A Holistic Approach Can Empower Your Data Process

Although marketers cite leveraging data as a top priority, many struggle to do so effectively.

In fact, only 5% of marketers report that they’re doing an excellent job making improvements based on data, according to research from Econsultancy. In the case of programmatic marketing, this rings even more true. With programmatic advertising generating an estimated 100 times more transactions than Wall Street, a tsunami of data is available to marketers.

The challenge many marketers face is getting fast, easy access to disparate data sets in an intuitive format. Outsourcing these challenges and establishing multiple vendor relationships, each with their own user interfaces, only multiplies the problem with data silos and dashboards. And throwing bodies at the problem in the form of data scientists is neither cost-effective nor scalable.

Marketers need to step back and evaluate their entire data lifecycles–the means by which data is extracted, shared, and ultimately acted upon–with a holistic approach encapsulating three principles: dashboard consolidation, data APIs, and data engineering.

Step 1: Unify Your Dashboards

Cutting and pasting, toggling between screens, recalling log-in names and passwords for multiple vendors; these are the tell-tale signs of a marketer suffering from dashboard fatigue.

A recent survey from DNN Software revealed that more than half of midsize companies work with five or more technology vendors, and 63% of marketers polled feel they have too many technology vendors to manage effectively. Marketers’ data processes are disjointed, cumbersome, and incongruous with the sophisticated nature of programmatic advertising.

The solution isn’t necessarily to eliminate vendors but to unify their dashboards. By collecting the data from various sources into a single user interface, marketers can reduce the number of dashboards to manage and passwords to remember. With this consolidated view, marketers will gain all of the information available in one place and more easily spot patterns to make smarter, faster decisions.

Step 2: Consolidate Your Data With APIs

The most effective means of achieving a unified dashboard flows through vendors’ data APIs. These are the interfaces (application programming interfaces, to be precise) that enable data to flow between services. It’s what allows Mint to talk to bank accounts and credit card providers and pull back all the data in a clean, structured way and present an overall picture of financial health.

APIs can be persnickety to work with and aren’t always well-documented, but when a proper investment is made, they can help transform cut-and-paste processes into automated workflows.

Step 3: Invest In Data Engineers, Not Data Scientists

As much as marketers think they need to hire the PhD genius data scientist who can model Quantum Wave Theory, they will actually benefit more from someone who can help create a data process that’s so simple, the data scientist becomes obsolete. Marketers who work with a team of data engineers that help manage vendor relationships, access APIs, and pull all of the right data into the right place so it is actionable are ahead of the curve.

It’s not about finding someone who can understand data themselves; it is about finding someone who can help create a process that makes data easy to understand for everyone. This will address another common data-related complaint: delays in information. Many marketers’ data processes require them to manually request information. Then they wait. Those lapses are eliminated if marketers can access and understand analytics themselves.

In today’s landscape, failing to understand and leverage data could be the kiss of death for a marketer. By prioritizing a consolidated view, clean access to data and a support team with the skills necessary to create a self-service approach to analytics, marketing will transform from informed guesswork to a data-driven science.

This article originally appeared on cmo.com on June 22, 2016.

Filed in Corporate, Technology

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