Lori Steele, General Manager, IBM Global Business Process Services

By Lori Steele 

This week, C-suite attendees representing all aspects of technology-fueled commerce will be convening at the IBM Smarter Commerce Global Summit in Nashville. Among the participants will be L’Oréal USA, with whom IBM is working on a three-year project for procurement services supported by an advanced cloud analytics solution to help transform the way L’Oréal USA buys from its large network of North American suppliers.

Over the years, L’Oréal USA has rapidly grown through both acquisitions and organically through its existing brands. With the new market advancement, the company’s ecosystem of suppliers and vendors has grown exponentially. In order to continue to realize more savings from procurement, L’Oréal USA needed its procurement workforce compliant with its spending processes to attain the best buying advantage.

L’Oréal is the first client to purchase IBM global procurement business process and technology services that include a new compliance analytics tool from IBM Research, integrated with strong spending analytics capabilities from the IBM SmartCloud procurement management software. The new smarter commerce solutions will enable L’Oréal USA to bring beauty products to consumers more quickly and efficiently.

The payoff to sourcing critical business processes like procurement is innovation. According to the new IBM Center for Applied Insights study, “Why partnering strategies matter,” which involves more than 1,300 business and IT sourcing decision makers worldwide, organizations like L’Oréal USA that source broadly to drive innovation, are outperforming on a host of financial measures, including revenue (2x) and gross profit (5x) growth.

In other words, the formula for success is based on metrics that are tied to business outcomes, transformational scope and integrated governance.

Technorati Tags: Big Data, Big Data analytics, IBM SmartCloud, IBM Smarter Commerce, IBM Smarter Commerce Summit, IBM Smarter Planet, IBM Smarter Supply Chain, innovation, supply chain

Jill Puleri, Vice President, Global Retail Leader, IBM

By Jill Puleri

These are crucial times for brick-and-mortar retailers as they evolve to put the consumer at the center of all that they do. Those that make good decisions are going to prosper; those who don’t are going to slip to the back.

Central to retailers’ ability to remain relevant is their response to the mobile opportunity. Mobile commerce is expected grow 115 percent over the next 12 months. Though the opportunity is clear, capitalizing on it is full of complexity as retailers integrate web sites and supply chains together with the numerous mobile devices that consumers are using to shop.

Just a few years ago, many retailers were working feverishly to push out shopping applications for mobile devices. There was good reason for the rush: tens of millions of consumers are jumping on the smart-phone band wagon and using them to shop.

As it turns out, mobile apps haven’t proven to be silver bullet to the mobile commerce challenge. From an IBM survey of 26,000 consumers, we learned that they would rather access a retailer’s website than launch a shopping app.  Only 15 percent of consumers were aware that a retailer had a mobile application; just 5 percent downloaded the app and a mere 3 percent actually used it.

That’s not to say that mobile shopping isn’t gaining momentum, it’s just that consumers want to shop on their own terms and on their preferred platforms. With mobile technology enabling new and unconventional retail models at every turn, more traditional retailers are going back to basics. 

Usability and accessibility are key to closing the mobile sale. Terms like, “single click to buy” or “thumb enabled” are now top of mind when it comes to mobile strategies. Today’s consumers have more choice and little patience, so retailers now need to act and act quickly. 

I’ve spent my entire career in retail, focusing on solving my clients’ most important business challenges, and showing them the next big possibility at the intersection of their business and advanced technology. If retailers miss major shifts like mobile now, they’re at serious risk. It’s exciting, scary, complex, intense, motivating – all at the same time.

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Today, Puleri was recognized as one of Consulting Magazine’s Top 25 Consultants for excellence in retail.

Technorati Tags: Big Data, IBM Smarter Planet, innovation, Mobile Retail, mobile retailing, mobile shopping, Smarter Retailing

Michael Haydock, Chief Scientist, IBM Global Business Services, Retail Analytics Leader

By Michael Haydock

Jewelry sales are set to shine this year and expected to grow more than 11 percent in the second quarter and nine percent overall this year, according to a new Big Data-based retail forecast from IBM.

According to the analysis, improved consumer confidence, lower unemployment and enhanced stock dividends from the fourth quarter of 2012 have combined to leave people ready to start spending on luxury items again, like jewelry.

