Changelog
Follow up on the latest improvements and updates.
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Released: September 16, 2025
Overview
Issue:
In Daily Plan to Actual, the Plan CPA measure in daily_plan_to_actual.view
referenced the wrong denominator (actual_new_customers
), producing inaccurate CPA values.Solution:
Corrected Plan CPA to use plan_marketing_spend / total_planned_new_customers
by replacing the denominator in the daily_plan_to_actual.view
measure with total_planned_new_customers
, so the metric now reflects plan inputs and aligns with other plan-based metrics.Released: September 16, 2025
Overview
Issue:
Amazon Ads — Sponsored Products spend in Daily Marketing Plan to Actual was shown in source currency, causing mismatches with vendor totals.Solution:
Applied currency conversion so Sponsored Products spend appears in your account currency throughout Daily Marketing Plan to Actual, aligning with vendor-reported totals.Released: September 16, 2025
Overview
Issue:
Email subject lines were coming through as NULL in Klaviyo V2, breaking dashboard/export fields.Solution:
Restored subject lines by sourcing the campaign’s saved subject, so dashboards/exports now populate correctly; we also enabled optional historical backfill on request.Released: September 16, 2025
Overview
Issue:
Target data showed differences between current and historical views, with missing product IDs, SKU mismatches, and duplicates affecting sales/inventory accuracy.Solution:
Standardized Target data across current and historical views, added missing product identifiers, corrected SKU mismatches, removed duplicates, and rebuilt history so sales and inventory now align consistently across reports (inventory repopulated after rollout).Release date: September 17, 2025
Summary
We are launching our first unified retail data explores, designed for cross-channel analysis including syndicated and retailer portal sales data. Our mission is to make it easier than ever to do complex analysis across your retail data sources with streamlined category/brand performance analysis, promotional effectiveness, and week‑over‑week tracking.
Ensured alignment with Omni V2 conventions (naming, metrics parity, date handling) to reduce context switching.
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Explores Included
1.
dm_retailer_brand_cat_perf__agg.explore.lkml
Aggregate view for brand & category performance across retailers; ideal for executive summaries and high‑level trend views.
- dm_retailer_brand_cat_perf__weekly.explore.lkml
Weekly‑grain view to analyze velocity, distribution, and pricing shifts over time; supports week‑over‑week ops and cohort drill‑downs.
- dm_retailer_promo_analysis.explore.lkml
Promotion‑focused view for lift, incrementality, and ROI questions; designed for trade optimization and post‑event readouts.
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Why It Matters: Improves our retail analytics offering
- Provides a single data model where you can run complex competitive analysis, or promotional analysis optimizations across all available retail markets, from your retailer portals and syndicated data sets and custom retail sales data inputs: no more data silos!
- Standardizes promo analysispatterns and modeling across retailer POS and syndicated data sources (lift, incrementality, ROI), ensuring your data is as smart as it can be (we make your basic sales data more sophisticated, to match the structure of syndicated data and the analysis these pricing/promotional and distribution/velocity metrics can unlock.
- Keeps Retail aligned with Omni V2 so cross‑channel narratives are consistent.
Who is affected
: This is a net-new feature, so none of your current dashboards or explores will be interrupted. All merchants using Retail explores will have these new explores available for analysis. Dashboards are launching over the next two weeks so we have Templates for quick analysis on top of these analysis dashboardsWhat's next?
New dashboards are being built for these unified explores and are set to release over the next 1-2 weeks (Sep 2025); We will be rolling out dashboards built on top of these unified data models, so that retail analysis can be unleashed from the source-specific explores and dashboards we were limited to prior to this update.Released September 15, 2025
Summary
We’re rolling out
Omni V2
and introducing new Omni models
in direct response to merchant feedback since our June app launch. The update gives teams a choice between:- Harmonized Dateviews that align all sources to the same most-recent fully-available week (ideal when anchoring the business to lagging syndicated sources like NielsenIQ/SPINS), and
- Latest Weekviews that always show each source’s most current week (ideal for fast-moving eCom/retail operations where recency is preferred).
What’s New
- Omni V1 → Omni V2data model migration (metrics parity maintained).
- New Omni exploressupporting bothHarmonized DateandLatest Weekreporting modes.
- Anchor‑date logic applied to harmonize across sources when needed.
- V1 explores will be renamed and retiredafter validation is complete.
