Elastic brands add real value to new categories. To stretch into growth, innovative, elastic brands do five things differently. Experimenting with AI and evaluating how it can streamline and enhance innovation is one of five tenets of success for elastic brands. 

Artificial intelligence (AI) and machine learning technologies deliver enhanced ways to solve consumer problems, which is often the foundation of successful innovation. Generative AI excels in synthesising data, and as it continues to develop, its role in innovation will grow. Embedding AI into business operations can help reduce costs, increase innovation agility, manage inventory, enhance forecasting, foster an experimental mindset, and help with go-to-market strategies.  

AI’s potential lies in product experimentation, efficiencies, and accuracy

Machine learning algorithms and predictive analytics take in vast amounts of data, identify patterns, and transform operations and the supply chain – key to successful innovation plans. AI can also prioritise ideas and allow for experimentation and concept testing if accompanied by the right organisational mindset. 

AI can fast-track the identification of market and operational risks and highlight competitive advantage opportunities. By analysing market trends, competitor data, and consumer preferences to suggest new product designs and features in a fraction of the time, brand-stretching idea generation is accelerated. For example, by using AI, PepsiCo experimented with various combinations. AI was also used to precisely control product characteristics of the Cheetos product for the perfect flavour profile .– a process that showcases how brands can test and capitalise on stretching objectives.   

But it’s important to recognise that AI doesn’t create deep human connection  

This is where analytics experts can derive comprehensive insights and formulate test- and-learn strategies for innovation from the data generated strategies. Why? Because AI and machine learning technologies can be the differentiator between a product launch and successful, sustainable brand stretch success. For example, YSL developed a “scent-sation” headset featuring brain activity monitoring that blends neurotech and AI. This is curated intelligence because of the personalised fragrance advice that it provides. Ultimately, machine learning is the foundation of the retail consultation experience. 

Personalisation strategies are also forging ahead thanks to AI tech, capitalising on the wealth of personal information generated by the explosion of e-commerce, data-driven marketing, and rapid tech advances in AI and machine learning. This empowers brands and retailers with wide-ranging, real-time consumer data such as browsing behaviour, purchase history, and demographic information. Together, these deliver an highly tailored, personalised arsenal of communications strategies to predict consumer preferences accurately. The result is a highly engaging and effective, hyper-personalised product or service – key to driving sustained growth and loyalty.   

Investment in seamless data infrastructure is essential for innovation and growth 

The engine that drives AI is data, and the right systems are key to the optimal collection and usage of real-time customer data to deliver targeted messaging at scale. And as AI evolves and businesses get better at optimising its outputs, it will further automate marketing, sales, and supply chain decisions and be a key linchpin for innovation and brand-stretching success. 

Circana’s comprehensive strategies ultimately drive growth and loyalty by delivering real-time analytics to measure and accelerate demand and stretch your brand to success.  

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