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For years, the ability to predict the future has been an alluring concept for individuals and businesses. What better way to make money than to know exactly what the latest consumer trends will be and when they will hit mass adoption? However, due to the inherent difficulty of creating a crystal ball, determining the elusive ‘tipping point’ — when innovation becomes widely adopted — has always been challenging. But with advancements in artificial intelligence, the possibility of predicting the next big trend and its tipping point is more attainable than ever.
It starts with understanding the different Philosophies of Prediction concerning business innovation: Search Signals, Social Signals, and Product Signals. By monitoring signals across these categories, companies can gain valuable insights into consumer behavior, emerging trends, and competitor strategies.
At Treacy & Company by Cherry Bekaert, we work with companies to integrate predictive AI tools into their innovation processes, boosting innovation effectiveness, speed and outcomes. Read on to learn how AI can turbocharge your own innovation and help your company stay ahead of the curve by combining all three philosophies.
Related: How to Leverage ChatGPT to Unlock New Levels of Innovation
1. Search Signals — or asking the question: What is going to happen?
This philosophy is about observing and examining the online search patterns of consumers to determine their interests and potential future searches. By tracking keywords and search data, businesses can understand which topics are gaining popularity and which are decreasing in interest.
These signals often represent the strongest leading and early indicators for a trend yet to fully develop or a product (or product extension) that is yet to go mainstream. The first matcha green tea seeds are said to have been introduced to Japan in 1191 by the Zen monk Eisai. Fast forward nearly 800 years later, and you’ll find the matcha green tea latte in a Starbucks, as of April 2006, the first indicator of matcha’s potential for mainstream appeal in the US. But it wasn’t until February 2015, when the first spike in search volume happened — until the trend took off. People were searching for matcha smoothies, ice cream, cakes and cookies, which tipped the industry to launch ten new matcha-related products by 2016.
Search signals can be beneficial in revealing valuable timing insights, like the rise in the popularity of matcha. Monitoring them closely can help businesses and industries identify the timing to capitalize on a trend.
2. Social Signals — or asking the question: What is happening?
This philosophy is about scanning social media activities, discussions in forums and product reviews to comprehend the consumers’ opinions and emotions towards different topics. Through the evaluation of metrics such as engagement and sentiment, businesses can determine what appeals to consumers, what creates hype and what could become popular in the future.
The bath bomb was a simple creation to improve the bathing experience. No one could have guessed in their wildest dreams the heights this unassuming ball would reach. On average, over 25 million bath bombs are sold yearly — that’s one per second.
Lush Co-founder and Product Inventor Mo Constantine created the first-ever bath bomb in her garden shed in 1989. In 2015, a huge spike in social chatter took hold, and the hashtag #BathArt became wildly successful, tipping the industry to develop more than 400 designs by 2021 when #bathbomb had more than 150 million views.
Social signals, such as the overwhelming popularity and engagement surrounding #bathbomb, highlight the power of social media in driving consumer trends and shaping product development strategies. Businesses can harness these social signals to gauge consumer sentiment, identify emerging opportunities and cater to evolving consumer preferences.
Related: How Successful Entrepreneurs Predict the Future
3. Product Signals — or asking the question: What has happened?
Lastly, innovation requires a certain historical perspective. We don’t create market-moving products in a vacuum but rather iterate based on previous niche launches. This involves analyzing data from previous product launches, patent filings, rebrands and other product-related sources to gain insights into business actions and potential future actions. It helps businesses understand what products and services are gaining popularity, what drives innovation in their industry, and what could be the next big thing.
The Instant Pot is a multi-functional pressure cooker that has recently gained immense popularity. It went from being relatively unknown — launched by founder Robert Wang and his wife Tracey in 2010 and sold to some local brick-and-mortar retailers with very modest success — to become a sensation in the kitchen appliance market. The pivotal moment for the Instant Pot came when people noticed it during an Amazon Prime sale on July 12, 2016.
During the sale event, the Instant Pot caught consumers’ attention due to its discounted price and the buzz generated by online shoppers. As people started purchasing and using the product, they shared their positive experiences and recommendations on social media platforms, blogs and forums. This created a ripple effect, leading to increased product awareness and demand.
Monitoring product-related data, such as sales data, customer reviews and social media mentions, could have helped identify the initial surge in popularity of the Instant Pot. Businesses and marketers could have capitalized on it by strategically promoting the product, creating targeted marketing campaigns and optimizing production and distribution.
By integrating knowledge from all three philosophies, companies can develop a thorough comprehension of the market and use this to make better decisions regarding their innovation and R&D strategies. Winning companies integrate knowledge from all three philosophies, recognizing that each signal offers unique insights into consumer behavior, emerging trends and competitor strategies.
It’s important to note that while AI tools can support and facilitate discovery and pre-discovery, human judgment remains crucial for decision-making. AI provides valuable insights and data analysis capabilities, but ultimately, human judgment drives innovation and determines the best course of action.
Nonetheless, with the help of AI, companies can more effectively monitor and analyze data from all three signals to predict the tipping point for the next big innovation and stay ahead of the curve. This holistic approach empowers organizations to navigate the dynamic marketplace, seize opportunities, and achieve long-term success in the ever-evolving world of business.
This story originally appeared on Entrepreneur
