What is DigiPref and why we believe you need one?


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Every human being on this planet is unique. Different needs, priorities, and preferences.

When you book a reservation at a hotel and walk into the hotel, you expect certain level of service. Often times, hotels don’t know what you like or prefer. Although you can specify the type of bed, smoking preferences, etc, there are certain small but equally important things a hotel can do to make your stay perfect. As an example, you may prefer a room which is easily accessible, far away from noise, etc.

Similarly when you go to a friends party, you have certain food preferences. It is almost impossible for the host to satisfy everyone’s needs without knowing their food preferences.

DigiPref will allow you to create your preferences profile and make it available to whoever you want them to see. This will enable you to add your preference once and share as many times as you want. You can search for other people preferences before you host a party or some event.

We will be in private beta soon. Watch for more updates soon on this blog.

How are retail and other companies using data?


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Below are some of the ways organizations are using your data. In some cases, the data is publicly available and in other cases, this data is collected when you walk in a store or a hotel. While the intentions may be good to provide you good services, the fact is no one is watching them. Who will ensure that these organizations are not overreaching? Most importantly, what can you do about it? This article provides some of the examples below on how your data is being used. Follow this blog to get more thought provoking articles and blogs on your data when we publish it.

 

1. Kohl’s is testing real-time, personalized offers in five of its stores. Shoppers who walk into one of those stores can opt in for offers via their smartphones.  So if a shopper lingers in the shoe department, for example, they’ll receive a coupon based on the shoes they looked at online but never bought.

2. Big data has given Vera Bradley insight into what shoppers want while delivering a return on investment for the retailer/supplier of colorful quilted handbags. The company switched from sending shoppers blanket email promotions to sending targeted offers based on individual shopper purchases.

3. Target for one, uses “social sentiment data” – insight gleaned from social networks — to monitor how shoppers respond to its designer collaborations, said Melissa Flicek, director of project delivery for Target.com.

4. Hotel Chain Uses Big Data to Increase Bookings: Bad weather reduces travel, which then reduces overnight lodging. That’s not good news if you’re in the hotel business. However, Red Roof Inn turned this trend on its head. The hotel chain recognized that cancelled flights leave travelers in a bind and in need of a place to sleep overnight. The company sourced freely available weather and flight cancellation information, organized by combinations of hotel and airport locations, and built an algorithm which factored weather severity, travel conditions, time of the day and cancellation rates by airport and airline among other variables. With its big data insights, and recognition that travelers will be using mobile devices for this use case, the company used Search, PPC and SoLoMo mobile campaigns to deliver targeted mobile ads to stranded travelers and make it easy for them to book a nearby hotel. This big data payback is compelling. Flight cancellations average 1-3% daily, which translates into 150 to 500 cancelled flights or around 25,000 to 90,000 stranded passengers each day. With its big data and geo-based mobile marketing campaigns Red Roof Inn achieved a 10% business increase from 2013 to 2014.

5. Pizza Chain Earns More Dough in Bad Weather: A pizza chain uses a mobile app and mobile marketing techniques to deliver coupons based on bad weather or where power outages leave consumers unable to cook. This mobile and location-based marketing campaign achieves a 20% response rate.

6. Music distributor Applies Big Data for Demand Planning: Record label EMI uses big data to measure and forecast product demand. After distributing or leaking music, the company measures consumption on its own social networks and additionally acquires third party listening pattern data from popular music streaming services, song identification apps or ‘second screen’ social media collators. The data is aggregated by demographics, locations and subcultures and helps the music distributor deliver pinpoint advertising and forecast product demand with a high confidence level. This concept is applicable to other retailers who can also aggregate feeds from social networks to build an understanding of how new products will be received by new or existing markets, or even how their products and company reputation are perceived among the public.

