# Description
Adds number format for display purposes
# 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.
- [X] I have checked for DRY opportunities with other models and docs.
- [X] I've picked the right materialization for the affected models.
# Other
- [ ] Check if a full-refresh is required after this PR is merged.
Adds number format
Related work items: #27609
# Description
Changes:
* Adds Onboarding MRR
* Refactors exclusion code for ongoing month / invoicing cycle
* Adds sign format on relative differences
# 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.
- [X] I have checked for DRY opportunities with other models and docs.
- [X] 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: #27609, #27805
# Description
_Describe your motivation and changes here._
# Checklist
- [ ] The edited models and dependants run properly with production data.
- [ ] The edited models are sufficiently documented.
- [ ] The edited models contain PK tests, and I've ran and passed them.
- [ ] I have checked for DRY opportunities with other models and docs.
- [ ] I've picked the right materialization for the affected models.
# Other
- [ ] Check if a full-refresh is required after this PR is merged.
Revert "Adds Onboarding MRR"
Reverted commit `dab210c6`.
# Description
_Describe your motivation and changes here._
# Checklist
- [ ] The edited models and dependants run properly with production data.
- [ ] The edited models are sufficiently documented.
- [ ] The edited models contain PK tests, and I've ran and passed them.
- [ ] I have checked for DRY opportunities with other models and docs.
- [ ] I've picked the right materialization for the affected models.
# Other
- [ ] Check if a full-refresh is required after this PR is merged.
Revert "Refactor display exclusion for clarity purposes"
Reverted commit `fdec616f`.
# Description
_Describe your motivation and changes here._
# Checklist
- [ ] The edited models and dependants run properly with production data.
- [ ] The edited models are sufficiently documented.
- [ ] The edited models contain PK tests, and I've ran and passed them.
- [ ] I have checked for DRY opportunities with other models and docs.
- [ ] I've picked the right materialization for the affected models.
# Other
- [ ] Check if a full-refresh is required after this PR is merged.
Revert "Relative increments with sign"
Reverted commit `f5718ded`.
# Description
Changes:
* Adds Revenue Churn Rate in YTD/MTD Overview. This has several implications, I finally understood how to properly compute a YTD.
The problem is that Revenue Churn Rate is a % of the Total "Churned" Revenue in a 12 m period vs. the Total Revenue in the same 12 m period. This is a bit tricky because it's not really additive, because of the Churn definition. Total Churned Revenue is the Revenue that the churned deals in a month generated on that past 12 months prior to churning.
So - in order to aggregate it properly, we need to do the sum of the Total Churned Revenue and retrieve the Total Revenue on these 12 months, and THEN compute the Churn rate.
This PR mainly retrieves the necessary input from the Churn models and then follows a similar computation as for the rest of YTD/MTD converted metrics.
I'll handle Onboarding MRR in a separated PR as this one is quite dense already.
# 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.
- [X] I have checked for DRY opportunities with other models and docs.
- [X] 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: #27609, #27805
# Description
Changes:
* Adds template for targets -> These need to be revised
* Adds comparison of values vs. targets
* Allows for multi-year last date computation (allowing multiple years to be selected, not just the last one)
# 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.
- [X] I have checked for DRY opportunities with other models and docs.
- [X] 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: #27609, #27805
# Description
First version of the model int_ytd_mtd_aggregated_main_metrics_overview
It aggregates data at the level of:
* Date
* Dimension
* Dimension Value
* Metric Name (or Id Metric)
This computes differences and relative differences in:
* current MTD vs previous month EOM
* current MTD vs previous year MTD
* current year YTD vs previous year YTD
This is applied to 13 metrics, namely:
* Total Revenue
* Revenue Retained Post-Resolutions
* Guest Revenue
* Invoiced Operator Revenue
* Invoiced APIs Revenue
* Billable Bookings
* Live Deals
* New Deals
* Churning Deals
* Damage Waiver Payout Rate
* Host Resolutions Payout Rate
* Invoiced Operator Revenue per Billable Booking
* Waiver Revenue per Billable Booking
This still does not handle:
* Comparison vs. targets (to be done later, need input)
* Missing metrics on Onboarding MRR / Revenue Churn (to be done later)
* Invoicing dependant data exclusion (to be done in reporting)
# 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.
- [X] I have checked for DRY opportunities with other models and docs.
