Attribution and last click models
For years, attribution has been a subject of great debate, but until now we have been missing a core piece of this. Without the ability to look at how consumers move across devices, how can we expect to attribute sales effectively?
With the channel premised on a last click CPA, we have seen the rise of publishers who are effective at attracting and converting the final click in a purchase path; cashback and voucher code site have been incredibly successful at doing so.
More recently newer business models have emerged to further target and re-target consumers to encourage conversion.
With all the clamour to receive the final click, have we forgotten about those publishers that are present in the customer journey prior to the final click?
While the ‘last click wins’ model is one that has worked for a number of years, it lacks flexibility. It isn’t necessarily something that needs to be moved away from as there is a lot of merit behind it, but advertisers need to be more flexible in their reward structure.
The telecoms, insurance and gaming sectors have always been open to experiment with additional payment metrics such as CPC models or paying tenancies to relevant sites with significant volumes of visitors.
With business intelligence tools in place, advertisers are easily able to identify those publishers that are heavily involved in customer journeys but are not converting. Once these have been identified, advertisers should be encouraged to think creatively about how the reward publishers for these ‘assists’, either across all publishers or focusing on a smaller group of identified ‘influencers’.
By offering these additional payments, advertisers are able to negotiate increased exposure across publisher sites. One of the elements that is neglected when paying out for transactions, is the additional branding opportunities and the halo effect of non-converting traffic. There are certain channels that are paid regardless of converting the sale – the additional branding opportunities the affiliate channel offers are often ignored.
Take the below advertiser as an example. Using programme data it is possible to identify the publishers that have been involved in a number of transactions, but convert less than 70% of these sales.
There is certainly a value in these publishers as it can be argued they have had influence over the conversion. Whether this is by initially providing a review of the product or offering a price comparison on a range of products.
By identifying and optimising these sites it can help them to convert in the future.
Advertisers that have already run trials with ‘payment’ on assist have seen strong results with traffic and sales increasing as a result. One advertiser saw an 85% increase in traffic month on month which resulted in a 25% increase in sales on the previous month.
This data and the tools that power this data also helps advertisers to dispel additional myths. One such common misconception is that incentivised traffic is overwriting affiliate traffic.
While there is some cross over, a typical pattern is for publishers who are the same promotional type to overwrite each other, rather than there being a more complex route to market. It is still the case that the vast majority of sales through cashback sites are single interaction sales, i.e. they are the only affiliate involved in the customer journey.
Members of these sites can typically be more loyal to the cashback site than to the advertisers they promote.
It is important that any ‘influencer’ data produced ties in with so called ‘click path’ data (the route to purchase as outlined above). Reports produced should allow for the identification of publishers that are assisting the customer journey while click path reports provide advertisers greater visibility on the interaction between affiliate sites, e.g. which promotional types are typically overwriting and also who each publisher overwrites or is overwritten by.
Cross channel data
Traditionally we have showcased our data within the affiliate channel and have had to rely upon advertisers sharing their cross channel data with us to see the true cross channel impact.
There is a shift occurring and advertisers are increasingly keen to share additional non-affiliate data with networks to enable additional insights directly from us. It is now possible to appropriately analyse the cross channel influence rather than be restricted to purely affiliate channel data.
While monitoring the influence of publishers across the channel has provided some interesting insights, this ignores the fact that costumer journeys span a number of devices. A typical consumer will own multiple devices and a report by Statista last year indicated that 19% of British people made use of three connected devices.
With such a cross over in device usage, without the ability to track cross device journeys we can never truly understand cross channel customer journeys.
A consumer could research a product on their way to work via a smartphone in the morning, check some additional reviews on their desktop at work, and then finally transact when they are home on a tablet. At present, the influence of the earlier customer journey will be completely ignored.
We have recently launched new tracking that is able to show the user path and this is based on actual (rather than probabilistic) data. By exploring cross device tracking, advertisers can ensure that their publishers are fairly rewarded for the sales they are driving and the value they offer earlier in the path to conversion.
Consider the fact that we have typically seen the channel have short click to conversion lapse times. Is this because we only take into account the final device activity? Will we appreciate that customer journeys may actually be lengthier when we really start to look at cross device data?
We know that smartphones have much poorer conversion rates than tablet and desktop but are we truly considering the role they play as an influencing device?
Rewarding on influence and cross device journeys is in its infancy but this is sure to accelerate throughout the year. As more advertisers start to offer cross device tracking we will really start to understand the role each device plays, from influencing right through to conversion.