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Hi Team ,
On the lifetime value graph (right) you have on the y-axis money gbp, and on the x-axis the number of months, so how much money made on average after the first 3 months, 6 months, 9 months,12month .Please let me know approach to create this graph in Power Bi
Sample Data
patientID | total | invoiceDate | invoiceID |
2 | £0.00 | 30-04-2022 00:00 | 1755704 |
26 | £97.50 | 04-04-2023 00:00 | 1865570 |
26 | £97.50 | 04-04-2023 00:00 | 1865595 |
26 | £47.50 | 06-04-2023 00:00 | 1866686 |
26 | £47.50 | 11-04-2023 00:00 | 1867180 |
26 | £47.50 | 13-04-2023 00:00 | 1867900 |
26 | £47.50 | 18-04-2023 00:00 | 1869237 |
26 | £47.50 | 20-04-2023 00:00 | 1870078 |
26 | £47.50 | 25-04-2023 00:00 | 1871132 |
26 | £47.50 | 27-04-2023 00:00 | 1871988 |
95 | £45.00 | 22-02-2022 00:00 | 1732839 |
95 | £45.00 | 19-04-2022 00:00 | 1751693 |
95 | £0.00 | 06-05-2022 00:00 | 1758092 |
95 | £45.00 | 14-06-2022 00:00 | 1771056 |
95 | £45.00 | 26-07-2022 00:00 | 1785525 |
107 | £2.50 | 05-12-2022 00:00 | 1828921 |
107 | -£2.50 | 05-12-2022 00:00 | 1828922 |
147 | £35.00 | 04-01-2022 00:00 | 1715616 |
147 | £40.00 | 11-01-2022 00:00 | 1717998 |
147 | £40.00 | 25-01-2022 00:00 | 1722622 |
147 | £35.00 | 08-02-2022 00:00 | 1727367 |
147 | £40.00 | 08-02-2022 00:00 | 1727399 |
147 | £40.00 | 22-02-2022 00:00 | 1732375 |
147 | £35.00 | 01-03-2022 00:00 | 1734711 |
147 | £40.00 | 08-03-2022 00:00 | 1737359 |
147 | £35.00 | 22-03-2022 00:00 | 1742137 |
147 | £40.00 | 22-03-2022 00:00 | 1742181 |
147 | £40.00 | 03-05-2022 00:00 | 1755919 |
147 | £35.00 | 03-05-2022 00:00 | 1755952 |
147 | £40.00 | 17-05-2022 00:00 | 1761237 |
147 | £35.00 | 07-06-2022 00:00 | 1767905 |
147 | £40.00 | 07-06-2022 00:00 | 1767923 |
147 | £40.00 | 21-06-2022 00:00 | 1772963 |
147 | £35.00 | 28-06-2022 00:00 | 1775334 |
147 | £40.00 | 08-07-2022 00:00 | 1779579 |
147 | £35.00 | 19-07-2022 00:00 | 1782551 |
147 | £40.00 | 19-07-2022 00:00 | 1782573 |
147 | £40.00 | 02-08-2022 00:00 | 1787571 |
147 | £35.00 | 09-08-2022 00:00 | 1790017 |
147 | £35.00 | 30-08-2022 00:00 | 1796522 |
147 | £40.00 | 30-08-2022 00:00 | 1796557 |
147 | £40.00 | 13-09-2022 00:00 | 1801531 |
147 | £35.00 | 20-09-2022 00:00 | 1803640 |
147 | £40.00 | 27-09-2022 00:00 | 1806009 |
147 | £40.00 | 11-10-2022 00:00 | 1810655 |
147 | £35.00 | 18-10-2022 00:00 | 1813129 |
147 | £40.00 | 25-10-2022 00:00 | 1815476 |
147 | £38.50 | 08-11-2022 00:00 | 1820107 |
147 | £40.00 | 08-11-2022 00:00 | 1820108 |
147 | £44.00 | 25-11-2022 00:00 | 1826128 |
147 | £38.50 | 01-12-2022 00:00 | 1827825 |
147 | £44.00 | 09-12-2022 00:00 | 1830455 |
147 | £44.00 | 23-12-2022 00:00 | 1834771 |
147 | £38.50 | 05-01-2023 00:00 | 1837337 |
147 | £44.00 | 06-01-2023 00:00 | 1837843 |
147 | £44.00 | 20-01-2023 00:00 | 1842422 |