- [X] I've picked the right materialization for the affected models. **At the moment I keep everything as views and seems ok. We'll see if this needs to be materialised as tables later on**
# Other
- [ ] Check if a full-refresh is required after this PR is merged.
Related work items: #27609
# Description
New model for the purpose of Main KPIs - Overview.
It computes:
* Current MTD value
* Previous Month EOM value
* Previous Year MTD value (12 months ago)
* Current YTD value
* Previous Year YTD value
for the metrics:
* Total Revenue
* Revenue Retained Post-Resolutions
* Guest Revenue
* Invoiced Operator Revenue
* Invoiced APIs Revenue
* Host Resolutions Amount Paid
* Damage Host Waiver Payments
* Billable Bookings
* New Deals
* Churning Deals
* Live Deals (dedicated logic handling)
* Waiver Revenue
Additionally it properly computes the following derived metrics:
* Waiver Payout Rate
* Resolutions Payout Rate
* Operator Revenue per Billable Booking
* Waiver Revenue per Billable Booking
Only for dimension = 'global', though should be easy to extend to other dimensions.
This does not handle (yet) Onboarding MRR nor Revenue Churn Rate, mostly because I need to think how this can be properly attributed in a YTD basis.
This does not compute variations (abs. diff. or rel. diff.) yet.
This does not handle the "hiding" of invoicing metrics due to the invoicing cycle yet.
This does not handle targets... yet!
# 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.
- [X] I have checked for DRY opportunities with other models and docs.
- [X] 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: #27609
# Description
Changes:
* Adapt business_kpis_configuration to include By Business Scope as production dimension.
* Sets in int_mtd_metrics_vs_previous_year the selection of business scope dimension for all KPIs models. This does not affect cross kpis models (churn/mrr). I might need to check later how to adapt Churn to include this dimension, but it's not considered as for this PR. Lastly, Billable Bookings excludes New Dash.
* Adapts condition in int_mtd_metrics_vs_previous_year so MTD values would appear independently of these appearing in the previous year. This is, the model was considering that to show current month MTD values, the dimension needed to exist the year prior. This does not happen with New Dash and I assume we never noticed because in any case, most of our dimensions have quite a long history.
* Adapts int_kpis__agg_dates_main_kpis to include the business scope dimension. By the way it's actually handled, it kind of assumes that a Deal can only be in New or Old Dash (this is correct), but while on New Dash, this deal won't have data for Old Dash (this might not be 100% correct). In any case, the global figure should be ok, and only on the deal + business scope dimensionality this could cause some potential problems. However, this is not being reported anyway at the moment.
* Adapts int_kpis__agg_dates_main_kpis to have a proper variable value for the dimensions, and this is further included in business_kpis_configuration as any other model.
Small changes:
* Adapts Churn metrics to read from dimension_deals rather than core__deals. This should be more accurate anyway.
# Checklist
- [ ] The edited models and dependants run properly with production data.
- [ ] The edited models are sufficiently documented.
- [ ] The edited models contain PK tests, and I've ran and passed them.
- [ ] I have checked for DRY opportunities with other models and docs.
- [ ] I've picked the right materialization for the affected models.
# Other
- [ ] Check if a full-refresh is required after this PR is merged.
Propagates New Dash/Old Dash/APIs split in KPIs as per Business Scope
Related work items: #27356
# Description
Quick improvement to be able to report the same setup of metrics by considering all account history up to a certain date.
It adds a new computation flow for this All History window. Note that I needed to update the macro to override this case by using unbounded preceding.
I also took the opportunity to update the exposures of the new report.
# 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.
- [X] I have checked for DRY opportunities with other models and docs.