In addition, key retailers are buttressing the economic landscape and driving sales by leveraging Big Data analytics to better understand and respond to customers and trends. Sterling Jewelers, for example, which owns the popular Jared and Kay brands, overhauled its digital channels to better respond to changing consumer preferences. The move led to an increase in online sales of 49 percent this past holiday season.

Sterling commissioned IBM for research that included a customer segmentation analysis, voice of the customer surveys and in-store observations. With deeper insights into customer needs and distinct shopping scenarios – as well as the capabilities required to support them online – they were able to extend the Kay and Jared in-store shopping experience online and into the mobile channel.

IBM’s retail analytics forecast examines some 22 years of historical retail data from the U.S. Census Bureau, which captures sales observations from over 46,000 retailers monthly from 1992 to the present. It also examines consumer confidence, disposable income, and unemployment data, stock market information, and a long list of other factors. The company then applies patented algorithms to the data to model seasonal peaks and patterns, making IBM’s retail forecasts over 97 percent accurate – four times more accurate than retailers’ own forecasts.

Armed with these hyper-accurate forecasts, retailers can get ahead of trends to ensure that the right product mix in their stores, allocate the best use of advertisement dollars and make sure they have the right number of staff to ride the peaks and valleys ahead.

In addition to the projected spike in jewelry sales, the latest forecast also predicts a boost to in-store consumer electronics sales, which are projected to grow 2.33 percent in the second quarter and 1.58 percent overall for 2013, after five years of decline. Though a modest gain, the news is welcome to an industry that has been challenged by the rising impact of new social retailing phenomena, such as showrooming, in which consumers look at items in a store before ultimately buying them online – usually at lower prices.

IBM is betting that Big Data analytics can be used to help companies unlock new areas of business and better serve clients. Researchers at the new IBM Customer Experience Lab are developing the IBM Virtual Closet, a prototype technology that enables retailers to look at items consumers recently purchased or showed an interest in – whether online, in a physical store or on a social network – and tailor recommendations based on that consumer’s unique taste and style.

The Virtual Closet is a great illustration of how retailers can use Big Data to better serve clients. By using information to provide exceptional customer experiences, whether online or in a store, companies will be able to attract more loyal customers and engage them in an ongoing relationship rather than a series of isolated transactions.

The challenge facing all retailers is how to successfully use Big Data to understand their customers and grow sales. The information is already out there. Now it needs to be optimized, analyzed and leveraged and that will require shifts in how retailers operate. But as the report shows, they’re starting to get it.

Technorati Tags: analysis, Analytics, Big Data, Big Data analytics, IBM Smarter Planet, innovation, mobile retailing, showrooming, smarter commerce, Smarter Retailing

Ari Sheinkin, Vice President, Client Insights, IBM

By Ari Sheinkin

Imagine an office full of static and noise. You hear YouTube blaring over bad speakers, competing with a dozen mobile calls and an in-person conference that’s interrupted by constant knocking on the door. And in this mayhem, you’re listening for one voice: the one whisper from one client talking about their experience or preference or plan.

CMOs face their own daily mayhem of data as they try to engage with customers as individuals. Marketing to industry segments and broad demographics is being replaced by the “era of you.”

Much of the data deluge comes from consumers via searches, clickstreams, mobile phones, and comments on Facebook and Twitter. Combine that with data about in-store traffic, conversations with call centers, and updates from suppliers, and today’s marketers confront a blitz of data waiting to be analyzed and acted upon to boost business.  Better insights enable companies, from retailers to banks, to literally design offers and services tailored to what consumers are telling them.

We all buy into the vision. But the question I keep hearing is, how do I prepare? How do take advantage? How do I start?

The answer I give marketing organizations is to embrace marketing science.  That point of view is the topic of a new study, Marketing science: from descriptive to prescriptive, just released by the IBM Center of Applied Insights.

Marketing science addresses the common misconception that with Big Data, clever computers will automatically capture all the required information and spit out answers. To the contrary, insight begins by asking the right questions and thoughtfully gathering information to support the analysis.

That means marketers need to become marketing scientists. They should start developing three core skills that may be new – architecting data, applying science and influencing action.

