Watching live sports can get very emotional, even for the fans sitting in front of their TVs. That’s why Fanmode, a London-based startup, is developing an app to help the audience express their feelings and be heard. The company even has plans to integrate the app into wearables for easier reaction tracking. By aggregating real-time sentiment data during live sport events, Fanmode’s platform would be transformed into a virtual arena, where all fans are connected to the action. It could also potentially open up a feedback loop between the fans and their teams, essentially revolutionizing the way we watch live sports.
Tag: big data
What Big Data Can Do for the Beauty Industry
Poshly, a New York-headquartered data company, just received $1.5 million in seed funding. Their secret? Bringing big data to the beauty industry on a “hyper-personal” level. By gathering data on individual user’s beauty regimen and interests, Poshly can generate insights on their personal preferences and help beauty brands better understand their costumers.
RFID Tracking Chip To Be Placed On Every NFL Player
You get a tracker. And you get a tracker. Everybody in the NFL games is getting a tracker! Oprah jokes aside, the trend towards big data has made its way to another stats-friendly domain: sports. The National Football League announced today that it is teaming up with Zebra Technology to deploy in-game player tracking chips in 17 stadiums for the 2014 season, effectively generating a myriad of proprietary new statistics in real time.
Two RFID chips will be place on each player’s shoulder pads and will provide various data, including positioning velocity, acceleration, distance run, and impact measurements, to Zebra’s real-time location system (RTLS). This move could transform the way teams and fans evaluate the personal performance of every NFL player, potentially changing the way America watches its favorite sport.
Google Looking To Turn NYC Payphones Into Wi-Fi Hotspots
Over 7,300 payphones in New York City may be transformed into something much more relevant in this mobile age, as Google proposes to convert them into free Wi-Fi hotspots. If completed, this project would basically blanket the whole city with Google-owned Wi-Fi networks, which in turn would benefit the Internet giant greatly with user location tracking and other valuable marketable data. Similar to Facebook’s lofty plan to bring free Internet access to the whole world, Google is looking to move closer towards the inevitable future of big data and ubiquitous computing.
Off Target: Retailers’ Big Data Management Fails
It is a truth universally acknowledged, that a modern consumer in possession of a retail membership card, must be tracked in collection of purchase data. Privacy and prejudice aside, however, people seems more than willing to offer up their personal information in exchange for some monetary rewards or membership benefits.
But what if your retailer figures out something personal through data tracking and starts doing something with that information without your consent? Starting with the Target pregnancy score scandal, in which a father found out about his teen daughter’s pregnancy through a baby product-heavy mailer, retailers as diverse as J.C. Penny and BestBuy and small tech start-ups like SceneTap have all been caught in the cross-fire of consumers’ indignation over privacy violation. Most recently, Target once again found itself in a comprising position with the media exposure on a widespread credit card breach affecting over 110 million Target shoppers. The incident alarmed a lot of previously unsuspecting customers and highlighted another landmine field of big data mismanagement—security concerns.
All these controversies have sparked several rounds of national debates on privacy and consumer rights. Still, the debates prove to be futile, as businesses continue to collect data from their customers without much protest. The conclusion here is that most people don’t really mind being tracked if they receive some value from it, and if their data remains secure. Retailers must behave responsibly with data and learn to manage it better if they want to remain in the good graces of consumers.
By The Numbers: Big Retail Data
Arguably the most established commercial application of big data is the way retailers have been tracking and building their consumer database. Whether through building consumer profiles, analyzing purchase records, or even tracking in-store movements, data can reveal unexpected insights:
- With systems in place to analyze unstructured data, retailers can now experience an uplift of 18 to 22% by doing simple behavioral profiling based on clickstreams.
This statistic, reported on retailcustomerexperience.com by Tushar Montaño and Monica Pal, highlights a big reason why retailers are jumping on the big data train.
Scouring through the consumer data for competitive advantage has become somewhat a standard practice among big retailers. Retailers like Zappos and Amazon are now also using personal data to develop customer relationships that could lead to brand loyalty. And if a simple, clickstream-based behavioral profiling could bring an increase of around 20% in purchases, imagine what the newer technology, such as measuring window conversion rates to measure storefront displays and connecting outdoor ad exposure to store visit through the WiFi-based platform, could lead to.
- In 2010, just 1.7% of small businesses were using business software; by last year, 9.2% had adopted such tools.
Reported in New York Times by Ray Boggs, the small-business market analyst at IDC cited easier-to-use products and lower prices as prime drivers of the growth.
The sharp increase of small business embracing intelligence databases nicely dovetails with the trend within big retail chains to track customer purchases with memberships and teaming up with credit card companies. While small business might not always have the recourses to handle the same amount of data those bigger retailers have, nevertheless they could leverage the limited but crucial data they could manage into building a rewarding, intimate relationship with their customers.
The followings are some of the key findings from Inmar 2014 Coupon Trends Report:
- Manufacturer digital offers in market are up 250%
- The number of digitally connected loyalty shoppers is up 40%
- Growth in digital coupon redemptions is up 141%, with over 66mm redeemed
While retailers have gotten fairly accustomed to managing the information they put out on traditional media sources, most of they are still trying to make sense of the new digital and mobile media. It is important to note that these fast growing new media offers the retailers far better channels for data acquisition, whose potential has yet to be fully explored. But with mobile-influenced offline retail sales expected to reach $700 billion by 2016, according to Deloitte, figuring out how to fully engage the online and mobile customers becomes increasingly crucial.
Me Want Cookies: Advertisers Pay 3X More For Interest-Based Ads
A study from the Digital Advertising Alliance found that advertisers will pay 3x more for cookie-based ads and 7x more if the cookie is 90 days old. Amidst White House efforts to review privacy implications of Big Data this week, groups like the IAB and DAA are hoping these numbers will position advertising as the lifeblood of the internet. For instance, 60% of small websites ad revenue comes from interest-based ads. Yet, the industry will need to do a better job of being transparent and educating the public on data and targeting if they want to maintain consumer trust. Companies like Enliken are already doing that, providing a service to ad networks and brands which makes it easy for the public to see which consumer segments they have been categorized in.
Stantt Uses Big Data To Size Clothing
The conventional wisdom surrounding clothing is that it fits into three simple categories: small, medium, and large. Stantt, a company that’s looking to meet its funding requirements via Kickstarter, hopes to change that in one of the more interesting applications of big data to a classic problem. Stantt started by 3D body scanning over 1000 men, ranging in age from 25 to 35, and each scan included approximately 200 body measurements. They then developed an algorithm – which extrapolates from chest width, waist width, and arm length, all common, at-home measurements – that determines which of over 50 sizes fits the individual. Though Stantt faces competition from the increasingly common ‘made-to-measure’ online sphere, Stantt is among the first fashion-oriented brand looking to leverage data to improve something we’ve considered standard for years.
Walmart Doubles Down On Big Data
This week Walmart acquired analytics startup Inkiru, adding to its portfolio of capabilities in their Walmart Labs arm. The move will enhance their predictive analytics capabilities so they can improve site personalization and marketing efforts.
What makes this deal especially powerful is that Walmart has so much data to analyze, they serve as a great case study in the power of analytics.
Inkiru’s primary focus areas include New User Activation for e-Commerce, Credit Risk analysis and Customer Targeting.
Gartner’s 2012 Hype Cycle for Emerging Technologies Identifies “Tipping Point” Technologies That Will Unlock Long-Awaited Technology Scenarios
“The Tipping Point” – Gartner’s 2012 Hype Cycle for Emerging Technologies
