Application traffic is a key component to understanding how much usage or demand a digital asset such as an application receives. Estimating traffic is often a combination of art and science due to a lack of ground-truth traffic data, which only the application owner and the infrastructure providers they rely on have access to.
We combine first-party traffic measurement data collected from our sensor network with data from 3rd party data partners to generate a comprehensive view into global application traffic for every company.
Intricately Traffic Value is an absolute scaled measure of requests over time (aka traffic demand) as seen by Intricately.
Intricately Traffic Value (ITV) Interpretation
Intricately Traffic Value (ITV) represents demand. The real-world traffic metric with the closest proximity to ITV is requests over time.
It is generated by normalizing our first-party traffic measurements with traffic data we receive from 3rd party data partners.
We normalize the traffic data so that it can be aggregated using our entity maps. This approach allows us to maintain a real-time view into the relative traffic of a company, their product deployments, networks, and data center deployments.
Traffic is an absolute measure of digital demand and is designed to represent the enormous (and growing) scale of the internet. Traffic is measured at the application level. We then report traffic across the following categories:
Company – Traffic at the company level represents the digital demand for a company’s applications. All the domains, websites and mobile applications operated by a company are included in this value.
Product Deployment – Traffic at the Product Deployment level represents digital demand supported by one of the company’s Products.
Product Category – Traffic at the Product Category level represents digital demand supported by a Product Category which the company has one or more Products deployed in.
Point of Presence (PoP) – Traffic at the PoP level represents digital demand for the applications hosted at the PoP. All applications deployed in the Point of Presence are included.
Product Deployment Point of Presence – Traffic at the Product Deployment Points of Presence level represents the digital demand supported by the Point of Presence.
Sorting and Prioritization – For example, you can sort companies by traffic to understand their relative rates of demand.
Comparing – For example, if Company A has a traffic value of 10 and Company B has a traffic value of 100, Company B has 10 times the demand of Company A.
Our network monitors global application traffic and can report on total demand and provide detail at the individual product deployment level. This enables you to asses how much demand a company has from a specific country and further segment usage by a given provider (i.e AWS vs Azure).
Our sensor network collects global traffic data on over 80% of companies with high-traffic digital properties. Think of these as web or mobile applications with an Alexa rank of at least 200,000.
Application Latency is the response times (in milliseconds) an application exhibits in a specific location. For example, one could measure the response times for ecommerce.nike.com in Japan and report that, on average, the application's latency was 35ms.
Because our system monitors the physical data center(s) an application is hosted in, we can model the latency experience for users from multiple locations around the world.
Our system monitors traffic at the country-level. The table below shows the demand, supply, latency and traffic volumes.
In the first row, Nike has 5% of its traffic coming from China, served by data centers in Japan, with an average latency of 70ms. In the 2nd row, Nike has 16% of its traffic coming from the UK, served by data centers in Germany, with an average latency of 25ms.
Our system monitors a company's product traffic at the country-level. The table below shows product demand, supply, and traffic volumes.
In the first row, Nike has 1% of its traffic coming from Australia, served by an Amazon EC2 region in Singapore. This traffic experiences 55ms of latency on average. In the 2nd row, Nike has 2% of its traffic coming from Mexico, served by an Amazon EC2 region in Mexico. Because both this traffic demand and supply occur in the same region, a latency of 0 ms is attributed to it.
Updated 6 months ago