Custom attribution models are key

Posted: Jul 25, 2013 in Data, Marketing, Tracking
Tags: , ,

Winner

You’ve spent months working with the data team setting up all of the marketing data feeds for the DMP and now it’s a case of setting the briefs for multi and custom attribution models.

Last click attribution is typically default and the most common. It’s not wrong to only stick to one and if there’s no motivation to work with others, then last click isn’t a bad choice to stick to.

Viewing multi custom attribution models gives you insight into the campaigns which are getting undervalued by contributing more higher up the funnel than lower for example. Off the back of the data, you can then increase targets / goals / CPA accordingly for the relevent campaigns / media buys.

The benefit of using custom attribution models is that you can amend certain exposures / campaigns in order for the output to make more sense in an actionable way eg. remove all banner impressions which did not get viewed, remove brand search clicks, remove remarketing impressions etc.

Firstly the data team will need to setup the 5 key out of the box attribution models:

    • Last interaction
    • Linear
    • First interaction
    • Time decay
    • Position based

    Once built out, within your visulisation tool there should be options to customise the data further eg. remove banners which weren’t in view, remove brand search, remarketing and CRM campaigns which will leave you with insight into the real performance of your prospecting campaigns across different attribution models.

    Google have been attempting attribution modelling over the past few years via DFA. They unfortunately still have a couple of bugs making the tool unusable, but they are still further ahead than any other third party attempting custom attribution modelling on a self sevice basis.

    It will always be difficult for third party companies to successfully deal with attribution because attribution models should be built using the data from the in house DMP, which includes back end customer / revenue / LTV data.

    In order to understand how all of your ad campaigns are really performing and what role they fully play, viewing performance data across multi custom attribution models is key.

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