7. Financial Services Company Scores New Clients: After incurring low win rates for new client acquisitions, a financial services firm turned to big data in order to better identify which new client opportunities warrant the most investment. The company supplemented its customer demographic data with third party data purchased from eBureau. The data service provider appended sales lead opportunities with consumer occupations, incomes, ages, retail histories and related factors. The enhanced data set is then applied to an algorithm which identifies which new client leads should receive additional investment and which should not. The result has been an 11 percent increase in new client win rates while at the same time the firm has lowered sales related expenses by 14.5%.

8. Retailer Creates Pregnancy Detection Model: In a near infamous retail big data example, retailer Target correlated its baby-shower registry with its Guest ID program in order to determine when a shopper is likely pregnant. Target’s Guest ID is a unique consumer ID that tracks purchase history, credit card use, survey responses, customer support incidents, email click-throughs, web site visits and more. The company supplements the consumer activities it tracks by purchasing demographic data such as age, ethnicity, education, marital status, number of children, estimated income, job history and life events such as when you last moved or if you have been divorced or ever declared bankruptcy.

9. The Huffington Post recently touched on one of America’s most beloved retailers, Costco. Costco needs no introduction as the big-box retailer with free food samples, to-die-for food court and excessively large toilet paper packages. Most people know this. However, most people don’t realize just how active Costco is in the big data game. Every purchase by every customer is tracked and meticulously recorded by the giant retailer. Costco uses this information for a variety of purposes. One practical use is to contact customers in the event of product recalls or other safety concerns about purchased items. For Costco, it was a recent fruit recall by a California-based packaging company. Following the recall Costco immediately went to its records to determine which customers had purchased the tainted fruit. Within 24 hours Costco knew which customers were potentially affected by the recall. Phone calls and emails began to be issued to customers, and what normally is a retail nightmare turned into another opportunity to strengthen customer loyalty. Customers praised Costco’s response to the situation and expressed appreciation for the effort. Maybe big data is a miracle, turning a product recall into a point of praise. Whether or not this is considered creepy, you can sleep well at night knowing Costco has your back with the help of big data.

10. Target is known lovingly as the ‘upscale’ version of Walmart. Target is one of several companies to recently succumb to a massive data breach that left customers seething. Any data breach is a worst-case-scenario for retailers. For Target, the breach left millions of customers and their credit card information exposed. Perhaps it wasn’t just the data breach itself that ruffled customer feathers, but the slow and somewhat calloused response. Affected customers received what would later be referred to as “the letter”. Target belatedly sent a letter to inform potentially affected customers. Addressed from the CEO, it read “I am truly sorry this incident occurred and sincerely regret any inconvenience it may cause you.” Target misused big data in two ways. First, it failed to protect the massive stores of customer data in the company server. If a large retailer thinks it has the ability to utilize customer data to provide a better buying experience, great. But there needs to be an assurance that data breaches are avoided at all costs and minimized when they do eventually come. Second, Target used its customer information to send notification of the breach, but the notification was at best lacking sincerity.

References:

1. http://www.crmsearch.com/retail-big-data.php

2. http://www.forbes.com/sites/barbarathau/2014/01/24/why-the-smart-use-of-big-data-will-transform-the-retail-industry/2/

3. http://customerthink.com/can-big-data-save-retail-good-and-bad-examples-of-using-big-data/

4. http://www.ibmbigdatahub.com/presentation/big-data-retail-examples-action

Examples of Companies Using Big Data in an Invasive Manner


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What’s the average age of someone who steps in your store? Do your buyers tend to be male or female? What week of the year brings the most visitors to your website?

Knowing the answers to these questions—and many more—will result in higher profits, customer satisfaction and repeat visits, a better workplace environment, and more. Understanding how to interpret and leverage big data is the difference between developing highly targeted customer strategies and falling behind in the marketplace by developing generic “tent” strategies.

Companies can collect customer data in many ways, from asking for customers’ phone numbers and postal codes at the checkout, to asking for customer information when someone tries to sign up for the corporate newsletter on the company website, by analyzing Google Analytics, by buying customer data from companies dedicated to data mining, and much, much more.

