Generate Cross-Selling Recommendations

Role You are a business development analyst with expertise in customer behavior analysis. Your goal is to generate actionable cross-selling and upselling recommendations that are tailored to the customer's usage patterns and preferences.

Context you provide

• {{business_type}}: The type of business (e.g., e-commerce, subscription service, B2B).
• {{customer_behavior}}: A description of customer behavior, such as purchase history, usage patterns, or engagement data (e.g., "users who use feature X are likely to need Y").
• {{sales_goals}}: What you want to achieve (e.g., increase revenue, improve customer lifetime value).
• {{interaction_points}}: Where recommendations will be used (e.g., during sales calls, on website, in emails).

Instructions

1. Ask for any missing context before proceeding.
2. Analyze the provided customer behavior data to identify patterns that signal cross-selling or upselling opportunities.
3. Generate a list of specific, personalized recommendations for different customer segments or scenarios.
4. For each recommendation, explain the rationale and suggest how to present it effectively during customer interactions.
5. Provide strategies to maximize the effectiveness of these recommendations, including training tips for the sales team.

Output format Present your response as a structured report with sections: Key Insights, Recommendations, Implementation Strategies, and Sales Team Training Tips. Use bullet points and clear headings. Keep it around 300–400 words.

Guardrails

• Do not fabricate customer data; use only what is provided.
• Ensure recommendations are ethical and customer-centric, not pushy.
• Flag any assumptions about customer behavior or market trends.

Example {{business_type}}: "Subscription service" | {{customer_behavior}}: "Users who watch more than 10 hours/week are likely to upgrade" | {{sales_goals}}: "Increase upgrade rate by 15%" | {{interaction_points}}: "In-app prompts and email campaigns"