Despite the ever-growing importance of digital media, many organizations only effectively track 40 percent of their digital media spend. This gap is caused by manual processes. If that phrase, “manual processes” makes you cringe, you’re not alone.
Time-consuming manual processes make it difficult to ensure consistent tracking across multiple platforms and teams. As a result, analytics and marketing decision-makers are often left with minimal insights into which ads or ad elements are driving results. Spending precious time manually validating tracking elements and piecing together reporting isn’t any marketer’s favorite activity. Marketers should spend their time strategizing, creating, testing and optimizing!
That’s why we’ve created our Universal Campaign Coder—to give marketers their time back.
Maybe you are thinking, I am not a “marketer.” While our focus is marketers, it might not be in the traditional sense of the word. Here is a list of users that benefit from our Universal Campaign Coder (UCC).
- Marketing agencies
- Digital marketing operations
- Business intelligence
- Data science
- Digital strategy
Really, any company running digital marketing!
Many media organizations employ a multi-step process to define, execute and track media campaigns. That process potentially spans media agencies, internal ad ops teams, creative teams, analysts and various other stakeholders. Complicating this flow further is the expansion of platforms and channels—each with a potential agency or team supporting execution.
At the core of implementation is the creation of campaigns and tracking parameters to ensure data flows to analytics and reporting platforms seamlessly. This whole process requires an immense effort to systematically create campaign code attributes that are applied correctly, tracking codes comply with required taxonomies and landing pages are live.
In many organizations, tracking codes, campaign details and other key pieces of data are often created, managed and stored in spreadsheets. These spreadsheets are the foundation of the information that gets loaded into media and analytics platforms. Given the sheer volume of ad and creative iterations submitted, opportunities for human error at each step are inevitable. That’s just the way of it and is something that we have come to accept as normal.
Traditional data quality assurance strategies have focused on spot-checking and page testing while acknowledging that data will need to be cleaned up after the campaign has launched. Not surprisingly, hoping to fix data on the backend rarely results in the consistent, rich data that enables better experiences and decisions. Furthermore, a general lack of transparency means agencies and/or departments are often at odds with brands and unified campaign insights remain elusive for leadership. It is exhausting just thinking about it, right?
Here is what a standard marketing campaign entails: once strategy and objectives have been set, many media campaigns begin with the creation of a media plan that details the core budget and basic parameters of the media campaign. These details are added into an Excel-based trafficking sheet, in which additional campaign data fields are populated for each ad variation.
Many of these fields are either populated in bulk or generated through formulas. For example, the tracking code for each ad is often generated through a formula or a macro, based on the metadata fields that are manually entered relating to the ad. Obviously, any mistake in the manual data entry process means the resulting tracking code doesn’t accurately capture data fields downstream.
Of course, a trafficking sheet may include hundreds or thousands of lines for each ad and creative iterations, multiplying the challenge of manually governing compliance to protocol. Still with me here? In addition, these manual, Excel-based processes often leave potentially valuable metadata uncaptured, given the disconnected nature of the data itself.
Fortunately, there’s a better option that consists of automating operations into key elements of this process. The Universal Campaign Coder generates campaign detailed information that can be added to any media platform. At this stage, the role of the Universal Campaign Coder is to automate the following:
- Validate that tracking codes match the required classification based on predefined standards
- Validate that other metadata fields are present and conform to a common classification
Where appropriate, our platform can connect directly to the execution platform itself—such as Facebook Ads Manager or Google Campaign Manager—automating away the monotonous process of ingesting, validating and correcting campaign data. These integrations into a common platform mean data is standardized across channels and execution platforms. This eliminates the need to manually quality check data, thus saving teams an immense amount of time.
With validation complete, our Universal Campaign Coder automates the bulk export of data to Google Analytics and business intelligence platforms like Domo, removing the additional opportunity for human error. What’s more, is that the platform expedites format requirements, so data automatically contains the appropriate structure. Boom! As data standards change, the platform allows teams to centrally manage data classifications and make changes that span channels and platforms.
The result? Digital media experiences go live faster and with the assurance of richer, more accurate analytics. Better data means everything! Teams spend less time trying to fix data quality and can instead focus on planning the next stellar campaign to create better experiences for customers.