Earn More, Sell Less: Find Your Niche in the $90B Tea Market with AI
Introduction
Are your export volumes up but profits flat? You're competing on price, not value.
The way to win is to stop selling more and start earning more. This means finding high-profit niches that will pay a premium for your product.
Finding these markets used to require expensive reports and dedicated data teams. Not anymore. We'll show you how to use an Terno AI and raw data to build an actionable, high-profit export strategy—all from a few simple questions. [See the full Terno AI conversation here]
Analysis of Global Production and Market Trends
A sound strategy begins with a macro-level understanding of the market. The first question is foundational: is the market for this commodity growing? Terno AI can instantly analyze decades of data to provide a clear answer.
Prompt: Make a curve to show global tea production."
This curve provides the essential starting point for our analysis. It clearly shows that global tea production is not a stagnant or declining market; instead, it has been on a steady upward trajectory for decades. This confirms that overall demand is robust, but it also signals a crowded and increasingly competitive field. In a growing market, simply producing more isn't a winning strategy—competing smarter is.
Prompt: Make a chart to show what % of countries account for 80% of global production/export?"
This chart is crucial for understanding the competitive landscape. It visualizes the high concentration in the tea market, showing that a small handful of countries are responsible for the vast majority of production and exports. For any business, this identifies the key market players and underscores the challenge of competing on volume alone. It forces the strategic question: "How can we compete if we're not one of these giants?
Differentiating by Value Over Volume
The core of a high-profit strategy lies in moving away from a volume-based model. The critical question is not "who sells the most?" but "who earns the most per unit?"
Prompt: Which exporting countries are getting less value for their tea compared to competitors — where branding/quality improvement could raise profits?
Prompt: How does the export value compare to the export volume – which countries make more money per ton of tea?
Prompt: How do producer prices vary across countries and years?
Identifying the Value-Add Opportunity
What fundamentally separates the "Value Players" from the "Volume Players"? The answer is often value-added processing. Selling a finished, processed good is more profitable than selling a raw commodity. This hypothesis can be visually tested.
Prompt: Visualize the ratio of processed tea to raw tea production over time with a stacked area chart.
This stacked area chart illustrates the critical gap between the vast amount of raw, primary tea being harvested and the much smaller, more valuable portion that is processed. This gap isn't just a statistic; it's a multi-billion dollar opportunity. The visual proves that the key to unlocking higher profits lies in adding value by turning a raw commodity into a finished product.
Strategic Market Identification and Selection
With a clear strategy—to export high-value processed tea—the final step is to identify the most receptive markets. The ideal target is a country with high demand but low domestic production.
Prompt: Identify supply gaps.
Prompt: Compare production vs. exports for each country — who produces a lot but exports less, and who exports more than they produce?
Prompt: Make a chart that groups countries by how much tea they produce, earn, and export, so we can see which ones are similar?
Executive Summary
- Global Production Surge
– Primary harvest soared from ~3 million t in 1990 to ~42 million t by 2021.
– Processed output (2010–2020) climbed from ~5.7 million t to ~9.2 million t, keeping the processed share at ~23 %. - Concentration of Output & Trade
– Just ~12 % of countries account for 80 % of global production; ~14 % cover 80 % of exports.
– Pearson r ≈ –0.02: no clear link between how much a country produces and the price it receives. - Top Producers & Exporters
– Leading harvesters (2021): China (≈13.8 Mt), India (5.48 Mt), Kenya (2.34 Mt), Türkiye, Sri Lanka.
– Russia and South Africa export far more than they grow (re-exports).
– Bangladesh, China, India among major growers but low export shares (<5 %). - Trade Balance in South Asia
– Net exporters: Sri Lanka, India, Nepal.
– Net importers: Pakistan, Bangladesh, Bhutan, Afghanistan, Maldives. - Supply Gaps
– Countries exporting beyond their own production: Jamaica, Djibouti, Antigua & Barbuda, North Korea.
– Several small territories run zero or negative net supply. - Elasticities & Shock Impacts
– Export elasticity w.r.t. production ≈ 0.53; price elasticity ≈ 0.45.
– A 10 % fall in output → exports down ~5.3 %; farmgate prices down ~4.5 %. - Market Clusters
– Four clusters emerge when grouping countries by 2021 production, export volume and export value. - Opportunity Zones
– Low-value, high-volume exporters (e.g., Vietnam, Indonesia, Kenya, Bangladesh, Argentina) earn USD 1 400–2 200/t versus USD 5 000–15 000/t in premium markets—prime targets for quality or branding upgrades.
Conclusion
The journey from raw data to a clear, actionable strategy highlights a fundamental shift in business analytics. We began with a common problem: the struggle for profitability in a high-volume commodity market. By asking a series of targeted, plain-language questions, we moved from a high-level view of global trends to the specific, granular insights needed to build a new export plan.
The analysis confirmed that the path to earning more, not just selling more, lies in a value-added strategy—transitioning from a raw material supplier to a provider of finished goods. More importantly, it demonstrated that the power to uncover this strategy is more accessible than ever. The ability to directly interrogate data and get immediate answers allows any decision-maker to test hypotheses, identify opportunities, and build a data-driven case for their next big move, all in a fraction of the time it once took.
While this blog synthesizes our key findings, the full conversation offers a deeper insight into the data. Explore the complete analysis here.
Useful Links
- Terno AI: https://terno.ai
- Dataset link: Tea FAO dataset
- Detailed analysis: https://nikita.app.terno.ai/chat/share/611abc46-79c8-48e0-8b17-86b65285e189
