What is biased attribution?
The term biased attribution refers to the conflict of interest that exists if attribution is performed by measurement platforms that also provide both the traffic and conversions. For example, if a paid advertising platform or ad network is both the source of traffic and the measurement provider, they may be incentivised to attribute traffic and conversions to their own platform as opposed to a competitor.
There’s no question that platforms like Google and Facebook provide advertisers with useful measurement tools, traffic insights, and user acquisition analytics.
That said, advertisers should use a third party attribution provider in order to avoid biased attribution and reporting. Smart marketers still use the data that ad networks provide, but use them in conjunction with a third-party attribution and marketing measurement solution like Singular to provide a holistic and unbiased view of ad performance. This ensures that the ROI of each marketing campaign is accurate, and that means that ad spend can be optimized properly.
Since advertising platforms understand the need for third party measurement providers, they have developed partnerships with these platforms in order to facilitate effective attribution and reporting of traffic, installs, and conversions.
Common examples of biased attribution
Since modern marketers often deal with multiple ad platforms and traffic sources, it’s important to avoid common mistakes that can lead to biased attribution results. Misattribution can ultimately lead marketers to not understand the true performance of their marketing campaigns and make them unable to optimize their budgets effectively.
A common challenge for mobile marketers is using multiple ad networks. Consumers see ads on both self-attributing networks and other ad networks, and the SAN reports an attribution thanks to view-through tracking … even if the more important impression — and perhaps the click — happened as a result of another ad network.
As Observe Point highlights, there are several of the most common misattribution mistakes and biases that marketers face, including:
- Correlation-based bias: This refers to the attribution bias that arises from assuming that one event causes another in the customer journey, when in fact the event was not related to a subsequent conversion, for example.
- In-market bias: This refers to the bias that comes from someone who was already in the market to purchase a product or install an app. In this case, the ad may have simply reminded them to complete a purchase that they already were going to make, although the ad still gets the attribution.
- Cheap inventory bias: This refers to a lower-priced product that may lead to higher conversion rates. In this case, the better performing ad campaign may simply be attributed to the low price point as opposed to the ad itself.
- Digital signal bias: Finally, this refers to attribution that doesn’t take into account both online and offline activity. If a company offers products offline and online, this may lead to a bias towards online sales as these are often much easier to track.
In order to resolve each of these biases, marketers rely on third party attribution providers to get an accurate view of their ad performance and ROI.
How Singular improves biased attribution
As a third-party attribution provider, Singular provides accurate attribution that allows advertisers to go beyond legacy measurement tools that may be inherently biased. In particular, the Singular platform provides mobile attribution with the following capabilities:
- Measure and report on all channels: Our open integration framework allows app businesses to measure cross-platform performance across apps, web, SMS, referrals, email, and TV.
- Track and analyze ROI: By combining attribution with cost aggregation, Singular is able to provide powerful data connectors that enhance advertising performance for every campaign, creative, and keyword.
- Measure the entire customer lifecycle: Since the customer journey is often highly fragmented, our deep links, web-to-app, and cross-device attribution allows marketers to track and report on the entire customer lifecycle.
In summary, by combining cross-device attribution with cost aggregation across multiple platforms, Singular removes the inherent biases that arise on ad network provided data. This provides marketers with an accurate and holistic view of their campaign performance in order to improve campaigns and increase ROI.