The Next Flavor Sensation: Using Big Data to Predict a Hit

Food manufacturers devote extensive development time and significant financial and human resources to the task of creating the next big hit. But what’s the best way to predict the next flavor sensation?

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With the holiday season approaching, food manufacturers are monitoring trends to see if their seasonal-themed products are a hit or a miss with consumers this year. The return of certain well-established seasonal food or beverage items is as predictable as birds flying south for the winter: Starbucks is selling pumpkin-spiced latte, bakeries are offering candy corn-topped cupcakes and breweries are producing pumpkin-flavored beer. Special fall blends will eventually give way to peppermint-flavored offerings just in time for the holiday shopping rush.

But somewhere among the tried-and-true flavor combinations that hit store shelves every year, a manufacturer will offer a new flavor sensation that will become the next salted caramel or cinnamon dolce — a product that bursts on the scene, generates sky-high sales and inspires countless imitators across multiple categories. Manufacturers devote extensive development time and significant financial and human resources to the task of creating the next big hit. But what’s the best way to predict the next flavor sensation?

Name the Candidates

For food and beverage flavor developers, the possibilities are virtually limitless, but few companies have the time or money to explore every idea. So the first step is to develop a short list — five to seven flavors that have potential to be a hit. Big data is indispensable at this step; with the right analytics platform, companies can identify flavors that are trending and narrow the possibilities down to the likeliest candidates.

To find a list of trending flavors, companies can search social media, trending products in adjacent categories and recipes that are generating significant interest in their target markets. A well-designed analytics platform can help identify the strongest candidates so that the manufacturer can narrow the field for further consideration.

Test Potential Flavors

A flavor needs two qualities to succeed: 1) it must attract consumer interest, and 2) it must have enough potential to give the manufacturer the confidence to invest in development. To get a new flavor project off the ground, companies should conduct testing, even if they don’t have a product prototype. Analytics can yield valuable information on which flavors people prefer and, just as importantly, who prefers specific flavors.

The latter dataset — the information that tells companies which people prefer certain flavors, can be incredibly valuable. Companies can pinpoint flavors preferred by proven influencers, such as people who correctly identified past flavor trends before they became big hits and people who experiment with new food choices and share their experiences. With a well-designed analytics strategy, it’s possible to identify early adopters and assign due weight to their opinions.

The Bottom Line: A Shorter Cycle

Traditionally, companies have conducted market testing on trending products and planned launches a year in advance, but the cycle is getting shorter. Big data and automated analytics are giving manufacturers a way to accelerate the testing and development cycle across industry sectors. For example, the fashion world has been upended by new “fast fashion” strategies deployed by retailers like Forever 21 and H&M, which have shortened a year-long cycle to just two months. Traditional apparel retailers are scrambling to keep pace and make up for lost market share and revenue.

Now the accelerated cycle is happening in the food industry. Big data and automated testing tools can help food manufacturers be more agile and identify and respond to trends much more quickly. The companies that use these tools to keep product concepts fresh will be ahead of the curve in the new data economy, applying analytics to the art and science of predicting the next flavor sensation. And that could translate into a huge advantage over competitors.

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