1. Generate random test click counts for campaign performance baseline
| Campaign | Channel | Spend | Clicks | Conversions |
| Email Blast Q4 | Email | $5000 | 450 | 45 |
| Social Ads | Instagram | $8000 | 1200 | 85 |
| Webinar Series | Online Event | $3000 | 280 | 22 |
=RANDARRAY(3,1,200,1500,TRUE)
Result: [[687],[1234],[892]]
Creates a 3-row array of random integers between 200 and 1500 to simulate click counts for each campaign channel. This baseline can be compared against actual clicks (450, 1200, 280) to test forecasting accuracy. whole_number=TRUE ensures counts are integers, not fractional clicks.
2. Generate random conversion rate estimates by channel
| Campaign | Channel | Spend | Clicks | Conversions |
| Email Blast Q4 | Email | $5000 | 450 | 45 |
| Social Ads | Instagram | $8000 | 1200 | 85 |
| Webinar Series | Online Event | $3000 | 280 | 22 |
=RANDARRAY(3,1,0.8,9.5,FALSE)
Result: [[3.47],[6.23],[2.91]]
Generates 3 random decimal rates (0.8% to 9.5%) to forecast conversion rates. FALSE produces realistic percentage decimals. Multiplying these by historical clicks estimates expected conversions for each channel—Email at 3.47% of 450 clicks ≈ 16 conversions.
3. Create random budget allocation matrix across channels and quarters
| Campaign | Channel | Spend | Clicks | Conversions |
| Email Blast Q4 | Email | $5000 | 450 | 45 |
| Social Ads | Instagram | $8000 | 1200 | 85 |
| Webinar Series | Online Event | $3000 | 280 | 22 |
=RANDARRAY(3,2,1500,8000,TRUE)
Result: [[5342,6891],[3567,7120],[6234,4589]]
Produces a 3×2 matrix of random budgets (dollars) representing three channels across two planning quarters. Rows correspond to Email, Instagram, and Online Event; columns to Q1 and Q2 budgets. whole_number=TRUE ensures whole dollar amounts for actual spend modeling.