DX Innovation

TriBIG Personalized Market Recommendation AI Algorithm: Cosine Similarity-Based Export Market Prediction

What Does the TriBIG Market Recommendation Engine Calculate?

TriBIG's personalized market recommendation algorithm is an engine that cross-analyzes company characteristics — product mix, export history, price positioning, and certification level — against each country's import demand, growth rate, competitive intensity, and trade barriers, all on a single screen. The core mechanism converts both the company and each market into vectors, then uses cosine similarity to compare the directional alignment of those two vectors, surfacing "markets that match our company's profile" at the top of the ranking.

Traditional market research typically starts with the largest import volumes, but TriBIG focuses on surfacing markets with the highest realistic entry potential rather than simply the biggest markets. This means that even for products where competition in advanced markets is already saturated, it can separately elevate emerging markets that score high on growth rate and Korea product suitability. This is precisely why markets like Bangladesh — where industrialization is accelerating but systematic Korean company penetration remains insufficient — frequently appear at the top of this algorithm's output.

85%+
Recommendation Accuracy
Based on Top-5 picks
100K+
Records Analyzed
Annual trade data processed
190+ countries
Recommended Markets
Per-company Top-N generated
18,000+
Active Users
KOTRA member base
120+
Key Variables
Company-market matching inputs
Under 3 sec
Response Time
Recommendation result generation

Data Pipeline: Collection, Normalization, and Vectorization

The strength of this algorithm lies in its data architecture rather than its AI branding. Korea Customs Service export/import records, UN Comtrade, WTO tariff data, KOTRA buyer databases, and supplementary logistics and payment data are first aligned into a single reference framework, then normalized so that HS codes, market sizes, growth rates, and barrier factors can be compared within the same coordinate system. When this preprocessing stage is unstable, recommendation quality degrades sharply — which is why maintaining data integrity in practice matters more than the cosine calculation itself.

TriBIG Market Recommendation Pipeline
1. Data Collection
Integrate 8 source types: Korea Customs, UN Comtrade, WTO, KOTRA DB, and more
2. Normalization
HS code alignment, unit conversion, missing value imputation, Min-Max scaling
3. Vector Construction
Build company vectors and per-country market vectors as multi-dimensional feature sets
4. Cosine Calculation
Convert directional similarity between two vectors into a 0–1 score
5. Rank Adjustment
Finalize recommended markets by incorporating tariffs, logistics, and policy events as correction factors

Matching Logic: Which Variables Actually Shift the Final Ranking?

Actual recommendation results are not determined by a single score. TriBIG calculates company-market fit by simultaneously evaluating four axes: market attractiveness, competitive environment, barrier level, and logistics executability. Cosine similarity serves as the core scoring engine, but the final ranking is re-ordered through correction factors that also reflect real-world execution feasibility. This is why the country with the largest import volume does not automatically rank first.

Company Vector Inputs
Product MixHS 6-digit export history
Trade ExperienceExport destinations over past 3 years
Price and SpecBudget / mid-range / premium positioning
Capability IndicatorsCertifications, patents, delivery capability
Market Vector Inputs
Import DemandImport volume by product category
Growth Potential3-year CAGR
Competitive IntensityConcentration of leading competitor nations
Entry BarriersTariffs, non-tariff barriers, logistics
Key Evaluation Axes of the Market Recommendation Engine
Evaluation AxisRepresentative VariablesPractical InterpretationDirectional Weight
Market AttractivenessImport volume, growth rate, demand expansion speedWhether sufficient revenue volume is achievableHigher is favorable
Competitive EnvironmentKorea market share, competitor concentration, price pressureWhether survival after entry is realisticMore saturated = less favorable
Barrier LevelTariffs, certifications, regulations, payment riskEstimate upfront entry cost and lead timeLower is favorable
ExecutabilityLogistics, partner availability, trade office support linkageProbability of converting recommendation to actual salesHigher is favorable

Why This Algorithm Is Useful for Bangladesh

Bangladesh is smaller than major advanced markets in absolute purchasing power, but accelerating manufacturing investment, large population, middle-class growth, and import substitution demand are all operating simultaneously — making it a textbook high-growth emerging market. Markets of this type can get pushed down the list when evaluated on raw import totals alone, but in an algorithm like TriBIG's that weighs growth potential, competitive intensity, and field executability together, they tend to score well. Especially in garment value chains, industrial machinery, medical devices, and IT hardware — areas where Korean companies can hold technology and quality advantages — Bangladesh consistently surfaces as a high-priority candidate.

Bangladesh Market Recommendation Examples
Product CategorySample Cosine ScoreRecommendation RationaleNext Action
Medical Devices0.87Growing hospital equipment demand and rising Korean product credibilityValidate distributors and track tender opportunities
Cosmetics0.83Middle-class expansion and Hallyu-driven consumer demand growthPrice point testing and online channel validation
Auto Parts0.81Increasing imported parts demand as assembly industry growsIdentify OEM touchpoints and initiate sample supply
Electronics and IT Components0.79Digital transformation and manufacturing automation demand expandingTechnical meetings and local partner sourcing
Plastics and Packaging0.76Recurring demand from expanding processing and packaging sectorCheck price competitiveness and run buyer consultations

How Companies Should Use This Algorithm

Companies that use TriBIG recommendations effectively do not stop at "running a market query" — they connect directly to an actionable pipeline. The key is rapidly cycling through four steps: HS code definition, comparison of top candidate countries, trade office verification, and transition to samples and consultations. Systematizing this process transforms market diversification projects from reports into real sales opportunities.

01
Fix the Representative HS Codes First
Wrong product codes destabilize the entire market recommendation. Cross-reference your export declaration history and customer orders to get the representative codes aligned before anything else.
02
Compare the Top 3, Not Just the Top 1
The top-ranked recommendation is not always optimal. Comparing market attractiveness, barriers, and logistics costs across the top 3 countries provides much better risk distribution.
03
Attach Field Verification Immediately After Recommendation Scores
Buyer reliability, agent capability, and payment habits cannot be fully assessed from platform data alone. Trade office consultation and local partner verification must follow immediately.
04
Feed Results Back into Data
Accumulating sample responses, consultation conversion rates, and actual contract outcomes makes the next round of market recommendation judgments more precise. Keeping data and sales operations integrated is the better approach.
TriBIG AI 빅데이터로 대체시장 발굴하기: 실전 매뉴얼How to connect recommendation results into a practical market discovery workflow
KOTRA DX혁신랩 28개 과제 종합 분석See the full digital trade innovation structure that includes TriBIG
2025 방글라데시 경제 개요Macroeconomic background for evaluating Bangladesh as a recommended market
TriBIGmarket recommendationcosine similarityAI algorithmexport market predictionDX innovation
TriBIG Personalized Market Recommendation AI Algorithm: Cosine Similarity-Based Export Market Prediction | Dhaka Trade Portal