According to the IBM study, traditional marketers collect a great deal of data, but only 28 percent say they consistently structure information for analysis and availability across the enterprise.  This unplanned approach won’t glean the kind of insights marketers crave, from what consumers are saying on social media about a new fashion trend, to whether the supply chain can support a spike in demand for ice cream based on an unexpected heat wave.

On the other hand, marketing scientists “architect” data to make it easier to analyze. Drawing on a wider range of sources, they structure and organize data in a more granular form that is digestible, dissectible, and easily retrieved.

With the data in hand, it’s logical to assume that marketing science will begin.  However, less than 20 percent of traditional marketers and analysts regularly use scientific approaches in their jobs. They don’t develop hypotheses or benchmark against control groups. They are more likely to rely on gut feel and past experiences, rather than on analytics.

Those organizations will be left behind — or worse still, paralyzed by the volume of the noise. To grab the data-driven future, we all need to instill the processes and skills of science and experimentation into our marketing work.

Even with the best science, there’s no point predicting the future, unless you’re able to act on it. Here again, marketing scientists are ahead of their peers. They are investing in organizational change, learning how to use science to influence action – and moving beyond data mayhem.

For example, marketing scientists are nearly three times more likely to collaborate with the rest of the enterprise – from the CIO to the head of HR — both to share insights and to help everyone apply findings.  They are effective at selling their insight on how to optimize a client touch point or how the company can better engage with customers on social channels. And marketers need help applying the insights – 82 percent of traditional marketers still rely largely on hunches and experience.

Marketing science can transform the way marketing professionals make business decisions. It can inject more discipline into the marketing process, enabling marketers to ask – and answer – complex questions they could never otherwise address.

Guided by these insights, CMOs can anticipate the future and begin to listen to their customers as individuals – and move beyond the data mayhem.

Where do you see yourself or your marketing organization? Do you rely solely on experience or are you incorporating rigorous scientific approaches? How are you handling the vast amount of data you have access to? Do you have the influence, the sales skills, to transform your marketing organization? We’d like to hear from you!

Add your comments below or tweet us at @IBMCAI

Technorati Tags: Analytics, Big Data, Center for Applied Insight, CIO, CMO, IBM, mobile, social business, social media

Keith Mercier, Associate Partner, IBM Global Business Services, Retail Center of Competency

Growing up in a military family, Keith Mercier‘s fashion choices were limited to what was available at the military base exchange. At age 12, his love of fashion hit him like a bolt of lightning in the form of a bright red, v-neck, cashmere Lacoste sweater.

Dubbing himself the “fashionisto,” Mercier says, “In the fashion business you have to think like a fashionista – a truly devoted follower of fashion – if you are going to surprise and delight them and keep them coming back.”

At IBM, Mercier is an associate partner for IBM Global Business Services (GBS)’s Retail Center of Competence, and helps retailers transform their business and their industry through products, solutions and best practices. In this role, Mercier travels extensively to meet with retailers around the world, specializing in those that operate across multiple channels – in-store, online, through mobile devices, etc. – and enabling them to provide consumers a seamless experience whenever they interact with the retailer’s brand.

Omni-channel is the only channel

Retailers need to ensure that their brand is consistent whether online or in the store. However, many retailers are still operating their e-commerce departments as totally separate divisions. That’s got to change, Mercier says, particularly as retailers look to capture the massive opportunity presented by mobile shopping.

Mobile commerce among consumers is soaring, growing 43 percent in the fourth quarter of 2012, according to the IBM Retail Online Index. However, mobile shopping isn’t just about offering clients a mobile app, says Mercier. Many consumers aren’t especially interested in using specialized shopping applications from their favorite stores. In fact, a recent IBM survey of 26,000 people found that a mere 3 percent of respondents use retailers’ mobile applications.

“Consumers want to shop on their own terms, on their preferred platforms,” Mercier says. “It’s essential that retailers’ web sites are fully optimized for tablets, smart phones and any other mobile device that a consumer wants to use. The longer it takes to load a site or process a payment, the chances of a sale drop significantly.”

Retail is detail

One of Mercier’s early mentors taught him that “Retail is detail.” When working to deliver on consumers’ extremely high expectations for fantastic products, personalization and convenience, the devil is in the details, says Mercier.