Explores Added/Updated
The following explores are now available in two parallel variants:
- dm_omni_company_performance_harmonized_date.explore.lkml
- dm_omni_company_performance_latest_week.explore.lkml
- dm_omni_omnichannel_sales_harmonized_date.explore.lkml
- dm_omni_omnichannel_sales_latest_week.explore.lkml
Data Model Logic:
Company Performance vs Omnichannel
- Company Performance: These (2) omnichannel explores are filtered to only your brand, and non-duplicative markets that total up to total enterprise sales.
- Omnichannel: These (2) omnichannel explores include all available markets and products. These will enable competitive analysis on top of the omnichannel market view (combine your syndicated data with POS retailer portals, for a total universe category analysis.
Date Alignment across Data Sources: Harmonized vs Latest Week
- Harmonized Date: Aligns all included sources to the most recentcommoncomplete week (e.g., when syndicated data lags 1–3+ weeks, you can still make apples‑to‑apples comparisons across channels against that same anchor week).Typically useful company performance analysis with a lagging data source, like syndicated data (SPINS/NielsenIQ/Circana)
- Latest Week: Surfaces the freshest available data per source (useful for near‑real‑time ops and pacing without forcing older lagging sources to gate the view). Updates weekly on Mondays with week through the day prior (all sources normalized to week ending Sunday).
How to Choose: Harmonized vs Latest Week
- Choose Harmonized Dateif leadership or FP&A wants to anchor the weekly business review tosyndicated (NielsenIQ/SPINS) timelinesand maintain strict apples‑to‑apples comparisons.
- Choose Latest Weekif your operational cadence prioritizesrecency(e.g., eCom performance, retailer week closures) and you accept that syndicated datasets will trail.
Tip:
Many teams adopt Harmonized Date
for executive/board and Latest Week
for day‑to‑day operations.---
Rollout & Impact
- Who is affected: All merchants using Omni explores. (Note: this has NOT impacted home page dashboard yet, but will in a following release. Should not impact your use of the homepage, and we will update again when that is copleted.
- Dashboards: Expectno or minimal changes; any differences will be documented during validation.
- Custom YAMLs: We are updating custom YAMLs as part of the rollout for all teams with custom Omni data model development or dashboards.
- Deprecation: V1 will be renamed and removed post‑validation.
Why It Matters
- Preserves metrics paritywhile giving youflexibilityto match your org’s preferred reporting cadence.
- Reduces reconciliation friction between omnichannelandsyndicatedtimelines.
- Directly addresses top feedback themes from the June launch around date alignmentanddata lag.
We're excited to announce the launch of our new Custom Revenue & Order Metrics Framework! This powerful update enables you to easily define and manage your own revenue calculations and order definitions directly within Daasity—without needing custom code or developer resources.
Explore these new capabilities now and take greater control over your business metrics today!
📈 Tailored Revenue Calculations
- Customize your revenue logic to match your specific business rules (e.g., excluding wholesale discounts or refunds). This metric definition will persist throughout all of your Daasity data models and downstream metrics that include the [Revenue] or [Orders] metric (ex: Avg Order Value (AOV), Returning Customer Revenue).
- UI allows you to quickly toggle inclusion/exclusion of discounts, refunds, and credits.
- Default: [Net Sales]
📦 Define Your Valid Orders
- Set your own criteria for "valid orders" to ensure your analytics align perfectly with your business practices.
- Easily configure logic to exclude subscription, duplicate, or canceled orders directly in the interface.
- Default: Excludes all special cases (gift-card only, fraudulent, free, cancelled and voided orders), add any of these back in using the UI.
🚀 Empowering Merchant Control
- No more costly or time-consuming customizations.
- Gain immediate control and clarity over critical business metrics.
This lays the groundwork for future advanced analytics features, ensuring your insights are always accurate, impactful, and fully aligned with how your business operates.
Where to find it:
In the Daasity app, navigate to:
Data → Digital Analytics →
Revenue Metric
Data → Digital Analytics →
Valid Order Metric
We’ve updated the naming conventions for several analytics Explores across Omni, Marketing, Ecommerce, Retail, and Retailer Portals—not just to keep you on your toes, but to make our platform easier to use, more consistent, and ready for what's next.
