At The Social Intelligence Labs ‘Trends Summit’ 2024, Nik Pearmine hosted a panel to discuss the utility of social data in product innovation.
Can social data drive foresight capabilities and more successful product innovation? We certainly think so.
But what does the industry think? More and more CPGs are moving beyond social listening. They are injecting predictive, social data into the innovation process to drive better decision-making.
Nik was joined by pioneering guests and practitioners within our industry to discuss the topic, including:
Alberto Romano, Global Futures & Consumer Planning at DIAGEO
Alberto agreed. He added that Diageo focus on macro trends. They see fads as the natural evolution and expressions of that larger trend over time.
AR: "We’re looking at 5 big macro trends. One of them is related to what’s positive for planet, the environment and communitites. 15 years ago we were talking about the ozone layers and aerosoles, then we we were talking about turtles and straws and circularity. And this will keep evolving.
"The trend is the same, but the fads, or signals and expressions of that trend is what changes. Being able to pick up on that larger, key insight that’s going to evolve is something we’re getting better at."
Kristina defined the differences between sustained trends and fads by their staying power.
Trends have tangible impact on a market and on consumer demands. Fads tend not to. Trends fulfil a key consumer need. Whereas fads are often more fun, reactionary and novel expressions of what consumers want at a specific moment.
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Defining the difference between a trend and a fad is a common challenge that Black Swan helps its customers solve.
Fads can be quick commercial opportunities. Especially for CPGs that can move swiftly. (We know this is harder for brands with longer innovation cycles.)
But trends, if they sustain, have the potential to shift a category and create much larger revenue opportunities.
Especially if that trend is underpinned by a real, unmet consumer need.
Being able to identify these new and emerging consumer needs is critical for translating fads and trends into products that consumers really want.
Nik’s next questions centered on prediction. Black Swan predicts a social trend’s trajectory in 6 months time to an average accuracy of 89%.
It helps the brands we work with anticipate future opportunities and make strategic bets.
But what did the panel think about using social data for scenario planning?
Kristina stepped up first. She referenced the pandemic to describe the challenges with accurate foresight.
KK: "Who could have predicted the pandemic? It’s very difficult to predict as trends are often driven by external factors. But we can size opportunities based on different metrics. So what’s key for me is having an always-on data architecture that tracks trends over time."
Alberto explained how Diageo have a slightly different perspective on prediction. He and his team focus on building the future, rather than simply trying to predict it.
AR: "The foresight system / trend framework we’ve created is giving us the right building blocks to build the future. Instead of being a passive observer, we have the power to act rather than react. It's a mindset shift from predicting to building."
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Social prediction is still a new concept to many within our industry.
Black Swan has developed metrics to help brands identify what trends to prioritize, understand why they should be activated and know when to move on them.
We also retrospectively analyze the performance of our trend predictions to verify their continued accuracy.
Prediction will always be disputed and distrusted while the front-end of innovation remains wooly. While it remains an art, more than a science.
But the addition of objective, unprompted social data into the front-end of innovation programs is beginning to change that.
Next, Nik asked the panel to share their thoughts on how observational, social data can make organizations more intelligent. Joseph stepped up first:
JA: "Social data allows us to peel back the layers and get to the consumers’ real issues, needs and desires."
Kristina explained how she introduced monthly ‘Consumer Pulse’ sessions to senior leaders.
KK: "Every month I was able to bring real-time consumer feedback and the latest trends to C-level management. Instant feedback allows for quicker response times and adjustments."
Alberto unpacked Diageo's slightly different approach:
AR: "Our innovation cycles are longer - so we don’t move as quicky. But the integration of social data with search and sales data allows us to shape our innovation cycles. We don’t have to wait for the next study to make a decision."
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The decisions made by insights, innovation and marketing teams are often only as good as the data that influenced those decisions.
Social data is a goldmine of immediate and often untapped consumer insight.
Especially when it is filtered, structured and transformed into always-on consumer intelligence and served in user-friendly tools for anyone to access within the organization.
The brands we work with are benefitting from injecting this data into their innovation programs.
It’s helping them make more scientific decisions. And taking some of the guesswork out of the process.
Kristina described social data as “a goldmine of inspiration”.
She also warned of biases within social datasets. Integration with other data sources is key to creating a rigorous data ecosystem.
Alberto rounded off the discussion with three valuable lessons from his experience of applying social data to NPD.
AR: "Stay curious and go down the rabbit holes. Translate for all. Make your info relatable and understandable for everyone. Try, learn, fail, repeat."
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We certainly agree that social data can be “a goldmine for inspiration”.
Our partners at PepsiCo, General Mills and Mars are all using our solutions to create powerful, ultra-relevant new product ideas.
Over the coming years, we expect the rest of the industry to adopt this approach.
Many thanks to our panel for their time and for sharing their thoughts.
You can watch the full discussion below:
