How is attribution bias impacting your brand?

In the digital marketing universe, accurate and fair attribution is essential to ensure that resources are allocated in the most correct and strategic way possible.

However, attribution drift—when credit for a conversion is given to channels or partners that don't develop directly for the result—can harm that allocation.

In many cases, this deviation is driven by unfair competition practices, such as partners seeking to withhold undue commissions or abuse of brand policies.

These errors not only distort data, but they compromise investments and harm relationships with business partners.

In this scenario, it is essential to have specialized solutions that protect your brand and ensure that resources are used in a fair and transparent manner.

That's where Branddi comes in, offering tools that help identify and correct these deviations quickly and effectively, ensuring the integrity and efficiency of your marketing campaigns.

Let's explore more about how to identify and correct these deviations, ensuring that your investments are used effectively and that your brand policies are respected!

What is attribution in digital marketing?

Before understanding what attribution bias is, it's important to understand the concept of attribution in digital marketing.

Briefly, attribution refers to the process of identifying and assigning the value of a conversion or sale to the different points of contact with the customer throughout the buying journey.

That is, it is the method used to determine which channel or marketing action was responsible for influencing the consumer's decision.

According to research from Predicta, 42% of the marketing leaders interviewed stated that they use data-driven methods to measure the success of their strategies, indicating a growing tendency to adopt more accurate and personalized attribution models.

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Attribution types

There are different attribution models used to distribute this amount among the various channels and interactions, among the main ones:

• Last-click attribution: assigns all credit for the conversion to the last touchpoint before the sale. It is the simplest model, but it may fail to recognize the contribution of other channels;
• First-click attribution: gives full credit for the first point of contact with the customer. This model is useful for strategies that aim to generate awareness, but does not take into account the importance of subsequent touches in the journey;
• Linear attribution: distributes credit equally across all customer contact points. This model attempts to provide a more balanced view of how each channel impacts the final decision;
• Position-based attribution: gives more credit to the most important contact points, such as the first and the last, but still recognizes the contribution of intermediaries;
• Data-based attribution: uses historical performance data to determine how value should be distributed across channels, providing a more personalized and accurate view.

For you to understand in a more practical way, let's explore some examples. If a customer sees an advertisement on a social network, clicks on a marketing email, and finally makes a purchase on your site, attribution will help determine which of these channels had the greatest impact on the final purchase decision.

In other words, a company that invests in paid ads on Google and Facebook can use attribution to understand which platform brought the most return on investment, helping to reallocate the budget more effectively.

What is attribution deviation?

Now that we understand the concept of attribution and the different models used in digital marketing, it is essential to understand what attribution deviation is and how it can improve campaign results.

Attribution bias occurs when the value of a conversion or sale is incorrectly attributed to a touchpoint or channel that had no direct impact on the customer's decision.

In other words, it's when attribution doesn't accurately reflect the true contribution of each interaction throughout the buying journey.

This attribution error may be caused by business partners who improperly appropriate commissions or use a brand policy in an unauthorized manner.

By diverting attribution to channels or touchpoints that were not responsible for the conversion, these partners generate unfair competition, hampering strategy efficiency and distorting the distribution of value between channels.

Understanding how to avoid these deviations is critical to ensuring that your resources are allocated correctly and that the integrity of your partnerships is maintained.

Main causes of attribution deviation

In addition to understanding what attribution deviation is, it's also important that you know that it can be caused by a number of factors.

Some of the main causes of attribution deviation include:

Inadequate attribution models

When using an attribution model that doesn't fairly account for all touchpoints, a significant deviation can occur. For example, if the last-click attribution model is adopted, it can ignore previous interactions that were also decisive in the conversion.

Lack of complete or accurate data

The absence of quality data on customer interactions can generate an inaccurate analysis, leading to a deviation in attribution;

Offline or multichannel interactions

When the customer interacts with the brand through multiple channels, including online and offline, the difficulty of effectively tracking all of these interactions can result in attribution bias. This is particularly challenging for companies that lack integration between channels;

Fraud and irregular activities

In some cases, digital fraud can manipulate data, creating significant attribution distortions.

This can occur through practices such as fraudulent clicks, falsification of information, or manipulation of conversion data, which end up redirecting credit to the wrong channel or interaction.

These deviations not only affect the accuracy of strategic decisions, but they also create unfair competition between partners, with direct impacts on marketing budget allocation.

Branddi, specialized in detecting and correcting these distortions, uses advanced technologies to identify fraud and ensure that attribution data faithfully reflects the true contribution of each channel and interaction, offering more effective investment management.

