Merged PR 3247: Enriches monthly_growth_by_deal model for top losers reporting
# Description Changes: * Explicit selection of fields in the last part of the query, rather than select *. * Adding a few more Hubspot attributes, namely: AM, Hubspot Stage, Live Date and Cancellation Date. The main idea is to enrich the reporting with these. * Adding the listings over 12 months. Here it's a bit more tricky than for Revenue or Bookings, since to me the main indicator is the amount of listings that are being booked in a month, over a period of 12 months (rather than unique count of listings that have been booked in the past 12 months). However, doing a sum of the listings booked in month will be very tricky for AMs and other users. I opted for averaging, and can be considered as, in average, a certain account has X amount of listings with bookings created, and this average considers the past 12 months. So I'd say it's a good estimate of the "real" size of a client in terms of potential for Superhog. # Checklist - [X] The edited models and dependants run properly with production data. - [X] The edited models are sufficiently documented. - [X] The edited models contain PK tests, and I've ran and passed them. - [NA] I have checked for DRY opportunities with other models and docs. - [NA] I've picked the right materialization for the affected models. # Other - [ ] Check if a full-refresh is required after this PR is merged. Related work items: #22883
This commit is contained in:
Oriol Roqué Paniagua
parent
5735251c67
commit
f230eb3af5
4 changed files with 279 additions and 9 deletions
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@ -3,6 +3,7 @@ with
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int_monthly_aggregated_metrics_history_by_deal as (
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select * from {{ ref("int_monthly_aggregated_metrics_history_by_deal") }}
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),
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int_hubspot__deal as (select * from {{ ref("int_hubspot__deal") }}),
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deal_history_from_previous_months as (
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select
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year,
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@ -30,6 +31,10 @@ with
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sum(deal_created_bookings_12_months_window) over (
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partition by first_day_month
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) as global_created_bookings_12_months_window,
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deal_avg_listings_booked_in_month_12_months_window,
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sum(deal_avg_listings_booked_in_month_12_months_window) over (
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partition by first_day_month
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) as global_avg_listings_booked_in_month_12_months_window,
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deal_revenue_12_months_window,
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effective_deal_revenue_12_months_window,
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sum(effective_deal_revenue_12_months_window) over (
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@ -39,6 +44,10 @@ with
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partition by first_day_month
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order by deal_created_bookings_12_months_window desc
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) as deal_contribution_rank_to_global_created_bookings,
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row_number() over (
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partition by first_day_month
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order by deal_avg_listings_booked_in_month_12_months_window desc
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) as deal_contribution_rank_to_global_avg_listings_booked_in_month,
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row_number() over (
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partition by first_day_month order by deal_revenue_12_months_window desc
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) as deal_contribution_rank_to_global_revenue
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@ -52,6 +61,9 @@ with
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coalesce(
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sum(previous_twelve_months.created_bookings), 0
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) as deal_created_bookings_12_months_window,
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coalesce(
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avg(previous_twelve_months.listings_booked_in_month), 0
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) as deal_avg_listings_booked_in_month_12_months_window,
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coalesce(
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sum(previous_twelve_months.revenue_in_gbp), 0
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) as deal_revenue_12_months_window,
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@ -141,6 +153,7 @@ with
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- 1 as yoy_listings_booked_in_month_growth,
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-- 12 Months Window (Account Size) --
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-- Bookings --
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aggregated_12m_window.deal_created_bookings_12_months_window,
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aggregated_12m_window.global_created_bookings_12_months_window,
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coalesce(
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@ -153,6 +166,29 @@ with
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0
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) as deal_contribution_share_to_global_created_bookings,
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aggregated_12m_window.deal_contribution_rank_to_global_created_bookings,
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-- Listings --
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round(
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aggregated_12m_window.deal_avg_listings_booked_in_month_12_months_window,
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2
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) as deal_avg_listings_booked_in_month_12_months_window,
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round(
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aggregated_12m_window.global_avg_listings_booked_in_month_12_months_window,
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2
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) as global_avg_listings_booked_in_month_12_months_window,
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coalesce(
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cast(
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aggregated_12m_window.deal_avg_listings_booked_in_month_12_months_window
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as decimal
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) / nullif(
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aggregated_12m_window.global_avg_listings_booked_in_month_12_months_window,
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0
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),
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0
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) as deal_contribution_share_to_global_avg_listings_booked_in_month,
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aggregated_12m_window.deal_contribution_rank_to_global_avg_listings_booked_in_month,
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-- Revenue --
