How ATIM Works

ATIM operates through processes of data aggregation, harmonisation, enrichment, and analysis. These processes transform integrated data into structured trade intelligence and actionable insights.

How ATIM Supports Digital Business Communities

ATIM operates as:

Data → Trade Intelligence →Trade-Development Execution

Where:

• Data is generated through international visibility signals, institutional data, and external sources.
• ATIM transforms data into structured trade intelligence.
• Protegra enables trade-development execution.

Integrated Trade Intelligence Model

ATIM aggregates, harmonises, enriches, and analyses multiple data sources to generate structured trade intelligence.

Visibility signals, global trade data, economic datasets, and payment intelligence are aggregated, harmonised, and integrated within a unified trade-intelligence solution.

Data Aggregation

Multiple data streams are combined:

• International trade data (including Comtrade, ITC, and other international sources)
• Payment flow data (bank-specific capability)
• International visibility signals

Data Structuring

Data is standardised and organised using:

• Sector classifications
• Product and service classifications (e.g. HS codes and BPM6)
• Geographic mapping

Analytical Processing

This stage identifies:

• Demand patterns
• Trade flows
• Comparative indicators
• Product, service and sector-specific trends

Intelligence Generation

This stage produces:

• Prioritised markets
• Analytical rankings
• Actionable insights

Intelligence outputs can be delivered through a range of ATIM merchandise and services trade reports supporting market, sector, country, bilateral, trade-corridor, and trade-bloc analysis.

From Intelligence to Action

Trade intelligence supports practical decision-making, market prioritisation, and trade-development activities.

ATIM operates as a continuous intelligence cycle, ensuring that intelligence remains current, accurate, and responsive to changing market conditions.

The Next Tab, describes the principal datasets that support the ATIM model and explains how they contribute to structured trade intelligence.

Data Sources

ATIM combines multiple categories of data to generate robust, multi-source trade intelligence.

It is designed to remain flexible and source-agnostic, allowing institutions to select and integrate data sources based on availability, cost, and analytical requirements.

ATIM can be deployed progressively, starting with accessible data and scaling to more advanced intelligence capabilities.

ATIM can begin with accessible data sources such as UN Comtrade and visibility signals. Additional transaction intelligence and advanced datasets can then be incorporated progressively as analytical requirements evolve.

Global Trade Data

ATIM integrates data from a range of international sources, for example:

• UN Comtrade (API available – free access)
• International Trade Centre (API available – licensed access, usage-based)
• Additional institutional datasets (e.g. UNIDO and other international sources)

Provides:

• Global merchandise and services trade statistics
• Market size indicators
• Product-level trade flows

Illustrative comparison of UN Comtrade and ITC data services.

Important Note on Data Source Selection

ATIM is designed to combine multiple data sources, rather than relying on a single provider.

In initial deployments, UN Comtrade is typically recommended as a starting point due to:

• Open API access
• No licensing cost
• Sufficient coverage for early-stage analysis

ITC data can be introduced in later phases where:

• Enhanced data structuring is required
• Additional analytical depth is needed
• Budget and usage parameters are defined

Services trade analysis can also utilise BPM6-based international trade-in-services datasets where available.

Payment Intelligence (Illustrative Bank Implementation)

The example operational model shown below illustrates a bank implementation using BICDetective payment-flow intelligence. Equivalent ATIM deployments can also be configured using alternative institutional data sources.

• BICDetective

Provides:

• Real transaction-level insights
• Actual trade corridors
• Client-level activity patterns

Online Visibility and Market-Interest Signals

• Microsites
• Multilingual Microsites

Microsites and Multilingual Microsites generate online visibility and market-interest signals, supported by analytics tools such as Google Search Console and Google Analytics.

