Last click attribution is the most widely used attribution method. The model ascribes 100% of the conversion credit to the last ad served before a conversion. But if you are using this solely to set your advertising budget, it may be skewing marketing spend and making your investment suboptimal. There are a number of reasons for this.
Last click recognises consumers who are just before they convert. These are people who are in the lower part of your sales funnel. They would have heard about your brand, researched other products, review others compared features. All of these touch points are not recognised in the last click model. But they certainly played a part in the conversion journey.
Long sales journey or instore conversion
Last click attribution works well for fast moving consumer goods that are transacted online. B2B business or a considered purchase, which involved research and some level of presales contact, would not be a good fit. Instore conversions, preceded by a digital research/shopping phase, will not be recognised by the last click.
The model can be gamed
This simple last-touch approach today is easily gamed and lends itself to manipulation. Here is how. The trick is to buy the cheapest ad, even if it is below the fold, at the bottom of a page or even hidden in an iframe, which is never seen. Quantity at a low cost, is more important than quality, as the last ad loaded & served will get the last view credit. A detailed explanation could be found on this Quantcast article.
Attribution only looked at the people who converted. Relying on the last click to explain the customer buying behaviour, you will never be able to understand those who did not buy. These may be the people who have seen your ads, viewed your video, visited your page multiple times, but never signup, selected items in cart. This could be 90% of your target audience.
The insight from this group is as important as the converters. This potentially tells you the reasons for not converting, the friction in the buying journey, the pattern that points to how you could refine your campaign or offer.
Is there a better way?
All models are just an approximation of real-world events. We could refine a model (with a hybrid of first/last, position, linear, time decay, or any combination of this. At the end of the day, it is a varying degree of usefulness.
A better way to approach this is to use the actual observations of digital touch points (Impressions & Views), across the different channels. Some refer to this as DDA – Data Driven Attribution. This is fundamentally a bottom up approach and technology is used to track and analyse customers’ digital journey.
Two more reasons
By collecting behaviour data at lowest ‘atomic’ level, it provides two important down important benefits.
Segments: define segment that is unique to your business
First party data: integrating this with your ecommerce platform, CRM and/or sales data to form a richer profile of your prospects and customers.
If you are finding limits to your growth, ask yourself this question: “are we rewarding all the channels that brings in the sales?”