Connecting the data dots keeps these companies alive

The Big Data MOPS Series with Tamara DullWhat do the following companies have in common: Google, Facebook, Twitter, LinkedIn, Orbitz, Airbnb, Angie’s List, Match.com, OpenTable, and Uber?

Here’s what I came up with:

  • Presence. They’re all online; they have no brick-&-mortar presence. If their website or mobile app is unavailable, it’s as if they don’t exist.
  • Primary asset. Their primary corporate asset is data, specifically data (mostly big data) created by users. They do not sell physical inventory.
  • Business model. Their primary function is to connect users with the right web page, person, and/or service. If connections aren’t relevant, quick, or easy, users move on.
  • Revenue model. They make their money by connecting the data dots, primarily through advertising or service fees. If connections aren’t made, money is lost.
  • Top companies. Interestingly enough, Google, Facebook, Twitter, LinkedIn, and Orbitz are included in Forbes’ 2014 ten best companies to work for list. And Google, Facebook, and Twitter are included in Glassdoor’s Top 25 Companies for Culture & Values 2014 list.

Bottom line: If any of these companies fail to keep collecting and connecting the data dots for its users, for whatever reason, they will go out of business.

About data as a corporate asset. Let’s take a closer look at the point that these companies’ primary asset is data. For over a decade, industry analysts, management consultants, and vendors alike have been talking about managing data as a corporate asset. What does that mean? Jill Dyché, co-founder of Baseline Consulting and current vice president of SAS Best Practices, explains it this way:

"To understand what it means to manage data as an asset, you first have to understand the business definition of the term ‘asset.’ First, the asset needs to have a value; second, that value needs to be measurable; and third, it helps a company achieve its strategic objectives. When managed the right way—that is, as an asset—a company’s data meets these three criteria."

Why this matters. Managing data as a corporate asset is no small feat. It’s just plain hard work that requires the rigor of and investment in data asset management tools—not to mention the cooperation of and coordination between parts of the business such as marketing and IT. Why sign up for this headache when you and your colleagues have more than enough to do and bigger fish to fry?

Here’s why: Data is driving your business. If it’s not, it will be and/or it should be. We are living in an already-connected economy that’s becoming even more connected because of the exponential growth of data and devices. This is what the Internet of Things discussion is all about. The good news is that this data can provide insight into your business performance and strategic direction.  The bad news is that you could drown in it. Manage your data before it manages you.

Questions to think about. Jill Dyché often tells executives: “A company’s ability to use information strategically is directly correlated to the degree to which the data is managed.” To help executives get a sense of how they’re doing with managing data as a corporate asset, she asks them these five questions:

  • Are you giving your corporate data – big and small – resources comparable to your other corporate assets?
  • Are you dedicating technology comparable to your other corporate assets?
  • Are you allocating funding relative to your other corporate assets?
  • Do you measure the cost of poor, missing or inaccurate data?
  • Do you understand the “opportunity cost” of not delivering timely and relevant data to the business?

These questions have made more than a few executives squirm. But if you were to ask the executives of the 10 companies mentioned earlier, they’d answer a resounding “Yes!” to each question. Why? Because their data is intimately tied to their company’s core strategic objectives. (And yes, I’m cautiously optimistic that they’re also managing this data well.)

One final thought. I kicked off this blog series with this strong admonishment: “If you’re not using big data to improve your business – e.g., revenues, profits, operational efficiencies, decision making, etc. – then don’t do big data. It’s not worth the time, money or hassle.” Or in other words, big data is about making money.

So even if big data is not your core business, like it is for the companies highlighted above, then managing your data – big and small – as a corporate asset is absolutely vital as your company makes its way in today’s connected marketplace. To not manage your corporate data is to rob your company of its strategic edge.

Originally written for and published on Smart Data Collective as part of the Big Data MOPS Series


Editor's note:

As always, Tamara is spot-on with the points she's making in this post and it's the reason I'm so pleased to include her Big Data MOPS Series as our Friday feature. On the question of resources and technology dedicated to big data, marketers should be thinking about cybersecurity.

Cybersecurity is a marketing problem.

There is a growing list of the who's who of big business - good companies with great reputations - who have experienced data breaches recently that exposed customer data to hackers. And because the damage to customers ripples throughout their lives, this is a marketing problem, too. One function of this blog is to connect marketing issues to analytical marketing solutions we call Customer Intelligence. In the context of big data, and because marketing is the steward of the customer relationship, cybersecurity matters to marketers, too. We can help - reach out and let's talk about it.

