Pumpkin flavor is in the mix — but what if a company doesn't have a pumpkin-flavored product? It needs to move fast, according to Dr. Anil Kaul, CEO and co-founder of Absolutdata. Flavor trends tend to be like fashion trends; people buy the trendy product for a while and then go looking for something new.
Food Dive spoke with Kaul about how to identify flavor trends and decide if they are a good business move.
Pumpkin (or any) flavor doesn't work for all companies or products. Does the product have any relationship to the flavor considered? It can use marketing research techniques to determine if a flavor fits with a product, and needs to identify the consumers who see the fit and who are the early adopters. They play a critical role in whether a flavor is a success. Taste tests are important to find out if people feel the flavor is right.
If the company is already using a flavor, how does it determine how long the flavor will remain in demand? Typically a flavor trend has an S-curve shape — it starts flat, grows fast, and then plateaus. Sometimes it can push up the plateau, but eventually the trend starts going down.
Finding the next flavor
The product development timeline requires good forecasting skills about where a trend is going and what may trend next.
Kaul sees the food industry starting to adopt what the fashion industry has historically done — quickly introducing a new product, testing it in the market, evaluating the results and then making adjustments. This model goes beyond marketing and requires efficient and fast production, supply chain, and back office support.
To help in this process, Kaul says companies need to use three sets of data:
- Data that identifies early emerging trends: Social media data is especially important.
- Sales data from market research companies: Companies can take this data and use analytics to identify early indicators of what's happening in the marketplace. What new products are starting to become successful and do they indicate a flavor trend?
- Past data: What has previously worked in particular markets? Using advanced analytics can pull out trends that aren't obvious. For example, companies can look for the types of flavors/ingredients that when combined were most successful and can then use this information to decide on future flavor/ingredient combinations.
Perhaps the biggest challenge for companies that want to do this type of big data analysis is the data hasn't always been digitized. It must first digitize the data, then have to figure out what signals the data can provide for the product/category. It then has to create viable recommendations for the market.
Kaul's advice for companies new to big data? Look at all the historical data already available, for both the company and its competitors. This data provides a lot information.
It needs to either develop analytical expertise within the company or to work with a company that specializes in data analytics. Also, this process isn't a one-time activity, it's ongoing.