- [X] 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: #26085
# Description
Mostly 2 changes:
* Fix metrics with coalesces so values are displayed
* Removes ratios, no longer needed. These are computed in PBI directly, to be able to compute the total figure correctly
# 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.
- [X] I have checked for DRY opportunities with other models and docs.
- [X] 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: #25829
# Description
* Creates new model monthly_aggregated_metrics_history_by_deal_by_time_window
* Modifies existing intermediate entry on schema to properly fill all fields
* Creates same entry in reporting.
# 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.
- [X] I have checked for DRY opportunities with other models and docs.
- [X] 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: #25829
# Description
This model aggregates at monthly by deal level different metrics for AM reporting purposes. It also includes revenue retained ratios for client profitability assessment.
There's part of the existing AM report that could be simplified, likely, by using the new macro. This will be explored in a separated PR, if it applies.
# 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.
- [ ] I have checked for DRY opportunities with other models and docs. ** Checked and there might be possibilities to simplify the code. I'll check ones I finish this line of work**
- [X] 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: #25829
# Description
Adds `is_end_of_month_or_yesterday` for Main KPIs.
Apparently, the fact that we do not show the ongoing value of the month on some tabs of Main KPIs is the main blocker for Ben C to consistently use Main KPIs, which he actually retrieves from the SH legacy reporting. Since I'm sceptical about the data shown there, I want to remove this blocker.
It will require a small PR on PBI as well.
# 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.
- [X] 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: #25342
# Description
New model:
* int_kpis__agg_dates_main_kpis - Serves as the skeleton of dates and dimensions for Main KPIs. It's aggregated since it follows a similar aggregation strategy. It's a single model to feed both Main KPIs visualisations. Note boolean fields are real booleans (true/false) while before these were integers (1/0). This also affects downstream models.
Main KPIs flow adaptations to new skeleton model:
* int_monthly_aggregated_metrics_history_by_deal
* int_monthly_churn_metrics - additionally, calls usual KPIs macro instead of old one
* int_mtd_vs_previous_year_metrics
Reporting changes to ensure report is not down:
* mtd_aggregated_metrics - adaptations on booleans (true-1, false-0)
Cleaning:
* get_kpi_dimensions macro is no longer used
* int_dates_by_deal model and schema entry
* int_dates_mtd_by_dimension model and schema entry
* int_dates_mtd model and schema entry
# 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.
- [X] I have checked for DRY opportunities with other models and docs.
- [X] 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: #23763
# Description
Eliminates models that have been switched with new kpis flow.
Also deletes temporary tests and schema entries.
# Checklist
- [X] The edited models and dependants run properly with production data.
- [NA] The edited models are sufficiently documented.
- [X] The edited models contain PK tests, and I've ran and passed them.
- [X] 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: #23762
# Description
Sets up warning for KPIs models that will be deprecated, which are:
* 13 in core
* 2 in xero
* 5 in cross
I will keep alive the cross models that handle the final aggregations for Main KPIs for the time being, as well as the newly created Churn model that has a dependency on the monthly by deal to be filled into the mtd flow. I think handling exposure logic for Main KPIs could be a separated migration.
In other words, this is already quite a bit to migrate.
# Checklist
**I just checked that dbt compiles correctly**
- [NA] The edited models and dependants run properly with production data.
- [NA] The edited models are sufficiently documented.
- [NA] 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: #23268
# Description
Simplifies the code for the models:
* int_monthly_12m_window_contribution_by_deal
* int_monthly_churn_metrics
By just removing the additive contribution approach. This also reduces the schema file information of these 2 models. I also adapted the description to clarify the state of the models.
No rush to merge this.
# 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.
- [X] I have checked for DRY opportunities with other models and docs.
- [X] 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: #22691
# Description
Re-aligned namings with Matt and Alex. This PR just changes the top losers, losers, winners and top winners to major decline, decline, gain and major gain respectively
# 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.
Rename of categories for top losers/winners
Related work items: #23170
# 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
# Description
Adapts deals lifecycle logic by including offboardings from hubspot. It mostly increases the number of churning and inactive states in decrement of active state.
I also updated documentation and added an accepted values test.
