Assortment Planning for Specialty on Looker, built for e-commerce
Your online and offline data live in different worlds. Ward detects specialty assortment movement in your Looker data in time to act, with what caused it and a recommended action attached.
How a specialty Head of E-Com runs assortment on Looker / Looker Studio
A Specialty Retail operator is tracking 5,000+ SKUs throughout boutiques. High-consideration purchases, curated assortments, and customer lifetime value. Ward tracks the metrics that matter for margin-rich retail.
Your online and offline data live in different worlds. Ward hands you daily cards scoped to e-commerce decision-making.
Assortment Planning is a insight card type Ward runs continuously. Ward analyzes sell-through by store cluster to recommend which SKUs to add, drop, or reallocate.
How it runs. Ward clusters stores by demographic, traffic, and sales patterns, then measures SKU performance against cluster benchmarks.
Getting the data in. Ward can query Looker via API or connect directly to the underlying database. Either way, Ward monitors while your team browses.
What it does
- SKU rationalization recommendations
- Whitespace opportunity detection
- Planogram optimization inputs
- Store cluster segmentation
Chat
Ask anything. Ward routes to the right agent and returns cited answers.
I pulled traffic against conversion by hour for the four flagships. Traffic is fine. The gap is coverage and depth.
| Signal | Finding |
|---|---|
traffic_conversion | Conversion 18.4% vs. 23.1% chain, all of the gap in 12–2p and 5–7p |
labor.coverage | One associate on the floor through both peaks at 3 of 4 doors |
inventory.depth | Top 20 styles at 1.4 units per size, walk-away rate +9% |
Recommend: add floor coverage to both peak windows, deepen the top 20 styles to three per size at the flagships, and route the walk-away list to clienteling.
traffic_conversion…
Reporting
Pinned views built from saved data-lake queries. Every number re-derivable from its SQL.
| Model | Horizon | MAPE |
|---|---|---|
holt_winters | 4wk | 4.1% |
arima_sarimax | 13wk | 8.9% |
gbm_demand | 1wk | 2.1% |
bayes_hier | new store | 11.4% |
Sources
Connect external systems to the data lake.
| Name | Type | Last sync |
|---|---|---|
shopify_orders_daily | import | 2m ago |
lightspeed_store_sales | import | 2m ago |
netsuite_inventory_snapshot | import | 14m ago |
retail_customer_ltv | import | 1h ago |
retail_traffic_conversion | import | 1h ago |
retail_clienteling_log | import | 1h ago |
retail_ga4_website_daily | import | 1h ago |
Policies
Browse and manage Cedar access policies for your tenant.
| Policy ID | Effect | Resources |
|---|---|---|
ops-read-default | permit | Model::* |
crm-read-ltv | permit | Model::"customer_ltv" |
associate-pii-blocked | forbid | Model::"customer_pii" |
merch-read-assortment | permit | Model::"sales_by_tier" |
Why Assortment matters for Specialty retail
In specialty, curation is the product, adding the wrong item dilutes the brand. Ward quantifies the curatorial instinct by scoring which items reinforce the store's point of view through customer fit and companion purchase patterns, and which are dilutive.
What Ward has eyes on.
Stock what sells. Cut what doesn't. Ward runs the model continuously rather than on a reporting cycle, which is why a finding lands the morning the pattern starts instead of at the end of the period.
Ward watches 5,000+ SKUs throughout your boutiques, at the store-category level rather than the chain roll-up. The metrics under watch include CLV, conversion rate, units per transaction. A roll-up hides a single-store problem inside a healthy average, which is how assortment curation stays invisible for a quarter.
The connection to Looker / Looker Studio is read-only and runs on your schedule. Ward pulls from looker API for query results, underlying database (direct), and the rest of the feed, then combines it with external context your BI does not carry: weather, local events, competitor pricing.
At the metric level. Ward tracks assortment coherence, customer-fit scoring, incremental contribution beyond existing assortment, and curatorial dilution risk, the danger of adding items that weaken brand positioning.
Why this combination
is its own problem.
Assortment Planning needs looker API for query results and underlying database (direct) at minimum. Looker / Looker Studio carries both, at the grain the model needs. That is the whole integration story: no middleware, no staging warehouse, no custom extract.