In order to show their customers that they know them, retailers must make use of Big Data to develop marketing tactics that enable them to “narrowcast” to individuals. Mercier holds up examples from the casino industry that are getting this right. Their business models are built on data, using knowledge about a guest’s previous visit to make them a repeat customer.

Retailers must now employ the same tactics. But that’s not as easy as it sounds, Mercier says. There are cultural, financial and organizational barriers to making it happen. Some of these can be broken down by new technology models like cloud computing, which would enable a retailer to more affordably provide access to data across their organization. However, this challenge can’t be solved with technology alone.

“This is no longer a discussion with just the CIO,” Mercier says. “This is now a discussion with the CEO, the CMO, and the entire leadership team. We are at a new crossroads in retail, the corner of technology and service. Our ability to enable retailers to blend these together and create an unparalleled shopping experience is our opportunity.”

The store as dead give-away

At the start of every project with a client, Mercier will spend a full three to five days in their store. “Everything you need or want to know about how well a fashion apparel brand is being run can be seen in an individual store,” he says. “Stores are the microcosm of everything good and bad about a fashion company.”

Mercier compares a store to a book with chapters: a story needs to develop as a customer progresses through the store. Brands that do this successfully keep customers engaged.

As the president of maternity brand Japanese Weekend, Mercier implemented targeted marketing practices tailored to customers’ due dates. Given their target customer would only need maternity wear for a short period, he worked to make Japanese Weekend customers brand evangelists that would recommend the line to their pregnant friends.

Experiences like these enable Mercier to work so effectively with his clients today. “I speak their language,” he says. “I’ve sat in that chair and I know the challenges it brings.”

Technorati Tags: Analytics, Big Data, business analytics, IBM Smarter Planet, People for a Smarter Planet, smarter commerce, Smarter Retailing

Erick Brethenoux, Director, Business Analytics and Decision Management Strategy, IBM Software Group

By Erick Brethenoux

CMOs would do well to heed Ernest Hemingway’s time-tested advice: “When people talk, listen completely.”

For some time, brand strategists have been underscoring the importance of listening as a strategic mainstay for brands seeking to delve into social media.

To this day, I believe that thoughtful, inquisitive listening – to public commentary like tweets, posts and the range of online data that we, as individuals, share as a way of expressing ourselves – is one of the smartest investments a marketer can make.

The sky is the limit in terms of the kind of data marketers can listen to today. From online reviews that consumers post and contributions to forums, to creative self-expression on Pintrest and, of course, succinct yet expressive tweets – all of these are Big Data insights that, together, form a true narrative of what makes customers tick.

However, a cursory glance of a sentiment chart, a highlights reel of brand mentions from your agency, or even a month by month count of total tweets is not enough.

At this point in time, CMOs should ask themselves: Is my organization merely listening, or is it listening completely?

I had the chance to illustrate the concept of using analytics to listen completely and uncover consumers’ emotional triggers in Advertising Age‘s first-ever data issue. The article explores an emerging practice known as finding your “kin,” in which CMOs don’t just uncover what makes one consumer tick; they uncover what makes 100 consumers tick, one heart beat at a time, and find the link between all of them.

And if you’re wondering what exactly it means to listen completely, consider the following scenario.

Imagine yourself as an excited consumer who is one month away from a hiking trip in the lush forests of Vancouver Island. As you prepare for the vacation, you know it’s essential to have the right hiking boots to keep your feet dry, protected and firmly planted on the tundra, should you come across a slippery rock formation.

So what do you do?

You begin your search online, perhaps combing Amazon for top-rated boots and reviews to justify the ratings. You turn to your trusted outdoors blogs for product recommendations. You tweet to your friends and your cousins for advice, and post in your favorite forums, to boot (pun intended). And then you visit the website of the brand to which you’ve narrowed down your search, to look at specs and pricing.

But these are boots, so the virtual trail is not enough for you. As an avid hiker, you know it’s time to visit the brand’s retail store to try the boots on for size and comfort. You enter the store, go straight to the wall of boots, and try on the pair you’ve been researching.

And then you buy a lesser brand’s boots because they are cheaper.

Something was missing in this process. You, the consumer, clearly did your homework. You clearly stuck your neck out in the online version of town square, to seek out opinions and ask the right questions. But in the end, there was an emotional trigger that compelled you to eschew your online learnings and act in the interest of your wallet.