As always, thank you for following!

Post a Comment

George Blankenship on doing the impossible

Word-of-mouth references and first-person accounts are usually the best way to get the “real deal” on something. It’s how you can get unfiltered information that’s almost as good as having the experience first hand. George Blankenship at the Premier Business Leadership Series.

With that idea in mind, I was more than pleased to hear George Blankenship share his unique perspective from a long career of creative breakthroughs at game-changing companies like Tesla Motors, Apple and The Gap.

George speaks with authority about doing the impossible.

The common thread at all three companies is that they’ve managed to pull off the impossible. So how and why did it happen at each of those companies? George attributes it to the ability to step back and see what’s happening more clearly than whoever happens to be the dominant player in the market at the time.

In the case of The Gap their new approach was to make quality, value and style accessible for customers. And they did it simply and in a way that they become a trusted editor (of style) for their customers. Their approach was to create 4 great sweaters and make them accessible, and not 40. And then repeat it across multiple channels to serve different markets – The Gap now operates successfully as Banana Republic, Old Navy and The Gap.

What’s interesting is that Steve Jobs wanted to sell technology at Apple like a fashion item – like Banana Republic. So Steve sought out George and asked him to spearhead Apple’s improbable move into opening retail stores in shopping malls. History has shown that move to be wildly successful and disruptive as a result. And then Tesla Motors – what approach did they want to take? They want to sell cars like Apple sells computers - big surprise!

But in those approaches is it really selling? Looking more closely, customers are not simply buying – they are having an experience. That’s part of the appeal and part of the differentiation of these companies. And tellingly they focus on making the customers satisfied and have been rewarded handsomely as a result.

Apple went from being a company whose products nobody wanted to own to the most valuable company on the planet. Part of their approach was to ambush customers – engage them with something nicely different at a moment when they’re not buying, or more importantly to get them when they don’t expect to be sold a product. That was the thinking behind the first two Apple stores – in Tysons Corner, VA and in Glendale, CA – that had opening-day lines to get in the store that were hundreds of people deep.

The other common thread among those companies is that Steve Jobs’ and Elon Musk’s laser focus on a concept is legendary and so was The Gap’s Mickey Drexler.

So what’s the big appeal of owning Apple products now?  It’s a combination of innovation, simplicity, design and an unparalleled ownership experience. The innovative part was that their products are user-centered and make it very easy to do what they need to do. Their design is both fun beautiful in their simplicity – both ergonomic and visually pleasing.

And the kicker is the ownership experience. It begins with people – their Geniuses are great people-oriented people. And they turn them loose to make their customers feel important, respected and taken care of. At the Apple store, no matter where or when you bought your Apple product you’ll be taken care of at the Genius Bar. And then there are the applications – remember “there’s an app for that?” To me it seems like Apple products are as much about the apps as they are about the devices themselves.

What has Apple revolutionized with their approach? Well for starters – the retail experience, music, mobile phones, mobile computing, and even babysitting. George points out how easy it is to let kids get wrapped up in games or videos on an iPad as his example of revolutionized babysitting – and he has a point!

So how can these approaches be replicated? It’s a matter of stepping back and seeing the synergies happening all around us, such as drones, streaming videos, personal activity monitors.

How can analytics help in doing the impossible? George sees the opportunity in data as telling you what everyone else is going to do, and by extension it also shows you what they’re not going to do. And to change the world, sometimes you need to do the impossible.

The Postal Service was founded in 1775, and UPS was founded in 1907, but it wasn’t until 1971 that Fred Smith decided to try offering an overnight package delivery service and founded Federal Express. Apple wasn’t even in the phone business before 2007, and Tesla was founded in 2003. George believes somebody is going to attempt the impossible and revolutionize many industries in the next 10 years. The question he leaves us with is – will that be you?

George Blankenship was a keynote speaker at the Premier Business Leadership Series conference.

Post a Comment

Does your loyalty program do what it’s supposed to?

Theoretically, loyalty programs are supposed to motivate customers to be loyal. But does it always turn out that way? Evidence is mounting that points to the fact that loyalty programs condition customers to expect discounts, and they don’t always cultivate loyalty. And the danger with that discount-driven scenario is that:

The loyalty program becomes only as good as the next discount.