Studies carried out by Amazon Ads team and published on their portal, indicate that incorrect attribution can lead to ill-informed marketing decisions.

We are talking about situations such as increasing the budget for a channel that is not really generating conversions or, on the contrary, cutting resources from channels that are, in fact, effective.

In this context, it is important to have adequate monitoring and attribution solutions, such as those offered by Branddi, that help brands identify and correct deviations.

In this way, ensuring that performance analysis is more accurate and marketing decisions are based on real data.

Impacts of attribution deviation

The impacts of attribution bias on digital marketing are profound and encompass both financial and strategic aspects.

It can distort the view that companies have about the performance of their channels and campaigns, making decisions based on incorrect data.

In addition, when attribution deviation occurs through partners that apply undue commissions or do not use authorized brand policy, it becomes an important factor of unfair competition, hindering the fair distribution of value between marketing channels.

According to a study published in Edufatec Magazine, anomaly detection is an effective strategy for optimizing digital marketing campaigns.

The study also highlights that data analysis and the identification of atypical patterns allow for real-time adjustments, improving campaign performance.

This illustrates how a detailed analysis of attribution data, using more accurate attribution models, can correct distortions and improve the overall performance of marketing actions.

That is, in addition to knowing what attribution deviation is, it is good to know that it causes the main problems:

Inefficient budget allocation

When the most effective channels or strategies don't receive due credit, the budget can be directed to tactics that appear to generate results but are less efficient in practice.

This, in turn, results in wasted resources and limits the company's growth.

Um study published on the Business Wire platform, revealed that 21% of media spending is wasted due to poor data quality, resulting in inaccurate segmentation and loss of customers.

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Wrong strategic decisions

Attribution bias can lead to the underestimation of important channels, such as branding or content marketing, while exaggerating the valuation of direct conversion channels, such as paid campaigns.

This restriction not only compromises the balance and effectiveness of marketing strategies, but also impairs long-term planning.

In the context of unfair competition, attribution bias becomes even more problematic, especially when unfair partners commit undue commissions or use a brand policy in an unauthorized manner.

A clear example of this is when a brand offers a service and its installation, but its partner only sells the service, charging for the installation on their own.

This type of deviation not only distorts the allocation of value between channels, but also generates direct conflict, affecting the competitive balance and harming the brand that follows its correct business practices.

This is a real threat that can directly impact the performance of campaigns and the health of marketing strategies, especially when partners take advantage of the attribution system to obtain undue advantages.

ROI distortion

With inaccurate data, the calculation of return on investment (ROI) is compromised, making it difficult to assess the actual impact of campaigns. This makes it even more necessary to demand expenditures and identify optimization opportunities.

When this deviation is caused by unfair partners, who commit practices such as undue commissions or make unauthorized use of the brand policy, the problem worsens.

These partners manipulate attribution in order to redirect the amount to the wrong channels, affecting the accuracy of ROI calculation and, consequently, affecting the ability to identify which campaigns or channels are actually generating positive results.

This change can create a false impression of performance, making it difficult to make informed decisions and preventing companies from effectively optimizing their strategies.

Loss of growth opportunities

Without properly understanding which channels and efforts are generating results, companies may fail to invest in promising strategies, limiting their reach and potential for expansion in the market.

These impacts reinforce the importance of adopting accurate attribution models and constantly reviewing the metrics used to measure the success of campaigns.

It is in this sense that it is reinforced how a well-founded approach helps to avoid losses and maximize results in digital marketing.

How to identify attribution deviation?

Understanding what attribution deviation is goes beyond knowing that it can occur; it is also essential to recognize how it affects the data and to find ways to identify it.

Deviation is not an obvious problem at first glance, but it can be discovered by analyzing specific signals in campaign data and behavior.

Here, we detail how to identify it and present practical examples for a deeper understanding.

Discrepancies between platforms

The first warning of a possible attribution deviation lies in the differences in data reported by different platforms.

Tools like Google Analytics, Meta Ads, and CRM systems can generate quite different numbers for the same conversions.

These discrepancies indicate that the attribution model used may be exaggerating or underestimating the impact of a specific channel, leading to an inaccurate analysis of the results.

Example:

• Google Analytics may point out that 70% of conversions are caused by paid ads;
• CRM, on the other hand, can attribute 60% of conversions to leads captured by email marketing campaigns.

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These divergences highlight what attribution deviation is, since the attribution model is not taking into account all points of contact throughout the consumer journey.

