Analyze This

Big Data is no small matter, that much is clear. But how can companies capitalize on the trends of today to see results tomorrow?

Back Longreads Jan 10, 2017 By Russell Nichols

In 2015, Lance Loveday found himself drowning in data.

The self-proclaimed “Growth Whisperer” had been running his digital advertising agency, Closed Loop, since 2001. Helping a range of brands from PayPal to Crate & Barrel, he built a reputation as an online marketing guru. He co-wrote the online business book, Web Design for ROI, on how to turn virtual window shoppers into real customers.

Still, something was wrong. The web had changed a great deal since he started. “Big Data” — a phrase for the massive mess of online data that can be mined for information — wasn’t even trending back then. By 2010, the advertising ecosystem had become fragmented, an archipelago of scattered platforms from Google to Facebook to Twitter to Bing. Loveday couldn’t afford to spend hours upon hours wrangling data for clients, so he did what any overworked entrepreneur would do: He started another business.

His new Roseville-based startup, called Forager, is an advertising data pipeline that funnels data from various platforms into a single feed to be analyzed. “We went from old-school Excel-based charts and graphs, which were ugly and manual, to nicely formatted data visualizations,” he says. “The insights jumped off the page at you.”

We’re living in a different world now where it’s really information that will be the differentiator. The product is important, but data and the information you can derive from that will be the key difference for firms in today’s data-driven world.”Ashwin Aravindakshan, associate professor of marketing, UC Davis Graduate School of Management

It was initially built as a time-saving tool for internal use at Closed Loop. But Loveday soon realized the product could help online advertisers spend time building campaigns instead of mining data. Once it was set up, all they would have to do is click refresh for new insights on interactive data sheets or visual maps that show, for example, which cities are eating the ad budget but producing no returns. With this automated tool and its reporting templates, marketers could save on average 30 hours monthly, Loveday says. After a year of beta testing, Forager is set to launch this month.

“It sounds kind of boring honestly,” Loveday says. “We’re selling people access to their own data. But there is latent demand out there. A lot of people are trying to figure out how to get data into their analysis tool of choice. When they hear we have a universal advertising data connector, they say, “Thank God, let me have that!”

This is the new age of advertising, a digital world dominated by big data, controlled by those who know how to handle it. New technology, such as mobile devices and smart speakers, has opened the door for advertisers to track everything from customer locations to spending habits. For convenience, some customers give up their personal information knowingly (e.g. online surveys). Others do so unknowingly (via third-party cookies that track web activity). Either way, for the people trying to sell things, big data is the golden egg. And companies that know how to collect and capitalize on this data will have a clear advantage over the more data-averse, says Ashwin Aravindakshan, an associate professor of marketing at the UC Davis Graduate School of Management.

“We’re living in a different world now where it’s really information that will be the differentiator,” Aravindakshan says. “The product is important, but data and the information you can derive from that will be the key difference for firms in today’s data-driven world.”


Compared to the analog days of paper trails, the information age is complicated. The unruliness of big data can create unprecedented challenges as companies demand faster results to stay competitive. Reliability, for example, isn’t always assured due to the volume of data produced.

The sheer amount of data out there is staggering by galactic standards, according to market research firm International Data Corporation. “Like the physical universe, the digital universe is large — by 2020 containing nearly as many digital bits as there are stars in the universe,” IDC wrote in a 2014 study. “It is doubling in size every two years, and by 2020 the digital universe — the data we create and copy annually — will reach 44 zettabytes, or 44 trillion gigabytes.”

Related: How Entertainment Companies Use Big Data

So how would a company bring these gigantic numbers down to size? By zooming in to target individual consumers more effectively, Aravindakshan says. Most of the digital data comes from them: phone calls, emails, location settings, movie downloads, etc. It makes sense for advertisers to convert this personal information into selective marketing strategies.

Humanyze creator Ben Waber calls his in-office analytics generator a “Fitbit for your career

“I think almost every aspect of our behavior can be quantified in some way,” Aravindakshan says. “If I know how many pages you browse before making a decision, I want to try and see if I can optimize the steps you take. I do that by trying to show you products you’re more likely to buy.”

Websites track views and mobile devices pinpoint locations, but Aravindakshan says the Internet of Things — connected devices that collect and exchange data — will take personal monitoring to a new level in no time. Just imagine, for example, a smart refrigerator that knows exactly when a person is running low on milk. “This is information that stores like Safeway would kill for,” Aravindakshan says.

Facebook and Google have dominated the industry with personalized, relevant ads for users. But beyond those platforms, media companies struggle to target consumers effectively because the browser world doesn’t connect to the app world. These companies may be able to identify users inside of an app, but users don’t typically log in on the web, so it’s harder for advertisers to tell who they are. To solve this problem, Carla Holtze co-founded Parrable, a San Francisco tech firm, and created a platform that enables marketers and publishers to deliver personalized content to users no matter what device they are on.

