During the Super Bowl XLIX telecast earlier this month, I was captivated by a commercial from MacNeil Automotive Products, not because I’m in the market for new car accessories. Rather, I was blown away that the little-known maker of WeatherTech all-weather floor mats and cargo liners would pay an estimated $4 million for a 30-second spot alongside big-name brands, such as Coca-Cola, Snickers, Doritos and Budweiser.
I couldn’t help but think that somehow big data analytics played a role in the company’s decision to spend big bucks to air a commercial during the Super Bowl. If so, this is a great example of how data can help organizations of all types and sizes take advantage of “in the spotlight” opportunities. In this particular case, providing the insight necessary to justify an investment that represented roughly 10 percent of the company’s purported annual advertising budget.
At first, this scenario seemed like a pairing of strange bedfellows till I realized that manufacturers actually have an edge over other industries, as this sector was among the first to make widespread data collection a standard practice. MacNeil has long had the ability to track and monitor much of what’s happening on its production line, so it makes sense that the company would be well positioned to know what happens to its products after they’ve come off the assembly line.
I’m sure big data provided some assurances to MacNeil that investing in a Super Bowl commercial made good fiscal sense. And, from what I’ve read about this so far, it did. As founder David MacNeil explained in a Forbes article that appeared right after this year’s Big Game, the decision to run a commercial was driven in part by the success of last year’s Super Bowl ad.
That’s right, the “little automotive products engine that could” debuted its first Super Bowl commercial in 2014; experiencing an 80 percent increase in website traffic and 57 percent jump in calls to its 800 number in the month following the placement. So running another ad in the Super Bowl was a smart business decision. And, based on the buzz created by this year’s ad, which reinforced the company’s heavily patriotic “Made in America” mantra, I predict WeatherTech products will be back next year for a three-peat!
What’s most interesting to me about this example is how this successful use case of big data analytics didn’t come from a really big manufacturer, just a really smart one.
There are endless opportunities to mine both big and small amounts of data to produce meaningful, actionable business insight. Another prime example that comes to mind involves Polyform U.S. Ltd., the world’s leading manufacturer of marine products, including buoys, fenders and mooring accessories.
A customer of Dell Software’s big data analytics solutions, Polyform accesses a slew of different data sources while taking advantage of Hadoop.
“We can easily access, connect and visualize all kinds of data to attain a complete, global view of raw materials, competitive pricing and everything else that goes into making and marketing our world-class products,” says Art Kuntz, IT manager for Polyform U.S. Ltd.
As a result, Polyform can easily attain a complete global view of every facet of its business, which has translated into increased automation, productivity and operational efficiencies. These benefits are within reach of any organization that understands the value of its data as well as the ability to collect and analyze it. Again, here’s where I think manufacturers, in particular, are well positioned to capitalize on a rich data collection heritage to drive new revenue streams through cross-selling and up-selling.
As a crafting enthusiast, I’m struck by the seemingly endless opportunities for makers of just about everything from paper to metalwork to reach new legions of customers with unique products to fuel a favorite pastime. I’m probably stating the obvious, but there’s a very specific demographic spending lots of dollars in this area and manufacturers can readily figure this out through data collected from crowdsourcing or targeted marketing efforts.
Having access to vast amounts of usage data that’s been sliced, diced and analyzed is the best way to improve customer experiences while revealing new revenue streams. Additionally, it’s the best route to forecasting which products are likely to gain rapid adoption.
In the future, I expect to see manufacturers lead the way in pre-emptively seeding the market with new products based on an analysis of social media metrics, among other data sources. Companies across all sectors can learn from the manufacturing industry, which traditionally has done a good job of staying in tune with their customers’ wants and needs while utilizing collective customer intelligence to inform product development.
In that sense, it’s not strange at all to find manufacturers taking advantage of big data analytics to augment and amplify business direction. In the future, I expect we’ll see many more examples of companies like MacNeil Automotive Products and Polyform along with natural synergies between scores of seemingly strange bedfellows.
What new partnerships do you think will be proven in time? Drop me a line at Joanna.firstname.lastname@example.org for continued commentary on the new alliances that will come from a need and respect for big data analytics.