These changes create a cleaner foundation for upcoming AI-powered features and enhanced analytics experiences. Each new name improves clarity while aligning with our long-term roadmap, including enriched metadata, standardized metric definitions, and improved contextual insights.
Here’s a complete list of updated Explore names:
Omni
- Omnichannel Weekly Sales → Company Performance(360-degree view, filtered to owned-brand and non-duplicative markets.)
- Omnichannel Weekly Sales → Omnichannel Sales(Detailed, product-level insights across all channels.)
Marketing
- Order & Order Line Revenue → Ecommerce Orders & Revenue (by Order Date)
- Vendor-Reported Marketing Performance → Marketing Ad Performance
- Email & SMS Campaign Performance Details → Email & SMS Performance
- Marketing Attribution → Marketing Attribution
Ecommerce
- Daily Plan to Actual → Forecast vs Actual: Ecommerce
- Customer Flags & Info → Customer Analysis
- LTV Time Series → Customer LTV & Repurchase
- Customer Segments - Historical → Customer Segment Performance
- Current Inventory Level → Ecommerce Inventory
- Product Page → PDP Performance
- Product Affinity → Product Affinity
- Shopping Stage → Shopping Funnel
- Subscriber Monthly Churn Rates → Subscription Churn
- Traffic → Traffic
- Customer Retention Performance MTD → Customer Segment Performance (MTD)
- Transactional Sales Report → Ecommerce Orders & Revenue (by Transaction Date)
- Product Repurchase Rates → Product Repurchase Rates
- Subscription Churn Time Series → Subscription Churn by Tenure
- Subscribers → Subscription Customer Details
- Subscription Future Charges → Subscription Forecast
- Subscription Shipment Series → Subscription Shipment Lifecycle
- Site Search - Detail → Algolia Search
- Amazon Business Reports - By Day → Amazon Business Reports - Daily Summary
- Reviews and Orders → Yotpo Reviews and Orders
Retail (Unified Data Models)
- URMS → Retail Promotional ROI Analysis(Unified syndicated retail and POS sources aggregated to the market-level, with baseline and promotional lift metrics, merchandising conditions designed for analyzing promotional efficiency and comparing different tactics across markets and products, including competitors..)
- URMS → Retail Brand & Category Performance(Unified syndicated retail data, advanced competitive insights.)
- URS → Retail Store Performance(Store-level sales from POS and wholesale data.)
- Retailer Sales - Costco Circana → Costco (Circana)
Retail (Syndicated Data)
- Retail-Market Sales - Latest Period (Circana) → Circana - Aggregated
- Retail-Market Sales - Weekly (Circana) → Circana - Weekly
- Retail-Market Sales - Latest Period (Nielsen) → Nielsen - Aggregated
- Retail-Market Sales - Weekly (Nielsen) → Nielsen - Weekly
- Retail-Market Sales - Latest Period (SPINS) → SPINS - Aggregated
- Retail-Market Sales - Weekly (SPINS) → SPINS - Weekly
Retailer (POS)
- Retailer Sales - Amazon Vendor Central → Amazon Vendor Central
- Retailer Sales - Sephora Portal → Sephora
- Retailer Sephora Inventory → Sephora Inventory
- Retailer Sales - Sephora EDI → Sephora Store Performance
- Retailer Sales - ULTA → ULTA
- Retailer ULTA Inventory → ULTA Inventory
- Retailer Sales - Ulta EDI → ULTA Store Performance
- Retailer Sales - Whole Foods → Whole Foods
For any questions or support, please us at support@daasity.com.
Warm regards,
The Daasity Team
Released: May 28, 2025
Overview
Issue:
The last_month field in the drp.calendar table is currently returning values from the same month of the previous year instead of the previous month of the current year for the previous_month category.Solution:
Update the logic for the previous_month category to correctly reference the previous calendar month within the current year in the drp.calendar table. This will ensure accurate time-based categorizations for reporting and analysis.Released: May 27, 2025.
Overview
Issue:
The Marketing Attribution explore currently returns data for only the most recent 30 days. Historical data outside this window is largely missing (NULL values), with only occasional records populated.Solution:
Implement logic to accurately associate orders with a rolling 30-day update list. Update the logic in both dm_stg.mkt_order_revenue_attribution and dm_mkt.fct_vendor_level_performance to support incremental updates, focusing only on the most recent 30-day period.This will ensure consistent and complete attribution data going forward.
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