with
    int_monthly_aggregated_metrics_history_by_deal as (
        select * from {{ ref("int_monthly_aggregated_metrics_history_by_deal") }}
    ),
    int_kpis__dimension_deals as (select * from {{ ref("int_kpis__dimension_deals") }}),
    deal_attributes as (
        select
            id_deal,
            coalesce(
                main_billing_country_iso_3_per_deal, 'UNSET'
            ) as main_billing_country_iso_3_per_deal,
            effective_deal_start_month,
            hubspot_deal_cancellation_month,
            coalesce(
                hubspot_listing_segmentation, 'UNSET'
            ) as hubspot_listing_segmentation
        from int_kpis__dimension_deals
        -- Exclude deals without live dates
        where effective_deal_start_date_utc is not null
    )
-- Calculate expected MRR per deal by each dimension
select
    (date_trunc('month', m.date) + interval '2 month' - interval '1 day')::date as date,
    'by_number_of_listings' as dimension,
    d.hubspot_listing_segmentation as dimension_value,
    sum(coalesce(m.total_revenue_in_gbp, 0)) / count(*) as expected_mrr_per_deal
from int_monthly_aggregated_metrics_history_by_deal m
inner join
    deal_attributes d
    on m.id_deal = d.id_deal
    and date_trunc('month', m.date) >= date_trunc('month', d.effective_deal_start_month)
    and date_trunc('month', m.date)
    <= coalesce(d.hubspot_deal_cancellation_month, '2099-01-01')
    and date_trunc('month', m.date)::date <> date_trunc('month', now())::date
where d.hubspot_listing_segmentation <> 'UNSET'
group by 1, 2, 3
union all
select
    (date_trunc('month', m.date) + interval '2 month' - interval '1 day')::date as date,
    'by_billing_country' as dimension,
    d.main_billing_country_iso_3_per_deal as dimension_value,
    sum(coalesce(m.total_revenue_in_gbp, 0)) / count(*) as expected_mrr_per_deal
from int_monthly_aggregated_metrics_history_by_deal m
inner join
    deal_attributes d
    on m.id_deal = d.id_deal
    and date_trunc('month', m.date) >= date_trunc('month', d.effective_deal_start_month)
    and date_trunc('month', m.date)
    <= coalesce(d.hubspot_deal_cancellation_month, '2099-01-01')
    and date_trunc('month', m.date)::date <> date_trunc('month', now())::date
where d.hubspot_listing_segmentation <> 'UNSET'
group by 1, 2, 3
union all
select
    (date_trunc('month', m.date) + interval '2 month' - interval '1 day')::date as date,
    'global' as dimension,
    'global' as dimension_value,
    sum(coalesce(m.total_revenue_in_gbp, 0)) / count(*) as expected_mrr_per_deal
from int_monthly_aggregated_metrics_history_by_deal m
inner join
    deal_attributes d
    on m.id_deal = d.id_deal
    and date_trunc('month', m.date) >= date_trunc('month', d.effective_deal_start_month)
    and date_trunc('month', m.date)
    <= coalesce(d.hubspot_deal_cancellation_month, '2099-01-01')
    and date_trunc('month', m.date)::date <> date_trunc('month', now())::date
where d.hubspot_listing_segmentation <> 'UNSET'
group by 1, 2, 3