Recent estimates by Colloquy are that there are over 2.6 billion loyalty program memberships in the USA. Considering there are about 240 million adults in the USA, that translates to a little over 11 loyalty memberships per adult and in the past two years the number has grown at about 26.7%. With overall population growing at 1% per year in the US, that accelerating loyalty program growth suggests that loyalty programs are quite popular. But do they engender loyalty?

Separate data from research by Maritz has revealed that active membership grew at a slower rate over the same period and that the percent of active memberships declined from 46% to 44%. So we have loyalty programs acquiring new members at a brisk clip, but the decline in active status suggests that a significant and growing portion of them are unengaged.

International Institute for AnalyticsThose market dynamics motivated us to work with two organizations this year to study loyalty programs from two viewpoints – one from the enterprise perspective, and one from the consumer perspective – and combine the two for some interesting conclusions. The IIA (International Institute for Analytics) conducted the research to get the enterprise perspective, Northwestern University's Kellogg School of Managementand we worked with the graduate program at Northwestern University’s Kellogg School of Management ("Kellogg") to get the consumer perspective. Many rich insights were gained in taking this two-pronged approach and a few clear conclusions emerged.

First and foremost, we found that loyalty programs may have once provided a competitive advantage but now they are expected by consumers. In addition, analytics play a key role in enabling the kind of relevance and customization associated with higher-performing loyalty programs. And organizations looking to engender loyalty should address the overall customer experience (across all channels) before turning to a loyalty programs to retain customers. The main reason behind that is:

A good loyalty program will not make up for
below average service, or poor product quality or selection.

Jack Phillips and Terri AlbertThose and other highlights from the two studies will be shared during a session at the Premier Business Leadership Series conference that I will moderate with Jack Phillips, CEO of the IIA and with Terri Albert, PhD, the Kellogg Professor that oversaw the consumer research. Customer loyalty is a strategic imperative for all businesses, so please join us for what I hope will be an informative session. If you are not able to join us, stay tuned here as we’ll share the content in other formats afterward.

As always, thank you for following!

Post a Comment

Exploring how to get in sync with mobile customers

Mobile Customers on a Journey

Customers on a Mobile Journey

Mobile technology and the advent of tablets and smartphones have transformed whole industries and are changing customer behavior in ways that impact marketers around the globe.

More than just another channel, mobile is digital and social at the same time.  It’s making the quest for marketers to stay in sync with the customer journey infinitely more complex and nuanced as the digitally empowered customer now has new expectations for a fully connected, mobile, personalized and relevant experience. And opportunities often show up disguised as challenges, and the challenge of mobile customers is no exception.

Great opportunities come with the stream of digital data from mobile. The rich data source enables marketers to learn more about customer preferences without being intrusive, opening avenues to inform product development, packaging, pricing, distribution, contact policies, and more.

Classic Mobile Customers

Classic Mobile Customers

The streams of data from mobile also allow for measurement and testing to drive efficiency gains and the ability to “fail faster,” and therefore recover sooner. Through that process we learn and get better at what we do. It’s all very exciting – but it’s not the data itself that gets the job done.

In order to reap all those rewards, you need marketing analytics to make the necessary connections among the data, to unlock the hidden insights and to go beyond understanding simply what your customers want. With analytics, it’s now within reach to understand and accurately predict how your customers want it, when they want it, where they want it, and you may even get insights as to why they want it.

Mobile is about location, but it’s also about time and mind-set. It requires a new marketing mindset that envisions the delivery of relevant content in parallel to the aggregation of this rich customer intelligence.

Contemporary Mobile Customers

Contemporary Mobile Customers

More than ever, mobile has become the cornerstone to experience, and it’s never been more important to use marketing analytics to be relevant in real-time with today’s mobile customers.

We’ve partnered with the CMO Council this year to explore mobile marketing with primary research around the question of getting in sync with our mobile customers.

The research findings have inspired a session at this year’s Premier Business Leadership Series Conference which is moderated by CMO Council Senior Vice President Liz Miller and features Sean Coar, Group Vice President at Time-Warner Cable and Michele Kelsey, Executive Vice President at Wells Fargo. If you are at the conference, please plan to catch this session and if not, stay tuned because we’ll capture the content and share it afterward.

As always, thank you for following!

