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CAO Fall Day 1: How Can You Apply Insights From Your Data?

If an analytics team collects data and reports on it, but no one else in the organization understands it, then what purpose does that data serve? This question was posed repeatedly throughout the presentations and discussions during the first day of the Chief Analytics Officer (CAO) fall conference in Boston.

The CAO conference brings together analytics leaders from several fields, with designated tracks for the financial services, healthcare and insurance industries, to discuss how to drive innovation, build a cross-function analytical culture and generate value.

One of the first sessions of the day focused on fuelling an analytics-driven culture across the enterprise, and Juan Gorricho, Senior Vice President of Data and Analytics at TSYS, shared his views on data’s growing influence and potential.

Gorricho noted that by viewing data as a product, companies can foster data capabilities that improve their own productivity. Taking it one step further, he explained how enterprises can use data as an enabler to build assets that are capable of improving operations across multiple sectors within the company – not an easy feat for large enterprises with seemingly endless divisions. Using an example from TSYS, Gorricho explained how data-driven tools help improve their fraud detection efforts. And while it might seem that using data to enhance internal capabilities is simple, it’s actually a very difficult step for most enterprises to take. The bottom line? Companies need people who can “talk data,” not only amongst other analysts on their team, but with all employees throughout the organization.

This takeaway came up again in a later session centered entirely on the Chief Analytics Officer as an innovator, enabler and change-agent, presented by Matthew Marolda from WarnerMedia Applied Analytics. He emphasized that in building analytics, one of the key aspects is to pick your battles wisely, ensuring they are aligned with your organizational goals. He pointed out an example from WarnerMedia, where the analytics team helped inform the creative process for the films the media studio produces. By utilizing data, he found that they can help direct the creative team on whether a particular casting choice would perform well with a specified audience.

Now an ongoing initiative, the insights gained by the analytics team help inform the strategies used for marketing each of the films that are released by the studio. As Marolda explained, traditionally Hollywood divides their audience into a quadrant – examining only by gender and age (male vs. female and over/under 25, respectively). But now, that quadrant is broken down much further into micro-segments based on input from dozens of quantitative analysis tools. “Lots of little, tiny pieces create a mosaic that gets us to that point,” he said.

For the studio’s recent release of “Crazy Rich Asians,” the analytics team saw it as a fresh take on a romantic comedy and, based on prior data, Marolda said, “we knew we could open it at a lower number and cultivate the audience over time.” So, the analytics team advised the marketing team to spread their efforts out over time, rather than focusing all of their advertising on the weeks prior to release. The strategy clearly worked in their favor.

While many large companies are beginning to recognize the importance of gathering and analyzing data, few are doing it in a way that derives actionable insights that have the potential to impact their bottom line. As Gorricho shared during his presentation, “everybody wants to go to heaven, but nobody wants to die.” In order to be successful, enterprises need to invest in data management capabilities, and analytics teams must focus on educating colleagues to fully understand and apply the outcomes.

With Google Cloud and machine learning technology, Maven Wave is changing the way marketers use their data to make decisions. Check out our marketing analytics page for more details, and stay tuned for more insights from CAO!

October 11th, 2018

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