Did you know that Branddi can be an effective solution to help identify and correct these discrepancies?

Our system ensures that data from all platforms is integrated and interpreted correctly, allowing a more accurate view of the consumer journey and helping your team to make decisions based on real data.

Visit our site and learn more!

Disproportionate results on certain channels

Another indication of attribution deviation occurs when a channel shows results much higher or lower than expected, without changes in the behavior of the campaigns.

This can happen due to an unbalanced attribution between touchpoints, distorting performance analysis and being manipulated by unfair partners.

Let's take a practical example: Imagine that your company invests in paid media, content marketing, and social networks.

If the attribution model is based solely on the last click, unfair partners can independently redirect attribution to channels that had no real impact.

In this case, we are talking about email marketing or other specific contact points, while essential or complementary services (such as the installation of a service, for example) carried out by partners may be excluded from the analysis.

This scenario distorts the allocation of resources, since we ignore the importance of previous contact points and the true contribution of each partner in the conversion process, leading to attribution deviation and compromising planning and marketing decisions.

Inconsistencies in the consumer journey

When performance reports don't reflect the consumer's actual journey, this may indicate that attribution bias is hampering the accuracy of the results.

In many cases, the attribution model used does not take into account the complexity of the interactions on different channels.

Imagine that a consumer may have discovered your brand through an advertisement on Google, searching for more information on social networks and, finally, made a purchase through email marketing.

If the attribution model is considered just the last click, all credit will be given to email marketing, disregarding previous interactions that helped the consumer make their decision.

This type of loss highlights what attribution deviation is in practice, as the model fails to highlight the importance of previous contact points.

What's more, all credit can be given to a participating partner in an unfair manner, who, by manipulating the attribution, improperly redirects the conversion to themselves.

In other words, traffic that was already destined for the main brand ends up being co-opted improperly, hampering the allocation of resources and compromising the performance of the campaigns.

Tests with different attribution models

An efficient way to identify attribution bias is to perform tests with different attribution models.

Different attribution models distribute credit differently across channels, and by comparing the results, you can see which channels are being unfairly favored or overlooked.

Here are some of the most common models:

• Last click: assigns all credit to the final channel, that is, to the last point of contact before the conversion;
• First click: give full credit to the first point of contact with the consumer;
• Linear: distributes credit equally among all channels that participated in the consumer journey;
• Time decay: gives greater weight to the channels closest to the moment of conversion.

By applying these models and comparing the results, you can quickly identify where attribution deviation is occurring, and adjust your strategies to ensure a more accurate and fair credit allocation.

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Count on technology to combat attribution deviation!

To combat attribution deviation and minimize its impacts, it is necessary to adopt both prevention and resolution strategies. Let's explore these approaches:

Prevention: constant monitoring

Track campaign measurements to quickly identify anomalies. Using integrated analysis tools can provide a more accurate view of the sales funnel.

Protecting brand keywords and maintaining transparency with partners helps prevent data distortions and improper attribution practices.

Tools to assist

Analysis tools help identify and correct attribution deviations. Some actions include:

• Continuous monitoring of campaigns;
• Testing of different attribution models;
• Analysis of behavior patterns;
• Detailed performance reports.

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The Role of Technology in Combating Attribution Deviation

Technology has advanced considerably to support the fight against attribution bias, allowing digital campaigns to be monitored more precisely and efficiently.

Automation and the use of artificial intelligence made it possible to detect inconsistencies in attribution data in real time, providing quick adjustments and increasing the effectiveness of campaigns.

Branddi stands out for offering robust solutions for real-time monitoring and brand protection, identifying infringing partners who practice unfair competition.

When identified, Branddi directly contacts these partners, requesting the deletion of the content or practice that causes attribution deviation.

By acting against attribution bias, technology helps marketers optimize their resources and maximize the impact of their actions.

See how Branddi's solutions can assist in this process:

• Constant monitoring: monitor campaign data in real time to detect any discrepancy;
• Data analysis: identify patterns and deviations in attribution data that may be distorting results;
• Corrective actions: identify offending partners and get in touch to resolve the situation, seeking the removal of the content or improper practice;
• Brand protection: prevent the misuse of keywords and other unfair practices that may affect attribution data.

These strategies are fundamental to ensure that marketing investments are directed efficiently.

Don't let your campaigns take unnecessary risks. Protect your results with Branddi's solutions, which enable quick and accurate action to combat attribution deviation.

Access the Branddi's website right now and discover how your solutions can transform the way you manage your marketing campaigns.

Click here to learn more!

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