Marketing Operations / E-Commerce Coordinator — House of Dank, Madison Heights, Michigan.
Rather than describe how I would approach promotion accuracy, I built the tooling I would actually use in the role. Three working systems, live below.
I have spent my career as the person responsible for what customers actually see: catalogues between 1,000 and 14,000+ SKUs, pricing, inventory, promotions, seasonal campaigns, metadata and the cross-functional QA that keeps all of it truthful. The products were tobacco and textiles rather than cannabis, and the compliance rules differ — but the failure modes are identical. A stale price, a promotion that outlives its funding, two offers colliding on one SKU, a menu that disagrees with the register.
Left column is the job. Middle is what I have actually done. Right is where you can see it working right now, rather than take my word for it.
| What the role requires | My directly relevant experience | See it live |
|---|---|---|
| Build, test and quality-check promotions in Dutchie | Built and QA'd promotional pricing across Shopify and WordPress storefronts for multi-location retail. I am new to Dutchie specifically — so I built a working promotion builder with a live price preview and a test-before-publish gate to show exactly how I would work inside it. | Promotion Builder → |
| Maintain listings, menu images, pricing, categories, promotional tags and store-specific settings | Day-to-day ownership of catalogues from 1,000 to 14,000+ SKUs — product data, imagery, categorisation, pricing and per-location settings across several brands at once. | Product Catalog → |
| Manage Weedmaps and Leafly menus | Managed the same catalogue published across multiple channels and kept them consistent. Third-party menus drift; the only reliable fix is a scheduled comparison against the system of record. | Menu Consistency → |
| Validate every deal against deal sheets, vendor agreements, inventory, dates and compliance | This is the core of what I do. I built a sixteen-point validation engine that checks a deal sheet against product data, live inventory, signed vendor agreements, margin policy and a compliance rulebook — and blocks the build until it is clean. | QA Workbook → |
| Flag aged, slow-moving and overstocked SKUs | Routinely used sell-through and days-on-hand to decide what to promote, bundle or clear. Promotional effort belongs on inventory that needs help, not on what already sells. | Inventory watch-list → |
| Coordinate with buying and inventory teams | Worked between buying, warehouse and storefront across multiple brands. Every validation failure in my tooling is auto-routed to the team that owns the fix, because "this is wrong" without an owner is just noise. | QA & Approvals → |
| Build and test email and SMS campaigns | Built and shipped seasonal campaigns end to end — copy, assets, segmentation and testing. Campaign copy is a compliance surface, so I check wording, opt-out language and purchase limits before anything sends. | Campaign Preview → |
| Run Monday.com for QA and approvals | Documented and ran repeatable QA and approval processes across teams. I have not used Monday.com specifically; I have designed the exact board — columns, statuses, automations and views — that I would stand up in week one. | Board design — walked through live |
| Produce weekly accuracy reports | Built recurring reporting for leadership. My weekly report writes itself from the validation data, so the numbers can never drift from what actually happened. | Weekly Report → |
| Prevent pricing errors and menu discrepancies before they go live | The whole point. On twenty sample promotions, the tooling below catches twenty-two hard errors and eight warnings — including a deal sheet quoting a $39.99 regular price on a product the system prices at $34.99. | Validation Engine → |
All data is fictional and created for this demonstration. The logic is not — the workbook and the app run the same sixteen checks and produce identical results down to the dollar.
A Google Sheet that takes a raw deal sheet and runs sixteen automated checks against product data, inventory, vendor agreements, margin policy and compliance rules. Red blocks the build, yellow holds it, green clears it.
A working app covering the whole cycle: catalogue with store-specific settings, a promotion builder with a live price preview and Test Mode, a Dutchie-vs-Weedmaps-vs-Leafly consistency view, a QA approval board and a campaign preview.
The intake, QA, approval and documentation process behind the tools — who submits, what gets checked, who signs off, and what gets recorded. Designed as a Monday.com board so approvals leave an audit trail instead of living in inboxes.
Every tool on this page opens in a browser and works in real time. Break something in it and watch the checks fire — that is the fastest way to see how I think about operational quality.
Built by Mousa Batarseh for the House of Dank Marketing Operations / E-Commerce Coordinator interview, August 2026. All product, brand, vendor, pricing and inventory data shown in the linked tools is fictional and was created solely for this demonstration. These are not House of Dank systems and contain no House of Dank data.