Financial service providers are looking for the best ways to leverage their organizational data to be more effective in their marketing campaigns. With so much data available, this should be simple, right? Unfortunately, it’s not that easy. The 6th annual analysis of financial industry marketing trends reveals that financial marketers aren’t doing so well when it comes to leveraging organizational data.
The Financial Brand covered the report and stated that “despite access to data and analytic tools, the industry continues to fall behind in targeting, personalization, digital communication and ROI measurement.” So why are financial marketers failing to leverage their data?
Financial marketers are data-challenged with complex, dated tools that require deep data science expertise. They want to make faster, smarter business decisions using trustworthy data, but they simply do not have the expertise or the tools required to do so.
In addition, requests to IT teams for data dumps cause bottlenecks and competing priorities across the organization. Therefore, financial marketers aren’t able to harness the full power of their data in a timely manner.
So how can financial marketers solve these challenges?
Archaic tools and/or bolt on solutions that require deep data science expertise have no home in the marketing departments of financial institutions. Financial marketers need a self-service, big data analytics platform designed to handle not one, but rather, multiple steps from data acquisition and preparation to data analysis and operationalization. The platform should have some type of built-in data quality capability to ensure that the data being analyzed is accurate, consistent and reliable. There is nothing worse than drawing conclusions on dirty data.
The platform should reduce the amount of time required to generate marketing decisions with an integrated self-service tool that accelerates time to analysis and operationalization of data insights. Analysis can be performed by a financial marketer directly in a matter of hours, not weeks, with minimal requests to an already over-burdened data science team.
By empowering financial marketers to aggregate and control data, they’re able to accelerate and improve the subsequent data analysis process, applying analytics to extract value from data. The result is the ability to personalize the customer experience based on accurate information.
To learn more about how marketers can better understand big data analytics, download this data sheet.
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