“If I’m spending millions of dollars to reach my users, I don’t want to spray and pray,” says Holtze, who was recruited by the Greater Sacramento Economic Council and chose Sacramento last year to be the site for Parrable’s dual headquarters. “I want to be targeted, I want to be relevant, I want to reach the right person.”


Instead of gazing into the abyss of potential customers, Ben Waber set his sights on a different space: the workplace. Time and again he found that data-driven companies focused on tracking consumer trends had almost no real data on the inner workings of their own organizations.

“How much does the executive team talk to the engineering team? Or the sales team?” Waber asks. “How much do you actually ever talk to a customer? Nobody knows the answers.”

His research began at the MIT Media Lab with the concept of “sociometric badges.” These are tricked-out ID badges that use microphones, infrared sensors, accelerometers and Bluetooth to monitor employees at work via key identifiers: movement, interactions and speech patterns. This method of people analytics is the basis for Waber’s Boston-based company, Humanyze, which he says uses “technology to measure the value of human interaction.”

Typically, companies conduct surveys or hire consultants for internal support. Humanyze measures the impact of management and environmental factors through two different approaches. In the first one, Humanyze hooks into the company’s digital data such as email, messaging apps and phone. The team does not look at the content, but analyzes different elements such as schedules and meeting times to see how that relates to performance metrics.

The second approach involves the sociometric badges. Again, Humanyze is less interested in what individuals say, but how they say it and to whom. Are managers dominating the conversations? Which departments are talking to each other? The process takes about four weeks to deploy at a company. Workers can choose to opt out.

“Companies today aren’t thinking hard enough about giving consumers not just a choice but control over their own data.”Ben Waber, founder/CEO, Humanyze

After at least a month, Humanyze can offer real feedback. For example, the results can show that when co-workers eat lunch together, it doesn’t just make people feel good, but also raises their performance levels. Other tactics that boost productivity include non-assigned seating and mass break times. These types of results showed Waber that social mechanisms improve performance more than new training or revised work charts.

Data gathered from the badges isn’t made public. This is private information for individual employees to use to track their own patterns and areas for improvement — a “Fitbit for your career,” as Waber calls it. He believes this method of empowering individuals through data should be a model for advertisers.

“Companies today aren’t thinking hard enough about giving consumers not just a choice but control over their own data,” Waber says. “A lot of advertisers are focusing on hyper-targeting an individual. They want to know where you are, what you need, what ad you respond to. But they shouldn’t care what your location is. All they need to know is when to serve you a particular kind of ad.”


For Sacramento Kings Owner Vivek Ranadivé, analytics is the most valuable player in the Big Data game. In 2014, the tech visionary and founder of TIBCO connected with Humanyze to bring the high-tech badges to the Kings’ sales team. From this experiment, they learned that the reps who talked less and moved through the stands more sold twice as much as their peers. As a result, the staff scrapped cold-calling and tripled their in-game sales from 2014 to 2015.

Related: Big Data, Big Demand

With the opening of the Golden 1 Center, Ryan Montoya, the Kings’ chief technology officer, was on a mission to transform the fan experience using data. Working with technology partners, his team created fan and customer profiles that users can manage through the Kings/Golden 1 Center app. All data is collected on an opt-in basis. Fans can provide as much information as they want, which Montoya says will allow his team to provide rewards tailored to each guest.

After the user signs in, Montoya can track customer movements and supply real-time data. Software pioneered by Ranadivé will use this data, linked with customer accounts and other features to create what Montoya calls a “hyper-personalized guest experience.” Fans will even have the ability to influence the temperature in the arena.

“It really enhances the fan experience, even before you get to your seat,” Montoya says. “With all of the emerging technology in the building and beyond, we can help plan your transportation and select your parking in advance, process guests into the arena faster, eliminate the need to pull out your wallet to pay.”

Montoya emphasizes that privacy is a high priority. Personal data will not be sold. But this trend of people giving up personal information for a certain benefit has truly taken off in the past 15 years, Aravindakshan says. Of course, advertisers aren’t the only ones vying for this valuable data. Hackers are always on the prowl, looking to vulnerable spots to breach. And as the big data gets bigger, Aravindakshan believes the world will continue getting smaller.

He points to the January 2015 issue of Science magazine, where a review titled “Privacy and human behavior in the age of information” highlights key factors that influence people’s behavior about privacy. One of them is malleability, which shows how easily people can be manipulated by governmental and commercial entities to disclose private information.

The report also notes that default settings also play a role. From 2005 to 2014, as Facebook grew, the default visibility setting became more revelatory with users sharing more personal information with larger audiences unless they manually overrode the defaults.

“Most people thought that nobody would exchange so much private information for surfing online,” Aravindakshan says. “There might be ups and downs, but the trend is definitely toward less privacy.” 


Fernando Vellanoweth (not verified)February 7, 2017 - 4:14pm

Very good article on big data... Ruth McCartney (sister of Paul) also is a very educated on this subject and has presented to large groups. I am interested in talking with Russell Nichols about making a presentation to an association of information professionals in Sacramento