Reference and Classification Resources

ExportersAlmanac

ExportersAlmanac integrates data from multiple reference sources, supporting:

• Country-level filtering
• Sector mapping
• Trade classification
• Structured trade context

Provides:

• Structured country and sector-level reference information
• Reference data for market analysis and filtering
• Support for sector mapping and trade classification

ATIM Reference Tools

• Code Mapping
• Classification Mapping
• Country Filtering
• Product, Service and Sector Mapping

Combined Value

By combining multiple data sources, ATIM produces more balanced, robust, and reliable intelligence outputs than can be achieved through a single source alone.

Different institutions may utilise different combinations of data sources depending on their objectives, available datasets, and operational role.

These combined data sources provide the inputs to ATIM. ATIM transforms this information into prioritised markets, analytical rankings and actionable trade intelligence.

The Next Tab, Outputs, explains how ATIM converts multi-source data into structured trade intelligence and actionable outputs.

Actionable Trade Intelligence

From Analysis to Actionable Outputs

The model below illustrates how ATIM transforms structured analysis into prioritised markets, sector insights and actionable trade intelligence.

Core Outputs

1. Market Rankings

• Comparative ranking of countries and markets. Based on selected analytical criteria and benchmarks

2. Trade Corridor Analysis

• Mapping of active and emerging trade routes
• Identification of underdeveloped corridors

3. Sector Insights

• High-demand sectors
• Product- and service-level opportunity identification

4. Client / Member Analysis

(Only where institution-specific datasets are available)

• Identification of underutilised clients
• Cross-border activity insights
• Targeted engagement opportunities

From Analysis to Action

ATIM reports are designed to be:

• Clear
• Concise
• Directly usable

They enable institutions to prioritise opportunities and take informed action.

ATIM intelligence can be delivered through ATIM merchandise and services trade reports, together with institution-specific analytical outputs.

The Next Tab, Illustrative Trade Intelligence, demonstrates how ATIM outputs are presented through practical examples of market, sector and trade-development analysis.

Illustrative Trade Intelligence

The following examples use illustrative data to demonstrate the types of analytical insights generated by ATIM.

From Digital Engagement to Trade Intelligence

Most digital solutions focus on tools or promotion.

ATIM goes further.

By analysing the market visibility and engagement generated through Digital Business Communities, ATIM produces aggregated trade intelligence, including structured insights into:

• Which countries are showing interest
• Which sectors and products are attracting attention
• How engagement evolves over time

This enables organisations to move from assumption-based support to evidence-based trade enablement.

These analytics do not simply report digital activity. They convert visibility signals into actionable trade intelligence.

In effect, ATIM transforms digital engagement into a continuous global market-sensing capability for participating organisations.

While the examples below present high-level summaries, in practice the underlying data can be analysed at significantly greater granularity and exported in structured formats (such as CSV) for integration with institutional systems.

Data and visibility infrastructure can reveal international demand patterns and emerging opportunities. However, Business Community Owners remain responsible for designing and implementing the programmes that convert these opportunities into tangible trade outcomes for their SME communities.

1. International Demand Signals Over Time

The first analytical layer tracks international engagement generated across participating Digital Business Communities.

This provides insight into:

• Seasonal patterns in international interest
• Growth or decline in demand signals over time
• The impact of trade missions or promotional campaigns
• Periods of accelerated international engagement

This represents the macro-level demand signal generated across the SME community.

2. Geographic Market Intelligence

Understanding where international interest originates is critical for designing effective export programmes.

This analysis highlights:

• Countries generating the strongest engagement
• Emerging geographic markets
• Market concentration risks
• Alignment (or misalignment) with institutional export priorities

Institutions can therefore prioritise markets based on measurable demand signals rather than assumptions.

3. Sector-Level Market Intelligence

(NACE Classification)

International engagement can be analysed at the sectoral level using structured industry classifications such as NACE.

This enables institutions to support:

• Sector prioritisation strategies
• Cluster development initiatives
• Targeted trade delegations
• Evidence-based allocation of support resources

Sector analysis can be viewed in aggregate or segmented by country.