Post a Comment

Want to predict your customer's next move?

Senior Solutions Architect Suneel Grover

Suneel Grover

People are funny. They’re often fickle, choosy, demanding and impatient. At times, they’ll say one thing and then do another. So when they become customers, how can you possibly predict what they’ll do? Well it turns out there are ways to do it quite effectively using data and analytics. One advocate of such approaches is SAS Senior Solutions Architect, Suneel Grover.

Suneel posted a blog recently about this topic on the Direct Marketing Association’s Annual Conference blog, which I am happy to cross-post here with permission:

----------

Predictive Marketing, Digital Intelligence, & Today’s Consumer
.

Today’s Consumer

Today’s consumer can access an increasingly wide range of media and online information in addition to their traditional offline shopping behavior. Due to the falling costs and increasing availability of smartphones and mobile devices, they are also exploring digital channels and mobile apps. This is driving multi-channel experiences and diversified media usage – often in parallel with higher expectations regarding their personal needs and preferences.  As a result, consumer marketing is becoming far more complex and time-dependent. The structures, processes, and systems currently in place in many companies are not able to deal with this omni-channel phenomenon. Valuable information is either lost not fully exploited – primarily due to the absence of central data management and control.

Digital Intelligence Enables Predictive Marketing

We are living in the age of the consumer, where consumer obsession is the new frontier of competitive differentiation — scaled and fueled by insights. Traditional web analytic practices cannot deliver the necessary digital insights to optimize the experiences of the newly empowered consumer. Today’s data-driven marketers must extend their digital analytic practices far beyond the limitations of web analytic practices to address:

  • Fragmentation of channels – Consumers who cross touch-points insist on harmonized outreach across these channels, raising the bar for marketing execution and analytics. Although the Web remains important, it no longer tells the entire consumer interaction story. Mobile, social, and video engagement continue to grow at a significant rate.
  • Multi-device consumers – In the United States, half of all online adults are “always addressable,” meaning they own and personally use at least three connected devices, accessing the Internet from various locations multiple times per day. To understand these consumers and the context of each interaction, marketers require analytics that provide transparency on users’ devices, locations, usage patterns, and preferences.
  • Predictive marketing analytics – With the increasing velocity of consumer interactions, marketers must complement traditional strategic analysis capabilities with advanced predictive analytics. Current web analytic methods produce isolated, backward-looking reports and dashboards, often delivering insights that are too late and lack clear actionability. In today’s digital world, you must be able to keep pace with your consumers and react to trend-shifts in consumer behavior.

As defined by Forrester Research, the term “Digital Intelligence” means:

“The capture, management, and analysis of data to provide a holistic view of the digital customer experience that drives the measurement, optimization, and execution of marketing tactics and business strategies.”

If you notice, I underlined the word digital within the quote above. If you remove it, doesn’t this definition look very similar to any marketing department’s analytic mission statement over the last ten years? The only thing that has changed is the digitization of society. As marketing organizations become more familiar with the opportunity of digital intelligence, senior business leaders will direct web & customer analytic teams to work together. However, in many cases, these projects will struggle to get off the ground due to a clash of approaches & culture. Obstacles will include:

  • Data types – Structured vs. unstructured data streams, known vs. anonymous audiences
  • Skills – Data scientist/data miner vs. web geek/digital analyst
  • Analysis – Advanced analytics vs. “good enough” analytics

This cannot be understated. The intersection of advanced analytics and digital analytics has arrived, and the resources who support both of these areas will need to work together. It is long overdue, but change is not easy.

Web (and social) analytics have typically supported descriptive and diagnostic analysis (i.e. What happened?). Digital intelligence aims to address predictive and prescriptive analysis (i.e. What will happen? How can we make it happen?). To begin on this journey, organizations will need to rethink how they collect data from digital sources (first party vs. third party), normalize digital data for the downstream purpose of predictive analytics (and not simply summary reports and dashboards), and subsequently execute on the promise of prescriptive marketing processes through optimized outbound and inbound interactions.

Interactions with consumers cannot be dictated by silos, but with an integrated decision-centric approach that enables the understanding of constantly-changing consumer behavior to bring insights in line with the structure of the corporate mission. By balancing analytic insights, business rules, and data-driven actions, modern marketers can be more agile operationally in consumer contact situations. Ultimately, the customer experience is the priority, and our ability to be relevant and adaptive at the pace of the consumer will differentiate us from our competition.