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aggregated_12m_window.deal_revenue_12_months_window,
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aggregated_12m_window.effective_deal_revenue_12_months_window,
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aggregated_12m_window.effective_global_revenue_12_months_window,
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@ -243,6 +279,12 @@ with
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m.global_created_bookings_12_months_window,
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m.deal_contribution_share_to_global_created_bookings,
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m.deal_contribution_rank_to_global_created_bookings,
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m.deal_avg_listings_booked_in_month_12_months_window,
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m.global_avg_listings_booked_in_month_12_months_window,
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m.deal_contribution_share_to_global_avg_listings_booked_in_month,
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m.deal_contribution_rank_to_global_avg_listings_booked_in_month,
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m.deal_revenue_12_months_window,
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m.effective_deal_revenue_12_months_window,
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m.effective_global_revenue_12_months_window,
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@ -300,20 +342,81 @@ with
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from metrics_attribution_to_given_month_per_deal m
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)
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select
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*,
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gsc.date,
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gsc.id_deal,
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gsc.main_deal_name,
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gsc.main_billing_country_iso_3_per_deal,
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gsc.deal_lifecycle_state,
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d.deal_hubspot_stage,
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d.account_manager,
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d.live_date_utc,
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d.cancellation_date_utc,
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gsc.given_month_first_day_month,
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gsc.previous_1_month_first_day_month,
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gsc.previous_2_month_first_day_month,
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gsc.previous_12_month_first_day_month,
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gsc.previous_13_month_first_day_month,
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gsc.aggregated_revenue_from_first_day_month,
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gsc.aggregated_revenue_to_first_day_month,
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gsc.given_month_revenue_in_gbp,
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gsc.previous_1_month_revenue_in_gbp,
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gsc.previous_2_month_revenue_in_gbp,
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gsc.previous_12_month_revenue_in_gbp,
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gsc.previous_13_month_revenue_in_gbp,
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gsc.mom_revenue_growth,
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gsc.mom_1_month_shift_revenue_growth,
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gsc.yoy_revenue_growth,
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gsc.yoy_1_month_shift_revenue_growth,
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gsc.given_month_created_bookings,
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gsc.previous_1_month_created_bookings,
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gsc.previous_12_month_created_bookings,
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gsc.mom_created_bookings_growth,
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gsc.yoy_created_bookings_growth,
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gsc.given_month_listings_booked_in_month,
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gsc.previous_1_month_listings_booked_in_month,
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gsc.previous_12_month_listings_booked_in_month,
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gsc.mom_listings_booked_in_month_growth,
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gsc.yoy_listings_booked_in_month_growth,
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gsc.deal_created_bookings_12_months_window,
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gsc.global_created_bookings_12_months_window,
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gsc.deal_contribution_share_to_global_created_bookings,
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gsc.deal_contribution_rank_to_global_created_bookings,
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gsc.deal_avg_listings_booked_in_month_12_months_window,
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gsc.global_avg_listings_booked_in_month_12_months_window,
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gsc.deal_contribution_share_to_global_avg_listings_booked_in_month,
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gsc.deal_contribution_rank_to_global_avg_listings_booked_in_month,
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gsc.deal_revenue_12_months_window,
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gsc.effective_deal_revenue_12_months_window,
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gsc.effective_global_revenue_12_months_window,
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gsc.deal_contribution_share_to_global_revenue,
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gsc.deal_contribution_rank_to_global_revenue,
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gsc.avg_mom_growth_score,
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gsc.avg_yoy_growth_score,
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gsc.avg_growth_score,
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gsc.weighted_avg_growth_score,
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-- Applies a categorisation based on the score value. These scores thresholds are
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-- opinionated
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case
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when weighted_avg_growth_score <= -1.0
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when gsc.weighted_avg_growth_score <= -1.0
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then 'TOP LOSER'
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when weighted_avg_growth_score > -1.0 and weighted_avg_growth_score < 0
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when gsc.weighted_avg_growth_score > -1.0 and gsc.weighted_avg_growth_score < 0
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then 'LOSER'
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when weighted_avg_growth_score = 0
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when gsc.weighted_avg_growth_score = 0
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then 'FLAT'
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when weighted_avg_growth_score > 0 and weighted_avg_growth_score < 1.0
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when gsc.weighted_avg_growth_score > 0 and gsc.weighted_avg_growth_score < 1.0
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then 'WINNER'
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when weighted_avg_growth_score >= 1.0
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when gsc.weighted_avg_growth_score >= 1.0