But what if the brand you had been researching all this time had, in turn, been listening to your calls for advice? Imagine if that brand had put in the same amount of knowledge-seeking as you did, listening to your public posts, tweets, reviews, comments and content shares.

Empowered by Big Data-driven insights, that brand could have known that the emotional trigger that would supersede your proclivity for choosing the cheaper option is the trusted advice of a fellow hiker; and one who has braved the rocky trails of Vancouver Island.

And with those findings, the brand could have served up a personalized e-invite to a retail store location near where you work, where a helpful store clerk named Bill will be waiting to tell you all about his recent trip to Vancouver and which boots he selected for his weeklong hiking excursion.

That – is listening closely and using data-backed findings to create a personalized, meaningful experience for your customer.

It’s why at IBM, we believe the death of ‘average’ is underway and a new era of ‘You’ is upon us.

Personalization, based on listening to what consumers say about themselves as people, is the key to effective brand engagement. We live amidst a wealth of public data where customers are living, breathing archives of personal expression.

But the most crucial step to targeting your marketing efforts is vetting consumer data carefully through marketing analytics technology and a disciplined eye. This practice of listening completely will reveal the emotional triggers that could compel your consumers to buy or click, comment, share, visit and endorse.

Technorati Tags: Big Data, Big Data analytics, CMO, IBM Smarter Planet, Social, social analytics, social business, social enterprise, social media

Ade Shannon, CEO, LabelSneak

By Ade Shannon

Interest in Big Data has reached new heights for many small companies as they attempt to capture information to glean insights from the ongoing conversations on social channels such as Facebook, twitter and consumer blogs.

Businesses large and small face the challenge of vying for consumers who look around and research extensively for the right deal before they buy. And when they do make a buying decision, they express their views and talk about it to everyone – instantly. They blog about it, they post reviews, they want to be heard, they want dialog. They also will loudly change brands and loyalties if crossed. In short, consumers are increasingly influencers, informed, expressive and networked shoppers who have evolved into “networks of intelligence” and a key voice for a brand.

With consumer behavior so volatile, marketers need to know what consumers want, before the consumers do themselves. Besides analyzing their own data to learn how they have performed in the past, businesses need to be able to look forward and change before the market does.

It’s this data that allows small businesses to provide personalization and customization tailored to the specific needs and wants of individual consumers – just as local merchants used to do, only better. However, many small businesses still lack Big Data expertise.

Small businesses are starting to grasp the gold that is buried in the vast amounts of data generated by shoppers using social media and mobile devices. They are just looking for ways to mine this data to gain insight.

By 2020, Big Data will help increase the level of personalization, localization and other considerations that enable small businesses to enhance their presentation. Take, for example, social shopping: consumers involve friends and others, sharing and liking real-time text and photo streams during the shopping experience, and perhaps driving these participants to buy.  Big Data also is driving automation, creating a wealth of new smart apps and technologies able to anticipate our needs. Or its prompting issue-influenced decisions, where consumers consider sustainability or conservation as part of their purchase decision process. 

Applying Big Data analytics can help small retailers track and understand what’s being said out there. But the leap in value comes when they combine this intelligence with theirs and other data sources in a meaningful way, to mute the social data noise from the valuable insights and move their business forward.  

The technologies to achieve these goals for small businesses are available and more affordable than most small businesses expect, especially when factoring in the losses from a lack of investment in a world where competitors are. What’s required are the smarts: knowing which questions to ask of the data and how the organization can best use what it finds. Understanding the value of Big Data is generating increasing demand among small businesses for insight on how to better understand and connect with consumers.

As small businesses learn how to take advantage of customer data and evolving consumer marketing channels, their operations will continue to change significantly. Small businesses will take note if you can show them how to gain consumer insights from their own data. The collaboration with a local technology provider can help a small business take advantage of some of the most effective methods to gain this data insight, while simultaneously bringing a deep level of industry expertise.

Small businesses that understand this consumer value variation will be best positioned to stay ahead of the competition in this Big Data revolution. 

Over the next few years, emerging analytical technologies will covert even more daunting data streams into actionable business insight and provide consumers with a more satisfying shopping experience – one worth spreading the word about.

