Big data has a story to tell – actually a different story for each one of your customers or users. If you pay attention and respond appropriately, the results can be truly extraordinary.
- Big Doesn’t Mean Off-Limits
- Getting Personal with Big Data
- Crowdsourcing as Fuel for a Better Buying Experience
- Better Modeling = Better Results
- Technology to Turn Users into Data Storytellers
Big Doesn’t Mean Off-Limits
As information has grown exponentially in recent years, big data has become a powerful technological ingredient. McKinsey suggests that harvesting the data and analyzing it creatively will result in $300 billion of revenue within the American healthcare system each year. If that number sounds enormous, compare it to McKinsey’s estimate of how much consumer surplus (difference between what consumers are willing and able to pay vs. the actual market price) will go up for companies incorporating device GPS locations with predictive models: $600 billion.
So, we’re talking on the scale of hundreds of billions of dollars. Looking at those huge dollar figures alongside IBM’s estimate that only 10% of our data existed prior to 2013, and the expansiveness of this opportunity becomes mind-boggling, even intimidating.
“Given the enormity of the data sets … and the logistical (and sometimes touchy) issues that accompany its use,” says Distilled outreach director Adria Saracino, “is it any wonder that big data has come to be regarded as a resource best utilized by … the Googles and Microsofts of the world?”
Why is it a mistake for SMB’s to think that big data is a field reserved for Silicon Valley enterprises? Simply put, that hesitation offers their competition a powerful advantage.
Getting Personal with Big Data
Looking at the data en masse obscures the fact that it is essentially granular. That granularity could allow you to have more personalized, and hence more impactful, interactions with customers.
Amazon is perhaps the best example of a company optimizing user experience by customizing based on your purchases and pages you access. It’s not the data that they are collecting that counts but the way that they are using it.
“Amazon has been collecting my information for years,” comments Ziba marketing director Sean Madden. “And while dozens of other companies do that, too, Amazon’s doing something remarkable with theirs. They’re using that data to build our relationship.”
How else is big data being used successfully? Let’s look at one example each from the private and public sectors.
Crowdsourcing as Fuel for a Better Buying Experience
Fast-growing vintage clothing site ModCloth customizes each shop by getting its customers engaged in every possible way, using crowdsourcing approaches to increase communication both within the customer community and with the business.
The ModCloth project that is the most impressive to Saracino is “Be the Buyer,” which allows customers to vote on products, basically giving them a thumbs up or down. The products that get the highest ratings are then categorized as “Be the Buyer” selections.
Okay, so how valuable is what they’re doing? Well, it allows the customer community to be more group-aware essentially, with almost 7000 shoppers voting on each item at this point. What results is a much, much better sense of what is going to sell well. There is no reason to leave a product on there for six months if it scores poorly. And items that should be featured are, automatically. It’s better to be inundated with user preferences now than to slowly gather bits and pieces of their perspective over time.
Big data is essential to the way that ModCloth sells, which in turn defines the experience. “The dialogue that develops between brand and customer is valuable to both parties,” says Saracino. “ModCloth knows what its customers want and its customers can easily see that their input informs the brand’s inventory.”
Better Modeling = Better Results
Well, sure, you can sell more handbags and skirts with big data, but tapping this resources isn’t just about sales. It can even help with education. The public schools in Mobile, Alabama, used predictive modeling to lower their high school dropout rate. In 2010, 45% of students were completing high school – which means that for every 11 kids who were graduating, 9 kids weren’t.
It was really hurting the local area, and something had to be done. When administrators started exploring the data they had available for students who ended up dropping out, the situation became much less confusing.
“For example, they found that suspensions and serial absences frequently preceded a student’s decision to drop out,” notes Saracino. “This knowledge allowed the school to flag students displaying these risk signs.”
Impressively – really, shockingly – Mobile has increased its graduation rate from 45% to 70% using its predictive model. Let’s look back at that idea of 20 people – now for every 14 people who graduate, you have 6 who don’t. That’s just an incredible difference.
Technology to Turn Users into Data Storytellers
Big data can help us create stronger relationships with our customers or users – to know just what they want. It can help us improve society, with more teens get high school diplomas. It most certainly can help us save lives through precision medicine. The possibilities are really endless; you just need the right technology to implement your ideas.
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By Kent Roberts