Case study

PepsiCo Northern Europe embraces SymphonyAI Retail shopper insights to build business across multiple categories

04.19.2023 | By Mark Speyers

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About PepsiCo

PepsiCo products are enjoyed by consumers more than one billion times a day in more than 200 countries and territories around the world. PepsiCo generated $79 billion in net revenue in 2021, driven by a complementary beverage and convenient foods portfolio that includes Lay’s, Doritos, Cheetos, Gatorade, Pepsi-Cola, Mountain Dew, Quaker, and SodaStream. PepsiCo’s product portfolio includes a wide range of enjoyable foods and beverages, including many iconic brands that generate more than $1 billion each in estimated annual retail sales.

Strategic Objectives

PepsiCo Northern Europe is committed to accelerating its digital transformation journey by advancing its AI-enabled analytics to fortify the business and build competitive advantages for the long-term. As a result of this strategic focus, PepsiCo has become a respected CPG innovator.

PepsiCo Northern Europe seeks to continually deepen collaboration with key retailers across the globe to leverage primary shopper data to better meet the needs of consumers, shoppers and retail partners while also achieving business performance objectives.

Business Challenge

Many of PepsiCo Northern Europe’s major customers harness SymphonyAI Retail CPG AI-based Customer-Centric Revenue capabilities, including Customer 360 Segmentation and Sales and Customer Insights. PepsiCo Northern Europe seeks to make sophisticated use of these solutions to engage with retailers and leverage primary shopper data in new and unique ways.

Solution

PepsiCo Northern Europe has emerged as a leader among SymphonyAI CPGs for its embrace of shopper insights to build its business across entire categories at their retailer partners. PepsiCo Northern Europe merchandisers and category managers use AI insights and combine it with their category knowledge and expertise to create a more shopper-informed assortment. PepsiCo Northern Europe today is integrating SymphonyAI Customer Centric Retailing into its collaboration with retailers all over the globe, driving better plans and superior business results.

Project Approach

PepsiCo merchandisers and category managers work with dedicated SymphonyAI success coaches in multiple retailer partners to unlock maximum value from SymphonyAI solutions and continually enhance shopper-centric business alignment and results.

The collaborative approach yields better processes and alignment and in turn, better productivity and results. SymphonyAI tools and solutions are never used in isolation, but cleverly combined with PepsiCo Northern Europe category knowledge, shopper understanding and internal advanced analytics capability.

Results / Value

PepsiCo Northern Europe’s data-driven culture permeates all levels of the organization. Senior leadership ask for deep data and invests strategically in giving merchants and category managers leading technology to get these deep insights, including those provided by SymphonyAI.

Today PepsiCo Northern Europe has deeply experienced, confident SymphonyAI users who systematically leverage retailer shopping data and insights provided by SymphonyAI to better drive the business. Success coaches report that PepsiCo users continually explore new areas for analysis to deepen and strengthen the value unlocked by SymphonyAI-enabled retailer collaboration.

PepsiCo Northern Europe frequently leverages SymphonyAI customer insights in their standard reset planning cycles, as well as in their “Big Bets” content around more dramatic strategic innovation. The reset in Salty Snacks category in 2022 at a leading Netherlands-based multinational groceris a great example of PepsiCo’s increased sophistication in data and analytics usage. PepsiCo Northern Europe combined retailer data and SymphonyAI solutions with their own internal advanced analytics capability and successfully brought shopper-led store clustering to life in more than one thousand stores.

Jan Haluza, manager of data science and analytics at PepsiCo Northern Europe, summarizes strengths in PepsiCo’s collaboration with the major retail player. “The Netherlands is one of the highest penetration markets for snacks, at nearly 96%, so PepsiCo and our partner can’t really deepen category penetration,” Jan explains. “Instead, we focus on understanding targeting shoppers very precisely to best align our assortment and category strategy with their needs. We worked with the retailer to undertake a strategic snack category overhaul including consumer insights, space management and supply chain, to drive a major strategic reset.”
PepsiCo Northern Europe and the retailer collaborated on an end-to-end data-driven approach centered on a four-step process:

  1. Integrate relevant data to create on powerful dataset
  2. Identify areas of highest growth potential
  3. Design a solution with tailored in-store value propositions and personalized shopper engagement to unlock growth opportunities
  4. Convert to growth using continual measurement and improvement

The huge dataset indexed as many as 1000 characteristics per store, and the comprehensive data meant that PepsiCo Northern Europe and the retailer could run advanced analytics models on the data. “We used the analytics to drive a shopper-led store re-clustering initiative,” Jan notes. “We grouped stores into three shopper-led clusters. Together with our retailer, we had deep discussions around the clusters and the solutions for each, and we used SymphonyAI for assortment optimization for each cluster. We analyzed incremental share of market and assortment model to generate the best scenario for each cluster. Then we generated planograms for each shelf specifically for different clusters.”

Tessa Maas, senior category manager, food at PepsiCo Northern Europe, was pleased at how the comprehensive approach met multiple strategic goals for both the retailer and PepsiCo. “The strategic approach tied to overall category vision and how to grow snacks in the future – by brand, flavor, etc., including incorporating shopper decision trees. We took the time to learn from shoppers how they actually navigate a shelf – do start with a flavor and then find a brand? Or start with the brand and search for a flavor? We developed different priorities, objectives and in the end solutions for each cluster.”

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