Technorati Tags: IBM Smarter Planet, innovation, small business, Smarter Retailing, SMB, social business, social media

George Murray, Senior Vice President of Marketing, Sterling Jewelers Inc.

By George Murray

Today’s retail environment is witnessing the convergence of competition and innovation evidenced by the growing trend in “show-rooming.”  Every company is looking for ways to make the consumer’s omni-channel shopping experience more convenient, and while the keys to achieving this are fairly universal the journey to integrating them in a relevant way is not.

At Sterling Jewelers, we launched ecommerce for our Kay® Jewelers and Jared® the Galleria of Jewelry brands as an additional means of meeting our customers’ evolving needs.  Since the introduction of our online platform, we have worked to develop a true digital eco-system, which is focused on how a shopper experiences, interacts with and ultimately purchases our products.

As part of this ongoing initiative, we recently focused on advancing our existing multi-channel retail strategy. This effort included a redesign of our Kay.com and Jared.com websites, the launch of new transactional mobile sites for both brands and the implementation of a social media strategy focused on engaging consumers in the spaces that are most relevant to them. We also launched a mobile app through the iTunes App Store and Google Play, and introduced our catalogs on the Google Catalogs app to offer mobile shoppers even more opportunities to interact with our brands.

Our goal was to deliver a more consistent, branded and personalized experience to Kay and Jared customers everywhere they shop – whether in a physical store, online or via mobile. To achieve this we leveraged our expertise in customer service and merchandising with the experience of strategic partners in terms of optimized navigation, functionality and mobile retailing.

To help define our roadmap, we commissioned research that included a customer segmentation analysis, voice of the customer surveys and in-store observations. With deeper insights into customer needs and distinct shopping scenarios, as well as the capabilities required to support them online, we were able to deploy an integrated omni-channel solution that extends the Kay and Jared in-store shopping experience online and into the mobile channel.

The initiative has already resulted in bottom line growth for our business, with consistent increases in year-over-year online sales for both brands. More importantly, it has also created new opportunities for us to continue to evaluate, improve and evolve our customers’ overall shopping experience.

Technorati Tags: Analytics, IBM Smarter Planet, mobile computing, retailing, Smarter Retailing, social business, social media

Jeffrey Nichols, IBM Research Staff Member

By Richard Silberman, Writer/Researcher, IBM Communications

Jeffrey Nichols is putting a new twist on Twitter that could change the way businesses use social media to identify, engage and market to customers.

“What we actually see from Twitter is just the tip of the information iceberg,” said Nichols, who manages the social media and crowd research team at IBM Research in Almaden, Calif. “Below every tweet there’s a lot more information that people have that they’re not sharing.”

Determined to extract hidden information from social media, Nichols is developing strategies to ask questions directly of targeted strangers over Twitter. The crux of Nichols work is to move from the ubiquitous reactive approach to social media, where marketers follow and respond to what people are saying, to a proactive model where they can reach out to individuals to collect specific information.

“The number one thing we’re trying to do is to get beyond social sentiment, which is basically an aggregation of whether the crowd feels positive or negative about something,” Nichols said. “Direct engagement with individuals over Twitter allows us to understand people and their opinions a lot better than we can with a coarse measurement like sentiment.”

Soliciting information from strangers over Twitter

Nichols, who studies human-computer interaction in the User Systems and Experience Research (USER) group at IBM Research, has led several experiments that validate the viability of engaging individuals over Twitter.

Two years ago, Nichols launched TSA Tracker, which collected and displayed wait times at airport security checkpoints. Nichols and his team identified people who were at airports, based on their Twitter status updates, and asked them to share their estimated wait.

“We got a much higher response rate than we expected — above 40 percent — which suggested that this is pretty fertile area to explore,” Nichols said.

Nichols’ next study, being presented at a social computing conference this week, not only measured response rates, but also analyzed the quality of the information respondents provided. In this two-part study, Nichols sent questions via Twitter to individuals who own a particular tablet computer — and also queried people who visited Los Angeles food trucks. He then compared the Twitter replies to reviews on reputable online sites to see how closely they align.

“Once again we got a response rate around 40 percent, which shows that people seem pretty happy to respond to questions over social media,” Nichols said. “The most exciting outcome, however, is that over 70 percent of the responses were really high quality answers, and in many cases people gave us more information than we asked for.”

