Suppliers
United States
Anodot
Overview
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this profile, please contact us at team@iotone.com
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Anodot |
| United States | |
| Ashburn | |
| 2014 | |
| Private | |
| $10-100m | |
| 51 - 200 | |
| Open website |
IoT Snapshot
Technology Stack
Case Studies
Number of Case Studies6
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Uprise’s “Monitoring on Steroids” with Anodot
Uprise, an ad-tech company, uses a 'continuous delivery' approach for its software development, pushing around 20 new software releases into production each day. Each new release can affect the platform’s performance, making it crucial to monitor results in a timely fashion to determine if the new release should be kept in production or rolled back. The ad tech environment itself has many moving parts, each of which is a potential point of failure. These can include server issues, changes at the ad affiliates, introduction of ad blocking software, or even fraud. Whenever a problem occurs, isolating the source can require complex, time-consuming analysis. Identifying issues in the first place is also tricky, since network traffic behaves seasonally. With the traffic naturally reaching various peaks and valleys throughout the day, noticing a 20% loss or gain at any given point is next to impossible. |
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Anodot Finds “All the Anomalies Fit to Print” for Media Giant PMC
Penske Media Corporation (PMC) was facing significant delays in discovering important incidents in their active, online business. The company was using Google Analytics’ alerting function to track business incidents but found it inadequate due to the millions of users across dozens of household-name and professional publications. The initial use case for PMC was to start using Anodot to track its Google Analytics activity, for example, to identify anomalous behavior in impressions or click-through rates for advertising units. |
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Affiliate Marketing Company Uses Anodot to Proactively Manage 1000S of Fast-Moving Accounts
The company, an affiliate network with over 200,000 members, was struggling to monitor business and technical incidents that were impacting their bottom line. The dynamic nature of their marketplace and the extensive metrics they had to track made it difficult to monitor changes in real-time. Factors such as changes in search engine algorithms and third-party trends, as well as changes in affiliate accounts, could significantly impact their business. The tools they were using required them to set thresholds manually, which allowed time for incidents to escalate. |
