Mastering Algorithmic Attribution: The Essential Guide

Algorithmic Attribution is a powerful method that lets marketers analyze and improve the effectiveness of marketing channels. AA helps marketers increase their ROI through smarter investment decisions for every dollar spent.

While algorithmic attribution can provide a variety of benefits for businesses, not every organization qualifies. Not every organization has access to the Google Analytics 360/Premium, which is a premium account that allows algorithmsic attributes.

The Advantages of Algorithmic Attribution

Algorithmic Attribution (or Attribute Evaluation and Optimization AAE, also known as AAE, for short) is an effective and data-driven method of evaluating and optimizing channels for marketing. It helps marketers identify which channels are most effective at driving conversions, while also optimizing their budget for all media channels.

Algorithmic Attribution Models (AAMs) are designed using Machine Learning and can be continuously updated and improved to increase accuracy. The models can be modified to the changing strategies of marketing and product offerings, as well as learning from new sources of data.

Marketers using algorithmic attributions have seen greater rate of conversion, and higher return on their advertising budget. Marketers can benefit from real-time information by rapidly adapting to changes in market trends, and keeping pace with the changing strategies of competitors.

Algorithmic Attribution is an additional tool that can aid marketers in identifying the content that is most effective and prioritize marketing efforts which generate the most revenue while decreasing those that aren't.

The disadvantages of Algorithmic Attribution

Algorithmic Attribution, or AA, is a modern approach for attributing marketing activities. It involves the use of machine learning and sophisticated mathematical models to assess the amount of marketing influences on the customer's journey.

This information allows marketers to be able to evaluate the efficacy of their marketing campaigns, pinpoint key factors to increase conversion, and distribute budgets in a more efficient way.

The complexity of algorithmic attribution, as well as the necessity of accessing large data sets from multiple sources makes it challenging for a lot of organizations to use this kind of analysis.

A common reason is a company not having enough data or the tools required to effectively mine the data.

Solution: A cloud-based integrated data warehouse can be the only source of absolute truth when it comes to marketing data. This makes it easier to gain faster insights as well as greater relevance and more accurate results when it comes to attribution.

The Benefits of Last Click Attribution

The model for attribution based on last click has grown to be the most popular model for attribution. This model permits credit to be given to the latest advertisement, keyword, or campaign that resulted in the conversion. It is easy to implement and doesn't need any data interpretation from marketers.

However, this attribution model isn't a complete representation of customer journey. It doesn't consider any marketing activities prior to conversion, and this could be costly in terms of lost conversions.

Now there are more robust models of attribution that could to give you a complete picture of the buyer journey, and help you identify which channels and points of contact have the best chance of making customers convert. These models include time decay, linear and data-driven.

The disadvantages of last-click attributing

The model of the last-click is one of the most well-known attribution models in marketing. It is perfect for marketers that want to quickly identify which channels are most important to convert. Its use should, however be evaluated carefully prior to it is implemented.

Last click attribution technology permits marketers to credit only the last point of customer interaction prior to conversion, producing inaccurate and biased performance metrics.

The first approach to attribution for clicks rewards customers for their initial communication with the marketing department prior to conversion.

On a smaller scale, this may be helpful however it can become confusing when trying to maximize campaigns or prove value to those involved.

This approach is flawed as it only looks at conversions that are caused by one marketing touchpoint. Therefore, it misses out on important information about the effectiveness of your brand awareness campaigns.