Suntory

How Suntory partnered with Whaly to turn complex field data into actionable sales execution

Background: Building the next pillar of commercial performance

Suntory Beverage & Food France operates in a highly competitive FMCG environment, where field execution plays a decisive role in commercial performance. In grocery retail, every store visit matters: sales teams must understand their market, prepare their actions, 

The priority was commercial efficiency: helping teams work with greater clarity, prepare more effectively, and align field execution with business priorities.

The Challenge: Turning fragmented data into coordinated action

The company relied on multiple sources of commercial intelligence: market data, sell-out indicators, store-level readings, CRM information, routing data, internal documents, and drive-related inputs.

The challenge was to make this ecosystem operational for the field. Data needed to be centralized, translated into usable recommendations, and embedded into existing commercial routines. At the same time, the project had to align business teams, IT stakeholders, European governance, and field users within Suntory’s internal project methodology.

This created a double challenge: build a solution that was useful for sales teams in their day-to-day work, while ensuring the project could move through the right validation gates, security requirements, and organizational checkpoints. 

The Solution: A commercial efficiency layer built around field routines

Suntory partnered with Whaly to create a centralized activation layer on top of its existing data and sales ecosystem. The goal was simple: provide the right information, to the right team, at the right moment, in a format that could directly support commercial action.

Whaly was designed to centralize and activate several key data sources, including Nielsen data for sales, sell-out, distribution and market indicators; Circana data for out-of-stock insights; CRM and store readings from Statigest; routing information; internal documents; and drive-related data.

The solution was structured around the moments where sales efficiency is won:

• Weekly planning
  Helping sales teams prepare their week with a clearer view of priorities, opportunities, and stores requiring attention.
• Visit preparation
  Equipping reps with structured insights before entering the store, so conversations are driven by facts rather than fragmented interpretation.
• Objective monitoring
  Giving teams and managers a clearer way to track cycle objectives, performance indicators, and commercial priorities.
• Management enablement
  Supporting Regional Directors and sales leadership with adoption tracking, team visibility, and a more consistent way to steer execution.

Rather than positioning Whaly as an isolated AI tool, the project was framed first as a commercial efficiency platform. AI becomes an enabler of better execution, not the headline, in order to focus on performance, adoption, and operational usefulness.

The Expected Impact: From data visibility to field execution

At this stage of the project, the success of the collaboration is measured less by final business KPIs than by the operating foundations it puts in place.

The expected impact is clear:

• Sharper prioritization: helping sales teams identify where to focus first.
• Better preparation: reducing the time and effort needed to collect information before a visit.
• More consistent execution: aligning teams around the same indicators, priorities, and recommendations.
• Stronger management visibility: enabling sales leadership to monitor adoption, objectives, and team activity.
• Scalable commercial routines: creating a framework that can support broader deployment beyond the initial test users.

By centralizing market data, CRM inputs, store-level readings, routing information, and internal resources into one actionable layer, Whaly aims to help Suntory move from fragmented intelligence to coordinated execution.

Beyond the Tool: A new operating model for commercial efficiency

For Suntory, Whaly is not just another reporting interface. It is a way to connect data, business priorities, and field action into a more coherent commercial system.

The collaboration also represents a broader shift: moving AI from experimentation to operational usefulness. The technology matters, but only because it serves a practical objective: helping sales teams prepare better, act faster, and focus on the stores and opportunities that matter most.