- 01 Customer-fit scoring requires loyalty data many specialty chains under-utilize; without segment-level signal, brand coherence becomes a guess.
- 02 Assortment additions get evaluated on standalone projected margin without modeling brand-coherence dilution, wrong-customer-segment items can damage long-term equity even when they sell well short-term.
Benchmarks. Specialty assortment-coherence-aware planning typically delivers 15-30% higher full-price sell-through on new-item additions and reduces end-of-season markdown by 200-400 bps.
What the first 90 days
actually look like.
-
01
Week 1: read-only connection
Ward connects to Looker / Looker Studio with read-only credentials and begins ingesting looker API for query results and underlying database (direct). No config changes on your side. First cards arrive within 48 hours.
-
02
Weeks 2 to 3: calibration
Baselines stabilize per store and per category. Ward stops flagging normal variance and starts flagging exceptions. This is the window where the false positive rate drops sharply.
-
03
Weeks 4 to 12: steady state
Ward delivers daily cards every morning, each with the driver and a recommended action. Volume settles at a level a single person can read over coffee. The measure of success is not how many daily cards arrive, it is how many get acted on.
How Ward connects to Looker / Looker Studio
Ward does not replace Looker. Ward watches the same data Looker visualizes and proactively alerts when something changes. Your dashboards stay. Ward adds intelligence.
Setup: Ward can query Looker via API or connect directly to the underlying database. Either way, Ward monitors while your team browses.
Data Ward reads from Looker
Impact metrics with Looker
Data lake enrichment
Ward enriches Looker data with: Looker query results, Underlying database, Weather & events, Competitor data, Customer segments
Your online and offline data live in different worlds.
- ×Nobody can see one inventory position across every channel
- ×Online promo performance is measured separately from in-store
- ×Customer behavior data is siloed by channel
- ×BOPIS/BORIS operational complexity is growing unchecked
- ×Digital marketing attribution stops at the click
- ✓Unified insight cards across online and in-store channels
- ✓Cross-channel promo effectiveness with true attribution
- ✓Customer journey tracking across digital and physical touchpoints
- ✓BOPIS fulfillment performance monitoring with exception cards
- ✓Full-funnel marketing attribution to in-store conversion
Retailers with unified omnichannel data see 30% higher lifetime value per customer. Source: Harvard Business Review
Specialty KPI impact
Frequently asked questions
Ward analyzes sell-through by store cluster to recommend which SKUs to add, drop, or reallocate. For Specialty retail specifically, Ward monitors 5,000+ SKUs across your boutiques and delivers automated insight cards with root cause analysis and recommended actions.
Ward tracks CLV, Conversion rate, Units per transaction, Repeat purchase rate, Sell-through by tier at the store-category level. Ward clusters stores by demographic, traffic, and sales patterns, then measures SKU performance against cluster benchmarks.
Ward can query Looker via API or connect directly to the underlying database. Either way, Ward monitors while your team browses. Data points include: Looker API for query results, Underlying database (direct), LookML model metadata.
Yes. Ward reads Looker data and combines it with contextual signals (weather, events, demographics) to generate Specialty-specific insight cards. No custom development required.
Your online and offline data live in different worlds. Ward solves this with automated insight cards: Unified insight cards across online and in-store channels. Cross-channel promo effectiveness with true attribution. Customer journey tracking across digital and physical touchpoints.
Ward delivers daily insight cards covering CLV, Conversion rate, Units per transaction, tailored for E-Commerce decision-making. Each card includes what changed, why it matters, and what to do next.
Ward tracks assortment coherence, customer-fit scoring, incremental contribution beyond existing assortment, and curatorial dilution risk, the danger of adding items that weaken brand positioning.
A buyer evaluates 60 new SKUs for the fall assortment. Ward scores each on customer fit, basket affinity, and margin contribution after displacement. It separates high-coherence items from those that score well on margin but would attract the wrong customer segment. The buyer selects the high-coherence group and sees meaningfully higher sell-through than prior season additions.
First insight cards arrive within 48 hours of data connection. Ward needs approximately 2 weeks to establish stable baselines for your specific operation.
No. Ward sits on top of your existing stack. It is the proactive intelligence layer that watches your data continuously and delivers insight cards, so your team acts on findings instead of hunting for them.
Related solutions
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Root causes, not just alerts. See it on your data.
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