Are the digital challenges facing your business more crucial than ever? If you find yourself spending more on multiple marketing channels and wondering what actually matters, then this article is tailored for you!
What do you need to understand before searching for an attribution solution? Whether you’re starting to explore attribution solutions or considering a change from your current one, there are fundamental concepts to grasp.
I. THE ESSENTIAL FOUNDATION OF RELEVANT MEDIA MIX PERFORMANCE MEASUREMENT: DATA COLLECTION
THE IMPORTANCE OF COMPLETENESS
The primary goal of an attribution solution is to ensure the capture of ALL interactions between your customers and your brand. This allows for the reconstruction of customer journeys and accurate attribution of credit to each channel based on its impact on the customer’s decision. If a marketing touchpoint is excluded from the attribution calculation, it renders the tool ineffective due to skewed data. Hence, it’s crucial to gather all your communication channels, be they media or non-media, paid or unpaid.
THE IMPORTANCE OF GRANULARITY
To optimize your digital channels effectively, it’s essential to collect detailed data in your attribution tool. Defining channel groups is a useful step, but it’s insufficient for building fine granularity in centralized tracking. Implementing a common campaign nomenclature shared across all your media buying tools saves valuable time during attribution tool setup.
The same applies to UTMs. Review and standardize the information reported in Medium, Source, and Campaign fields. This precision allows for more precise recommendations. For example, instead of a generic statement like “SEA generated more sales than Social,” you’ll receive a granular recommendation like “Consider moderating investments in Facebook Retargeting campaigns as sales objectives aren’t being met for targeted audiences.”
The quality of information obtained from an attribution tool relies on the quality of information provided.
HOW THE MODELS WORK
Once the necessary tracked and qualified data is available, the attribution solution comes into play. It utilizes user conversion paths to calculate the contribution of each touchpoint to final conversions, guided by an attribution model.
HISTORICAL MODELS: RULE-BASED
These models range from simple methods like Single Touch Point to more advanced ones like Multi Touch Point. While they follow pre-established rules, they don’t adapt to changes in customer behavior or media mix evolution, leading to deviations from reality.
For more details, refer to our article: “All about the different models.”
DATA-DRIVEN ALGORITHMIC MODELS: WHAT ARE THEY?
An algorithmic model is a set of actions performed to accomplish a given task. In this case, the task is attributing the contribution of each touchpoint in the user journey to the final conversion.
Data-driven refers to variables that feed the algorithm based on user behavior, such as clicks, views, time spent on site, and pages visited. These variables provide an objective user experience, moving beyond approximations or generalities.
Unlike rule-based models, algorithmic models allow for variations within a media mix. They dynamically attribute importance to touchpoints frequently present in conversion paths, regardless of their order.
Additionally, algorithmic models adapt to changes, such as investment variations or the activation of new channels, without requiring new parameterization.
👉 Learn more about Wizaly’s data-driven attribution algorithm.
II. WHAT TO EXPECT FROM YOUR ATTRIBUTION SOLUTION?
RECONSTRUCT USER PATHS
AN EXHAUSTIVE POST-CLICK AND POST-VIEW
While tracking clicks is fundamental, it only captures part of the influence that media campaigns exert on users. Post-view tracking completes the user’s journey, considering the impact of seen but unclicked ads on brand presence and purchase decisions. Therefore, a robust attribution solution must have excellent post-view measurement capabilities.
In display advertising, post-view measurement involves implementing an impression pixel or JavaScript tag to track banner views. At Wizaly, we prefer JavaScript due to its higher precision compared to pixels.
Now, let’s address the challenge of paid social environments, known as “Walled Gardens.” They don’t allow third-party post-view tracking, limiting measurement of unclicked banners’ influence on conversions. At Wizaly, we developed a proprietary attribution algorithm based on probabilistic measurement to overcome this tracking limitation.
ANTICIPATE EXTERNAL LIMITATIONS
Recognizing users is vital for reconciling touchpoints and mapping user paths. However, players like ad-blockers and certain web browsers block access to tracking information, complicating path reconciliation. Your attribution solution must react and adapt to these challenges. At Wizaly, we ensure maximum efficiency in user-centric measurement through first-party tracking measures.
QUALITY OF RECOMMENDATIONS
Collecting data correctly is essential but not sufficient for maximizing the benefits of your attribution solution. Due to the subject’s complexity, methodological support is crucial. This includes data visualization, metric combinations, and relevance in studying channel groups, campaign strategies, periods, and various levels of analysis. The platform’s richness, coupled with human support, especially during the initial phase, enhances your team’s skills.
The solution should unite various areas of expertise to leverage marketing data for the company’s overall benefit.
THE RICHNESS OF ADDITIONAL DATA
To gain a deeper understanding of user behavior, integrating additional data sources beyond post-click and post-view tracking becomes inevitable.
For assessing campaign profitability, integrating cost data for each campaign is essential. Connector tools facilitate recurring cost data integration, simplifying the process within Wizaly.
Other data types, such as information on communication formats and purchase methods, enhance the relevance of analyses. A comprehensive understanding of customer actions helps refine the attribution model.
III. SETTING UP YOUR ATTRIBUTION TOOL AND MAINTAINING DATA QUALITY: WHAT YOU NEED TO KNOW
ONBOARDING THE SOLUTION: PROJECT MANAGEMENT UNDER YOUR CONTROL
During the implementation of your attribution solution, the importance of data collection factors mentioned earlier is considered. If data collection is done in-house using proprietary tags for post-clicks and pixels/JavaScript for post-views, rather than through an existing analytics solution plugin, your solution provider manages interactions with your agencies. Validated nomenclatures are distributed to agencies to optimize tracking template adherence.
MAINTAINING DATA QUALITY OVER TIME: A COMMON THREAD
A quality setup doesn’t exempt you from regularly monitoring exhaustive, integrated, and granular tracking of site traffic and sources. A media mix is rich and constantly evolving, demanding continuous vigilance. Ensure new campaigns adhere to the validated nomenclature and include proper UTMs, track behavior on new website pages, and implement post-view tracking for new display campaigns.
This ongoing diligence can be managed by your team or the solution provider, which should be determined at the beginning of the collaboration.
Scheduling global reports for relevant checks allows for detection of potential pitfalls and subsequent communication with intermediaries (data layer teams, media agencies, IT teams, etc.).
Challenging an attribution solution requires a comprehensive understanding of the digital media mix and rigorous project follow-up throughout the collaboration. The attribution tool should act as a trusted third party, demonstrating impeccable data accuracy and processing. The efforts invested yield an unaggregated view of media mix performance, enhancing productivity for marketing teams and enabling strategic management based on comprehensive insights.
Lastly, remember that a good attribution solution integrates both online and offline behaviors, providing data that considers all customer actions. This comprehensive view helps better understand customers, anticipate future behaviors, and drive effective marketing strategies.
