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Oracle Data Cloud Blog

Making the cut: What basketball star Steph Curry can teach marketers

This guest blog was contributed by Kal Rucker, Principal Analyst, Oracle Data Cloud.

If you have a hoops hound in your home, you know the team from Oracle is setting records. What you may have missed, however, is a key lesson the team is teaching us about building marketing audiences.

The Golden State Warriors, who play their home games at Oracle Arena, won 73 games this season against just 9 losses. That’s more wins than any team has ever had in the 70-year history of the National Basketball Association.

The Warriors are led by Steph Curry, the league’s reigning Most Valuable Player. If the Warriors followed a common marketing practice, they may have never acquired him, and missed out on the opportunity of a lifetime.

See, the average height of the top 20 scorers in pro basketball history is 6 feet 9 inches (6.76 feet). They’re tall—even by NBA standards, where the overall average is 6’7”. When acquiring players, teams might be tempted to focus on those above 6’7”.

If the Warriors did that, though, they would have missed getting Curry, who is just 6’3”.

Kal Rucker What Basketball Star Steph Curry Can Teach Marketers

Curry more than makes up for his relative lack of height. He is arguably the best outside shooter ever. He leads the league in steals and free-throw shooting, and is among the leaders in assists. He is an excellent rebounder and defender for a guard. Bottom line: For a wiry dude, Curry is quite well-rounded, enough so to make him the best player on the winningest team ever.

Fascinating, but what does Curry have to do with marketing? The lesson is to take a holistic view when sizing up prospects.

As a marketer, you understand your customers and want prospects who look like them.

If your customers are predominantly under age 50, it’s tempting to restrict targeted prospects to that age range. But you could be cutting Steph Currys from your team—folks who miss the age cut but otherwise have all the attributes you could want.

This is where big data and advanced analytics come into play. When building audiences for digital advertising or direct-mail campaigns, Oracle Data Cloud looks at the whole household. That includes demographics—such as age, income and length of residence—but also retail purchases, as well as interests and geography.

We consider thousands of variables when comparing prospects to your existing customers. Our customized equation scores millions of prospects to identify those best suited for your offer.

This is not to say that pre-selection (such as age 18-49) has no place. But when it comes to selects, it’s best to test. The key is how the next names up perform compared to those they would replace.

For example, say you want 1 million prospects for a campaign. We build a model and score potential prospects. Most of the top million are 18-49, but some are 50+. Should you take the top million according to our model, regardless of age? Or should you dig deeper and take the top million aged 18-49?

The answer is found in testing a sample of top-scoring 50+ names against the next tier of 18-49 names. This can be done through a back-test (analyzing a prior campaign) or in a live campaign.

Kal Rucker What Basketball Star Steph Curry Can Teach Marketers

In this case, the natural top million names had the greater result. Selecting by age would have cut some Currys from your team.

Unsure of who, and how, to target? Oracle Data Cloud is here to help.

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