Using a more accurate attribution model helps you to improve the quality of your data. Having better quality data helps you make better investment decisions. Being able to make better investment decisions means better returns on your investments.

Let’s solidify this with examples:

You decide to scale back ad spend on broad keywords that are not recorded as having driven any conversions (because you’re using a last-click attribution model). However, those broad keywords were actually driving the initial awareness into your conversion funnel that then turned into a conversion through a branded ad. By making the decision to curb spending on the broad keyword no recorded conversion set – which is completely logical – without considering your attribution model (and contribution to conversion funnel) you have just decided to reduce significantly how much money you can make. Worse still, if you don’t understand attribution modelling you will stare at the screen, scratching your head trying to understand why your performance has nosedived.

One more and then let’s move on:

You (or your agency) decide to reduce bids on mobile because the data you are looking at in your interface is saying your cost per conversion from desktop is way, way, way better. This is a completely logical conclusion but, the majority of those desktop conversions are actually coming from people who found you on their phones and then used their desktops to complete the transaction. If you reduce mobile bids you’re going to be losing lots and lots of conversions.

A better understanding of the data you are looking at (and its limitations) makes for better decisions and means objectives are more likely to be achieved.

Author Israr Sarwar

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