AgentSkillsCN

Evaluate Channel Performance

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SKILL.md

Skill: Evaluate Channel Performance

Domain

retail

Description

Evaluates sales channel performance comparing metrics across channels to optimize omnichannel strategy and resource allocation.

Tags

omnichannel, retail, sales, performance, ecommerce, analytics

Use Cases

  • Channel comparison
  • Resource allocation
  • Strategy optimization
  • Performance benchmarking

Proprietary Business Rules

Rule 1: Channel Metrics Calculation

Key performance indicators by channel.

Rule 2: Attribution Analysis

Cross-channel customer journey attribution.

Rule 3: Efficiency Comparison

Channel cost efficiency evaluation.

Rule 4: Investment Optimization

Channel investment recommendation.

Input Parameters

  • analysis_id (string): Analysis identifier
  • channel_data (dict): Channel details
  • sales_data (list): Sales by channel
  • cost_data (dict): Channel operating costs
  • customer_data (dict): Customer behavior data
  • benchmark_data (dict): Industry benchmarks

Output

  • channel_metrics (dict): KPIs by channel
  • performance_ranking (list): Channel ranking
  • efficiency_analysis (dict): Cost efficiency
  • attribution_insights (dict): Customer journey
  • recommendations (list): Optimization actions

Implementation

The evaluation logic is implemented in channel_evaluator.py and references data from channel_benchmarks.json.

Usage Example

python
from channel_evaluator import evaluate_channels

result = evaluate_channels(
    analysis_id="CHN-001",
    channel_data={"ecommerce": {"type": "direct"}, "retail": {"type": "owned"}},
    sales_data=[{"channel": "ecommerce", "revenue": 5000000}, {"channel": "retail", "revenue": 10000000}],
    cost_data={"ecommerce": {"operating": 500000}, "retail": {"operating": 2000000}},
    customer_data={"ecommerce": {"aov": 85}, "retail": {"aov": 65}},
    benchmark_data={"ecommerce_growth": 0.15, "retail_growth": 0.03}
)

print(f"Top Channel: {result['performance_ranking'][0]['channel']}")

Test Execution

python
from channel_evaluator import evaluate_channels

result = evaluate_channels(
    analysis_id=input_data.get('analysis_id'),
    channel_data=input_data.get('channel_data', {}),
    sales_data=input_data.get('sales_data', []),
    cost_data=input_data.get('cost_data', {}),
    customer_data=input_data.get('customer_data', {}),
    benchmark_data=input_data.get('benchmark_data', {})
)