Review product performance

Creating products and handling orders are only part of daily operations. Managers also ask whether orders are rising or falling, which dates perform best, which channels drive sales, and whether those changes justify an adjustment.

TMS already contains the order data, but an ad hoc question may not exist in a fixed report. An operator may have to export a spreadsheet, filter fields, or wait for technical support. By the time the result is ready, the best moment to adjust inventory or channels may have passed.

Now the operator can give T-Agent the question, time range, and calculation rules:

Analyze orders over the last 7 days, show a line chart, and tell me which day had the most orders.

Processed in 28s

Using skill tyaio-data-analysis

Running TMS data analysis

Order trend

Last 7 days · Example data

Total orders

443

T-Agent

There were 443 valid, paid orders over these 7 days.

Day 7 had the most orders: 84.
Day 1 had the fewest: 42.
Orders increased overall, with dips on days 4 and 6.

These figures show changes in order volume; they do not establish the causes.

Would you like me to compare order counts by primary channel to see which sold the most?

Yes, compare sales by channel using order counts.

Processed in 19s

Using skill tyaio-data-analysis

Analyzing TMS data by primary order channel

Orders by primary channel

Last 7 days · Example data

Total orders

443

Grouped by primary order channel · Channel names anonymized

T-Agent

Here are valid, paid orders by primary channel over the last 7 days:

Channel A：176 orders, accounting for 39.7%
Channel B：104 orders, accounting for 23.5%
Channel C：72 orders, accounting for 16.3%
Channel D：55 orders, accounting for 12.4%
Channel E：36 orders, accounting for 8.1%

Channel A had the most orders: 176, or 39.7% of the total.

T-Agent analyzes the TMS data that the current account is permitted to access, explains the calculation, and creates a chart in the conversation. The operator can follow up by channel, product, or date without exporting another spreadsheet.

The data can show what changed in order volume and channel mix. It cannot by itself prove why the change happened. Campaigns, advertising, weather, pricing, and inventory still require business context. T-Agent separates confirmed data from causes that need further review.

The goal is not another report. The operator can decide whether to increase inventory, change a sales channel, or inspect errors and refunds. The data from those actions then enters the next review cycle.

Tyaio · Updated 2026-09-20