The last click conundrum: Why relying on traditional attribution models is failing us

The last-click conundrum; why relying on traditional attribution models is failing us

Every website will use an analytics tool to understand where their traffic came  from. Did users arrive after searching a specific keyword in Google? Did they click on an online ad? Did they arrive through an affiliate? The list goes on..

Understanding this is critical in a cross-media world where brands need to know for certain  which of their campaigns or other marketing activities worked and drove traffic to their website, so they can optimally split the budgets between the different media moving forwards.

Every marketer will probably be able to tell which activities drove traffic to their website, but the problem is that their view is incomplete at best and wrong at worst. The reason? Marketers continue to  use attribution models that look at the last click and disregard the entire past journey that led to conversion.

Here’s an example. If a user is exposed to a campaign on email, billboards and TV and then clicks on an online ad, that online click will get 100% of the attribution and the rest of the journey will be disregarded.

This causes brands to make wrong decisions as they have  an incomplete view on what worked and what didn’t. In addition, during ViewersLogic’s own analysis, we  see that the brands that stop their TV campaigns and move their budget online see their online costs soar as users were not ‘prepped’ beforehand to click on the online ad.

So what can be done to solve this problem?

Luckily, single-source data can capture the entire customer journey to purchase and gives weight to each and every advertising exposure,  not just  to the last click.

This way, brands can fully understand which media channel drove their traffic and split their marketing budget in an optimal way.

Furthermore, because single-source data sees all the actions of the user across all websites and ad exposures for all brands, it enables marketers  to see which media worked best for their competitors and assess how they can do better.

Below you can see an example of the real traffic sources for  Airbnb (website + app) – this includes email, Facebook, Google search (organic), Organic (e.g. opened the app or input the URL of the site), Google paid ads, Affiliates, TV and TV brand (e.g. the longer term effect of TV – users who viewed at least 3 ads in the month before visiting Airbnb but did not see any TV ads in the week before).

What does this mean for brands?

In order to manage cross-media campaigns brands MUST go beyond the last-click attribution model and look at the entire journey – anything else will cause brands to distribute their budget in a way that will harm them.