4. Product-Level Market Intelligence

(Harmonised System - HS Classification)

International demand can also be analysed at the product level using the internationally recognised Harmonised System (HS) classification.

This supports:

• Product-specific export readiness programmes
• Identification of high-potential product categories
• Alignment with tariff and regulatory frameworks
• Market-entry preparation by product type

As with sector analysis, product demand can be examined globally or at individual country level.

5. Linking Market Intelligence to Participating SMEs

The next step is to put this intelligence into action.

Aggregated demand signals can be cross-referenced with companies participating in the Digital Business Community, without compromising privacy.

Companies already publish structured information including:

• Industry classifications
• Product categories
• Core business capabilities

The system links demand signals to all relevant companies within these categories without exposing individual traffic data.

This preserves anonymity while enabling structured institutional engagement.

The resulting internal reference ID can connect directly to:

• The organisation’s CRM system
• The company’s Multilingual Microsite
• Internal export advisory workflows

6. Mapping Product Demand to Participating Companies

The same methodology can be applied at the product level.

Institutions can identify which companies operate within high-interest product categories and design targeted initiatives such as:

• Advisory outreach programmes
• Export readiness workshops
• Buyer introduction programmes
• Trade mission invitations

This is where analytics becomes operational action.

Strategic Implications

ATIM therefore functions not merely as a reporting tool, but as a decision-support capability for organisations responsible for business growth, market development and internationalisation.

It supports:

• Export programme design
• Trade mission targeting
• Cluster development initiatives
• Financial support allocation
• Policy engagement and economic development planning

Most importantly, this intelligence is derived from real market engagement and digital activity, creating a continuous demand signal from global markets.

These illustrative insights demonstrate how aggregated digital activity can be transformed into actionable trade intelligence. The examples shown are based on aggregated and anonymised data, and Protegra does not rely on the processing of personal data for its core functionality.

Further details on data protection and GDPR compliance are available in the Digital Business Community FAQs.

The Next Tab, Value, summarises the strategic and operational value of ATIM for institutions.

A Data-Driven Intelligence Capability

ATIM transforms data into a strategic asset, enabling institutions to operate with greater precision, clarity, and confidence.

ATIM operates as an ongoing process:

Data → Analysis → Insight → Refinement

This cycle ensures that intelligence remains current, accurate, and responsive to changing market conditions.

In parallel, refined intelligence can be applied through Digital Business Communities implemented using the Protegra Framework to support market engagement and practical execution.

Value for Telecommunications Providers

• Strengthen corporate client relationships
• Support SME growth and internationalisation
• Support digital capability development
• Support market-development initiatives
• Increase the value of business-service offerings

Value for Banks

• Visibility of real client trade activity
• Identification of revenue opportunities
• Optimisation of trade corridors
• Enhanced client segmentation
• Improved utilisation of FX, payments, and trade finance

Value for Chambers of Commerce and Trade Associations

• Evidence-based trade programme design
• Improved targeting of trade missions
• Enhanced SME support
• Better alignment with market demand

Value for Export-Promotion Organisations

• Support market-selection activities;
• Identify priority sectors and opportunities;
• Improve programme targeting;
• Strengthen trade-development planning; and
• Support more effective resource allocation.

Measurable Benefits

• Improved decision-making
• Targeted resource allocation
• Increased effectiveness of trade initiatives
• Demonstrable outcomes

Beyond Reporting

ATIM supports market discovery, trade intelligence, decision support, and trade-development planning.

Trade Reports represent one output of a broader intelligence capability.

Role within the Protegra Framework

ATIM provides the trade intelligence capability within the Protegra Framework.

It supports Digital Business Communities through market discovery, decision support and actionable trade intelligence.

Next Step

Continue to the Protegra section to see how ATIM intelligence is translated into coordinated SME engagement, business development and measurable trade outcomes.