Transforming the Enterprise with AI Innovation

Lessons learned from Latin America’s leading retailers and CPGs

Top retailers and CPG companies operating throughout Latin American illustrate why the region is the ideal proving ground for the use of artificial intelligence. The region’s unique circumstances and business challenges and innovation driven culture make AI a necessity to optimize decisions to serve diverse shoppers.

Understanding why Latin America is the ideal use case for AI begins with insight into what makes the region special.  For starters, the phrase Latin America oversimplifies the complexity and vastness of a region that extends from Mexico to the southern tip of Argentina and Chile. The land mass and population are twice that of Europe (or the United States), spread across 20 countries, each with unique histories, cultures, economies, social structures, and diverse populations with great variations in spending behaviors.

In addition, to the diverse geography, Latin American shoppers are some of the most digitally connected consumers in the World  with Brazil and Colombia in the top three, each spending more than 10 hours per day online living in huge, highly urban and dense cities.

In such an environment, merchandising strategies and promotional execution need to be digital and personalized to be successful. As a result, retailers and CPGs are reliant on technology, AI specifically, to make crucial strategic decisions to serve shoppers and create business value. We see companies focused on AI driven transformation in the following ways:

  1. Market leaders have embraced AI solutions to cope with the breadth of variables and variations in shopper behaviors that exist in an area as large as Latin American. This is especially true for retailers who operate in multiple countries as well as the CPGs who sell to them. They understand AI is essential to uncover actionable shopper insights that are relevant for each country and the many distinct shopper segments within those countries.

  2. They use authentic AI. If solutions are lacking a foundation of data science and sophisticated machine learning capabilities simply can’t deliver results in challenging market conditions. Only authentic AI can correlate countless variables simultaneously and prescribe appropriate actions to achieve optimal results, whether that is in the supply chain, through assortment optimization or more accurate demand forecasting. As the volume of stores and number of countries and regions increase so does the complexity of operations and the need for authentic AI. Consistent results correlate with sophisticated solution. With other solutions, results might very well be a one-time only (positive) coincidence!

  3. They avoid simplistic solutions and approaches that sound too good to be true. What we see happen with non-AI based solutions is decisions based on flawed or incomplete insights may produce short-term results, but they can be largely coincidentally. Problems arise is these results are relied on to validate further sub-optimal decisions. This is a real risk because retailers and CPG’s may never know the potential upside that was missed, or worse yet, overly simplified assumption about consumer behavior can lead to decisions that alienate shoppers.

  4. They pursue intelligent experimentation. The key to a properly structured pilot is to select a typical business challenge rather than the most complex challenge to better quantify the impacts of AI more readily. The time frame is also important. If the pilot involves demand forecasting and supply chain elements, then several replenishment cycles are needed to observe accurate results. If an initiative involves customer loyalty, then the pilot period would need to be set on an appropriate purchase history timeframe. This is a very common situation that I see with clients. With early results comes confidence, and with confidence comes creativity—new ideas of where else they could be applying AI.

  5. They set realistic ROI expectations. Moving from implementation to the realization of benefits depend on variables related to the type and scope of the action being taken. For example, assortment decisions that span 1,000 stores take longer to implement and to realize benefits. Conversely, benefits related to pricing adjustments or loyalty program features can occur more quickly.

Retail has always been a detail driven business where success comes to those best able to master its intricacies, and there more intricacies today than ever before. That is the case globally to be sure, but Latin America stands out as an example of a particularly complex operating environment where the effective use of AI is imperative for success.

(NOTE: Symphony RetailAI is participating in AI-LATAM.Com, the leading artificial intelligence event in Latin America, March 23-26. 

Please join me, our Head of Data Science Analytics, Withiel Cole, and Renato Stefanoni (Commercial and Logistics VP, Extrafarma Brasil) and Flávio Almeida (CRM and Private Label Manager, Extrafarma Brasil) in a unique session on “Know more. Predict better. Execute faster. Increase revenue and margin with breakthrough AI solutions”.

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