Digital marketing campaign classifications—metadata—are the wild, wild west of marketing data due to a lack of industry-wide protocol. The names vary widely: metadata, dimensions, or classifications. We refer to the organization of metadata as taxonomy or hierarchy.
What exactly does all of that mean?
Simply put, metadata is information that describes other information. Metadata helps us dig into our campaign performance and describe metrics or events like impressions, clicks, conversions, and ROI. For example, you could drill into impressions, clicks, and conversions through metadata like channel, source, or campaign name to better understand the performance of a given channel or publisher.
Metadata is the foundation for attribution analysis and models, making it critically important to your brand. So how can you make sure you get it right? In a word: standardize. Here are 5 steps you can take to standardize, scale, and improve your campaign classifications and metadata.
1. Standardize naming conventions with picklists
In a complex marketing and advertising landscape, establishing an organized framework for metadata is critical. But that system needs to do the seemingly impossible: keep it simple, consistent, and robust at the same time. How can this be achieved?
Some companies use non-standardized free-form text values for metadata, but this often creates down-stream data problems that don’t scale. For example, if we attempt to describe a metadata value and associated touchpoint ID without a standardized, non-mutually exclusive value in place that describes the medium or channel of “search engine marketing,” we might refer to it as a more generic term like SEM, Paid Search, or PPC.
The problem? When viewing metrics later on within a report or dashboard, search engine marketing will show up as three line items as opposed to one. To address this problem, the data team would need to transform the data with a rule that merges all three categories into one, and that requires data transformation rules to be managed and implemented.
It is best to use pre-defined, consistent values for metadata to ensure consistency and save time down the line. Ensure that values for each category are mutually exclusive (so you don’t have to merge categories later on) and associate values with customized picklists.
How ObservePoint Can Help:
In ObservePoint’s performance measurement solution, these metadata picklists are built into one centralized repository with touchpoints for all paid, owned, and earned media channels.
2. When using text-based values, enforce governance where possible
While picklists are the golden standard, there will be times you’ll need to use non-standardized, text-based values.
Hint: Non-standardized text-based values should only be used when there are many non-mutually exclusive values within a classification category. One important instance would be in the description of the touchpoint name or tracking code name.
However, even when using non-standardized text-based values, efforts should be taken to create consistency in the exactness of each name and possible values.
By having specific syntax guidelines in place, you can maintain a measure of governance and standardization. For example, guidelines for a text-based campaign name may include requiring a specific:
- Number of characters
- Inclusion of month/year
A tracking code or touchpoint name / description might always include the following classification categories and values:
Using non-standardized free-form text values for attributes that lack any form of governance or standardization.
Implementing as much standardization and governance as possible for non-standardized free-form text values.
3. Expand attributes to generate increased data value
Most of us use fewer than five classification parameters popularized by the UTM methodologies: source (or publisher), medium (channel), content, campaign, and term (for search). And rarely do we have more than a few metadata categories that are standardized via picklists.
While the UTM methodology paved a path, it’s lacking in the breadth necessary to fulfill the objectives of today’s data-driven companies.
In thinking beyond just marketing campaigns (which are typically limited to medium, source, and a few content attributes with UTM) and evolving to tracking and describing experiences with many metadata categories—such as image and video assets, call to action, headline, messaging strategy, and more—businesses can use attribution to assess a wider range of business questions and goals.
In short, by implementing more metadata categories and associated standardized values, companies can tune into exactly what’s working (and what’s not) and get a higher value from data insights.
Tracking medium, source, and content attributes through standard UTM campaign tracking methodologies.
Leverage dozens of attributes to track and describe experiences.
How ObservePoint can help:
Some homegrown systems can automate the population of 20+ classification categories via integrations, or by creating shortcuts where one value is populated and multiple values are then automatically mapped. However, creating these systems is an enormous endeavor and the result may still be limited in scope. ObservePoint’s performance measurement solution offers a library of dozens of out-of-the-box content and channel variable attributes and allows users to easily create custom attributes—so you can tailor your attribution strategy to specific business questions.
4. Apply a flexible, flat structure to metadata taxonomies
Not every method of organizing metadata is equal, so what’s the best way for your business?
Many analytics services implement rigid classification mapping, which hardcodes the hierarchy and associated touchpoint ID based on dependent values from other metadata categories.
With a rigid classification, if you have Google Display Network as combined publisher and channel detail, you know that Google is the publisher, the channel is Display, communication type is Digital, and that it’s Paid media ownership. If the hierarchy is rigid, you won’t be able to parse out any one metadata attribute for reporting. If you wanted to look at channel or publisher, depending on the reporting tool, you’d need to go through every level within the hierarchy just to view performance of Google Display Network.
Investing in a solution that doesn’t rely on rigid classification mapping allows users a greater measure of flexibility in how they view attributes.
How ObservePoint can help:
In ObservePoint’s performance measurement solution, touchpoint IDs aren’t tied to other metadata dependencies, so one attribute can be defined without needing another. As a result, users can easily view a report of singular attributes or multiple attributes of their choosing.
5. Organize each metadata category
While individual classification is ideal in helping to determine specific attribution, there are times it’s useful to group common elements of metadata. Combining them allows you to see the full picture once filtered down (but of course is reliant on a system using picklists). The following metadata can be appropriately grouped: Channel and Content.
Channel Metadata: Describes “where” a touchpoint is delivered (or promoted) to an end customer or visitor.
Content Metadata: This is the message, creative execution, CTA, and product. These attributes are critical in understanding how to deliver the optimal experience to both prospects and customers.
Customer Journey Stage Message
Awareness Dive into Fall
Content Type Ad Account Name
Landing Page Acme
Campaign Theme Ad Campaign Name
Fall Campaign Display Network - Awareness Campaign
Language Ad Description
English Demand more performance, for less
When different publishers or sources use the same types of metadata (but follow different naming standards), inconsistencies make it difficult to track specific strategies across these sources. Often, you may find the same attributes and associated values represented as if they were completely different categories and values. For example, what Google Adwords calls a “headline,” Bing may call a “title,” though they are both referring to the same object. Making sense of these different native taxonomies is not impossible, but it often requires some herculean efforts.
Further, the proliferation of subcategories (due to different naming standards across tools) typically results in unnecessary data columns and makes it difficult to combine metadata categories.
Implement a system that allows for certain metadata categories to be grouped together, improving the visibility into both efforts and performance specific to those categories.
How ObservePoint can help:
ObservePoint’s performance measurement solution intentionally maps across systems—replacing native taxonomies with a single taxonomy for your organization, so you can easily see how specific strategies are performing across all channels.
Drive Actionable Insights with ObservePoint
Data-driven companies often have no shortage of data collection. It’s making that data accurate, complete, and actionable that’s the challenge. The key to solving this challenge is using a system that can:
- Establish governance and standardization that ensures consistent and complete data
- Validate data collection for ongoing accuracy
- Disassociate touchpoint ID metadata attributes and define categories to allow for better data manipulation and insights
- Apply flexibility to retroactively make updates as your business changes.
See how ObservePoint can help you drive results with data by scheduling a demo.
About the AuthorMore Content by Cameron Cowan