Data Driven Chicken Sandwiches

How do you compete in a world of extreme competition, demanding consumers and a shrinking availability of commercial real estate? Well if you’re Chick-fil-a you mix billions of data records, topped with predictive analytics and a side automation to get targeted locations that meet both the needs of consumers and the organization.

In only a few years Chik-fil-a has completely digitized their site selection and the results have been amazing. Site selection, especially for a restaurant that sees a lot of vehicular traffic is imperative to success. Chik-fil-a historically would take pieces of available data like traffic patterns, potential new development, and physical drive-bys to determine new sites.

Using new technologies, Chik-fil-a is able to import massive data sets into their system to analyze and simplify decisionmaking. Chan Lee, enterprise GIS manager for Chick-fil-A’s strategy and analytics team stated:

We’re looking at transactional levels of data.  You’re thinking about billions and billions of records. And that’s great and all, but really what we’re trying to do is trying to figure out, find the signals from the noise

Lee’s team developed a system to import all the available data sets into one centralized system. Taking into account traffic patterns, mapping data, development plans and even cell phone traffic, the GIS team can overlay relevant information on top of a map to get an informed picture of a potential new site. And so far the results speak for themselves. Chik-fil-a plans on opening 90-100 new locations this year.


Why It’s Hot

Data-driven decision making is a proven way of getting the complete picture, but the challenge today is less about finding and obtaining data – but turning those massive recordsets into something useful. Predictive analytic techniques use historical patterns and real-time information to deliver actionable insights. Combined with AI technologies these data lakes can now be sorted, ranked and used to make informed business decisions


what we should eat is defined by our DNA

A startup called Habit is providing personalized nutrition/diet plans and meals based on customers’ DNA. For $299, with few drops of blood and saliva, scientists and nutritionists can tailor nutritional advice specified to your biological make up – what food your body craves, rejects, etc.

Once customers’ metabolic and DNA analyses are gathered, Habit also recommends individual’s health goals through its Nutrition Intelligence Engine algorithm to place them into one of seven Habit types. Each type has different plan specifies the ideal ratio of carbs, protein, and fat in each meal in addition to the TYPES of carbs, protein, and fat their body will respond best to.

Meal plans and access to health coach are further complemented by personalized meals that are delivered fresh to your door – for extra cost of course. Working with biometric devices such as Fitbit, participants can use their devices to monitor their progress and enable Habit staff to input any changes to plans/meals as needed.

Why it’s HOT:

  • this is a business model around hyper personalization, based on individual biological make up, can’t get more personal that this.
  • there will be the growth of converging science/nutrition/data to create consumer facing products and services.
  • Habit was valued at $210 bil by Morgan Stanley Research for its meal-delivery services – with the potential to disrupt and clearly differentiate itself from Blue Apron and other food delivery services.

Snapchat Gets Smarter

Snapchat has taken its capabilities to the next level recently with new filters and lenses, but the channel is now going further to specifically help brands capitalize on these new features. Snapchat is partnering with big data firms to provide better insights on its users to advertisers. Using firms like Datalogix, Epsilon, Acxiom and BlueKai Snapchat will soon be able to tell advertisers how Snapchat users are using their mobile devices to connect with other brands—including what they’ve recently bought, viewed, or downloaded on their phones.

This data coupled with geolocation information will provide brands key insights into the interests and demographics of Snapchat users. Knowing how Snapchat fans are using their phones and what type of content they engage with most often on mobile will allow advertisers to create content on the platform that will truly resonate with their target. The data firms can even tell brands if specific users are millennials so they know whether or not they are reaching their desired audience.



And speaking of Target, the brand has jumped full speed ahead on the Snapchat trend—recently using the platform’s geofilters on Black Friday to engage with customers in the checkout line. Read more about the integration of Snapchat into Target’s holiday campaign here.

Snapchat has recently signed on other big-named brands as sponsors, including Nordstrom and Starbucks, meaning that these new insights could lead to more strategic integration of Snapchat into brand campaigns in early 2016.

Why It’s Hot: Though the partnership with big data is a smart way for Snapchat to lure advertisers, it also provides an opportunity for brands to use the platform in a more effective way than ever before. By understanding the habits of Snapchat users that engage with their channel and knowing other mobile content they interact with, brands can optimize the content they push through the site to deliver what will resonate most with its consumers. The result? Smart, strategic executions that will be authentic and engaging to the consumer.


Snapchat is cutting data deals to lure advertisers

A “Sick” New App

A new app called HEALTHYDAY, developed by Johnson & Johnson, uses sickness-searching algorithms to warn you when sickness in lurking in your neighborhood. The app’s algorithm syncs self-reported data form local doctor’s offices, Google searches, social media mentions on Twitter & Facebook and user data from people using the app, which it funnels down into easily digestible trends, blurbs and infographics. The goal of the app is to answer the question “What’s going around?”. Learn more about the app here.



Why It’s Hot:
This app serves as a best-in-class example of using “big data” to create something educates & addresses a need, while subtly pushing core products in the Johnson & Johnson family of brands.

