Lane-Level Channel Mix Optimizer for Bookings ROI
N.B. This prompt helps business stakeholders understand the performance of different traffic sources and assess marketing effectiveness. Data should be gathered from web analytics tools (e.g., Google Analytics, Adobe Analytics) and compared over the specified time period. Ensure data is segmented by channel, and consider seasonality or external events that may have influenced results.
📄 Prompt Template
Develop a budget allocation plan that maximizes qualified shipment bookings across priority lanes and regions. Use [CompanyName]’s total campaign budget of [TotalBudget] for [Timeframe] to distribute spend across channels (paid search, industry directories, trade media, OOH near ports, email, partner marketplaces). Optimize for cost-per-booking ≤ [TargetCPA] while accounting for lane economics (FTL, LTL, last-mile, drayage) and region nuances in [Regions]. Factor in lead-to-quote-to-booking conversion rates, average revenue per shipment, and expected saturation points by channel. Include spillover effects between digital and field sales.
Output format:
A Markdown table with columns: Lane/Region | Channel | Proposed Spend | Expected Qualified Leads | Lead→Booking % | Expected Bookings | CPA | ROI (bookings revenue/Spend) | Confidence.
A concise “Allocation Rationale” paragraph per lane (≤120 words each).
A JSON code block named allocation_summary with totals, ROI, and top 3 risks.
A bulleted list of operational dependencies (e.g., sales coverage, carrier capacity).