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<\/a><\/p>\nIn that scenario, under last touch attribution, the credit is given to the display ad, because this is where the last touch\u00a0occurred.<\/p>\n
The narrative of advertising is that all the touch points before the click are adding value. This makes last click false because it is not capturing the value of those touch-points. In most cases, the last click is a search ad for example. Search is known to be a demand capturing channel not a demand generating channel (search doesn’t increase purchase intent, it merely captures intent that already exists). It makes sense as well that post click benefits search since the company that owns the largest share of search made\u00a0last click \u00a0mainstream (Google).<\/p>\n
So why is last click, a model so clearly flawed, still in use and even the most common method of attribution?<\/p>\n
Let’s have a look at the alternatives.<\/p>\n
Multi touch attribution<\/h2>\n
The long promised alternative has been\u00a0multi-touch attribution<\/a>\u00a0(MTA). With the walled gardens (Facebook and google) restricting tracking on their properties though, MTA is for the time being a pipe dream. Although MTA vendors are a dime a dozen and trade publications\u00a0pump out\u00a0fluff piece<\/a>\u00a0after\u00a0fluff piece\u00a0<\/a>after\u00a0fluff piece<\/a>\u00a0about MTA\u00a0we’re far from it. With GDPR coming up, for the EU I suspect MTA is going to get even more difficult. That’s not to say MTA is not possible today. It’s just very expensive and you won’t get a complete picture of the attribution chain. In my chart above, how would you track TV? So for all your efforts with MTA you’ll end up with a flawed answer, kind of the same as you would on last click. The noise generated by MTA, the difficult to identify correlation vs causation, the cost and the resources needed make this approach ill-advised for all but the most sophisticated advertisers.<\/p>\n Some would say incrementality measurement is the answer. Well, it is AN answer. Switch the ad off and see if your sales\u00a0dip or not. I like this approach but not everyone can afford to do this and it’s very hard to get learnings from it. There’s alternative incrementality measurement methodologies but very few are transparent (Facebook and Google have “uplift” measurement but it’s not verified by third parties. And given Facebook’s tendency to get basic math wrong<\/a> and Google’s tendency to do anything it can to keep spend within its walls<\/a>, one can be forgiven for being cynical).<\/p>\n Accurate incrementality testing today comes at the expense of market opportunity – you stop spending and you willingly miss out on opportunity to see what would have happened if you had spent or you spend some money on PSAs. There’s some fringe ways to test incrementality in different ways but the hard comparison is still the cleanest and most widely available.<\/p>\n Some would say blockchain will solve the attribution problem. Those folks tend to also say blockchain will solve every other problem.\u00a0Until Google or Facebook outright adopts a blockchain based attribution system I don’t see that happening and it’s against both Facebook and Google’s interest to do this because one of their USPs is the data they own. Blockchain threatens to democratize that. As long as Google and Facebook have primacy in the digital world, they won’t open up.<\/p>\n So basically, once you look at the mainstream alternatives to last click (and please comment if I’m missing anything, I’m writing this article quite late at night), you’ll see that while the logic behind these attribution methods is sound, none of them really fully works. Kind of like last click but at least last click is simple.<\/p>\nIncrementality measurement<\/h2>\n
Blockchain<\/h2>\n
In summary<\/h2>\n