Making Music with Tennis Data

IBM and the U.S. Open teamed up together for last year’s summer tournament to bring an interesting twist to what is often thought of as an older sport. IBM’s data team partnered with James Murphy of LCD Soundsystem fame to translate the raw data that IBM collects during matches into listenable music. The raw data that is collected passes through an algorithm that James and his collaborators created that eventually spits out something that is pleasing to the ear. Some tweaks are then made by James and tracks are created.

Why It’s Hot:

We often hear the buzzword of Big Data being thrown around constantly but have many different ways of interpreting its definition. Some may say it’s for optimizing experiences, uncovering insights, or seeing patterns that we normally would not have been able to uncover. In this case, the data is actually used as a medium to create art with. There are tons of ways to think about and use data, this just happens to be one of the more creative and sonically appealing.


Twitter Sentiment a Predictor of Heart Disease?

Much has been made of technologies that help track and predict disease geographically. Now scientists have found correlations that might help predict one of the nation’s biggest killers: heart disease.

Researchers at the University of Pennsylvania have analyzed  the language and sentiment in public Twitter data to better understand patterns across the U.S. And in a study of over 1,300 counties, researchers discovered that the level of anger in tweets was more closely correlated with instances of heart disease than 10 other leading health indicators, including smoking, obesity and hypertension.

What the data suggests, however, isn’t that these angry Twitter users are more likely to develop heart disease. Rather, the researchers uncovered patterns that linked higher concentrations of angry users with higher incidents of heart disease by other people in the nearby geographic area. In other words, angry Twitter users could be a sign of geographic stresses that make certain environments more dangerous to live in for maintaining good cardiac health. In other words, angry Twitter users could be a predictor of environmental stress in a given geographic area.

Why It’s Hot

This study demonstrates the power and potential within our social networks and the data we create. Big data analysis offers new opportunities to understand the connections and patterns that go unnoticed in our world every day. And by identifying these trends, hopefully we can invent solutions and remedies to live healthier lives.

Source: NPR

U.S. Government Names Its First Chief Data Scientist

The White House has named DJ Patil its first ever Chief Data Scientist and Deputy Chief Technology Officer for Data Policy. Obama recruited him personally and will work in the Office of Science and Technology Policy. DJ Patil comes from a deep background working with tech and internet companies Skype, PayPal, eBay, and LinkedIn. Patil was instrumental in codifying and inventing the practice of data science, spending 20 years helping companies and organizations measure data, while also writing much publicized papers about data-science for the Harvard Business Review. He has previously worked with the U.S. Department of Defense to use social network analysis to spot growing threats to national security.

In an official White House release, current CTO Megan Smith said, “As Chief Data Scientist, DJ will help shape policies and practices to help the U.S. remain a leader in technology and innovation, foster partnerships to help responsibly maximize the nation’s return on its investment in data, and help to recruit and retain the best minds in data science to join us in serving the public.”

Keynote Speakers At The Minds + Machines 2012 Conference


(photo: Paul Morris/Bloomberg/Getty Images)

Why It’s Hot:

This shows the U.S. governments placing a much needed emphasis on using public data to better design and make better policy decisions for the citizens of the U.S. This has major implications on how policy is shaped and avoiding party bias based on what uninformed political heads want instead of what the citizens need. This also shows the U.S. government seriously pursuing and tempting some of technology’s larger names, helping to avoid debacles like of repeating again.

Customer Experience Platform

With so much data and so many tools, many companies are now issuing dashboards to bring everything together.

The latest is NewBrand, a provider of customer experience software for social listening, analytics, and reputation management. The Washington, D.C.-based company is today launching its new Command Center to surface the most important information in its system.

Any differentiation can help a social monitoring platform distinguish itself in an increasingly crowded category.

“You can [go outside] and spit and probably hit a social monitoring service,” CEO Kristin Muhlner told VentureBeat.

Her company’s system, she said, measures not only social data, but other sources as well, including surveys, point-of-sale, and transactional data.

“Pulling all of that info into a single platform gives us a singular lens,” she said, which is the idea of the Command Center.

The dashboard is intended to present anomalies in customer data and offer alerts about possible issues. There’s also the ability to drill down into more detail, make comparisons with competitors, and share information across an organization.
Why It’s Hot:
We pride ourselves in being a top customer experience agency and how skilled we are in utilizing our tools such as social listening and performance data. Now a tool exists that could be meant for us. This presents not only a new application for big data, but also an interesting opportunity to bridge the data to directly impact our business goals. Is there something we can take from this? Are we able to create a similar solution?

Birth Control Data-fied

Screen Shot 2014-12-12 at 7.18.30 AM

Say hello to daysy, a fertility monitor that learns and tracks a woman’s menstrual cycle, allowing her to plan or prevent pregnancy. Daysy claims to show a woman if she’s fertile or not, with a 99.3% accuracy rate.

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Why It’s Hot:
Daysy is the big data version of an old school method of natural family planning, much like our grandparents generation would have used, that many young adults these days are embracing. The motive is not a factor of trendiness, but rather dissatisfaction with birth control. Interesting to see technology reinvent something once considered old school, and making a more natural option available to women.