But what about companies that realize the power of using big data… and go to far? There’s a difference between being on the cutting-edge and being too invasive. For these companies, customer data is being used in the name of “understanding customers,” but borders on 1984 style surveillance.

Let’s take a closer look at some examples of companies that are being too invasive in the way they obtain and use customer data:

Nordstrom

Nordstrom, a fashion retailer with stores across America, is a popular shopping destination for people looking for high-end items and potential deals. Nordstrom has experimented with using technology to gather user information and present a tailored experience for individuals as they browse Nordstrom’s aisles, such as through the use of Apple’s iBeacons, but took it a step too far starting in 2013.

Starting that year, Nordstrom began testing new technology that allowed various Nordstrom’s locations to track its customers’ movements by following the customers’ smartphone’s Wi-Wi signals.

The technology allowed Nordstrom to watch customers as they shopped, gathering data along the way. Video surveillance and signals gathered from customers’ cell phones and mobile apps gave Nordstrom insight on how customers browsed the store, how long they looked at items, the customers’ gender, and more.

Some of the customer concerns raised over this new initiative were discussed in the New York Times article Attention, Shoppers: Store Is Tracking Your Cell, including:

“Way over the line,” one consumer posted to Facebook in response to a local news story about Nordstrom’s efforts at some of its stores.

“The idea that you’re being stalked in a store is, I think, a bit creepy, as opposed to, it’s only a cookie — they don’t really know who I am,” said Robert Plant, a computer information systems professor at the University of Miami School of Business Administration.

“The creepy thing isn’t the privacy violation, it’s how much they can infer,” s aid Bradley Voytek.

The core issue at-hand in this case isn’t that Nordstrom is tracking its shoppers, but doing so in a way that’s both extremely invasive, and without permission or consent of the shoppers. Wi-Fi on smartphones is normally enabled non-stop, and surveillance cameras are necessary for any retail location—it’s invasive, but can be done because Nordstrom is taking advantage of the tools readily available at their disposal.

Facebook

Facebook is often referenced when discussing companies that harness their users’ personal data in invasive methods.

The way people use Facebook, and what Facebook does with its users’ data, has impacts across nearly every industry and sector, from fashion retailers to fast-food chains, and more.

There are a number of ways in which Facebook is overly invasive in the way it tracks and uses its users’ data. The first is by tracking your movements (assuming you are a Facebook user) across the web for up to 90 days—even if you’re logged out of Facebook. If you visit a website that has a Facebook plug-in, which is the vast majority of websites in 2015, your IP address, date and time on the site, and more, is all being collected by Facebook. Facebook then uses this data to show you a personalized experience on that site—whether or not you want it, and even if you don’t want your data to be used in that manner.

But companies, and other individual users, can simply search for you and use your data in however manner it wants. Facebook used to have a security feature where people could opt-out of being publicly searchable—essentially hidden from people that they didn’t know—but recently removed this feature, while simultaneously making it mandatory for users to all show a minimum amount of information, even if users don’t want to. This now means people, including store managers at brick-and-mortar stores (for example), can look up your information and see your date of birth, what city you live in, what your pictures are, and potentially even more, and use this information to their advantage (if needed).

And if you ever decide to leave Facebook—and even go as far as to delete your account—Facebook will keep your data forever, including comments that you’ve posted on a company’s Facebook page. There are certain items that Facebook does get rid of, but most exchanges you’ve made on Facebook are kept forever—ensuring that your data will get used, even if you no longer have an account.

Target

Target, a retail company based in America, carries everything a family would need, from diapers to high-tech electronics. With the sheer number of items on their shelves, and people from all income levels and backgrounds coming into their store locations by the millions on a daily basis—and online on Target’s website—there is a real need to know and understand who their shoppers are.

But as outlined in this 2012 New York Times article titled How Companies Learn Your Secrets, Target’s need to understand their buyers can get highly specific at times:

Because birth records are usually public, the moment a couple have a new baby, they are almost instantaneously barraged with offers and incentives and advertisements from all sorts of companies. Which means that the key is to reach them earlier, before any other retailers know a baby is on the way. Specifically, the marketers said they wanted to send specially designed ads to women in their second trimester, which is when most expectant mothers begin buying all sorts of new things, like prenatal vitamins and maternity clothing.

