Data Analytics & Reporting

Explanation:
Analyzes comprehensive data sets from the target market to derive meaningful insights.
Subtopics:
- Analysis of Customer Behavior Data:
  - Analyzes customers’ shopping habits, preferences, and purchasing methods.
  - Example: Identifies the hours when customers are most active on e-commerce platforms.
- Sales and Trend Correlations:
  - Evaluates relationships between sales data and market trends.
  - Example:Sales in a product category are found to increase by 40% during holiday seasons.
- Segmentation-Based Data Analysis:
  - Analyzes the behavior of different customer segments.
  - Example:Premium segment customers spend 30% more than the standard segment.

Explanation:
Analyzes competitors’ pricing strategies in the target market to develop optimal pricing policies.
Subtopics:
- Dynamic Pricing Models:
  - Determines prices dynamically based on market demand and competitive conditions.
  - Example:Recommends a 10% price increase during high-demand periods.
- Continuous Monitoring of Competitor Prices:
  - Continuously monitors competitors’ price changes.
  - Example: A competitor is found to have reduced prices by 15% for certain products.

Explanation:
Analyzes sector-specific risks to forecast future threats and opportunities.
Subtopics:
- Macroeconomic Risks:
  - Analyzes the impact of currency fluctuations, inflation, and economic crises on the sector.
  - Example:Exchange rate increases are forecasted to raise import costs by 20%.
- Technological Risks:
  - Analyzes changes that new technologies may cause in the sector.
  - Example: Automation technology is identified to reduce labor costs but may increase unemployment risks.
- Sectoral Competition Risks:
  - Analyzes market saturation and risks of new entrants to the sector.
  - Example: A foreign firm’s entry into the target market poses a risk of market share loss for local companies.

Explanation:
Uses data modeling and simulation techniques to predict future market movements.
Subtopics:
- Demand Simulations:
  - Models how product demand will change under different scenarios.
  - Example: Simulates the impact of price increases on demand.
- Logistics Simulations:
  - Analyzes potential bottlenecks in logistics processes.
  - Example: Simulates how delivery delays will be managed if warehouse capacity is exceeded.
- Scenario-Based Strategy Development:
  - Develops strategies based on potential market scenarios.
  - Example: Cost-cutting strategies are recommended in a demand decline scenario.