As mobile traffic across the network grew at a disproportionate rate to mobile sales, the industry had a new challenge to be tackle: how to identify and match those users that view publisher websites on a different device to the one they use to make their purchase?

The inability to recognise the true value of publishers’ traffic is a clear threat to the affiliate marketing channel.

In the UK on average between 4% and 15% of transactions are missed by performance marketing tracking tools because these technologies are based on ‘single-device’ tracking, which incredibly is still the norm amongst the vast majority of the industry.

With more than 60% of online adults in the UK using more than one device, a single-device tracking tool is now just no longer a feasible or practical way of rewarding any online marketing activity, especially one which is only paying out when transactions are made.

Advertisers now focus their marketing strategies on providing a consistent, effective message to the same customer accessing their business across a variety of platforms.

If affiliate marketing is to meet the needs of advertisers in terms of cross-platform marketing, then the right tracking needs to be in place to ensure publishers can be properly incentivised. 

Matching the same user accurately across multiple devices is the biggest hurdle in cross device tracking.

There are two methods for cross device matching: deterministic and probabilistic.

Probabilistic

A probabilistic cross-device tracking method collates a number of anonymous data points such as device type, location and operating system, and then uses statistical algorithms to create likely matches between devices.  

Deterministic

A deterministic cross device tracking method uses specific, first party data provided by the user to create links between devices. This is the method commonly used by the likes of Google and Facebook, who rely on users logging in across multiple devices to create cross device linkage.

The cost-per-acquisition model that dominates affiliate marketing means there can be no room for assumptive-based tracking, where sales are awarded based on degrees of probability.

Pros and cons

The industry has to be sure that when a transaction is credited to a publisher a user has interacted with that publisher’s links, even if that interaction takes place across multiple devices.

This means deterministic cross device tracking is the only viable choice, in order to provide a robust and sustainable solution.

The probabilistic method contains too many uncertainties around user matching to be effective for tracking sales in affiliate marketing.

For example, it may assume a user connection between a phone and a tablet which both access the same WiFi hotspot at the same time each day.

However, these devices could belong to two colleagues who meet up at the same coffee shop each morning, rather than the same user.

Although companies using probabilistic cross device tracking claim accuracy levels of anywhere between 60% and 90%, the main problem with any form of probabilistic tracking is that it might create an incorrect connection between devices, and when advertisers and publishers rely on sales to track accurately this might begin to seriously undermine affiliate marketing’s publisher model.

There are some nuances with how matching is done under the probabilistic method, with some providers combining probabilistic data with third party deterministic data to improve match rates, however there are still no guarantees on accuracy.

Of course, deterministic also has its challenges, and the major one is scale.

Because deterministic cross device tracking relies on definitive user matches it means less user matches are made. The key is getting enough confirmed device and user relationships stored up to ensure the trackability of all the cross device sales being made on the network. 

While deterministic cross device solutions have accuracy on their side, they have often been called walled garden solutions because the technology can only be used inside the ecosystem of the data owner.

For example, Facebook’s login data is hugely powerful for cross device tracking, but is only useful for Facebook advertising.

However, because affiliate networks partner with a number of different publishers, the deterministic method does not have the same restrictions. In fact because all publishers can benefit from cross device technology in the same way, as more user matches are made the more accurate the solution becomes. 

In conclusion

Introducing deterministic cross device tracking is a significant step for the affiliate marketing industry, not just because it means more sales can be credited to the channel.

The reality is for a cost-per-acquisition model, it is necessary to ensure the channel’s long-term viability.