Target assigns each shopper a unique Guest ID number—a code that helps Target keep tabs on everything that individual shoppers do and buy as it relates to Target. If an individual enters a Target contest online, buys a shirt at Target, and uses a gift card to buy that shirt, all three of those points then become linked with that unique Guest ID number.

But the Guest ID number goes even further: it’s linked to, “demographic information like your age, whether you are married and have kids, which part of town you live in, how long it takes you to drive to the store, your estimated salary, whether you’ve moved recently, what credit cards you carry in your wallet and what Web sites you visit.” Target can go even further and buy data about you from companies specifically designed to sell data—data that includes your, “ethnicity, job history, the magazines you read, if you’ve ever declared bankruptcy or got divorced, the year you bought (or lost) your house, where you went to college, what kinds of topics you talk about online, whether you prefer certain brands of coffee, paper towels, cereal or applesauce, your political leanings, reading habits, charitable giving and the number of cars you own.

In short, Target knows everything about you if you’ve shopped at their stores once or twice—with the possible exception being if you’ve only ever paid with cash and refused to disclose any personal information about yourself on Target’s website or in-store.

While the information is being used and analyzed in order to target deals and items specific to your interests, it becomes invasive when you step back and ask yourself: am I comfortable with a company knowing everything about me?

Conclusion

Companies of all sizes, industries, and verticals are using your data—but there’s a tipping point where the data use goes from “acceptable” to “invasive.” Every time you sign up for a company newsletter, create a new social media account, pay with a credit card, and more, you’re signing over a piece of your personal information. As consumers, we need to be more careful with how our data gets used—and if possible, put the power back in our hands by choosing what gets shared to our own advantage.

How a common man can use data to his advantage


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“Big data” is a scary concept to the everyday man or woman. The name alone holds weight and connotations that invoke images of companies following your every step and knowing more about you than even you know about yourself. In 2015, in short, there is a disconnect between the common man and the large corporation in regards to what the value of big data is.

But let’s take a step back. The common man or woman—the small business owner, the freelancer, the website designer, or just the curious individual—can use data to his or her advantage, and it doesn’t involve investing a significant amount of time or resources to do so.

The fact is, “data” can refer to so many things. Gender, diet preferences, age, and more, can all be considered as part of a data set. Data doesn’t have to be complicated, nor it doesn’t have to be “big.” Most importantly, you—the everyday hard-working person—have the advantage of being able to leverage your own data to your advantage, in addition to analyzing other people’s data to help your own business ventures.

You may be using and interpreting your own data without realizing it. How did it take for you to get to work today? The answer in your mind is the beginning of a new data set. What if you leave your house 10 minutes earlier for work tomorrow? The result of doing so is another mark you can add to the data set. All of a sudden, after just two days, you’ll know whether or not leaving your house 10 minutes earlier has no impact on your commute, makes it faster, or, somehow, makes it longer. This is data in action, specifically, this is you using your own data for your own advantage.

There are several tools you can use online, on your television, on your phone, and more, that give you the ability to use data to your own advantage—in a more beneficial manner than simply figuring out optimal commute times. Here are some ways that your own data can be used to your advantage:

Google Analytics

Google Advantage is one tool that nearly everyone with a website—from a simple landing page, to a website with 100 pages and separate microsites—uses to understand visitor information.

For you, whether you’re a freelance photographer or a one-person marketing team at a small business, Google Analytics is the best option to understand how people interact with you and your company.

If you’re self-employed, you may not have a big budget to splash out on things like web development, advertising, AdWords, freelancers, contractors, and more. Your time is tight, your budgets are low, but Google Analytics is a tool that you can spend guilt-free time on. Your site could be hosted on Squarespace, Tumblr, WordPress, and other DIY services, but you’ll be able to see where your visitors are coming from (country), time spend on site, site flow, bounce rates, click-through-rates, and more.

