A taste trade-off
Launching food products with features like 'free from' can help boost sales. But restricting ingredients has an impact on taste, texture and sensory experience - often negatively. Fortunately for producers, for the time being consumers seem more willing to overlook this.
The pace of innovation will increase
But what is the next phase of the 'free from' evolution? As this trend moves from early adopters to mainstream, creating and defending market share in the segment will depend on more traditional drivers like taste, texture and appearance. And the age-old challenge of getting the right product features in front of the right consumers will intensify as variety increases.
Keeping up with the consumer
Responding to more complex consumer needs requires an approach that minimises time at each stage in the value chain. Waiting months for results on consumer studies or spending valuable time and resource evaluating multiple ingredient samples is no longer an option. Nor is hoping you built the right product for the segment your marketing team is targeting. Finally, 'free from' products present additional challenges around taste quality control, both in production and in preserving consistent sensory profiles over the entire shelf life of the product. In this fast and complex world, over-stressed teams can improve success by leveraging data in the right way.
Here are six points to think about when setting up a data collection and management strategy that meets the unique needs of the food industry.
1. Customise your data: Too often producers make critical decisions using generic and high-level industry information that does not have specific project or organisational needs in mind. This results in ‘me too’ products that fail to stand out, or miss the intended target market altogether.
2. Speed: Innovation and launch cycles need to be optimised for speed. Extra time spent collecting, analysing and explaining consumer insights, formulation and marketing data can delay product launch by months or years.
3. Accuracy: Incomplete or insufficient data often hurts more than helps. It is important that any data and insights solution delivers enough consumer feedback to ensure statistical accuracy as well as robust analytics to validate the reliability of the findings.
4. Standardise data: Each step of a new product launch has friction, and focusing all stakeholders on the same strategy is challenging. As is communicating taste, sensory and quality specifications to suppliers and co-manufacturers. If sales and marketing teams are using a separate data set with retail partners, the product can again miss the intended segment. Standardising insights and product data so it can be used across the value chain avoids these issues by aligning teams around the same information.
5. Adapt data analysis for each purpose: Flexibility of data analysis is key. Misunderstandings often occur because the information that fits one stakeholder cannot adapt to the needs of another. For example, R&D may need specific sensory insights while sales and marketing requires granular preference data for specific geographies, demographics or retail segments (eg E-Commerce, hypermarket, convenience shop, etc). A successful solution is flexible enough to customise analysis for these specific stakeholder needs.
6. Share data: Securely and selectively sharing information, both internally and externally, saves time and encourages stakeholders to examine and act on that information. Online portals with secure data access are an ideal solution.
To learn more about successful data collection and management for the food industry visit www.flavorwiki.com
Daniel D. Protz