----------

So do you want to predict your customer's next move? What I gathered from Suneel is that it's all about using the digital intelligence available to you and addressing the 3 major obstacles of data types, skills sets and caliber of analysis.

Suneel will share these insights and more at the DMA Annual Conference this year, presenting in two separate sessions:

  1. The Analytics, Digital Intelligence, & Experience Management Pre-Conference Workshop, and
  2. The Marketing Analytics, Business Communication, and the Art of Interpretability Breakout Session.

SAS is proud to sponsor and participate on the program advisory committee of the DMA Annual Conference, the global event for data-driven marketers. As always, we'll capture content at the show and make it available for you in different formats.  Thanks for following!

 

 

Post a Comment

Dear Facebook, it’s not you. It’s us.

The Big Data MOPS Series with Tamara Dull

Dear Facebook,

Last week, we reached our 7-year anniversary mark. Have we really been together that long?! Because, honestly, it feels like forever. I’m sorry we didn’t celebrate, but I really didn’t feel like it. Ever since you asked me for my home address a few months ago, my feelings have begun to change. You crossed a line, dude.

Granted, it’s not the first time you’ve crossed the line—you’ve done it many times before—but this time, it was different. I know that I don’t talk much about my work with you and my friends, but I’m keenly focused on big data and privacy issues—two topics you know all about and use to exploit / build our relationship. But I’m getting ahead of myself.

Facebook Screenshot

I used to think it was about me.

I remember when we first hooked up. It was fun. It was new. You made it easy for me to connect with friends, family members and colleagues from years gone by. You even suggested that I connect with interesting strangers from all around the world. I started getting 25-50 friend invitations a week—many of which I accepted—and within a few years, I had almost 5,000 “friends,” with about 2/3rds of them living outside the United States.

Good grief, Facebook. Who has 5,000 friends?! Really? Not me. Not anyone. I know you cap the total number of “friendships” a person can have at 5,000—not because you think it’s too excessive for any one person, but because you want to have some level of control over the amount of “big data” processing you have to do to keep each person’s Facebook world intact. It’s good to know that you’ve set some limits for yourself.

The bottom line is this: You redefined “friend.” Not just for me, but for all of my friends. You made it seem like it was all about me and connecting my world online, when, in fact, it was always all about you. And collecting data.

You change the rules. A lot.

Let’s face it: You’re not my friend. You’re a big data machine. You collect, process, store, aggregate, and analyze all types of data 24/7—like status updates, comments, photos, videos, likes, notes, pokes, and the list goes on. Collecting data is what you do—and you’re always looking for ways to make money from it. I get that. That’s why you’ve been sharing and selling my data—and my friends’ data—for years.

The fact is that without all this data—my data and the data of my 1.3+ billion “friends” on Facebook—you would shrivel up and die. You need our data to stay alive.

It’s important to keep this in mind as people like me share data with you. I know you told me what you would do with my data when we first connected. You told all of us. And yes, I know that I clicked on the “Agree” button in the Terms of Service pop-up window (does anyone read that stuff?!)—so I get that you’ve covered your legal tracks.

Yet, every time you change your policies on how you are using my data and/or keeping it private, it just feels icky. And you change it up a lot. It’s hard to relax because I never know what or when you’re going to spring something new on me—or any of us. Not to mention the gymnastics we have to go through each time to make sure your “new & improved” settings aren’t exposing us in ways we don’t want. Frankly, I don’t trust you, but I want to.

You know how to keep yourself top of mind.

You remind me of some people I know: Negative attention is better than no attention at all. The Facebook chatter these past several weeks has been no exception:

New York Times. “We are all lab rats,” a New York Times article declared. This was after you told everyone about the news feed experiment you conducted on 0.05% of us. Despite the results of the experiment, the key takeaway was: Folks don’t like being manipulated without knowing they’re being manipulated.

Misplaced outrage. Yet, I tend to agree with industry consultant and analyst, Dr. Barry Devlin, who said the “outrage about Facebook’s psychological experiment is misplaced.” In his post The Ethics of Big Data…Again, Barry concludes:

“Internet services such as social media or search funded by advertising allow and invite manipulation of the data gathered for increased profit. If we agree that such services are socially desirable or now necessary, can we afford to expose them to even the possibility of such manipulation?”

