Summary
AI Recommendations reads your shipment data every day and every week and tells your team what changed, what probably caused it and what to do about it, broken down by carrier, destination country and shipment band. The day starts with the picture already assembled instead of with hours of pulling data.Who it’s for
Logistics and operations teams who spend the first hours of the day working out what happened yesterday, and leadership who only spot trends at the monthly review. Customer service and marketing teams use it for notification engagement, where a slow decline is caught while it is still small.Key benefits
- It arrives without being asked. Insights are generated on a schedule you set, so the daily and weekly read is waiting before the morning stand-up.
- Every insight ends in a next step. Where the data is clear, the insight recommends an action. Where it is ambiguous, it says so and lists what to check first.
- A number is never shown on its own. Each metric is read against the previous day, the same day last week, the 7-day average and the 28-day average, above a 56-day trend.
- It names what dominates. Breakdowns by carrier, country and band size each contributor, so effort goes to the bottleneck rather than to whatever moved most.
- It uses your own definition of late. The SLA breach rate metric is calculated from your Performance Aspirations rules, not a generic transit time.
How it works
AI Recommendations needs no rules, alerts or reports to be set up first. It reads the shipment data already in Perform.AI and produces insights at the next scheduled run after it is switched on. The one exception is the SLA breach rate metric, which stays empty until Performance Aspirations rules exist.Daily and weekly insights
Data periods are evaluated in UTC. You can set the trigger time in your local timezone, but a period such as “24 November” refers to the UTC date.
What an insight contains
A metric opens with a plain summary of what moved and what probably caused it, then carries several separate insights. Each insight has a headline stating the finding, the figures beneath it and what to do. The shape follows the evidence rather than a fixed template:- Finding and analysis. What moved, and what that movement is consistent with.
- Possible causes. The competing explanations, where more than one fits the data.
- Key questions to explore. What the team has to answer before the cause is known.
- Implications. What follows if the reading holds.
- Recommendation. The action to take, where the evidence supports one.
- Recommended diagnostic steps. An ordered checklist to run first, where it does not.
Comparisons, trends and breakdowns
- Scorecards. The evaluation day against the same day last week, and the last 7 days against the previous 7, each with its own change indicator. Some metrics carry a 28-day view as well.
- Historical chart. A 56-day trend with figures on hover.
- Breakdowns. By carrier, by destination country with each country’s share of volume, and by the bands that matter to the metric, for instance shipments delivered within one day against those taking more than five. Breakdowns go down to the individual notification configuration or carrier service.
Metrics covered
Metrics are organised into tabs by stage of the e-commerce journey: All Experiences, Post-Purchase, Checkout, Logistics and Returns. A badge on each tab shows how many insights it holds. Today the metrics are Post-Purchase metrics; the other tabs fill as metrics are added. Hover a metric name for its definition.
A metric only appears when there is enough data for the period. Notification metrics are absent on a day when no notifications were sent, and a thin account may show fewer than ten.
Homepage summary
The portal homepage shows a daily AI summary with up to five critical items, each linking straight to the insight behind it. A date toggle opens the summaries from the last 14 days.Feedback
Each insight carries thumbs up and thumbs down buttons and an optional text box. Feedback goes directly to the Perform.AI product team.Set up in the portal
Go to AI Decision Intelligence > AI Recommendations. Insights appear at the next scheduled run after the feature is switched on; no integration work is needed.- Select the Settings icon in the top-right corner of the page.
- Choose the Timezone used for scheduling.
- Set the time for Daily Insights and the day and time for Weekly Insights.
- Save. The new schedule applies from the next run.
Changing the trigger time does not regenerate an insight that has already been produced for that day or week. The change applies to future runs only.