AI for
ecommerce.
Ecommerce is where many interconnected systems meet at once — inventory and working capital, merchandising, marketplaces, paid media, lifecycle marketing, service, supply chain, and returns. It is one of our deepest areas of specialization.
Everything here is downstream of something else.
A merchandising decision becomes a demand signal, which becomes an inventory position, which becomes a cash requirement, which becomes a marketing constraint. Tools that only see their own slice cannot act on that.
Working capital is on the line
Inventory decisions commit cash weeks before revenue arrives, against lead times that drift.
Catalog complexity compounds
Attributes, variants, and channel requirements multiply faster than a team can maintain by hand.
Channels disagree
Storefront, marketplaces, and wholesale each hold part of the truth about demand.
Spend outruns supply
Paid media can accelerate a SKU straight into a stockout if nothing connects the two.
Service volume follows operations
Most contact volume is caused upstream — by shipping, stock, or catalog accuracy.
Unit economics are measurable
Margin, contribution, and landed cost are knowable, which makes good decisions provable.
The work worth
building around.
Not a menu to buy from. These are the places where connected systems most often remove work, improve a decision, or keep the operation moving.
- 01
Leadership & Analytics
A daily operating picture assembled across storefront, marketplaces, finance, and inventory rather than rebuilt in a spreadsheet.
- 02
Finance & FP&A
Coding, reconciliation, contribution margin, and cash requirements tied to committed purchasing.
- 03
Purchasing
Reorder recommendations and draft purchase orders prepared from demand, coverage, and supplier lead time — queued for approval.
- 04
Inventory & Supply Chain
Coverage, velocity, shortfall risk, inbound status, and landed cost monitored against current demand and supplier lead times.
- 05
Vendor Management
Supplier performance and lead-time drift tracked with evidence instead of memory.
- 06
Merchandising
Assortment gaps, cannibalization, and catalog health reviewed on a cadence.
- 07
Pricing & Promotions
Competitive monitoring and promotion review inside margin guardrails, with pricing changes approved by a person.
- 08
Product Catalog / PIM
Attribute enrichment and content consistency maintained at catalog scale across channels.
- 09
Amazon & Marketplaces
Listing health, case handling, and channel economics kept under watch.
- 10
Paid Media
Spend pacing informed by coverage, capacity, and contribution margin — not impressions alone.
- 11
Email, SMS & Lifecycle
Segmentation and campaign preparation grounded in real purchase and behavior data.
- 12
Customer Service
Responses drafted from order, account, and policy data; humans keep the difficult ones.
- 13
Retention & Loyalty
Cohort behavior, churn signals, and lifecycle interventions kept in view.
- 14
Returns & Reverse Logistics
Return reasons, disposition, and cost recovery handled as a workflow rather than a queue.
Spend moves. Everything downstream knows.
One chain of awareness across marketing, ecommerce, inventory, purchasing, and finance. Each step is informed by the step before it, and the commitment of money stays with a person.
- 01Marketing
Paid media spend increases on a product line
Observed - 02Ecommerce
SKU sales velocity accelerates
Observed - 03Inventory
Coverage falls below supplier lead time
Observed - 04AI Environment
Stockout risk identified and quantified
Reasoned - 05AI Environment
Reorder quantity calculated from demand and lead time
Reasoned - 06AI Environment
Draft purchase order prepared with supplier terms attached
Reasoned - 07Purchasing
Approval request received with the reasoning shown
Human authority - 08Finance
Cash requirement visible before the commitment is made
Human authority - 09Marketing
Warned about the inventory constraint before spend compounds it
Human authority - 10AI Environment
Decision, inputs, and outcome written back and logged
Reasoned
One illustrative workflow, not a product. The architecture behind it — how systems, context, and approvals fit together.
What stays
with a person.
AI prepares, calculates, and recommends. Committing money, changing prices, and speaking for the brand stay with the people accountable for them.
- Purchase orders and any commitment of working capital
- Price changes and promotional structure
- Marketplace and supplier communications with commercial consequence
- Customer-facing exceptions, goodwill, and escalations
- Catalog changes that affect how a product is represented or sold
How Big Timber works
We don't start with
a product.
We learn how the business works, then identify where connected AI creates useful capacity — and where it does not.
See the engagement model →Discover
We learn how the operation actually runs — systems, handoffs, and where work stalls.
Design
We map where connected AI creates capacity, and what stays with a person.
Build
Integrations, context, workflows, approvals, and logging built into your environment.
Train & Maintain
The team is brought with it, and the environment keeps an owner afterwards.
Find where AI fits in yours.
A working session against your actual operation — storefront, marketplaces, inventory, purchasing, and finance. We will tell you what is worth building first, and what is not worth building at all.