OKCupid. It was nice for Christian Rudder, co-founder and president of OKCupid, to come to your aid and let the cat out of the bag. (Did you pay him?) In his blog post, We Experiment on Human Beings!, he wrote:

“If you use the Internet, you’re the subject of hundreds of experiments at any given time, on every site. That’s how websites work.”

Petitions. My guess is that the folks at these website companies are not the ones signing these petitions going around—you know, the ones that would cut your revenue stream off at the knees, like this one: Do not sell off our information to advertisers. You can’t seem to win.

Like. Like. Like. I could go on and on and on, but I’ll stop with the article about Mat Honan’s experiment, where he liked everything you put in his timeline for two days—just to see how you would respond. You nearly messed the young man up. Not to mention his timeline.

I really want this to work. Seriously.

Sometimes I miss the good ol’ days. The days before we met. I have fond, but faint, memories of my life before I met you and all your internet buddies. I was more physically active back then and I read more hardback books. And I saw the whites of more eyeballs. But I digress.

We both know that there are a lot of other fish in the internet sea; yet I want this relationship to work because I see value in it. But I need to trust you more, so here’s what I’m asking (for now):

  • If I give you my personal data for free, don’t go behind my back and share/sell it to someone else without my knowledge.
  • Figure out a simple way to help me understand who owns my data, who has rights to it, and for how long. I know a lot of people don’t care, but some of us do.
  • You act so arrogant when I or my friends scoff at your ever-changing privacy rules and features. Drop the arrogance act and make it easy for me to manage my own data.
  • Be transparent about what and how my data is being used, what requests have been made by external entities, and the steps you’re taking to keep my data secure.
  • And last, don’t ask me for my home address. It’s none of your business.

Let me be clear: I’m not breaking up with you. Yet. I’m willing to work on our problems. Are you up for it? I hope so. Because I’m not quite ready to accept that it’s not you, it’s me.

Originally written for and published on Smart Data Collective as part of the Big Data MOPS Series


Editor's note:

I love the way Tamara has elevated the big data discussion for marketers way above and beyond Gartner's 3V's construct for defining big data.

  • In her first big data series on this blog, she laid out a 10-step "archipelago" of big data islands as a more practical way for everyone outside of I.T. to understand big data.
  • This series - the "MOPS Series" - gives marketers a framework for knowing what to actually do with big data (and also what not to do with it). The monetization, ownership, privacy and security of big data all matter to marketers and cannot be simply relegated to I.T. or another department.

I hope you're getting as much out of Tamara's Big Data MOPS series as I am. As always, thank you for following!

Post a Comment

Leveraging analytics for mobile marketing

Recently, I was reading a conclusions paper created from an American Marketing Association webinar about mobile marketing featuring Brian Vellmure of Innovantage and John Balla of SAS. As I was reading, one line stuck out to me on the first page of the paper: “The key to making sense of mobile is analytics.” I thought that was a very simple, bold statement that was very much to the point.

The key to making sense of mobile is analyticsThat statement led to the next logical question, which is, “How?” How are mobile analytics being handled today in organizations? What are their maturity levels and opinions on mobile analytics? Vellmure and Balla answer that question and even provide analytical- and optimization-based suggestions for solving mobile analytics challenges.

Their starting point is to describe the current mobile environment, beginning with mobile in the workplace indicators. Did you know that 37% of corporate employees in a recent study are using mobile for more than 60 minutes a day? Similarly, 70% of respondents to an in-webinar survey claimed mobile is either “Very Important” or “Important” to their organization.

These stats illustrate the fact that humans, whether in a personal or professional setting, are device dependent. This should come as no surprise, but Vellmure goes on to summarize the main uses of mobile in a few key phrases that I really liked. First, he noted that mobile is now our “primary gateway to communication, commerce, and sharing.” Secondly, he compared mobile to a “human sensor,” telling those with access to our data “who we are, what we’re doing, and where we’re going.”

Later, we learn a bit about how users engage with mobile devices, including the concept of “no-mo-phobia,” or the anxiety and withdrawal that one experiences when not having their device at hand. The struggle is quite real, since I've personally sensed anxiety over the misplacement of my device. This anxiety is likely due to the fact that we as consumers know that our devices now encompass so many interaction channels and provide the “digital interface” to our lives. Whether you use it for the Web, social media, text messages, or simply to make phone calls, the mobile device today is a prime facilitator of interactions between consumers and brands.

