Drawing Insights from Big Data Using Gamification

Drawing Insights from Big Data Using Gamification

Big data analytics offers the potential to draw detailed insights about all sorts of behaviors and business decisions. But the benefits of big data do not come without problems. In some cases, the problem is gathering the data itself. In nearly all instances, big data’s challenge it its sheer volume – there is so much information that analysis is incomplete.

Gamification can help. Gamified approaches are typically regarded as tools to engage consumers, motivate workers, or encourage a particular behavior. They can also be applied to data analysis. By improving the connection people have to the data produced, gamification gives data researchers better ways to gather and study data. Even so, using gamification to draw insights from data is often an overlooked tool.

Gamification analytics taps into consumer preferences

Perhaps the most visible use of gamification is in the consumer space. Business-to-consumer companies are trying new approaches to understand customer likes and dislikes as they build support for new products. One example is Dunkin Donuts, a company known primarily for its baked treats rather than its beverages. Dunkin Donuts sees beverage sales as a way to boost revenue. One of the ways that the company has tried to boost beverage sales is by promoting its coffee. Gamification has become a key part of that promotion strategy.

Dunkin Donuts allows its Facebook fans to plan an online game called On Your Mark, which presents a virtual assembly line serving customer coffee orders. The player has to fill a customer’s coffee order in the allotted minute of time, Xconomy explains. As the line progresses, the assembly line gets faster and the coffee cups get bigger. How a player performs earns a chance to win a $10 give card to Dunkin Donuts. The doughnut company certainly benefits from the customer engagement. But PartingGift, the company that developed On Your Mark for Dunkin Donuts, says that there’s more to gain from the game. The gamification platform collects data on players. Before the game starts, players must input their own favorite Dunkin’ Donuts beverage.

“We are looking to figure out what people’s preferences are in terms of beverages – that’s sort of the starting point of being able to understand what we can do with those preferences,” PartingGift CEO Brad Crowell told Xconomy.

The idea for this data collection actually came from the auto industry. Ford and other automakers jumped into the data collection game early with online apps that allowed consumers to design their dream car before going into a dealership, Xconomy explains. That information allowed Ford to produce and deliver to dealerships cars that most closely resembled what the auto-buying public was seeking.

Athletics analysis leads to marketing and more

Analytics has taken over the sports world as athletes, coaches, and managers aim to translate any analytical insight into an advantage on the field of play. But athletics apparel companies also got on board with the analytics trend. Nike developed its Nike Fuel fitness tracking system around the idea of tracking movement via the wearable FuelBand device. Movement translated into points system that offered a way to measure activity and give users motivation to do more.

As an apparel company, Nike’s move into wearable electronics made sense. The company quickly capitalized on its growing cache of athlete data through partnerships with companies that could tap into that data, AdWeek reported. Partners included a company that integrated FuelBand data into employer-sponsored fitness programs, and another company that a reward system to encourage children to exercise. Nike also developed plans for the athletic data it collected, planning to mine the information to shape personalized marketing campaigns.

Nike was quickly eclipsed in the growing wearables market by companies that are pure play technology companies, notes Appcessories. FitBit might now be the best known of the fitness tracking companies. The launch of the Apple Watch introduced a new player in wearables with the capability of gathering the wearer’s vital signs. As Nike fell behind its competitors, it laid off most of its wearables team in 2014. There’s life yet, for Nike’s Fuel ambitions and the data analytics ambitions it introduced. FuelBand lives on as an Apple iOS app, and the company has other fitness apps as well, Appcessories notes.

Turning big data analysis into a game

Gamification has emerged as a novel tool for genetic research. Scientists at the Scripps Research Institute developed a game called Dizeez that helps with big data analyses, according to Fast Company magazine. Dizeez is an online quiz that calls on players to match diseases with the genes that cause those diseases. It starts with well known gene-disease links and increases in difficulty to tackle the lesser known connections. The game covers areas such as cancer, metabolism, immunology, and mental health.

Andrew Su, the Scripps professor who developed Dizeez, explains in a blog post that the amount big data created is growing by leaps and bounds. Some of that data creation assumes that the genes are added to databases correctly and completely. Dizeez works in two ways. First, it helps players reinforce the scientific knowledge that they have. Additionally, and more importantly, the player data aims to reveal links between genes and diseases that are not yet known. That is new information that can be logged into databases, creating connections that could lead to potential new treatments for those diseases. Think of it as crowd sourcing scientists for genetic analysis.

“Filling this gap between the knowledge represented in the biomedical literature and the knowledge in gene annotation databases is the motivating factor behind our interest in games, and more broadly, in community intelligence,” Su says.

Gamification’s place in the data analysis toolbox

Both gamification and big data are big business buzz words today. It might be surprising to some that these two separate concepts actually work well together. Gamification can be a helpful tool to gather data, and in some cases, it can also help analyze that data. Gamification won’t replace the data mining and other traditional tools of big data analysis. But under the right circumstances, gamification has an appropriate place in the data analysis toolbox. Contact us to learn more about how to apply gamification to big data analysis.