Early Detection of Revenue-Impacting Events for Business Operations Teams
Business operations teams at online retailers understand that it only takes a few minutes of downtime or operational hiccups to cost them significant amounts of revenue. Volumes are too high and environments too complex to catch anomalies using yesterday's rule-based approaches. Businesses don’t have time to be deluged with false alerts or glued to dashboards. Learning about problems from monthly reports or angry users leaves you troubleshooting after the fact and lamenting lost revenue.
Prelert automates analysis of real-time transaction data such as orders per minute, carts created per minute, invoices per hour, or deposits per hour, so that revenue-impacting events can be found and fixed quickly. Prelert’s behavioral analytics as applied to retail order metrics provides one of the most critical functions of advanced analytics, which is near-real-time anomaly detection on key business performance metrics. This enables early detection of events that could cause a negative impact across your entire business. For businesses running thousands, millions or even billions of dollars’ worth of transactions every day, the impact of this can’t be overstated.
For business operations teams:
global eCommerce entities
any business with real-time revenue-related data
Detect issues like:
unusually high rate of abandoned carts for a time of day
anomalously low completed checkouts for a day of week
operational or process-related errors and externally-caused problems
With Prelert, retail business operations teams can:
Detect Incidents Early
Protect key revenue streams by detecting issues early.
Find deviations in expected behavior that can indicate costly problems.
Slash troubleshooting times and resource usage up to 90 percent, freeing subject matter experts to focus on creating value for the business.
Automate Data Analysis
Automatically baseline normal behaviors using the power of unsupervised machine learning.
Accurately model periodic behaviors such as daily and weekly order cycles.
Quickly adapt to changing patterns in your data.
Realize Faster Root Cause Discovery
Accurately identify critical problems in near-real-time, with minimal false positives.
Find Anomalies and Link them together to build the story behind incidents using Prelert’s advanced Insights features (currently available in our AD App for Splunk).
Quickly spot operational issues, process-related issues, or even issues caused by external factors.
We’ve helped companies from consumer telecommunications providers to online dating sites to major online retailers catch operational problems before they wreak havoc, saving them millions of dollars in the process.
Easy and Accurate Retail Order Analytics
Automate data analysis, eliminate manual effort, and reduce human error.