Organic Food CPG Company

ORGANIC FOODS CPG COMPANY USE CASE

Background:

Consumer preferences and behaviors are changing rapidly during the COVID pandemic.  Understanding these preferences, predicting where they are headed, and most importantly, what to do about them is core to any CPG brand’s ability to survive and thrive.  A key element fueling that understanding is having efficient access to the most relevant internal and external data.


Objective:

An organic brand’s company seeks to understand factors effecting the sale of organic foods so they can identify new offerings and optimize targeting and messaging.


Approach:

Their analytics team needs to quickly identify relevant features that will enable a more complete view of the customer and the competitive landscape.  Having access to data from a variety of sources that are normally off limits is important to understanding the consumer and developing a growth strategy, especially during these extraordinary times.

The brand’s Nitrogen.ai Data Feature Lake manages internal category sales, shipments data, integrates retailer data, and includes features from public and commercial data providers.  Additionally, the combination of consumer sentiment data, social media / online browsing behaviors, foot traffic data, and household panel data allow modelers to find features that expose otherwise hidden patterns in the sales data.   In this instance, the Nitrogen.ai recommendation engine unearths consumer behaviors that may be predictive and proscriptive.


Outcome:

Data scientists can quickly identify features signaling preferences for purchasing organic food.  These features coupled with categories that correlate with increasing sales, fuel the development of new products and messaging that may appeal to the changing tastes and preference of organic food buyers.

Example:

The analytics team needs to quickly identify relevant features to enable a more complete view of the customer and the competitive landscape.  The N.ai platform automatic feature selection capability makes finding surprising predictive nuggets efficient and easy.