Click here to view the embedded video.

Modeling personalities based on Twitter text

Targeting the right people on Twitter is, of course, essential to getting high response rates and good data. To that end, Nichols and his team are currently exploring ways to analyze personality traits based on the text in social media messages. By modeling and understanding personality types, it will be possible to reach out to the right individuals, in the right way, at the right time, to elicit the best response possible.

“If you just send a person a message out of the blue and it doesn’t offer any value to them, then that’s spam and they’re not going to respond to that,” said Nichols, who is developing analytics to infer who will likely respond to unsolicited questions on a particular topic.

“If we choose to reach out to someone, we want to know there’s a very high probablilty that they’re going to react positively,” Nichols said. “Response rates of 40 percent are great, but wouldn’t it be awesome if we could get that up to 80 percent?”

New tools for Enterprise Marketing Management

Nichols’ fascination with crowds has its roots in the massively multiplayer games he once played. His interest in harnessing massive social communication and using Twitter in new ways evolved from there.

In one of his first social media experiments, Nichols and a team member used only the status updates posted to Twitter to generate summaries of sporting events comparable to those created by professional journalists. Encouraged by the results, Nichols has been on a steady path of innovation ever since.

“Going forward we hope to take what we’ve done so far, make it more business-relevant and bring it to market,” Nichols said. He is currently working to incorporate some of his techniques into IBM’s Enterprise Marketing Management (EMM) solution to support a very focused, individualized and interactive approach to marketing.

“I think our approach to using Twitter will become a routine part of doing business in the next couple of years,” Nichols said. “It’s not only going to enable companies to hone valuable relationships with individuals, but also to reach beyond and expand their established customer base.”

Technorati Tags: Enterprise Marketing Management, human-computer interaction, Jeffrey Nichols, twitter

Zoran Lemut, CIO, Kemofarmacija

By Zoran Lemut

Kemofarmacija is the leading wholesaler of healthcare products in Slovenia, offering customers more than 16,000 different products ranging from medicine and medical devices, to nutritional and cosmetic products. Though we have enjoyed the industry leadership position, we only recently began to fully exploit our online sales channel. It was an area that we knew required analysis and insight of our growing data volumes – our Big Data. 

While more and more of our customers were looking to make their purchases online, our competitors were over taking us with more aggressive web-driven sales models. We were not maximizing opportunities for cross-selling or more targeted online marketing and on top of it all, our website was simply not easy to navigate. Our challenge was as simple as it was profound: update our online operation to meet the needs of the evolving market.

With the IT and marketing divisions working side by side we envisioned a plan to use technology to drive more profitable sales – through tailored website advertisements and promotions, offering customers the products they wanted at the right time. But, for this plan to be successful, we first needed to gain greater insight into our online customer base. 

What we needed were insights to our customers’ preferences. We needed to mine, sift through and analyze our Big Data. Then, based on these insights, our marketing teams could promote specific products for strategic time periods and fine-tune the forecast for marketing campaigns.

Working closely with IBM and its partner MZR we designed a new IT infrastructure capable of giving us the advanced analytics and cloud capabilities we needed to transform our business. 

Now, utilizing an IBM Power System server running WebSphere and other key software tools, we are able to offer our customers a personalized online shopping experience, automatically promoting different ad spots to different customer segments. This capability has significantly increased the amount of sales orders placed through the company’s web portal, and the average customer-spend per visit. Measureable results include: 

• 30 percent increase in online sales order lines;  
• more than 90 percent of all sales order lines now processed through our web portal;
• improved cross-sales by presenting more targeted product recommendations, encouraging customers to buy more during every visit; and
• as a result of the increase in online sales orders, we have been enabled to transfer a number of staff from our call centers into higher-value areas, such as field sales and marketing. 

Added together, these results have translated into sustained market leadership, with an estimated 42 percent share of the market.

I believe the best medicine for companies right now is to think about the role that Big Data analytics can play in their business. If they fail to transform in this way, their competitors will figure it out, and by then it will be too late.

Technorati Tags: Analytics, Big Data, Big Data analytics, IBM Smarter Commerce, IBM Smarter Planet, innovation, Slovenia, smarter commerce