Take, for instance, the product purchase process. Transactions can now be done completely from the mobile device. With the exception of the occasional “showroomer,” the process of researching, price comparing, and purchasing is all being done online, accounting for billions of dollars of spend annually.

As time progresses, organizations will need to become more and more adept at handling the consumer entirely from a digital perspective – potentially never having a person-to-person interaction. Organizations are certainly aware of the importance of having a presence across digital channels, as we have seen mobile advertising spend continually increase year over year – one projection forecast U.S. mobile ad spending at over $11 billion in 2014 alone. But how do brands continually improve when and where they are advertising, to whom and across what combination of digital media? How do they deliver a consistent message as consumers move seamlessly between digital marketing channels? How do brands use responses from customer interactions to refine their digital marketing messages over time?

The key to making sense of mobile is analytics.

Let’s consider the concept of “showrooming” - a real problem today for brick-and-mortar retailers. When showrooming, a consumer goes into their local big box store, tries a product, price compares (sometimes while in the store), and makes the purchase online for a better price. How could a brand overcome this issue?

Well, what if the store put a GPS based “geo-fence” around its store, allowing them to know exactly when a mobile-enabled consumer entered the confines of the store? What if, using advertising technologies, a mobile offer could be sent to the device when inside of the store for the exact product that is being “showroomed?” What if, when a consumer accepts or declines this offer, a subsequent action could be taken, such as sending a more appealing offer – all delivered at the individual consumer level? And what if all of this could be optimized, as to ensure that the consumer never receives a repetitive offer and always receives the offer at the optimal time, place in the store, and channel (perhaps they prefer an offer in the store’s mobile app versus over a social network)?

With technologies from SAS, all of this can be done. It’s not as far off as it seems, as SAS is already working with organizations, many well-known, to put this exact use case into action. If you and your organization want to enable better interactions over the mobile channel with your consumers, take a look at what SAS can provide today.

Start by downloading the paper, Leveraging Analytics for Mobile Marketing. After reading the paper, take a look at our Customer Intelligence web pages and then contact us. I promise we can help you make sense of mobile.

Post a Comment

If you think data security is IT’s responsibility, think again

The Big Data MOPS Series with Tamara Dull

What do Ebay, Living Social and Adobe have in common? These companies, among countless others, have all experienced a significant data breach in the last year. While these breaches have cost millions of dollars to fix, they’ve also cost some executives their jobs. If you don’t think data security is important, especially in this new age of big data, think again.

About data breaches. In April 2014, Verizon Enterprise Solutions released its 2014 Data Breach Investigations Report (DBIR). For this report: 50 organizations from around the world contributed; 63,000+ security incidents were analyzed; and 1,367 confirmed data breaches were studied. One key discovery Verizon made this year is that over the last 10 years, 92% of the incidents they’ve seen can be summarized with these nine classification patterns:

  • Miscellaneous errors – any user mistake that compromises security
  • Crimeware – malware, phishing
  • Insider and privilege misuse – includes outsiders and partners
  • Physical theft and loss – loss of devices and information assets
  • Web app attacks – use of stolen credentials, exploit vulnerabilities
  • Denial of service (DoS) – attacks, not breaches, designed to bring systems to a halt
  • Cyber-espionage – state-affiliated breaches, intellectual property theft
  • Point-of-sale intrusions – attacks on POS applications to capture payment data
  • Payment card skimmers – physical installation that reads your card as you pay

These nine patterns classify almost all of the attacks an organization is likely to face. Organizations can use these patterns to better understand the threat landscape and prioritize their own security investments.

Why this matters. Even though data security may sound like it’s IT’s responsibility, it’s not. It’s a company-wide responsibility that affects every employee regardless of role. Not only can data breaches cost a lot to fix (both legally and technically), your customers may lose faith in your ability to protect their interests, your reputation will most likely be damaged, and your bottom line may be negatively impacted. Some companies never really recover from such tragedies.

Questions to think about. As I mentioned earlier, data security is a company-wide responsibility. Even if you aren’t in IT, how prepared are you to answer the following questions?

