How Big Data Helped the Norman Rockwell Museum Grow Revenue

How Big Data Helped the Norman Rockwell Museum Grow Revenue

Nestled among the Berkshire Mountains, along the Housatonic River, is the bucolic town of Stockbridge, Mass., which for centuries has served as a refuge and inspiration for writers, musicians and artists.

It is in Stockbridge that painter and illustrator Norman Rockwell, whose work has become emblematic of America in the middle of the 20th century, spent the last 25 years of his life working. Stockbridge is now the home of the Norman Rockwell Museum, which holds a collection of 574 original works of Rockwell art - including many of his famed The Saturday Evening Post cover paintings and the Four Freedoms - and more than 100,000 various personal items, including photographs, fan mail and various business documents.

The nonprofit Norman Rockwell Museum has a gift shop and online store that offers prints, books, stationary products and other gifts. In 2012, it did $1.5 million retail business and $120,000 in ecommerce business, says Margit Hotchkiss, deputy director of Audience and Business Development at the museum.

Perhaps unsurprisingly, as Rockwell's art is often associated with the holidays, sales tended to be highly seasonal. The museum, founded in 1969, needed to drive more incremental revenue. But it also had a more insidious problem: The audience for Rockwell's work was getting older.

"Today, so many people that know Norman Rockwell are in their 60s and 70s," says Lisbeth McNabb, founder and CEO of DigiWorksCorp, which specializes in helping organizations translate their data into insight that drives revenue using a software-as-a-service (SaaS) platform. Their children or grandchildren might be exposed to Rockwell's work through them, she notes, but on the whole the audience was aging.

The museum needed to get a younger audience to tune in to Rockwell's work and then turn them into purchasers. And not just one-time purchasers either; it needed to bring them back for more.

The museum turned to DigiWorks for help.

Norman Rockwell Museum Leverages Big Data

"What they realized is that somebody comes during the holiday season and buys once," McNabb says. "We help them look at what many people who have bought an item look like and then figure out what's a second thing that customer would like to buy?"

As a first engagement, the museum's goal was to increase annual revenue in ecommerce sales - the low-hanging fruit. McNabb says DigiWorks took the data the museum already had, analyzed it for insight and then executed a series of four campaigns over 90 days. The results speak for themselves:

  • The campaigns increased the number of second-time purchasers by 150 percent
  • They delivered $20,634 incremental revenue vs. 2012, a 49 percent increase
  • The campaigns delivered a 77 percent increase during campaign weeks
  • Overall, the campaigns exceeded their revenue increasing goal by 16 percent

At the end, the museum signed a year-long SaaS commitment with DigiWorks. So how did DigiWorks do it?

The secret, McNabb says, is to take your data and use it to build an authentic one-to-one relationship with your customers. You need to know your customer, build loyalty by listening to your customer and then deliver the right offer to the right person at the right time.

"We need to help retailers get to precision: 20 percent more precision translates into 80 percent more revenue," McNabb says. "Your customer told you they bought something? Talk to them about the second transaction. They bought something for the living room? How can we get them to buy something else for the living room?"

Know Your Customer Using Transactional Data

The key to getting to know your customer is locked in your existing transactional data. You have a name, address and specific information about what your customer wants or needs to buy. With a single transaction, you can see what your customer spent, but also what they spent it on. That information can help you determine what the customer's next likely purchase might be.

"All your customers' interactions with your business - whether through your website or in person, on the phone or through social media - provide you with data to learn more about them," she says. "What tools are they using to learn about your business? What is an individual customer's preference for how he or she makes a purchase: mobile device or tablet, in the store or through the website?"

For the Norman Rockwell Museum, DigiWorks took the transactional data of all purchases and then used weighting patterns and data rules to set a high, medium and low price of product recommendations. It then used A/B testing to discover patterns in how people clicked on offerings within an email - which content and images attracted them.

By doing so, DigiWorks built up data on segments of the museum's overall consumer base so it could reliably recommend unique products to a first-time purchaser built on the patterns of many first-time purchasers. For anyone with an existing transaction history, it provided unique recommendations based on that history as well as the patterns it had identified.

"Picture that you have a portion of total consumers that literally every single one of them was getting a one-to-one recommendation that was unique from the others," McNabb says. "For anybody that hadn't purchased before, they were put back into an A/B test. The bottom line is that when you look at those one-to-one recommendations and then walk through the results of the campaign - we were able to look back across several years - the amount of growth was 150 percent higher than the previous year."

Of course, privacy is important, she notes. You want to know more about your customer, but you also want to avoid the "creepy factor."

"You need to have visible privacy," McNabb says. "You need to allow people to opt in and out. When a customer is talking with you in a more one-to-one way, they opt in more. For many age groups, when they're asked on surveys, they say they want more privacy. But when they're asked to opt in, they're willing."

Build Loyalty Using Social Media and Big Data

Using social media, you can have conversations with an unlimited number of potential and actual customers. Your customers can tell you what they're thinking, and you can leverage that information to tweak your offering or expand your market.

"Each data point tells you something valuable about your customers' purchasing habits," McNabb says. "Leverage client engagement into a source for big data through social media interactions. Distributing a coupon or other offer through social media tells you far more than if your customers are clipping newspaper coupons."

Deliver the Right Offer to the Right Person at the Right Time

The principle is simple: If you offer someone something they need, right before they need it, they're more likely to buy. To do that, you need to understand your customers as individuals. If a customer once bought something for an infant six months ago, you need to understand what that means.

"If a child is six months older, talk to me like you know that," McNabb says. "Don't still talk to me about summer Huggies. You need to understand their life stage."

In other words, if a customer bought something for a living room, help them complete the room's transformation. If the customer bought a piece of clothing, help them complete the outfit. Of course, you need the customer to see the offer in the first place. It's not just about making the right offer; it's about reaching the customer with it in the right way.

"You want to move from mass communication to acknowledging what an individual looked at or first bought," McNabb says. "What trips them over is you're actually talking to them, not en masse. Potentially it's the subject line or the content of the email. You're recognizing something I bought and talking about something that would be complementary to me."

The first-time customers receive a personalized, one-to-one email, average open rates go up by 15 percent to 25 percent, McNabb says. The message after that tends to have open rates that increase by 30 percent to 60 percent, she adds.

Thor Olavsrud covers IT Security, Big Data, Open Source, Microsoft Tools and Servers for Follow Thor on Twitter @ThorOlavsrud. Follow everything from on Twitter @CIOonline, Facebook, Google + and LinkedIn.

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Tags softwareapplicationsindustry verticalsemail marketingdata miningecommerceTechnology Topicstransactional dataTechnology Topics | Big Datasocial media marketingOpen RatesDigiWorksCorp

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