within the context. Themes of meaning are nothing but sets of words or topics that all connect together naturally because the consumer associates a shared set of meanings with them. For example, you may see a theme of meaning that connects sustainability in personal care to the use of certain chemicals in the manufacturing of packaging. Turns out, the consumer is looking beyond packaging waste, plastics, even, natural products to think about the supply chain — specifically, all the chemicals and chemical processes that are required for packaging production that are often hidden from the spotlight but heavily damaging to the earth nonetheless (toxic for the environment). This is an example of what we would call a ‘real’ trend. Now, within this set of meaning, there are many chemicals that consumers may mention quite a bit like Trichloroethane. But it’s important to distinguish the ‘meaning’ from the ‘mention’. Trichloroethane is a pointer. It doesn’t matter how much or how little it has been mentioned on the internet. What matters is what it points to. Which in this case is the concern over chemicals used in packaging. That is the ‘real’ trend here. Once we get here, we’ll need to start thinking about quantification and relevancy. To do so, we need the ability to quantify the relative importance of each theme of meaning in the underlying context. This is when we’ll examine not just the volume and frequency of each theme (within context) but also the linguistic relationship established by consumers through the natural discourse they carry with each other. The net result is the ability to develop a semantic scoring system that allows us to identify the most dominant themes in a given context. What we end up with is a set of prioritized trends. Themes of meaning that tell us about what is really shifting in culture, with examples of how that might be manifesting today. This approach is really critical because it gets us away from focusing on the mentions (which are mere manifestations of trends). In the context of the earlier example, it gets us away from focusing on Trichloroethane and instead on what it means to the world of sustainable personal care. If we can do that, then we’ll identify trends that will offer long-term opportunities for corporate innovation rather than short-term blips on the tactical radar. It will allow us to create a truly healthy innovation pipeline and think proactively about the macro (and consequently, micro) shifts affecting our categories.

Back to the Future. Why innovation teams need to get back to business, before it’s too late.

Ok. We made it. 2020 is in the rear view mirror. And sure. It wasn’t easy for some of our clients. Many innovation and insight teams had to hit pause on their long-term planning. Instead, they turned to MotivBase to better understand short-term cultural changes taking place as a result of Covid-19. But some of our biggest and best clients actually accelerated their long-term planning. And it’s due to a little secret I will share with you by the end of this article. When I’m asked for a metaphor to describe what MotivBase does, I like to say it is a flashlight in a dark room. We use AI to study the meanings that consumers link and associate with things in culture. By mapping this meaning, we are able to shed light on the biggest opportunities. Because meanings reveal long-term, healthy trends. The challenge with Covid-19 is that many companies got so scared of what was happening, they dropped the flashlight all together. Instead they started focusing on reactionary initiatives to counter short-term shifts in consumer behavior. Look. We get it. It was a crazy year, and I for one, hope I never have to use the word “unprecedented” ever again. But the companies that are going to thrive in the next 3 to 5 years are the ones that never stopped looking out to what the future had in store. Or, they paused briefly but are now looking back to the future (wait a minute… that’s the name of this article!) to plan accordingly. In fact, Harvard Business Review was reinforcing this message as early as last June. In their article “Why Now Is The Time for “Open Innovation” Linus Dahlander and Martin Wallin call out a number of ways that companies should be taking advantage of our current predicament. This future-forward approach is important, because solving for 2021 isn’t enough. Clients need long-standing innovations that are going to withstand the test of time. They also need help understanding the ideal timeline for launching new solutions and renovations for some of their biggest brands. They need to know where culture is going. But how do you do so, when there is still so much uncertainty? So many organizations feel like they are frozen in place, struggling to understand if something is just a short term blip created by Covid-19 versus a critical, valuable and meaningful long-term, healthy trend? So what do you do? Well, remember that secret I promised you? You identify trends that were already growing pre-covid. And ideally, you measure to see if Covid-19 has caused them to accelerate. You measure the meanings that are shaping consumer culture, to find out where Covid-19 has acted like gas, being poured on the fire. Because the fire was burning before the pandemic. The unprecedented situation has just been an accelerant. That is what Motivbase has been designed to do. And that is why we are the flashlight many insight and R&D teams have been fumbling to find in the dark. At MotivBase, our goal from day one was to help our clients predict where culture was heading. By taking proven social science theories from the past century and finding innovative ways to leverage big data to make them more powerful, and more relevant than ever before, we’ve been able to help our clients solve problems that were, before our engagement, unsolvable. And while yes, it is a model that can be used to culturally identify acquisition targets that will grow in relevance with consumers, or pinpoint consumer needs that yield award-winning innovations, our goal is to take the fear out of some of the most stressful aspects of the innovation process. Because the insights are not just powerful. They are sized, and measured and prioritized. With the ability to look back at where culture was before Covid-19, measure the changes in culture that have taken place during Covid-19 we are able to better calculate how consumers will act after Covid-19. By looking back to the past, we can help you get back to focusing on the future.

