# 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
Context: I'm intending to work on Account Managers reporting, that mostly will include reporting at Deal level the Resolutions Payouts as well as the new Retained metrics. While checking the great increase on Resolutions Payouts for October 2024:
I decided to take a quick look into the main players... and surprise surprise we have Guesty:
So Guesty represents 37k over the 73K of October. 50%. Not bad.
The main issue is that we've been aware for months now (since Churn efforts, mostly) that we're not reporting in KPIs those deals that are NOT created in Core. Most notably, API deals which includes... well, Guesty. So creating this kind of in-depth Account Managers improvement without reporting Guesty I think it would be very misleading. Note that the overall figures (Global dimension) are still accurate, though.
What's new:
* A new model named `int_kpis__dimension_deals` that basically retrieves Deals from both Core (as before) and Hubspot. It combines information from both and mostly assumes Hubspot as a better source of information than Core - although we do not have the Main Billing Country there afaik.
* Propagates changes, mostly in the monthly by deal view of Main KPIs. Here I confirm that now Guesty appears, and it only has metrics that come from Xero (APIs Revenue, Total Revenue, Resolutions, etc)
# 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
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
Switches Listings and Deal metrics to production.
I also modified the dependencies on the old lifecycles to read from the news, so we can remove these in a following PR.
I'm considering re-computing also the dimension - specific models to operate within KPIs folder, but will do this later on in a dedicated PR.
# 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.
- [ ] 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: #23761
# Description
Changes:
* Creates lifecycle_daily_deal, metric_daily_deals and agg_daily_deals. These follow a different strategy due to the nature of the metrics
* Modifies the dimension macro to ensure deal dimension is included in all models except these ones
* Fixes production issue on currently deployed deal lifecycle and metrics
# 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: #23566
# Description
Switches Xero metrics to the new KPIs flow. This uses the 2 new entities around Invoiced Revenue and Host Resolutions.
The metrics affected will change computation source in PBI as well (for MTD per category and Monthly by deal views). This directly affects the following metrics:
* Invoiced Operator Revenue
* Invoiced Booking Fees Revenue
* Invoiced Listing Fees Revenue
* Invoiced Verification Fees Revenue
* Invoiced APIs Revenue
* Invoiced Athena Revenue
* Invoiced E-Deposit Revenue
* Damage Host-Waiver Payments
* Host Resolutions Amount Paid
* Host Resolutions Payment Count
Additionally, the following metrics will be indirectly affected since depend partially on Xero:
* Total Revenue
* 4x Total Revenue per (Booking Created, Guest Journey Created, Deals Booked in Month, Listings Booked in Month)
* Waiver Retained
# 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. **Same as last time - the way models are called could be improved, but let's switch everything first and then discuss. There's chances these cross models will die anyway**
- [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: #23759
# Description
Same old story: includes all metrics coming from Xero.
Adds a daily model, monthly, mtd + monthly agg and mtd agg
A test to compare values new vs. old
AND fixes the issue I mentioned with the timestamp - an issue in the old KPIs.
# 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: #23565
# Description
Exposes New KPIs of Bookings, Guest Journeys and Guest Payments in the 2 main flows: Monthly+MTD per Global, By Billing Country and By # of Listings Segmentation & Monthly By Deal
I did some checks on Global and By Billing Country and looks good.
I checked some examples for Monthly By Deal and looks good.
# 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.
- [NO] I have checked for DRY opportunities with other models and docs. **Likely there's ways to create default configs for KPIs saying "hey, this is Main KPIs for a specific view so use this models and these filters". But at this stage since it's a transitional stage I don't want do overthink. Let's tackle this later on if that's ok for you. It means we will live with some repeated expressions**
- [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: #23455
# 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
Exposes Churn Rates into Main KPIs, specifically Revenue Churn Rate, Bookings Churn Rate and Listings Churn Rate. This is based on the average approach.
Additionally, it adds these 3 metrics in the kpis_additive_metrics_per_dimension_are_consistent test.
Additionally, it removes from int_mtd_vs_previous_year_metrics the computation of the additive Churn Rates. The removal of further unused code will be handled in a separated PR.
# 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: #22691
# 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
Small PR to ensure all values within the computation will be treated as decimals. I apply this at the beginning of the code for the 4 main inputs used. This avoids later integer divisions.
# 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: #22691
# 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
- Bugfix on nullif then 0 - it was applied to the numerator of Revenue computation, which made MoM growth be considered as null and propagated as 0 in the scores, which is not true.
- Bugfix on cast as numeric - this was introduced because PBI didn't read well some decimal figures when loading the data. However this impacted somehow in the score by some weird magic I don't understand. I just replace the casts by rounds, that are applied after the computation of the scores, and PBI seems happy with 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.
- [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:
* 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
# Description
Main changes:
* Guest revenue is now guest payments. PBI uses Guest revenue, so alias is changed at reporting level, while it uses guest_payments_in_gbp field.
* Removal of Waiver Amount Paid back to Host to Guest revenue and Total revenue.
# 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.
- [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: #22688
# Description
Adapts revenue figures in Main KPIs - MTD scope or global view. This includes MTD, Monthly Overview, Global Evolution over Time, Detail by Category. In essence, everything that is not by deal.
The changes are mainly 2:
* Remove the line that deducts the `Waiver Amount Paid Back to Hosts` in all metrics except the `Waiver Net Fees`. This effectively means that the previous `Guest Revenue` = `Guest Payments`, thus I dropped all 3 `Guest Payments` metrics.
* Do a renaming at metric display level, but not in the code. This means that I remove the computation of `guest_revenue_in_gbp` for instance and keep `guest_payments_in_gbp`, and apply the renaming later on, since the modelisation already accounts for defining metric names differently from those of the fields. For the rest of metrics, I revised all metrics name and did changes based on the [whiteboard](https://whiteboard.office.com/me/whiteboards/p/c3BvOmh0dHBzOi8vZ3VhcmRob2ctbXkuc2hhcmVwb2ludC5jb20vcGVyc29uYWwvcGFibG9fbWFydGluX3N1cGVyaG9nX2NvbQ%3d%3d/b!T2D3opQuBECSDnhuFZrUacFu3TxvSvdIsnI4Dxsh2IuaB1AigbciRqkqte61I4wz/01H5SI4J4L7HTPJGUT7JGYKTOSQYYWACXU). I also changed the dedicated data tests in Main KPIs to ensure it's working. I also changed the exclusion logic in reporting based on the name of the metric to not display metrics that depend on the invoicing cycle unless it's 2 months ago or before.
To keep in mind:
* Merging this will automatically display the new figures/naming in production. Might be wise to communicate to stakeholders since some key metrics (namely, Guest Revenue / Total Revenue) will change the meaning.
* We also need to do these changes in the metrics by deal part of the computation. I'd do first the removal of these fields in the PBI report (and take the opportunity to change the Data Catalogue) and then do the PR in DWH to change the logic. Before that though let's check that the names included in this PR are the correct ones :)
# 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.
- [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: #22688