  • Is data security taken seriously at your organization? If not, why not? Remember that if you suffer a breach of any kind, the potential loss could be devastating.
  • Are you encrypting sensitive data? Whether the data is being stored on-premises or in the cloud, make sure proper encryption (and decryption) techniques and practices are in place.
  • What proactive steps have you taken to make sure the data you’re collecting is secure? Even though you may never be asked by a customer, be prepared to answer, “How is my data being secured?”
  • Who has access to the customer data you’re collecting? And who’s accessing this data? (The answers to these two questions may be different, which could indicate a problem that needs addressing.) It’s important to keep data on a need-to-know basis and make sure access is revoked when an employee leaves the company.

One final thought. It’s not enough anymore for companies to primarily focus on protecting themselves from external, malicious data breaches. As Edward Snowden, the NSA whistleblower, has aptly demonstrated, giving an employee too much access can also work against you. Be vigilant and pay attention to the warning signals. Even if that warning signal is coming from your gut.

Originally written for and published on Smart Data Collective as part of the Big Data MOPS Series


Editor's note:

Tamara is 100% right in saying that data security is a company-wide responsibility that affects every employee regardless of role. As the steward of the customer relationship, it should be a particular concern of marketing because most of the data in big data is customer data.

That's not to say marketing should take the issue on single-handedly - be ready to participate in the dialogue and expect to spend more time at the table with I.T. on this and other big data issues. For more details about that, take a look at this CMO Council report called Big Data's Biggest Role: Aligning the CMO and the CIO. It's worth the read.

Post a Comment

Leading marketing excellence with analytics

There is no shortage of technology buzzwords today - digitization, big data, the internet of things, mobile, social, cloud computing, and so on. For marketers, all these buzzwords can be at once astonishing, thrilling, exasperating, potentially overwhelming, and sometimes even downright cliché. But together, they're all part of the ways that technology is rewriting the rules for how marketing is conducted. And they're changing the way that marketing organizations need to be led.
.
Effective leadership has always been about combining what you know with the resources at your disposal to address what you don't know. That combination enables you to make the necessary decisions to address the issues before you. in today's technology-driven environment, leading your organization to faster, better decisions requires skill, agility, resourcefulness and above all, analytics.
.
In marketing, analytics allows executives to align strategy and operational execution to orchestrate positive customer experiences. And when the customer experience can improve across the organization, so does the bottom line. The infographic below is from research conducted by HBR earlier this year shows how managing the customer experience manifests itself positively across a range of key business measures.
.
Infographic showing how customer experience management improves the bottom line.On October 22, 2014, marketing executives will discuss customer experience and the role of executive leadership in driving marketing excellence through analytics at the SAS Premier Business Leadership Series Conference. That session will be simultaneously webcast live by HBR at this link.
.
The discussion will be moderated by Angelia Herrin, HBR's Director of Special Projects and Research, and will feature the following analytical marketing leaders:
.
Executives are invited to attend the Premier Business Leadership Series, taking place at the Bellagio Hotel & Resort in Las Vegas, Nevada. If you're not able to join us in person, you can certainly tune in from wherever you are by signing up for the HBR live webinar.
.
Either way, I hope it's an opportunity for you to learn from these experienced leaders about how you can lead marketing excellence through analytics. After the event, it will be offered on demand and I'll update this post with the new link.
And as always - thank you for following.
.
Post a Comment

The White House recently completed a study on big data privacy. Do you care?

The Big Data MOPS Series with Tamara Dull

“Big Brother?! Ha! I’m not afraid of what the government knows about me. I’m more afraid of the internet and what it will expose about me. Heck, I’m even more afraid of people on the street with their smartphones who can take my picture without my permission and post it anywhere. I’ve been so diligent about living a private life, but now I live in fear.”

An attendee who went by the name of “Dee” at a technology public sector event in May 2014

The big data privacy reports. On the heels of Edward Snowden’s proclamation about the U.S. government’s misuse of consumer data, President Barack Obama asked his counselor, John Podesta, in January 2014 to conduct a 90-day study on big data privacy with recommendations on how to move forward as a country. In May, two reports were publicly released:

Both reports are a good discussion starter about balancing the effective use of big data with the intrusions of privacy and discrimination, and they aptly demonstrate that the government understands the big data questions on the table – from both a policy standpoint and a technological standpoint. However, they didn’t go far enough to address tough, but common, privacy concerns, like the ones expressed by “Dee” in the quote above.

What needs to happen next? Read More »

Post a Comment