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Get a QuoteEvery metric on your ecommerce platform is tracked. But right now, spotting an anomaly means staring at dashboards. Redefine's artificial intelligence reads every signal, flags every deviation, and forecasts every trend before your team has had coffee.
Anomaly detection, 30/60/90-day forecasting, and cohort discovery are all native to your reporting layer. No export to a business intelligence tool. No waiting for an analyst.


Numbers count up on entry. Anomaly alerts pulse in real time. Forecasts update as new orders flow in. Every metric is live.
Revenue Today
$0
Orders
0
Cart Abandonment
AI Alert0%
Average Order Value
$0
Revenue Forecast: 90 Days
Artificial Intelligence Anomaly Alerts
3 activeCart abandonment spiked +18 percentage points in last 2 hours
Checkout page, mobile segment
Product information management completeness dropped below 82%
Category: Electronics, 214 SKUs affected
Marketplace listing errors up 34%
Amazon channel, last 6 hours
Revenue per visitor +9.3%, no action needed
All channels, trending up 5 days
Artificial Intelligence Cohort Discovery
Auto-segmentedRevenue by Channel: Today
versus 30-day average
The artificial intelligence monitors every metric on every channel continuously. When any signal deviates from expected range, it fires an alert with an explanation, not just a number. You know what happened and why.

Every key metric shows a 30, 60, and 90-day AI-predicted trajectory alongside actuals. Revenue, orders, product information management completeness, marketplace listings, all get a confidence-banded forecast. No separate forecasting tool. No manual model.

Artificial intelligence identifies high-value customer and account segments automatically, names them based on behavioral patterns, and surfaces the actions most likely to grow each cohort. No manual segmentation. No analyst required.
Commerce, product information management, marketplace, operations, and program store data feed a single reporting layer. No fragmented dashboards. One view of the whole platform.
Executive, operations, and channel dashboards each surface the metrics that matter for that role. No noise. No irrelevant rows. Every stakeholder sees their signal, not the whole firehose.
Set thresholds and schedules, or let artificial intelligence decide when something is worth interrupting you for. Alerts fire over Slack, email, or in-app. Reports land in inboxes before standup.
Every artificial intelligence reporting capability runs on the same unified data layer that powers your operations. No extract, transform, load pipeline. No manual exports. No third-party business intelligence contract.
Day 1
Unified data ingestion
Commerce, product information management, marketplace, operations, and program store data all stream into a single reporting layer automatically.
Day 2
Baseline modeling
Artificial intelligence builds seasonal baselines and expected ranges for every metric using your historical commerce data, not a generic template.
Day 3
Forecast and cohort activation
Forecasting tracks go live on every dashboard. Cohort discovery runs its first segmentation pass and names identified groups.
Ongoing
Continuous artificial intelligence refinement
The artificial intelligence model improves with every week of new data. Alert thresholds tighten, forecasts sharpen, and cohort definitions self-correct.
Step 1: Data Ingestion
No extract, transform, load pipeline required. All data is already unified in the platform layer.

