Spreadsheet: 879013d1726436464-formula-algorithm-to-establish-accurate-target-forecasting-revenue-example-zdr23-
Sheet: Data

 | Week | 2024-05-04 00:00:00 | 2024-05-11 00:00:00 | 2024-05-18 00:00:00 | 2024-05-25 00:00:00 | 2024-06-01 00:00:00 | 2024-06-08 00:00:00 | 2024-06-15 00:00:00 | 2024-06-22 00:00:00 | 2024-06-29 00:00:00 | 2024-07-06 00:00:00 | 2024-07-13 00:00:00 | 2024-07-20 00:00:00 | 2024-07-27 00:00:00 | 2024-08-03 00:00:00 | 2024-08-10 00:00:00 | 2024-08-17 00:00:00 | 2024-08-24 00:00:00 | 2024-08-31 00:00:00 | 2024-09-07 00:00:00 | 2024-09-14 00:00:00 | 2024-09-21 00:00:00 | 2024-09-28 00:00:00 | 2024-10-05 00:00:00 | 2024-10-12 00:00:00 | 2024-10-19 00:00:00 | 2024-10-26 00:00:00 | 2024-11-02 00:00:00 | 2024-11-09 00:00:00 | 2024-11-16 00:00:00 | 2024-11-23 00:00:00 | 2024-11-30 00:00:00 | 2024-12-07 00:00:00 | 2024-12-14 00:00:00 | 2024-12-21 00:00:00 | 2024-12-28 00:00:00 | 2025-01-04 00:00:00 | 2025-01-11 00:00:00 | 2025-01-18 00:00:00 | 2025-01-25 00:00:00 | 2025-02-01 00:00:00 | 2025-02-08 00:00:00 | 2025-02-15 00:00:00 | 2025-02-22 00:00:00 | 2025-03-01 00:00:00 | 2025-03-08 00:00:00 | 2025-03-15 00:00:00 | 2025-03-22 00:00:00 | 2025-03-29 00:00:00
 |  | Week 5 | Week 6 | Week 7 | Week 8 | Week 9 | Week 10 | Week 11 | Week 12 | Week 13 | Week 14 | Week 15 | Week 16 | Week 17 | Week 18 | Week 19 | Week 20 | Week 21 | Week 22 | Week 23 | Week 24 | Week 25 | Week 26 | Week 27 | Week 28 | Week 29 | Week 30 | Week 31 | Week 32 | Week 33 | Week 34 | Week 35 | Week 36 | Week 37 | Week 38 | Week 39 | Week 40 | Week 41 | Week 42 | Week 43 | Week 44 | Week 45 | Week 46 | Week 47 | Week 48 | Week 49 | Week 50 | Week 51 | Week 52
Revenue | Prior Year | 519135 | 646047 | 1074350 | 865550.84 | 884868 | 978237 | 997818 | 688072 | 1025771 | 584645 | 1101091 | 752790 | 1227834 | 836305 | 373982 | 868979 | 799721 | 626696 | 6940 | 678124 | 1063475 | 1125524 | 1674390 | 1073117 | 1030989 | 1159279 | 1266052 | 906706 | 690496 | 625446 | 1030261 | 246847 | 672328 | 897300 | 824255 | 1220261 | 652280 | 926358 | 754250 | 607855 | 785899 | 654852 | 571480 | 734925 | 810227 | 745051.32 | 836137.1826000001 | 836933.635252
 | Target | 936475.21 | 936475.21 | 936475.21 | 936475.21 | 936475.21 | 936475.21 | 936475.21 | 936475.21 | 936475.21 | 936475.21 | 936475.21 | 936475.21 | 936475.21 | 936475.21
 | Actual | 975097 | 1252780.63 | 899637.75 | 1264998.15 | 1072123.37 | 1487692.02 | 879096.99 | 899395.51 | 1013152.71 | 480886.67 | 651359.67 | 472135.74 | 720614.91 | 1502484.26
# Appointments | Prior Year | 126 | 126 | 118 | 122 | 119 | 119 | 125 | 132 | 127 | 121 | 128 | 125 | 147 | 143
 | Target | 140 | 140 | 140 | 140 | 140 | 140 | 140 | 160 | 160 | 160 | 160 | 160 | 160 | 165
 | Actual | 155 | 178 | 195 | 205 | 195 | 189 | 179 | 178 | 142 | 130 | 152 | 166 | 194 | 195
Correlation | 2 Week
 | 3 Week
 | 4 Week
Week
Appointments
Revenue
The actuals are weekly actuals
I am not 100% sure there are any seasonality patterns that hold true given the variability within prior year actuals and current year actuals
I think that higher # of appointments should mean higher revenue within 2-4 weeks, but I need analysis prove/disprove
Ultimately would like a formula / algorithm to better forecast revenue