The only way too look at match rates scientifically, in our experience, is look at accuracy rates as well, which is dependent on the technique used.
Convertro has developed its own proprietary cross-device solution that leverages our pool of unique Convertro user IDs observed online across 160+ brands over the past 4.5 years. Specifically, in particular for brands that rely on user logins, we are able to identify different cookies and devices that belong to the same user with 97% matching accuracy. This means we can match almost 100% of devices for some brands. Other brands that by nature do not have great ways to identify customers (e.g. CPG, store-heavy retail) need to settle for 30% or even less.
Before developing our own solution, we evaluated several 3rd party solutions, but none of them yielded the level of accuracy of our technology. Many vendors, for example, use a statistical method to match devices whose accuracy is too low to be useful for user-level attribution purposes. Considering that we track more than 5.4 billions unique device IDs, if we used statistical inference we could probably match 1 billion devices, but with an accuracy rate of less than 50% – you would be better off tossing a coin! Instead, using our tracking-based, binary ID-based reassociation method, we match a lower number of devices overall, but the accuracy is almost perfect and the number is still significant.