Client
CCTV Security Pros
Security / RetailGlobal provider of security camera systems for residential and commercial customers. Operates on BigCommerce with multi-channel digital marketing and analytics at scale.
Problem
Marketing performance was difficult to track across channels. Budget allocation was based on instinct rather than attribution data. Revenue growth was inconsistent and hard to attribute to specific campaigns.
Solution
Unified Google Analytics 4 analytics and attribution setup across paid search, social, email, and marketplace channels. Continuous performance-driven optimization enabled by accurate cross-channel reporting and return on investment tracking.
Result
Revenue scaled through data-driven campaign execution. Enhanced attribution and reporting enabled more efficient budget allocation, improved return on investment, and sustainable global growth across digital channels.
Point-solution artificial intelligence analytics sit outside your commerce platform. They can only report what you export to them. Redefine artificial intelligence is native to the same layer that processes every order, every listing, every product information management change. That is a different class of reporting.
| Capability | Typical artificial intelligence analytics tool | Redefine Artificial Intelligence Reporting |
|---|---|---|
| Native to the commerce platform | ||
| Anomaly detection with explanation | Flags only, no context | |
| 30/60/90-day forecast on every metric | Revenue only, manual setup | |
| Automatic cohort discovery and naming | ||
| Cross-module data (product information management, order management, marketplace) | ||
| No separate business intelligence tool required | Requires export and business intelligence licence |
Managing revenue across storefront, marketplace, and business-to-business portal means dozens of dashboards. Artificial intelligence unifies every signal and flags the anomalies that matter, so your team stops tab-switching.
Account-level cohort discovery and pipeline forecasting help business-to-business teams identify which accounts are growing, which are at churn risk, and where to focus next quarter's energy.
Large catalogs mean product information management completeness, listing health, and content scoring all drift over time. Artificial intelligence tracking across all those dimensions catches gaps before they affect search ranking or conversion.
When you don't have a full analytics team, artificial intelligence reporting does the monitoring work for you. It watches everything, surfaces what matters, and gives your small team the leverage of a much larger one.
Cross-border operations generate signals in every region simultaneously. Artificial intelligence reporting tracks regional revenue anomalies, channel discrepancies, and conversion shifts across all geographies in one view.
Leadership needs clean, role-specific views of the numbers that drive decisions. Artificial intelligence generates executive-ready dashboards automatically, with forecasts attached to every metric they care about.
Not sure if this fits your situation? Tell us your situation and we'll be straight with you.
Other analytics tools bolt on to your platform and pull data via application programming interface. Redefine artificial intelligence reporting is the platform's own reporting layer, fed by every module in real time. That means richer signals, faster anomaly detection, and forecasts that factor in every dimension, not just revenue.

Full analytics module overview, executive dashboards, and cross-platform reporting.
Order-level, stock-keeping-unit-level, and channel-level commerce data feeding the artificial intelligence layer.
Role-specific dashboards with artificial intelligence forecasts attached to every headline metric.
Warehouse, fulfillment, and service-level agreement data contributing to anomaly detection baselines.
Amazon, eBay, and other channel data tracked in real time by artificial intelligence alert monitoring.
Approval times, service-level agreement compliance, and form completion rates visible in artificial intelligence dashboards.
No. Artificial intelligence reporting in Redefine is native to the same platform that processes your orders, product information management updates, marketplace listings, and operations data. There is no extract, transform, load pipeline and no separate business intelligence tool. Everything runs on the data that already exists in the platform layer, which means anomaly detection and forecasting update in real time as your commerce operations run.
The artificial intelligence baseline models start producing meaningful thresholds within 30 to 90 days of data, depending on your transaction volume. Lower-volume operations may take longer to establish statistically reliable thresholds, but the system will still surface hard deviations from the moment it activates. Forecasting accuracy improves with each additional month of data and self-corrects with seasonal patterns as they recur.
Artificial intelligence monitoring covers every metric in the platform, including revenue, order volume, cart abandonment, average order value, product information management completeness scores, marketplace listing health, fulfillment service-level agreements, approval times, and more. Because the artificial intelligence layer reads from the unified platform data, it tracks every dimension that any module produces, not just the front-end sales numbers. This is what makes it fundamentally different from a point-solution analytics tool that can only see what you export to it.
Customer relationship management and email tool segments are typically rule-based, defined manually using filters you set. Artificial intelligence cohort discovery identifies patterns in behavioral data that no rule would have found, then names the cohorts and tracks their performance over time. You don't define the segments in advance. The artificial intelligence finds them, labels them, and tells you which cohorts are growing, shrinking, or showing churn signals. This is especially powerful for business-to-business account-level analysis where purchase behavior is complex and account health signals are scattered across multiple data points.
Alert volume is configurable at both the threshold level and the delivery channel level. You can set minimum deviation thresholds before an alert fires, choose which metrics get artificial intelligence monitoring, and decide whether alerts go to Slack, email, in-app, or a combination. The artificial intelligence model also reduces false positive rates over time as it learns your normal variance patterns. Most teams configure alerts so that only genuine anomalies worth acting on interrupt them, with a daily digest covering minor deviations.
Submit your brief and we will show you what anomaly detection, forecasting, and cohort discovery look like running on your own commerce platform. No commitment. No pitch.
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Stop checking dashboards manually. Stop waiting for analysts. Let artificial intelligence handle anomaly detection, forecasting, and cohort discovery so your team can focus on decisions, not data gathering.