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Why CPGs Struggle to Grow in Emerging Markets

9/3/2021
a crowd of people at a fruit stand

Emerging markets account for 55% of the global consumer spending of consumer-packaged goods (CPG), and in the next five years, consumer spending in these markets is expected to grow three times as quickly as that in the developed economies, with total spending expected to exceed $6 trillion. Despite these stats, still most CPG companies struggle to grow in emerging markets.

However, these tremendous growth opportunities often remain elusive for large international CPGs. The primary reason for this is that international CPGs often try to use the same recipe of growth in emerging markets which they have perfected in developed markets.

Unlike developed markets, where strong brand and adequate shelf-space in large chains is often sufficient for growth, emerging markets have their own unique challenges.

Above all, e-commerce has very little role in these markets; physical stores and markets generate a large fraction of the sales. At the same time, growth in these markets doesn’t simply result from occupying shelf-space in large chain stores but ensuring precision distribution at hundreds of thousands of small corner shops in every neighborhood. Since these small shops do not have point-of-sale scanning devices, there is no way to directly track sales and stock levels at each shop, making it very difficult to accurately determine sales targets, optimize supply-chain and plan trade promotions. Similarly, there is also no granular data about population and consumer profiles, making it equally hard to estimate demand, and pinpoint opportunities of growth.

Essentially, these emerging markets are not lit-up with data and insights which are granular and actionable to grow market share. We refer to these markets as “dark markets.”  

In these dark markets, data-driven sales execution often holds the key to unlock growth. This, however, requires forward-looking insights, which can “lead” sales planning and operations. Lagging insights, such as previous month’s Share-of-Market (SOM), are not actionable. Especially, sample-based third-party data which reports country-level market share is only useful for high-level trend analysis. Such data cannot guide decisions for sales planning, supply-chain optimization, demand estimation, and ROI analysis of trade and marketing promotions.

While many might imagine that emerging market insights would require relatively simpler technology, our experience at SurveyAuto has been quite the opposite. It turns out that lighting up these dark emerging markets with forward-looking, granular, and actionable insights, requires technology that is even more sophisticated and complex than the technology used in developed markets.

In order to estimate population, CGs should use a solution that leverages AI on satellite imagery analysis to automatically extract built-up area, and combines this with granular socio-economic mapping, to generate neighborhood-level data about population and socio-economic classification.

Since point-of-sale scanning data is not available in these dark markets, machine learning algorithms can estimate sell-out volumes using secondary sales data. This secondary sales data is extracted from distributor management platforms commonly used in these markets. This enables CGs to be able to track hundreds of thousands of small retail outlets for each product type, segment and SKU, building millions of machine learning models internally to generate accurate demand and sales forecasts for each store, channel type, consumer profile, and distribution territories.

Combining this with geo-spatial analysis, CGs can also pinpoint neighborhoods with under-indexed numeric distribution, unmet product demand, opportunities for optimizing product assortment and potential to grow market share. Algorithms can also create a digital twin for every trade promotion and marketing campaign, and generate real-time insights about changes in demand, incremental lift and return-on-investment.

The application of AI and machine learning for CPGs in emerging markets has received little attention in the past. As physical markets re-open after COVID, the importance of appropriate technology to light up these emerging markets is expected to grow.

Dr. Umar Saif is CEO of SurveyAuto Inc.

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