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then 'TOP WINNER'
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else 'UNSET'
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end as categorisation_weighted_avg_growth_score
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from growth_score_computation
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from growth_score_computation gsc
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left join int_hubspot__deal d on gsc.id_deal = d.id_deal
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@ -670,6 +670,28 @@ models:
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Identifier of the lifecycle state of a given deal
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in a given month.
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- name: deal_hubspot_stage
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data_type: string
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description: |
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Current hubspot stage for a given deal.
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- name: account_manager
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data_type: string
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description: |
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Current Account Manager in charge of a given deal, according
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to Hubspot.
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- name: live_date_utc
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data_type: date
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description: |
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Date in which the account has gone live, according to Hubspot.
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- name: cancellation_date_utc
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data_type: date
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description: |
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Date in which the account has been offboarded, according to
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Hubspot.
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- name: given_month_first_day_month
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data_type: date
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description: |
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@ -1061,7 +1083,7 @@ models:
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- name: global_created_bookings_12_months_window
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data_type: integer
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description: |
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Total created bookings generated by a deal
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Total created bookings generated by any deal
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in the months from the period ranging from the
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aggregated_revenue_from_first_day_month to
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aggregated_revenue_to_first_day_month.
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@ -1097,6 +1119,61 @@ models:
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tests:
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- not_null
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- name: deal_avg_listings_booked_in_month_12_months_window
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data_type: decimal
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description: |
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Average listings booked in month by a deal
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in the months from the period ranging from the
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aggregated_revenue_from_first_day_month to
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aggregated_revenue_to_first_day_month.
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It cannot be null.
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tests:
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- not_null
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- dbt_expectations.expect_column_values_to_be_between:
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min_value: 0
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strictly: false
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- name: global_avg_listings_booked_in_month_12_months_window
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data_type: decimal
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description: |
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Sum of the average listings booked in month by
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any deal in the months from the period ranging from the
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aggregated_revenue_from_first_day_month to
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aggregated_revenue_to_first_day_month.
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It is used for the deal contribution share with respect
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to the global average listings booked in month.
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It cannot be null.
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tests:
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- not_null
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- dbt_expectations.expect_column_values_to_be_between:
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min_value: 0
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strictly: false
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- name: deal_contribution_share_to_global_avg_listings_booked_in_month
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data_type: decimal
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description: |
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Represents the size of the deal in terms of average listings
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booked in month.
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In other words, what's the percentage of the global average listings
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booked in month that can be attributed to this deal.
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It cannot be null.
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tests:
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- not_null
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- dbt_expectations.expect_column_values_to_be_between:
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min_value: 0
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strictly: false
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- name: deal_contribution_rank_to_global_avg_listings_booked_in_month
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data_type: decimal
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description: |
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Represents the ordered list of deals by descending size
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in terms of average listings booked in month.
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If more than one deal have the same share, the order is
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not under control.
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It cannot be null.
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tests:
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- not_null
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- name: avg_mom_growth_score
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data_type: decimal
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description: |
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