Three numbers this brand runs on. None of them exist in a standard dashboard.

One sneaker, many identities

A conceptual brand built on Indian textile traditions. The team built the brand. I built the dashboard.

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Left Quarter PanelRight Quarter PanelVamp / Toe Overlay

The brand around it

Brand identity, storefront, packaging and visual language were developed collaboratively.

The assumed setup

• One online storeNo physical retail
• One warehouseEverything ships from here
• Small teamNo analyst, no ops team
• One operatorRuns the whole system alone

Everything below follows from the fourth card. One person, no analyst. So the dashboard had to answer, not just report.

One person runs everything

No ops team. No analyst. One person keeps orders moving and stock honest.

RahulE-commerce Operations Manager

Role

E-commerce operations manager. One online store, one warehouse, a small team.

Goal

Keep the online business running smoothly, and act quickly on anything that needs attention.

Pain point

Information is spread across different operational areas, making it difficult to know what needs attention first.

Works across

• Orders
• Inventory
• Customers
• Performance

Their daily loop

1. 01Check the business
2. 02Spot an issue
3. 03Understand why
4. 04Take action

The dashboard had to fit inside this loop.

A patch is a product and a part

A patch sells on its own and works as half of a bundle. A normal dashboard counts each sale, but cannot tell you whether the modular idea is working.

What Svaroots actually sold

• Base sneakerSold on its own
• Textile patchSold on its own
• 
  BundleSneaker + patch, sold together

The same patch sits in card two and card three. Sell one on its own, and a bundle quietly disappears.

Questions this created

1. 01Are customers actually using the customization system?Answered by Customization Rate.
2. 02How many patches are being sold per sneaker?Answered by Patch-to-Sneaker Ratio.
3. 03How many complete bundles can we fulfil?Answered by Bundle Readiness.
4. 04Which inventory is becoming dead stock?Answered by standard reports.

I stopped assuming and opened Shopify

I had assumed a generic dashboard could not run this. Rather than keep asserting it, I set up a Shopify store and checked.

Competitive audit · Run inside a live Shopify store

Shopify runs the bundle calculation. It never reports it.

Searching the report library for “bundle” returns four reports. All four are Sales. None is Inventory.

Where Shopify stops

The evidence · Shopify’s own report library

What the audit returned, metric by metric

• Patch-to-sneaker ratioNot reported

  No default report expresses a ratio between two product categories.

• Customisation rateNot reported

  No default report on attach rate. Custom exploration only.

• Bundle readinessCalculated, never shown

  Shopify computes it to gate the storefront. No inventory report shows it.

• Dead stockMeasured, not managed

  Shopify reports slow stock well. It has no reason, no status and no threshold alert.

Verified 5 Sept 2026 in a live Shopify store. I had expected to build the dead-stock measurement myself. I did not need to. I did not test Zoho, Katana or third-party bundle apps, so I make no claim about them.

Three numbers I had to add

Standard metrics covered most of this business, including how to spot slow stock. The modular half needed three that no report provides.

Concepts I had to learn

• Customer Lifetime Value
• VIP & Dormant Customers
• Inventory Runway
• Return Rate
• Revenue
• Product Performance

Metrics specific to Svaroots

• 2.4Patch-to-Sneaker RatioPatches sold per sneaker.
• 68%Customization RateHow actively customers use the modular option.
• 195Bundle ReadinessHow many complete pairs can actually ship.

That moved the dashboard from reporting sales to showing whether the business model was actually working.

Patch-to-sneaker ratio · Analytics

Customization rate · Operational insights

Stock you own is not stock you can sell

Sneakers, patches and bundles all sell separately. So every patch sold on its own quietly reduces how many bundles are left to ship.

What a bundle actually needs

Four items in stock. One bundle can ship.

And the other patches keep selling on their own, so this number moves without anyone touching a bundle. That is why the operator needs it as a live view, not a checkout rule.

Bundle readiness · Inventory

1. 1Sneakers and patches are counted separately.
2. 2Can Ship Today is the smaller of the two counts.
3. 3IND 9 holds 62 patches but only 10 sneakers, so 10 pairs.

Every chart ends in a button

A dashboard that only reports leaves the hard part to the operator. Every insight here carries its action.

Data → insight → action, on one screen

1. 1
   Data

   The chart shows how big the problem is.

2. 2
   Insight

   The line underneath says whether it needs attention.

3. 3
   Action

   One button opens the SKUs themselves, already grouped.

Measured vs managed · Dead stock

What Shopify gives you

Shopify measures it. That is where it stops.

Products by sell-through rate shows how quickly stock is selling. Its dimensions are product title, variant and SKU. You get a number and nothing to do with it: no reason it stopped selling, no status, no action.

Below is what I built instead.

1. 1Reason comes first: why it stopped selling.
2. 2Status is the triage state, waiting for a decision.
3. 3The response sits on the same row as the reason.

Three things I got wrong first

Each fix came from a specific failure.

Iteration 01 · One long page became tabs

1. V1Everything stacked verticallyKPIs, charts, insights and actions on a single page.
2. →
3. ProblemToo much scrolling, competing informationReviewed the layout with a peer experienced in data visualization.
4. →
5. V2Tabular + tab-based structureRelated information accessible within the same workspace.

More information doesn’t mean better visibility.

From scrolling to structure

Iteration 02 · Fewer visible actions

Before

After

Tables exposed every action at once. I cut to two, with the rest in an overflow.

Iteration 03 · The dashboard speaks first

Everything in one workspace

Six areas, organised around the decisions one person actually makes.

The six areas, as built

This isn't a screenshot. It's the working dashboard, live. Click the tabs, open the tables and try the actions.

I built it, not just designed it

Seven Figma screens are not seven working screens. Building it forced the details.

From design to working prototype

• Navigation
• Date ranges
• Tables
• Actions
• Dashboard states
• Interactions

1. Figma
2. →
3. Figma Make
4. →
5. GitHub
6. →
7. Vercel

What I’d test with real operators

The tooling question is answered. The human one is not. Nothing here has met a real warehouse.

What I’d do next

1. 01Speak with e-commerce operators and warehouse teams
2. 02How they actually monitor inventory
3. 03How they define dead stock
4. 04How they evaluate performance and decide what needs immediate action
5. 05Whether Bundle Readiness and Customization Rate are useful day to day
6. 06Check whether a third-party bundle app already surfaces component readiness
7. 07Pressure-test the dead-stock threshold with someone who has traded a bundle catalogue

I started with “What should I put on the dashboard?” I ended with “What decision should this information help someone make?”

That shift, from displaying data to designing for decisions, was the biggest learning from the project.