The Webinar is this Thursday: How the social justice movement will impact food.

Are you uncovering societal trends that will reshape how your company does business? In our upcoming webinar this Thursday, we will showcasing an example of just that. We are all guilty of spending too much time focusing on category trends. But, to truly understand how culture is impacting your business, you need to be able to identify the intersection of different forces shaping consumer expectations. Take the current shifts in the social justice movement. This will change how consumers view food. How? Join us Thursday, January 28 at 1 pm EST. In this webinar, MotivBase's Chief Anthropologist and CEO, Ujwal Arkalgud, will outline the impact of the social justice movement on food. Using our AI Anthropologist MotivBase, Ujwal will not only outline the dominant microcultures emerging in this space but also explain what each microculture means to the consumer, quantifying its relevancy and growth trajectory over the next 12-48 months. Here's a sneak peek at a small part of the content:

Solving for perception problems related to your brand or product

A lot of us work on brands or products that are completely or partially misunderstood in culture. Of course figuring out that something is misunderstood is fairly straight forward. Even simple surveys will help us do that. The problem comes when we attempt to solve the issue or correct the misunderstanding. We quickly realize — It’s easy to be misunderstood. But very difficult to correct an inaccurate perception. Logical ideas and scientific approaches just don’t work. A while ago we had a food retailer tell us that no matter what they do they can’t seem to shake off the perception that their produce isn’t fresh. Despite numerous initiatives to empirically correct the issue and logically communicate the correction, they hadn’t been able to break out of the perception that they do not carry the freshest 'fruits and veg'. To solve the perceptual misfire, we knew we had to identify the meanings that create the perception and of course, examine those meanings that go beyond obvious logic - those are often the places where the gains can be truly made. Exploring the meanings that shape people's perception of freshness allowed us to identify the not-so-obvious connection to food waste. In essence, the consumer believed that if a retailer has the freshest produce, then they must also have a best-in-class food waste program so as to not only minimize waste but also ensure that excess food is donated to various communities programs. It's not one of those obvious connections but once it was uncovered, it just made so much logical sense. If you believe you offer the freshest produce, then you must demonstrate that you truly value your product offering. And the best way to demonstrate its value is by minimizing waste and maximizing the benefit to consumers and the community. So, instead of trying to demonstrate logical reasons for why their produce was fresh, the retailer focused on creating and excelling in their food wastage initiative, especially when it came to fruits and vegetables. Within a quarter, they began to see a lift in their brand perception studies and over the course of a year added new equity to their brand and business and sizable gains to their balance sheet. By going through the lens of meaning, MotivBase was able to identify the right narrative with which to attack the perception problem. We didn't assume what that narrative was. We discovered it by exploring the implicit meanings that make up the consumer's perception of freshness. Meanings offer incredible value to our respective businesses. They don't just teach us about what the consumer is really thinking. They also teach us about how that thinking is modeled and framed up in their minds.

Webinar: Impact of social justice on food

How will the social justice movement impact food? In this webinar, MotivBase's Chief Anthropologist and CEO, Ujwal Arkalgud, will outline the impact of the social justice movement on food. Using our AI Anthropologist MotivBase, Ujwal will not only outline the dominant microcultures emerging in this space but also explain what each microculture means to the consumer, quantifying its relevancy and growth trajectory over the next 12-48 months. When? Jan 28, 1pm ET. Click here to sign up.

© MotivIndex Inc. 2020. For our privacy policy, click here.