“Customer 360,” or the practice of obtaining a holistic, real-time view of customers from multiple data sources, can unlock massive improvements in customer lifetime value and retention. But due to inefficient data and analysis ecosystems within global marketing organizations, it’s still a pipe dream for many brands. 

Marketers are well aware of the untapped benefits of personalization and are investing in their analytics capabilities accordingly. The challenge is effective implementation to drive ROI. 

On the one hand, the share of marketing budgets spent on analytics is expected to reach 11.6% in 2022, up from 4.6% in 2018, according to the August 2019 CMO Survey from Duke’s Fuqua School of Business, which was sponsored by Deloitte and the American Marketing Association. The obvious inference is that marketers are investing more because they’re seeing results. However, respondents scored the contributions of marketing analytics to company performance at 4.1 out of a possible 7, a rating that’s only slightly increased over the course of seven years’ worth of survey data, suggesting that progress is slow.

Data Silos: A Roadblock to Data-Driven Marketing 

Data silos—the practice of storing different types of information in separate, unconnected systems—are part of the underlying problem. Marketers are collecting more customer data than ever before, including purchase data, CRM data, website traffic data, paid-media data, and so much more. But it’s onerous, if not impossible, to piece it all together and see the bigger picture of how customers are interacting with your brand when using legacy technologies. 

Continued reliance on legacy data warehouses, which don’t allow for accessing and querying information in real time or in parallel, also makes it difficult for brands to attract and retain top data and analytics talent that could accelerate their progress toward Customer 360. A lack of flexible and scalable infrastructure to support their work is a primary driver of turnover among data workers, and because demand for their skills outstrips supply, they have the wherewithal to be highly selective. 

How a Cloud-built Data Warehouse Addresses Marketers’ Top Challenges

A modern cloud-built data warehouse addresses these challenges—and helps make Customer 360 a reality—in several ways. First, it enables querying and analyzing separate data sets in real time and in parallel. This ability is fundamental for a holistic personalization strategy, letting you identify high-value customers and ensuring they have a good experience at every touchpoint. That simply isn’t possible unless you can see the big picture of how and where those individuals are interacting with your brand as it happens.

Implementation of a modern data warehouse also reduces latency, making data and analytics teams more agile and productive. They have increased capacity to experiment and try new queries that may improve the effectiveness of Customer 360 initiatives without fear of disrupting core activities. A modern data warehouse also helps marketing organizations hold onto valuable talent by relieving data scientists and analysts of tedious “data munging” tasks, letting them focus on higher-impact work. 

It’s important to remember that interesting, meaty challenges, coupled with the tools and technology to make meaningful progress, are as important as compensation when it comes to attracting and retaining data talent. Customer 360 is a lofty but achievable goal, and B2C marketers need their data teams to stay engaged and happy to make progress that justifies increasing levels of investment. 

To learn more about how a modern data warehouse can make Customer 360 a reality for your organization, download our ebook Five Reasons B2C Marketers Should Care About Their Data Warehouse