Despite the odds, consumer packaged goods (CPG) innovators are constantly seeking out ways to create new and exciting food and beverage flavors. To make sure their products stand out on crowded shelves, they must keep up with rapidly shifting market trends and consumer preferences. Successful product launches hinge on flavors and flavor combinations that meet market demand.
Whether they’re looking to satisfy increasing demand for global and health and wellness flavors, or a desire for multi-sensory mashups, CPG experts have their work cut out for them. A fast, efficient, and exacting flavor creation process is key to success.
In this blog, we’ll explore the four tenets of flavor creation. An understanding of these principles will ensure your new and improved products succeed in the market. You’ll meet the preferences of today’s consumers while decreasing costs and minimizing the number of chemicals required.
1. Smell and taste create flavor
A flavor is comprised of smell and taste – how receptors in the nose and mouth perceive chemicals found in food.
The five basic elements of taste include sweet, salty, sour, bitter, and umami. Smells fall into one of ten categories: fragrant, woody/resinous, minty/peppermint, sweet, chemical, popcorn, lemon, fruity (non-citrus), pungent, and decayed. The way different flavor components impact one or a combination of these traits is the foundation of successful flavor creation.
However, according to research from the American Chemistry Society, the chemicals that produce flavors are notoriously difficult to study. A single natural flavor might contain hundreds to thousands of different substances, some of which are present in minute quantities.
For example, one of the nine main aroma compounds found in pineapple is so potent that people can detect it at only six parts per trillion—the equivalent of a few grains of sugar in an Olympic-size swimming pool.
2. Interactions unlock product breakthroughs and innovations
Depending on how different food and beverage ingredients interact with each other, we achieve different responses (e.g., liking, saltiness, sweetness, bitterness). Common interactions include salty and sweet, sweet and sour, and fat and acid.
Traditional flavor experimentation has involved changing one ingredient at a time and then testing the result. For simple flavors with a minimal number of components, this trial-and-error method leads to satisfactory results.
However, for complex food and beverage products, this process is time-consuming and labor-intensive. And, it results in less flavor diversity and innovation. In other words, changing only one flavor ingredient at a time won’t tell you how that component responds when other variables also are changed.
A model that allows you to change multiple ingredients simultaneously is ideal. It will help you efficiently and quickly understand the impact of many different interactions on your product flavor. Such a model will increase preference and likability scores while decreasing undesirable chemicals, all at a lower cost.
3. A data-driven process drives flavor optimization
Data-supported ingredient adjustments lead to better products.
Once you can measure how various interactions impact your flavor, you can optimize your product. For example, you can determine how to reduce the number of artificial ingredients in watermelon popsicles while cutting cost. Or, you can increase likeability while decreasing sodium in chips.
To optimize flavor, you’ll gather data about how your flavor affects the prepared product. That way, you’ll understand how different components in the flavor interact with each other and your food product (e.g., ice cream, cereal, chip, sparkling beverage, etc.). So, if you want to create a watermelon-flavored cereal, you would apply the flavor to the prepared cereal to determine how all the flavor and product molecules interact.
Then, a panel of trained tasters will evaluate that product flavor, and you can fine-tune it accordingly. A data-driven model allows for real-time adjustments to multiple flavor components, so you can create a more desirable product in less time at a lower cost.
4. Data allows you to account for variability
Howard Moskowitz famously shifted the entire product creation landscape in the 1980s when he introduced the concept of variability versus universal products, starting with spaghetti sauce.
Working with Campbell’s Soup, he discovered that you cannot satisfy the market with one product (e.g., plain spaghetti sauce). Instead, he found that people who like spaghetti sauce can be clustered into three categories: those who like plain sauce, those who like chunky sauce, and those who like spicy sauce.
Campbell’s Soup went on to launch Prego extra chunky sauce, which took over the market, generating $600 million in profits over the next decade. Since then, CPG companies have known they must account for variability to grow their business, increase customer satisfaction, and build brand loyalty.
With more than one-third of consumers actively looking to try new products, speed to market is key. A data-driven flavor creation model allows you to quickly and seamlessly analyze many different product variations so you can deliver the right product mix to meet market demand.
Connect with Intellex
Whether you’re launching a new product or improving upon one that is already on the shelf, data-driven flavor creation delivers. If you’re looking for a CPG expert who can apply the data-driven flavor creation process to your products, reach out to Intellex to learn more.
About Steve Leusner
Steve Leusner holds a bachelor’s degree in Chemistry from Rutgers and an MS in Organic Chemistry from the University of Maryland. He has more than 30 years of product development and flavor creation experience working at companies including Kraft, General Mills, and Ottens Flavors on brands including Jell-O, Cool Whip, POST, Wheaties, CHEX, and Cheerios.