147 | £38.50 | 26-01-2023 00:00 | 1844090 |
147 | £44.00 | 03-02-2023 00:00 | 1846780 |
147 | £44.00 | 08-02-2023 00:00 | 1848174 |
147 | £44.00 | 10-02-2023 00:00 | 1849108 |
147 | £38.50 | 16-02-2023 00:00 | 1850850 |
147 | £44.00 | 17-02-2023 00:00 | 1851282 |
147 | £44.00 | 03-03-2023 00:00 | 1855751 |
147 | £38.50 | 09-03-2023 00:00 | 1857484 |
147 | £44.00 | 17-03-2023 00:00 | 1860101 |
147 | £38.50 | 30-03-2023 00:00 | 1864087 |
147 | £44.00 | 31-03-2023 00:00 | 1864680 |
147 | £44.00 | 15-04-2023 00:00 | 1868516 |
147 | £38.50 | 20-04-2023 00:00 | 1869700 |
147 | £44.00 | 28-04-2023 00:00 | 1872094 |
187 | £10.00 | 19-01-2022 00:00 | 1721066 |
187 | £10.00 | 14-02-2022 00:00 | 1729798 |
187 | £0.00 | 28-02-2022 00:00 | 1734549 |
187 | £10.00 | 28-02-2022 00:00 | 1734578 |
187 | £10.00 | 14-03-2022 00:00 | 1739729 |
187 | £10.00 | 28-03-2022 00:00 | 1744357 |
187 | £10.00 | 11-04-2022 00:00 | 1749336 |
187 | £10.00 | 11-04-2022 00:00 | 1749345 |
187 | £10.00 | 25-04-2022 00:00 | 1753605 |
214 | £22.50 | 16-09-2022 00:00 | 1803338 |
214 | £50.00 | 04-10-2022 00:00 | 1808464 |
214 | £50.00 | 29-11-2022 00:00 | 1826983 |
218 | £36.00 | 04-01-2022 00:00 | 1715587 |
218 | £36.00 | 01-02-2022 00:00 | 1724976 |
218 | £36.00 | 08-03-2022 00:00 | 1737421 |
218 | £36.00 | 19-04-2022 00:00 | 1751260 |
218 | £36.00 | 17-05-2022 00:00 | 1761302 |
218 | £36.00 | 14-06-2022 00:00 | 1770642 |
218 | £36.00 | 12-07-2022 00:00 | 1780203 |
218 | £36.00 | 09-08-2022 00:00 | 1790084 |
218 | £36.00 | 06-09-2022 00:00 | 1799123 |
218 | £40.00 | 18-10-2022 00:00 | 1813177 |
218 | £40.00 | 15-11-2022 00:00 | 1822289 |
218 | £40.00 | 13-12-2022 00:00 | 1831366 |
Solved! Go to Solution.
Hi @Anonymous ,
Please have a try.
measure =
CALCULATE (
AVERAGE ( TABLE[total] ),
FILTER (
ALL ( table ),
table[patientID] = SELECTEDVALUE ( table[patientID] )
&& table[invoice] <= EDATE ( SELECTEDVALUE ( table[invoice] ), -3 )
)
)
More details: Customer Lifetime Value (LTV) | KPI example | Geckoboard
How to Get Your Question Answered Quickly
If it does not help, please provide more details with your desired output and pbix file without privacy information (or some sample data) .
Best Regards
Community Support Team _ Rongtie
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
Hi @Anonymous ,
Please have a try.
measure =
CALCULATE (
AVERAGE ( TABLE[total] ),
FILTER (
ALL ( table ),
table[patientID] = SELECTEDVALUE ( table[patientID] )
&& table[invoice] <= EDATE ( SELECTEDVALUE ( table[invoice] ), -3 )
)
)
More details: Customer Lifetime Value (LTV) | KPI example | Geckoboard
How to Get Your Question Answered Quickly
If it does not help, please provide more details with your desired output and pbix file without privacy information (or some sample data) .
Best Regards
Community Support Team _ Rongtie
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.