“The Future of NPD: Why Social Prediction is a Game-Changer for Glanbia Performance Nutrition (GPN),” was presented by Nikolas Pearmine, Chief Strategy Officer at Black Swan Data, and Shiho Ng, Senior Manager, Insights & Analytics at Glanbia Performance Nutrition.
In the case study, Glanbia, an active and healthy lifestyle brand focused on nutritional products, shows how it is leveraging social prediction technology to predict future consumer behavior and deliver reliably successful product launches to market.
“We’ve been on a journey of modernizing our insights capabilities for the past couple of years since the appointment of our new vice president of insights and analytics,” says Ng. “We’ve been building a robust stack of insights capabilities so that we can continuously monitor the markets, categories, competitors, and consumers in an efficient and effective manner, as well as to allow us to spot the early trends so that we can capitalize and act upon them. And it’s really activating the insights that are extracted from various observation analysis, data analysis to drive the innovation to make it more consumer driven, consumer relevant and salient.”
Social Directions
As for Black Swan Data, the company aims to collect social data, so social media, blogs, forums, reviews, in essence, anything publicly available, and structures that data around categories like snacking or supplementary nutrition and markets like the U.S. AI helps in that regard, especially with the volume of big data available.
Pearmine relates, “The first goal is to understand within those millions, tens of millions, at times hundreds of millions of conversations people are having online, what are they talking about? Once we understand that, the second job is then to use our technology to look at how those conversations are going to affect purchase behavior and perception around our category up to three years into the future. Once we’ve achieved that, the third job is then to understand which of those opportunities are right for that portfolio, and then how can we move through a process to accelerate bringing products to market.”
For Glanbia, says Pearmine, “We’re going to look at supplements in the U.S. over the last two years. There’s almost seven million different unique conversations people have had on the platforms. Within those seven million conversations, there’s nearly twelve and a half thousand individual topics. We call them topics deliberately, not trends. Those topics are defined by ingredients, benefits, products, brands, occasions, emotions, and so on, that people are making reference to in the content of their Instagram posts, their tweets, their Pinterest, posts, etc.”
So how do we take those seven million conversations, twelve and a half thousand different topics, and identify what are people talking about? How do we project that to influence category behavior, by predominantly purchase behavior and perception into the future?
Pearmine notes, “A lot of the time, the questions posed to us by clients is, well, how do I use you? What use cases is it appropriate for me to consider social data for? And in simple form, the questions that we ask as marketers, as researchers of our agencies, of our partners, of consumers is exactly the same questions we’ve been asking for the last hundred years. But we help identify where social data should be a primary methodology versus a supplementary one and then how it sits within sort of the broader ecosystem of methodologies.”
Identifying the Key Trends
For Glanbia’s Ng, using Black Swan Data gives her the ability to scan the big trends in the space, identify the future pockets of growth, and refine and prioritize at the granular level to make the innovation relevant to today’s consumers. This brings new products to the world of innovation, the big trends within the space.
Ng says, “What we are seeing is big trends within the supplementary datasets. At GPN, we primarily serve in the health and wellness space. Monitoring these datasets is pretty spot on. But depending on the industry category you are serving, Black Swan Data offers multiple datasets. You can mix and match the datasets you want to monitor continuously. Now what we are seeing is, basically, each trend depicted as a bubble, and the size of the bubble is based on the volume of the conversation that is happening on the social platform. We can understand which one is the scale. And then the location is depicted by the past growth of such conversation and the predicted future growth of such conversation. We can understand where the future pockets of growth are, based on the social, volume and the velocity of the social conversation and social prediction.”
GPN can also see the sub-trends bubbling up underneath. For example, from consumable beauty it can be seen to be supporting the growth of hair, skin, and nails. In protecting healing, it is more about supporting and boosting your immunity and anti-inflammatory needs. The company can double click further to see the individual topics.
While it’s a substantial undertaking, it’s about uncovering these specific layers of research. “We are able to then identify every single ingredient, benefit, claim, product, brand that has an association with those spaces,” says Pearmine.
He adds, “We understand the trend life cycle. Each of these individual, red dots represents one of the hundreds or thousands of different ingredients or products that are being discussed within the context of this particular trend, we’re able to then understand which maturity phase that particular topic is in today and its forecasted growth then over the next twelve to thirty six months, depending on if it’s a more breakthrough or incremental innovation opportunity.”
Ng points out, “Paying attention to emerging adoption cycles or growing adoption cycles would be the way to go to consider the innovation for the next period of time. Take colostrum, for example, or especially bovine colostrum. It’s the first milk that mother cows produce for several days after giving birth. For the baby cows, to adapt to the new world coming out of the mother’s wombs, they need a little bit of a nutrition boost for their health and immunity protection. The mother cow’s fast milk is designed to be very nutrient rich, packed with unique protein, fats, antibodies, bioactive compounds, growth factors, and so on. It’s basically a super food and it caught the attention within the health and wellness space and the word spread.”
“Primarily, we can see that the category is a good fit when it comes to organizational capability, portfolio fits, brand fits, and so on,” notes Ng. “Hence, we pay attention to colostrum as one of the viable options. But depending on the category industry you are serving, you might pay attention to another trend as a viable option. Your mileage may vary, but it gives you an idea how this can be powerfully utilized for the innovation process. With that said, we introduced Isopure colostrum powder supplements, which was launched a few months ago.”
Ng concludes, “Black Swan Data helps us innovate with speed and better conviction. Because it turns the millions of consumer conversation into consumer insights, consumer foresight, evidence-based narrative that helps us to activate and back up why this innovation in the development will drive the consumer relevance in the markets we are serving, not only for today, but also for tomorrow.”
For more of the Glanbia Performance Nutrition product innovation case studies in partnership with Black Swan Data, watch the full presentation in the video from TMRE 2024.