When deploying and refreshing prod, figures in main kpis will be impacted
# 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: #22689
# Description
Moves from intermediate/core to intermediate/cross the following models:
- `int_core__mtd_deal_lifecycle`
- `int_core__mtd_deal_metrics`
to their equivalents:
- `int_mtd_deal_lifecycle`
- `int_mtd_deal_metrics`
This also changes the schema entries, from core to cross, including changing the name of the model in the entry.
This also changes the dependencies, namely in `int_mtd_deal_metrics`, `int_mtd_vs_previous_year_metrics` and `int_monthly_aggregated_metrics_history_by_deal`.
This does NOT aim to alter the logic of the lifecycle in any case; it will be done in a separated PR.
Runs correctly end-to-end. We might need to drop the old models from production manually.
# 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.
- [X] I have checked for DRY opportunities with other models and docs.
- [X] 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: #22689
# Description
Main changes:
* Includes 4 new fields to take into account 12 month created bookings. Specifically:
`deal_created_bookings_12_months_window`
`global_created_bookings_12_months_window`
`deal_contribution_share_to_global_created_bookings`
`deal_contribution_rank_to_global_created_bookings`
This also renames a CTE, that was previously stating it was revenue. Same for inline comments. Also includes documentation of this fields.
* Score range modification: Now, growth scores are multiplied by 100 and weighted score by 1000. This makes it easier to display and understand (Growth cannot be less than -100, threshold value is now -1, 0 and 1).
I checked that the content already in production has not change (ex: we still have the same 15 top losers for September).
# 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: #22635
# Description
Main changes:
- Creation of `int_monthly_churn_metrics` model. This follows a similar approach as for mtd models, with jinja loops to aggregate the metrics at different dimensions. This reads from the previous monthly model, thus creating a dependency on Global KPIs with By Deal KPIs.
- Adds the 6 metrics in the main aggregated model of Global KPIs `int_mtd_vs_previous_year_metrics`. It doesn't necessarily mean that the 6 metrics will be made available in the report.
This does NOT display these metrics in the report, and won't be done until deal lifecycle is enriched to consider hubspot offboarding in the state "05-Churning".
# 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.
- [X] I have checked for DRY opportunities with other models and docs.
- [X] 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: #22691
# Description
This PR creates a new model that depends on int_monthly_aggregated_metrics_history_by_deal. The idea is that this is used for Churn computation (Booking Churn, Revenue Churn, Listing Churn) later on.
The idea is relatively simple. Measure how much a Deal has been contributing to a Global amount (sum of metric for all deals) over the preceding period of 12 months. You will notice that there's 2 computations, the "additive" and the "average" one. This is because we still need to align with Matt/Suzannah on which approach makes more sense, but we need data for it. I'm not sure the namings are good though so happy to see your suggestions.
You will also notice that there's no filter by deal_lifecycle_state = '06-Churning'. This will be done in a separated model, whenever we attribute this model to the mtd computation. The reason is simple - this model stays at deal level, thus meaning we can do the dimension aggregation and even a lifecycle aggregation if needed, depending on the needs.
Be aware that this effectively means that MTD KPIs models will depend on the "monthly by deal" models. This has some cons in terms of dependency management but cannot be overcome since we the metric total revenue depends on many subsets. In essence, I don't see another way of doing it unless doing a massive KPIs refactor. I prefer to wait until the Product KPIs discussions are finished and then we see how we approach it.
# 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.
- [X] I have checked for DRY opportunities with other models and docs.
- [X] 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: #22691
# Description
Copies intermediate to reporting for growth score by deal. Schema is copy-paste from intermediate changing the model's name.
# 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.
- [X] 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: #22635
# Description
Creates a model to identify deal growth based on YoY performance of Created Bookings, YoY performance of Listings Booked in Month and one month shifted YoY performance of Revenue.
Also added weighted score to account for revenue size.
# 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.
- [ ] I have checked for DRY opportunities with other models and docs. **Probably something can be done here, sorry I've not checked.**
- [X] 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: #22635
