Coca-Cola Is Turning Intelligent Decisions into a Competitive Advantage
In retail, deciding what to order today and how much may seem like a routine task. But when a business serves tens of thousands of stores, these everyday decisions have a direct impact on revenue, inventory efficiency, and supply chain performance.
The challenge is this: when every store has different customer needs and purchasing patterns, how can businesses move beyond simply keeping shelves stocked to actively creating new sales opportunities?
Coca-Cola is exploring that opportunity through AI.
In Malaysia, Coca-Cola’s B2B platform, Coke Buddy, features Perfect Basket, an AI-powered solution that recommends the right products and order quantities for individual retailers before they confirm their orders.
What makes this approach compelling is not simply that AI makes ordering easier. It is that Coca-Cola is turning data into actionable recommendations at the exact moment a purchasing decision is made.
In today’s competitive landscape, knowing what a customer bought in the past is no longer enough. The real advantage lies in understanding what that customer should consider buying next, and how that recommendation can create greater business value.
From Purchase Data to Smarter Business Decisions
Perfect Basket analyzes multiple data signals, including purchase history, ordering frequency, seasonality, weather conditions, and purchasing patterns from similar stores. These insights are then used to generate recommendations tailored to each retailer.
Consider two stores located just a few kilometers apart. One may see demand for beverages rise during hot weather, while the other may experience increased demand for certain products during holidays. Although both sell products from the same brand, their demand patterns can be very different.
Applying the same recommendations to every store risks overlooking these differences and missing valuable sales opportunities.
AI enables Coca-Cola to bring these signals together in a more systematic way, supporting decisions with a broader range of data rather than relying solely on past orders or individual experience.
This represents a shift from a one-size-fits-all approach to more personalized, data-driven selling.
From a business perspective, this creates opportunities to improve product recommendations, expand product mix, and anticipate changing customer demand.
Revenue growth does not always require acquiring new customers. Sometimes, it starts with understanding existing customers better and uncovering the opportunities hidden in every order.
Beyond Insights: Turning Intelligence into Action
Having large amounts of data does not automatically translate into business value.
Dashboards can show how sales performed last month. Analytics can reveal which product categories are growing. But for business leaders, the more important question is: What should we do next?
This is where AI can help bridge the gap between insight and action.
Coca-Cola’s approach is particularly interesting because AI is not confined to back-office analytics. It is embedded directly into the retailer’s ordering journey, transforming data into recommendations that can be acted on immediately.
This reflects the broader concept of Decision Intelligence: going beyond helping organizations understand what is happening to actively supporting better decisions in real business contexts.
Importantly, AI does not have to replace human judgment. Retailers remain in control of their purchasing decisions, while AI processes large volumes of data to provide more relevant recommendations and additional decision support.
The same approach can extend to other B2B use cases, including sales forecasting, demand prediction, inventory optimization, and customer recommendations.
By reducing the analytical burden, AI can also create opportunities for sales and business teams to focus on higher-value activities, from strengthening customer relationships and refining account strategies to identifying new growth opportunities.
Ultimately, the value of AI is not measured by how much data it can analyze. It is measured by how effectively it helps a business make better decisions and turn those decisions into results.
When AI Becomes Part of the Business Workflow
One of the biggest challenges in enterprise AI is turning technical capabilities into tangible business outcomes.
An AI model may generate highly relevant insights, but if those insights remain buried in reports or require users to navigate multiple systems and change their established workflows, their business value may never be fully realized.
Coke Buddy offers an interesting example of a different approach. By embedding AI-powered recommendations directly into the ordering process, Coca-Cola brings intelligence into the workflow where it can influence a decision that matters to the business.
According to AI News, Coke Buddy serves approximately 39,000 stores in Malaysia. During a campaign trial, 83% of participating stores opted to use AI-generated recommendations.
These figures provide an encouraging signal of user adoption in a real-world setting. However, adoption alone does not establish that revenue or sales increased by the same proportion. Measuring those outcomes would require additional performance data.
Still, the case highlights an important principle: the AI that creates the greatest impact is not necessarily the most sophisticated. It is the AI that addresses a meaningful business problem and fits naturally into the way people work.
When AI becomes an integrated part of the workflow, organizations have a stronger foundation for extending intelligent decision-making across more customers, teams, and business processes.
For executives, this is a critical consideration that goes beyond technology selection. The real challenge is not simply building AI that works. It is embedding AI in a way that creates sustained, measurable business value.
AI Does More Than Analyze
Coca-Cola’s approach reflects a broader shift in enterprise AI, from using data to understand what has happened to using intelligence to identify opportunities and support decisions that directly influence business performance.
For organizations with large volumes of customer and transaction data, the key question is no longer just how much data they have.
It is whether that data can help sales teams understand customers more deeply, forecast demand more accurately, and uncover growth opportunities that might otherwise go unnoticed.
At Sertis, we help organizations turn data into intelligent decisions that drive real business value. By connecting data, AI, and business workflows, we develop solutions that address practical business challenges—from customer behavior analytics and demand forecasting to intelligent recommendations and the integration of AI-driven insights into day-to-day operations.
The goal is not simply to introduce AI into an organization. It is to identify where AI can create meaningful value, translate business objectives into practical solutions, and establish the right metrics to measure success.
AI that creates a competitive advantage should do more than analyze data.
It should turn data into recommendations, recommendations into decisions, and decisions into measurable business outcomes.
Is your organization making the most of the data it already has? And more importantly, are you ready to turn customer insights into your next growth opportunity?
Sertis helps you connect Data, AI, and Business to turn intelligent decision-making into a lasting competitive advantage.
