Redbox has come a long way since its first bright-red kiosk made its debut nine years ago. Consider these statistics: Redbox outlets are now situated in more than 28,000 spots around the country. Customers rented 59 million movies and games monthly during third-quarter 2011. The number of Redbox movie rentals to date has hit more than 1.5 billion.
Redbox's rise to such prominence among video rental providers has required some serious business smarts -- a strong understanding of brand development, consumer behavior, growth strategy, and marketing practices. Jayson Tipp, vice president of analytics and CRM, has been driving the company's business intelligence efforts since late 2010. He's responsible for building out database marketing, consumer intelligence, and marketing analytics capabilities.
As Tipp says in our newly posted video, Red Hot Analytics, getting data organized in a way "that allows us to stay on top of changes in consumer behavior and leveraging advanced analytics solutions with the right enabling technologies" can make the difference between success and failure for his team. In the video, Tipp takes us inside the marketing analytics efforts at Redbox, detailing how the company uses data to better understand and cater to consumers.
Here he adds additional insight about the importance of testing and measuring the effectiveness of a marketing campaign. Testing and measurement, often overlooked at companies, is "ingrained in everything we undertake" at Redbox -- and has always been, Tipp says. "That pre-dates my involvement with the company."
Since joining Redbox, Tipp has implemented an advanced analytics platform for test and learn, and rigorously uses holdout samples, whether a program is at the market, kiosk, or consumer level, he says. "We measure lift but also use these techniques to improve the targeting of marketing programs. We measure dozens of activities every quarter."
By enabling effective decisions, the test-and-learn approach led Redbox to rollout of a number of programs in 2011, Tipp says.
An upsell offer at the kiosk is one example.
"We tested multiple variations before we identified a version that generates impressive customer acceptance and a strong value proposition for consumers and Redbox. We've fielded the offer a number of times since and have been able to consistently measure lift vs. holdout samples."
An upgrade to the kiosk user interface is a second.
"We made changes to the user interface based on research and had a sample of kiosks in market test for months. Once we had real confidence around our test vs. control analytics, we were able to accelerate the decision-making cycle to roll the user interface. Results over the last few months suggest it was a great decision for the consumer," Tipp says.
More recently, Redbox has been developing analytics to better target email. "Using regression models, we have been able to quantify the value of our email program and learn how to better target content which has led us to implement new capabilities in this area."
What's really been refreshing as Redbox has taken on such projects is "how much more powerful and automated the analytical tools have become," Tipp says.
Still, that's not to suggest this stuff necessarily gets any easier.
As Tipp says, "the perceived ease of implementation is much greater than 10 years ago. But, data has exploded. And, you still have to be able to connect analytics to business impact, provide a compelling vision for the role analytics can play, and develop a cross-functional coalition in order to be successful. Analytics can't be confined to desktop databases and have impact these days."
How does the Redbox experience compare to your own? Watch the video, and share your story on the message board below.