Marketing Data Platform | Enterprise Marketing Data Standards | Claravine
Marketing Data Standards Platform
Speak the same marketing data language, org-wide
You can’t be data-driven if you don’t have data standards.
Build the fields, lists, and values you need into templates for data input
Tap into your org’s data expertise globally, across teams, and between agencies
Maintain core relationships between metadata across channels and tactics
Take a proactive data approach as observation narrows
Standardize and control org-wide data attributes to advance how you understand what works — and doesn’t — across acquisition and retention, end to end.
Create your source of truth, then deploy it far and wide
To trust your outputs, you have to control your inputs. The Data Standards Cloud helps you define and manage attributes and data relationships custom to your workflows and objectives.
Spot data errors & gaps for easy campaign validation
Define and govern all the data you connect for simple review and validation. Quickly identify data issues and make sure every campaign is tracked right from the start, without disrupting your workflow.
Connect & control all your data for better results from every tool
Control your marketing data’s integrity at every source for maximum ROI across every tool, team, and channel. Be ready for the digital transformations of today and tomorrow.
Need a custom API? No problem.
Your trusted authority in marketing data standards
“We had issues around data quality, getting the metadata into Adobe in a timely manner, and maintenance of the tool. Essentially all those problems were almost completely solved by Claravine.
The result is higher trust in analysis and reporting coming out of web analytics + much reduced time to keep the data accurate and fresh.”
Empower and leverage all your data creators
A data blueprint allows you to define and govern. Create and own your master data standards strategy, then hand it off and have it executed seamlessly by teams and partners.
The Data Standards Cloud is a collaborative tool for swifter-acting teams and better adherence to your carefully architected plans — whether they’re assigning creative, generating tracking codes, confirming campaign readiness, or working in other teams, regions, and units.
Be the driving force of your organization’s data integrity. Book a data strategy consultation to get started.
Data Standards Resources for Digital Marketers
Marketing Data Standards FAQ
In order for the data that informs and drives your campaigns to work, it needs a framework or a structure to follow. This framework is known as a marketing taxonomy.
Two key elements of a marketing taxonomy are metadata and tracking codes. Building an effective marketing taxonomy is an organization-wide collaborative effort and needs to consider both your legacy data and analytics and report implications. It is something you may need to update or tweak over time to keep your system as efficient as possible.
A data dictionary is foundational to any marketing taxonomy. It is an outline of your taxonomy that lists out your different channels, core business fields, and the input values by channel. This is an incredibly important tool to ensure internal alignment around input values across various organizational teams.
A good data dictionary should be created through a collaborative process. It should include values that are relevant to each team while also identifying any values that can be preset or filtered.
Metadata describes other data. It labels information so that it can be sorted appropriately. This could include data around experience (e.g., web page, content, images, mobile app), people (e.g., team, channel, group, business unit, agency, region), creative (e.g., ID, name, size tags), product (e.g., SKU, name, category), or campaigns (e.g., name, placement, ad group, objective).
Metadata lives in nearly every component of an organization. Typically this includes marketing, merchandising/inventory management, project management, creative/content management systems, CRM systems, product management systems. Once you identify your categories, you can start to understand the relationships between them so you can create a hierarchy.
It is a common misconception that tracking code taxonomy needs to be consistent in order to have a mature, clean data model. If you are dependent on a consistent taxonomy structure to decode and parse out components of your system, then generate your metadata fields, it can prevent you from pivoting your data and viewing your reports in a beneficial manner. That, by definition, is not a mature data structure. It is one that is prone to error.
Consistency is nice and it makes your tracking codes look pretty, but pretty doesn’t matter. What matters is the data you get from those tracking codes.
It isn’t necessary for tracking codes to be exactly the same in order to be effective. Consistent does not mean everything needs to be organized identically. Instead it is important that tracking codes are applied consistently, or applied using the same standard.
It is important that the data being associated with these tracking codes meets the same standard. And, it is important that tracking codes make sense. This is far more important than having them all look the same. The goal should be for tracking codes to leverage the features of various platforms to help you achieve your goals.
A template is constructed using a collection of different taxonomy elements (e.g., fields, patterns) that express data standards for a specific type of data (e.g., campaign, digital asset).
The Data Standards Cloud enables organizations to configure templates to support each of their unique use cases across teams, channels and regions – including advanced and custom configurations.
Platform users then browse, draft, review and edit data in these templates which provide the familiarity of a spreadsheet view in a no-code platform.
To succeed in the cookieless future, companies need privacy-compliant strategies for acquiring new customers, creating personalized experiences, and measuring campaign performance. These new strategies hinge on first-party data, collected across a brand’s website, apps, loyalty programs, and other digital experiences.
So seize this moment as an opportunity to define your marketing data strategy, and invest in what is needed to achieve it. Here are three critical steps to consider.
- Create data standards
- Invest in data-sensitive technologies that enable end-to-end data management: organizing inputs, handling sensitive data, and organizing outputs
- Go all-in on change management
The Data Standards Cloud, empowers your marketing tech stack to live up to its fullest potential. Even more, it can be deployed across other departments including content & creative, ad ops, analytics, and more to share common-language data and maximize ROI for every team and tool.
With The Data Standards Cloud, you can balance decentralization and control of your tech’s data integrity across all channels. Define and enforce tracking standards and link creation with automated processes that improve team collaboration and campaign creation.
Defining and applying data standards — a common structure for all your data and metadata, from campaign tracking codes to creative assets and ecommerce inventories — creates a common data language accessible and insightful to users across the enterprise.
By establishing a marketing taxonomy (and similar taxonomies in other departments) and governing it with The Data Standards Cloud, you’ll avoid incomplete data that lead to misinformed decisions.
Sing from the same songbook across your solutions. Share a marketing taxonomy standardized through templates to tie data points together.