New research is forecasting data investments to grow from $27 billion this year to $33.8 billion by 2027. This spend, according to Winterberry Group’s recent “Demystifying The Data Layer” report, is “in response to the critical need for a privacy-compliant, secure, and actionable data layer,” which Winterberry Group defines as the segment where data is ingested, consolidated, and standardized to ultimately be used in the subsequent intelligence and activation layers).
(Source: Winterberry Group)
“[This] investment in data, data services and data technology [reflects] a commitment to leveraging data as a strategic asset for driving business growth and enhancing customer experiences,” the study says, which projects $270 billion in U.S data-driven ad spend this year. “As organizations adapt to these shifts, the journey toward architecting an effective data layer remains pivotal in shaping the future of marketing and advertising.”
Of the 200 organizations surveyed, only 19% of U.S. organizations are “significantly” increasing their investments in data infrastructure and technology (compared to 60% in the U.K. and 35% in the EU). 74% of U.S. companies are increasing their investments in some measure, but the U.S. also has the largest percentage (7%) of those maintaining their investment. In its analysis, MediaPost posits that “it could be that spending on data infrastructure has slowed down in the U.S. because firms have already made these investments.”
In terms of current solutions that organizations use to “store, manage, and analyze” data, 83% use a CRM’s engagement marketing platform, 59% use a customer data platform, and 57% use a data warehouse or data lake. The top three barriers companies had for leveraging that infrastructure to support marketing and advertising efforts were data accuracy and quality (50%), security (41%), and cost (41%).
“‘Garbage in, garbage out’ remains a fundamental challenge in realizing the full potential of data layer investments,” the study says, which points to accuracy, consistency, and validity for data-leveraging effectiveness. “While incomplete data was once a significant obstacle, advancements in AI have mitigated this concern to some extent. However, challenges such as siloed information, inconsistent formats, outdated data, and evolving privacy regulations persist, collectively undermining data reliability and demanding immediate attention from marketers.”
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