Navigating the Algorithmic Attribution Landscape: A Comprehensive Handbook

Algorithmic Attribution (AA) is one of the latest methods that marketers have to evaluate and optimize the performance of their advertising channels. AA maximizes the return on each penny spent by helping marketers improve their investments.

While algorithmic attribution comes with numerous advantages however, not all companies are qualified. Not all have access to Google Analytics 360 or Premium accounts, which make the use of algorithmic attribution available.

The Advantages of Algorithmic Attribution

Algorithmic attribution (or Attribute Evaluation Optimization or AAE) is an effective, data-driven method for evaluating and optimizing marketing channels. It helps marketers identify the channels that drive results while maximizing media expenditure across different channels.

Algorithmic Attribution Models (AAMs) are created with Machine Learning and can be continuously updated and improved for greater accuracy. They can be tailored to new marketing strategies and product offerings, all the while learning from new sources of information.

Marketers who employ algorithmic attribution experience higher rate of conversion and greater return on their advertising budget. Being able to quickly adapt to changing trends in the market while staying pace with competitors' evolving strategies makes optimizing real-time information easy for marketers.

Algorithmic Attribution is also a tool to help marketers identify material that generates conversion and can help prioritize marketing initiatives that generate the highest revenue while reducing those that don't.

The Drawbacks Of Algorithmic Attribution

Algorithmic Attribution, or AA is a contemporary method for attribution of marketing activities. It involves the use of machine learning and advanced statistical models to measure the marketing elements that affect the customer journey.

This information allows marketers to better assess the effectiveness of their campaigns, identify factors that increase conversion rates and allocate budgets more efficiently.

But, the algorithmic process is complex and requires access to large datasets that come from multiple sources. This causes numerous organizations to be unable to implement this kind of analysis.

One common reason for this is that a company may not have enough data, or the technology needed to mine the data effectively.

Solution: A modern, data warehouse on the cloud serves as an unifying source of truth for all marketing information. This allows for faster insights that are more accurate, higher relevancy, and more accurate results when it comes to attribution.

The Advantages of Last-Click Attribution

The attribution model for last clicks has rapidly been able to become one of the commonly utilized attribution methods. It allows all credit for conversions to return to the previous ad or keyword that contributed to the conversion, making the setup process easy for marketers while not necessitating any kind of interpretation on their part.

But, this model of attribution isn't a complete representation of customer journey. It doesn't take into account marketing activities prior to conversions, as a hurdle which can be expensive in terms lost conversions.

Today, there are more powerful models for attribution that can give you a more complete picture of the buyer's journey, and help you identify the channels and touchpoints that are more successful at making customers convert. These models cover linear attribution, time decay and data-driven.

The drawbacks of Last Click Attribution

The last-click model is among of the most well-known attribution models for marketing. It is perfect for marketers who wish to quickly determine which channels are the most critical for conversions. However, its use should be considered with care prior to the implementation.

Last-click attribution is a marketing technique that allows marketers to only credit the final point of engagement with a customer before conversion. This could result in untrue and inaccurate performance metrics.

The first approach to attribution technology of clicks gives customers a reward for the initial marketing contact prior to their conversion.

This strategy is great on a small-scale, but it could be misleading if you're trying to improve your marketing campaigns and demonstrate how valuable they are to all those who are involved.

Since this approach only takes into account conversions caused by one marketing touchpoint - meaning it misses important information regarding the brand awareness campaign's effectiveness.