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Scenario

From monthly report to the next move

A scenario where the monthly report doesn't stop at aggregation — it moves through to the next move. An AI agent pulls together Shopify, ad, inventory, and CS data, then drafts anomaly detection, cause hypotheses, and improvement proposals. Prioritization and the final recommendation to the client stay with the account manager.

Updated: 2026-07-11

01

Input

  • Shopify order and sales data
  • Ad platform reports
  • Inventory data
  • Customer support history
02

What accrues in the knowledge base

  • Per-client product characteristics and margin structure
  • Tactics that are off-limits for that client
  • A record of past wins and losses
03

What the AI agent does

  • Aggregate the data and flag anomalies
  • Draft cause hypotheses
  • Prepare improvement proposals and explanation drafts
04

Where a person approves

  • Prioritization
  • The final business call
  • The final proposal sent to the client
Flow diagram for the EC operations use case: order, ad, and inventory data flow in, the AI drafts anomaly detection and improvement proposals, and a person approves prioritization and the final proposal before action is taken.

Projected outcomes

約60%

月次レポート作成の工数削減

Illustrative

当日中

改善提案の提示速度

Illustrative

The figures above are general industry benchmarks, not measurements from a specific client engagement. Actual results vary by workflow.

FAQ

Are these real client results?+

No — this is an illustrative use case to show how the engagement could work for an EC operations business. The figures are general industry benchmarks, not our own measured results. Named case studies will be published as client permission is obtained.

Does the AI act on tactics by itself?+

No. The agent goes as far as aggregation, anomaly detection, and drafting improvement proposals; budget allocation, discount and inventory calls, and the proposal to the client are approved by a person. We draw the line per workflow between what runs automatically and what needs sign-off.

I handle several clients — do their data get mixed?+

No. Each client’s product characteristics, margins, prohibited tactics, and past wins and losses live in a separate knowledge base, so adding accounts never leaks client A’s policy into client B’s work.

We don't sell the same setup to every client — we design it around your judgment criteria and the tools you already use.

Consult on LINE
  1. 01Add A&A on LINE
  2. 02A short intake chat
  3. 03A&A organizes the requirements
  4. 04A meeting only if needed