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Conversion Attribution – How to Use Online Budgets Efficiently

Those who take a closer look at the allocation of advertising budgets will notice that an isolated examination of individual marketing channels is inefficient. Multimedia use is increasing and consumers interact with brands and companies in various ways, creating numerous contact points. This is why you should never evaluate individual advertising efforts as effective or ineffective. It is much more important to look at the big picture and to analyze how the channels are being used by the consumers in the different phases of the purchasing process.


How does each channel contribute to the conversion goal?

How does each channel contribute to the conversion goal?

Far-reaching display campaigns can be used to call attention to new products. Specific search queries, on the other hand, come often at the end of a purchasing process – and under the “last cookie wins” principle more conversions are attributed to them. However, due to the increasing interaction between the different digital channels this method does not adequately evaluate the effectiveness and the efficiency of the marketing measures.

The conversion attribution, currently much discussed in online marketing, can help you solve this problem. It determines to what percentage an advertising channel contributed to the conversion. By using alternative attribution models advertisers can find out which channels initiated the purchase and which channels profited from it. With this knowledge advertising efforts can be directed more precisely than ever towards those channels, which are most frequently used by the target group. Ideally, this way you can find out how much each channel contributes to the conversion goal. You can depict different attribution scenarios in order to detect which advertising channel reaches the user in which phase of their purchasing decision process.

The probably best-known form of conversion attribution is the “last cookie wins” model: if a user clicks on several advertising mediums from different advertising channels before he decides to purchase the product, the conversion will only be attributed to the last advertising medium he or she clicked on. Despite many critical voices this model is still widely used since it can be easily calculated and is very comprehensible. Many publishers criticise this allocation method for rewarding only absorbing channels such as coupon portals and retargeting – informative portals calling the user’s attention to new products get a raw deal.

If you want to identify the channels that initiated the conversion it is worth displaying the click path with the “first cookie wins” model. This means even if the buyer clicked on several advertising mediums, the conversion will only be attributed to the first click.

These two opposing attribution possibilities allow you to claim among others “first cookie wins” or “last cookie wins” channels. If the conversion shares for the advertising mediums are very different between each method, it only underlines the importance of the interplay between the respective channels. For instance, banner advertising is given much attribution in the “first cookie wins” model but only a few in the “last cookie wins” model, which is an indication that this measure creates mainly awareness but it depends on absorbing channels such as SEA brand or retargeting. The analyses are therefore good indicators to help learn more about the advertising effect of one’s marketing measures.

Overall, advertisers should look at their marketing efforts as a whole and calculate different attribution scenarios in order to find out more about their customer’s behavior. Channels initially regarded as ineffective might reveal themselves to be very valuable in calling the user’s attention to the offer.

In our next blog entry we will use an example of the different allocation scenarios and illustrate the effects it has on the evaluation of each channel’s effectiveness. This results in particular in a different cost-per-order for each channel, depending on the selected attribution scenario, which represents the basis for online budget management.

1 Comment

  1. […] have already mentioned that the last cookie counts method falls far too short when it comes to evaluating the […]

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