Thanks to privacy regulations, new compliance needs, signal loss and heightened pressure to increase return on ad spend (ROAS), first-party data is becoming a high priority for organizations.
As a result, many are prioritizing data strategies and supporting tech stacks, bringing about new use cases for content management systems (CMS) and customer data platforms (CDP).
For example, once CMS data flows into a CDP, it can be used for acquisition, customer value and retention with tactics such as personalization, loyalty programs and customer experience. But this level of data enrichment is only possible if data is transferred in a standardized way.
The challenge with these new, evolving practices is they’re often built on top of outdated data practices. Marketing, IT, sales and other departments are still operating in silos. There isn’t a common language for data, which creates challenges for gleaning insights across the enterprise.
Gartner estimates the impact of poor data quality costs businesses $15 million annually. Pair that with economic uncertainty and tighter marketing and advertising budgets, and it’s a recipe for trouble. To weather the storm, it’s time for organizations to align their data strategies.
Common data challenges
Because CDPs and CMS systems are only addressing data received – and not considering where it’s from – inconsistencies emerge and can impact campaign ROAS, ultimately hurting ROI and profitability.
One common challenge is campaign tracking, which can get very messy. Campaign tracking codes and parameters often become inconsistent or go missing altogether. The process of creating connections between data sets, especially at scale, is often slow and prone to error. But most importantly, valuable metadata about campaigns is frequently lost – meaning analytics teams don’t have what they need to provide robust insights and measurement.
The lack of enterprise data taxonomy can also waste content and creative efforts. Content and creative teams have the potential to be a superpower, but updating subpar or nonexistent taxonomy needs to be prioritized. When data standards are applied to digital assets and webpage data, discovery, automation, personalization and analysis become much easier. This activates content as another measure of optimization to drive better experiences and ROI.
Data processes need an upgrade
Organizations don’t have control over signal loss, cookie deprecation, privacy regulations and other industry trends that are shaping data usage. What organizations can control is how they organize and use data.
To account for industry realities and economic uncertainties, implementing a better data governance process should become a business imperative for all organizations. A 2022 Deloitte study reported that reconfiguring data processes to be more automated resulted in the organization achieving cost reduction of over 70%. The same study reported that 85% of organizations are rethinking how work is done and 92% of implementers are already implementing some form of end-to-end automation.
As more companies try to do more, faster, with reduced spend and fewer people, more organizations are looking to optimize their data organization processes.
And this doesn’t need to be an all-or-nothing initiative. A phased approach to implementation is usually an easier route to take. Marketers should first align on needs for a single use case and build from there, developing the specifics as they pertain to taxonomic categories and data design.
The noticeable gap in data usage within CDPs and CMSs shines a light on the misalignment with data across the entire enterprise. In the year ahead, businesses will need to examine data pitfalls and implement new data practices that scale across the entire organization.
“Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.
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