Weighted Average Seasonality

[badger123]

Hello, hoping someone can help with this please. I'm looking to calculate a weighted average of seasonality. Here are simplified tables with some dummy data. I am looking for a measure to calculate seasonality for each "item_id" weighted by "weight". 

Seasonality Table

item_id	region_id	month	seas_component
1	1C	January	-3.93547454
1	1D	January	-0.16991384
1	1E	January	-4.4186439
1	1F	January	-6.11735502
1	1G	January	-0.41507024
1	1H	January	4.548411558
1	1I	January	2.718233471
1	1J	January	2.439170349
1	1K	January	-2.43710404
1	1L	January	-7.8258547
1	1M	January	-4.41261574
1	1N	January	-11.8819123
2	1C	January	-3.93547454
2	1D	January	-0.16991384
2	1E	January	-4.4186439
2	1F	January	-6.11735502
2	1G	January	-0.41507024
2	1H	January	4.548411558
2	1I	January	2.718233471
2	1J	January	2.439170349
2	1K	January	-2.43710404
2	1L	January	-7.8258547
2	1M	January	-4.41261574
2	1N	January	-11.8819123

Weight Table

item_id	country	region_id	weight
1	UK	1C	644.1667
1	UK	1D	2228.333
1	UK	1E	1641.667
1	UK	1F	1184.167
1	UK	1G	2025
1	UK	1H	1645
1	UK	1I	8841.667
1	UK	1J	2575.833
1	UK	1K	1240
1	UK	1L	873.3333
1	UK	1M	1775
1	UK	1N	555
2	UK	1C	13.33333
2	UK	1D	38.33333
2	UK	1E	26.66667
2	UK	1F	17.5
2	UK	1G	34.16667
2	UK	1H	35.83333
2	UK	1I	155.8333
2	UK	1J	50
2	UK	1K	23.33333
2	UK	1L	15.83333
2	UK	1M	28.33333
2	UK	1N	10

[badger123 · Accepted solution]

I think I have solved it with this measure... 

Weighted_Average_Seasonality =
DIVIDE(
SUMX(
    ADDCOLUMNS(
        SUMMARIZE(
            'Seasonality Table',
'Seasonality Table'[item_id],
'Seasonality Table'[region_id],
'Seasonality Table'[month],
'Seasonality Table'[seas_component],
"av_weight",CALCULATE(AVERAGE('Weight Table'[weight]))
        ),
        "test",
'Seasonality Table'[seas_component]*[av_weight]
        
    ),
    [test]
), SUMX('Weight Table','Weight Table'[weight]))