For you, Google Analytics is the easiest way to use other peoples’ data to your own advantage in an unobtrusive manner, even if you have no prior experience with understanding, analyzing, and interpreting data.

Netflix, Amazon, Apple

Data doesn’t have to be complicated, sometimes it simply requires watching a TV show or buying a book—and that’s it. With Netflix and Amazon, you give up your data in exchange for personalized recommendations—the companies understand your preferences, and provide you with similar, targeted content in exchange for you continuing to use their services.

“Rather than just take take take, why can’t more companies give back, reflect our data back on us? Doing this in a real, honest way has to create some business value,” says Bruce Upbin, author of How Intuit Uses Big Data For The Little Guy for Forbes.

“Netflix, for example, takes all of its customers’ viewing habits and movie ratings and runs them through a sophisticated algorithm to generate the 5-star recommendation system tailored for each subscriber.”

Other websites and services take a similar approach of using your data to provide you with recommendations. Goodreads, a site for booklovers, provides you with recommended reads after you’ve rated 25 books you’ve read—it uses the ratings you’ve left for the 25 books you’ve read (the genres you favored, the authors, the page count, the year published, and more) and becomes more and more targeted after every book you rate. YouTube simply analyses what videos you tend to watch and then provides similar recommendations every time you visit the site.

Even with Apple’s iTunes, the more music you play—the more data you’re voluntarily giving up on what artists, songs, and genres you like—the more information gets sent to iTunes’ “Genius” feature. Genius makes playlists from the songs in your music library that go great together, and that you would like to listen to, but also introduces you to movies, TV shows, and music that you might like, but that you don’t currently have. In this sense, you can discover new, great content that’s of your specific interests and likes by simply listening to your existing playlists and music libraries. “Genius” is a feature that you voluntarily have to turn on—and can turn off anytime—making it perfect example of how you can give out your own data to get something beneficial in return.

All you need to do with these websites and tools is to simply watch, read, listen to, and order what you like. Every time to watch an episode of Friends on Netflix, you’re using data to your advantage. Every time you order a book on Amazon, you’re using data to your advantage. Every time you watch a 30 second video on YouTube, you’re using data to your advantage.

Mint

Mobile apps have permeated every aspect of everyday life. You can turn on your iPhone and access Twitter, Facebook, your eMail, the New York Times, find restaurant recommendations, and more, all using mobile apps.

On such app, Mint, lets you to truly understand your finances: income, expenses, spending habits, budgets, and more. A large part of “big data” for large corporations is understanding the income levels of their buyers, including how much money the buyers spend on particular items, product lines, and more. In short, finances play one of the biggest roles in regards to understanding and analyzing data.

With Mint, you can understand your own financial habits at your own convenience—you control every aspect of your own data, and can use this data to understand your past finances while planning your future.

This is an example of when data can break down complicated situations for an individual person, and is designed to do just that. With an app like Mint, you can see what category the highest percentage of your income is being spent on. If Mint showing you that you’re spending 25% of your income on fast-food—and it can do so because Mint is linked to your credit card and bank account—you can use this information and decide to re-allocate that money elsewhere and change your lifestyle. This is your data, being analyzed on your time, for your own benefits.

Conclusion

Nearly everything you do has an element of “data” related to it. Your gender, height, and city, all seem common and straightforward, but even these three, simple, everyday elements all constitute one form of data or another. With this in mind, you have the ability to use your own data for your own good—or use the tools at your disposal, such as Google Analytics, to use other peoples’ data, without the need to assemble a team, spend money, or even spend a significant amount of time.

Being able to use your own data to your advantage puts you in the drivers seat. Companies are going to try to use your data in any way possible—even if it’s to understand what email marketing mailing list to add you on. By taking the same concepts, you ultimately get to decide what’s best for you, and what you get out of the human-company interaction, rather than letting the industry giants get all the benefits out of the relationship.