Enterra Insights

Is There a Difference Between Segmentation and Personalization?

Judy Bayer, Director of Strategic Analytics for Teradata International, and Marie Taillard, a professor of marketing and Director of the Creativity Marketing Centre at the ESCP Europe Business School in London, wrote a very interesting article in which they stated that they no longer believe in segmentation. ["A New Framework for Customer Segmentation," HBR Blog Network, 12 June 2013] Obviously, the headline for their article (which they may not have personally selected) undercuts that statement; nevertheless, their arguments are both interesting and persuasive. They believe that segmentation (like dividing consumers by gender, ethnicity, geography, religion, etc.) promotes a "rigid methodology that carves out the market" in unnatural ways. They accept the notion that you "can't be all things to all people," and they believe that rigid segmentation defies that concept. They continue:

"To resolve these contradictions, we had begun pleading with students and clients to look for 'jobs to be done.' The approach echoes Ted Levitt’s famous comment about selling ¼ inch holes rather than ¼ inch electric drills, and advocates a mindset shift away from selling products to 'doing jobs' that solve customers’ problems. In Clay Christensen’s words, customers 'hire' products or other solutions because they have a specific job to fulfil, not because they belong to a certain segment."

To continue reading, click on the link to the new Enterra Insights site.

SAP Discusses the Future of Business, Part 2

In Part 1 of this two-part series, I indicated that I divided the facts presented in an interesting SAP slideshow entitled "99 Facts on the Future of Business" into thirteen separate categories. In that post, I discussed the first five categories: Big Data; Business Leadership; Customer Service/Experience; and Education. In this post, I'll discuss the remaining eight categories, namely: Emerging Markets; Innovate or Perish; the Internet of Things; Risk Management; the Supply Chain; Targeted Marketing; Urban Growth; and a Miscellaneous category. SAP introduced the presentation by explaining:

"Business Innovation is the key ingredient for growth in the future of business. Changes in technology, new customer expectations, a re-defined contract between employees and employers, strained resources, and business and social networks are requiring businesses to become insight-driven businesses. In this presentation, we have gathered 99 facts that represent the changes taking place in the world today. Each fact represents a key insight and suggests where we need to focus and change to become viable, sustainable and growing future businesses."

As noted in Part 1, I placed these facts into thirteen categories to help paint a more coherent picture of the future as seen by the analysts at SAP. In the first post, I included the first five categories: Big Data; Business Leadership; Customer Service/Experience; and Education. In this post, I'll discuss the remaining eight categories, namely: Emerging Markets; Innovate or Perish; the Internet of Things; Risk Management; the Supply Chain; Targeted Marketing; Urban Growth; and a Miscellaneous category.

To continue reading this post, click on this link to the new Enterra Insights site.

SAP Discusses the Future of Business, Part 1

In an interesting slideshow entitled "99 Facts on the Future of Business," the folks at SAP paint a picture of the future to which businesses should pay attention. The company introduces the presentation by explaining: "Business Innovation is the key ingredient for growth in the future of business. Changes in technology, new customer expectations, a re-defined contract between employees and employers, strained resources, and business and social networks are requiring businesses to become insight-driven businesses. In this presentation, we have gathered 99 facts that represent the changes taking place in the world today. Each fact represents a key insight and suggests where we need to focus and change to become viable, sustainable and growing future businesses." I've placed these facts into thirteen categories to help paint a more coherent picture of the future as seen by the analysts at SAP. In this post, I'll include the first five categories in this post. They are: Big Data; Business Leadership; Customer Service/Experience; and Education. The remaining eight categories will be provided in the next post.

To continue reading this post, click on this link to the new Enterra Insights site.

The Future of Retailing is All About Personalization

"The individualization of customer relation," writes Bertrand Duperrin, Consulting Director at Nextmodernity, "is the new concern of marketing departments." ["The individualization of customer relationship: why and how?" Bertrand Duperrin's Notepad, 24 June 2013] Tresilian Segal, head of Adobe's Digital Marketing across Northern Europe, agrees that "a commitment to personalisation seems a relative no-brainer." However, she asks, "Is the case for personalisation is well understood?" ["Maximise your personalisation process with these 8 tips," Fourth Source, 14 June 2013] A February 2013 survey conducted by inContact helps make the case. According to the survey, "Consumers are making less of their buying decisions based on brand loyalty, but rather on which companies can match their desired experience." ["Consumers Value Personalized Service Over Brand Loyalty," Progressive Grocer, 25 March 2013] The article continues:

"According to the findings, 56 percent of U.S. adults would be at least somewhat likely to switch to another brand or company if it offered more options and channels than their current provider. Additionally, younger consumers aged 18 to 44 (64 percent) indicated this was true significantly more than their counterparts aged 55 or older (45 percent), showing a major shift among the younger consumer base in terms of decision making. Based on the findings, the younger generation of consumers — who are used to an influx of information and a variety of choices — showed a desire for options that allow for a tailored experience in their interaction with brands. To that end, younger consumers demand more options and availability to handle these interactions, while companies are at risk of losing customers if they neglect to accommodate preferences or adopt evolving channels of communication in providing service. 'The survey results are clear: consumers expect more choices and more ways to interact with business today,' said Paul Jarman, CEO of inContact. 'The smartest companies are quickly adapting to changing consumer behaviors and needs, extending customer service beyond just phone and email to mobile apps, text messaging, chat and social media.' Survey respondents showed overall that they not only prefer, but expect, companies to offer options for a variety of channels and devices."

In previous posts, I have discussed the fact that consumers are increasingly looking for an "experience" as they shop (be it online or in store). Lauren Hertler insists, "At the end of the day, creating an optimal experience for a customer is determined by the ability to deliver personalized communications." ["Driving Performance through Personalization," ExactTarget Blog, 30 September 2013] Although most pundits concern themselves with online experiences associated with multi-channel retailing, Gavin O'Malley believes that personalization is just as important when a consumer is in a brick-and-mortar store. "Consumers are craving more personalized, less siloed shopping experiences," he writes, "and [they] could be convinced to stop 'showrooming' and actually make in-store purchases." ["Consumers Desperate For More Personalization During Purchase," Online Media Daily, 26 September 2013] The one thing that all of these analysts agree upon is that there is a case (they believe a strong case) to be made for understanding and engaging in retail personalization.

Natasha Hritzuk, senior director of consumer insights at Microsoft, told O'Malley, “Consumers are absolutely desperate for more personalization during their purchase journey. The idea of personalization isn't new, but [the industry as a whole] is still not delivering on its promise." O'Malley continues:

"The retail industry is also failing to appreciate consumers' desire for a more seamless shopping experience, according to Hritzuk. Consumers don't want to encounter gaps between a brand's online, mobile, and in-store presence, she said. 'They want to operate seamlessly.' Along with breaking down the barriers between digital and physical-store experiences, retailers can also use ecommerce learnings to increase in-store purchases, according to Hritzuk. 'We need to understand why people showroom,' she said, referring to the increasingly popular consumer practice of testing products in-store, but preferring to buy them online. For one, 'It’s easier to buy [products] online,' said Hritzuk. 'You can [buy something] online in 3 to 4 minutes compared to the 20 minutes it can take to buy [a product] in stores,' she said. 'We need to take that friction free purchase transaction, and [implement] it in stores.'"

Eric Tobias, Vice President of Web Products at ExactTarget, told Hertler that "personalization can be achieved using four main building blocks." They are:

• Collection and identification of data
• Data aggregation
• Taking action on the data
• Providing continuity to the customer by nurturing the 1-1 relationship

Tobias continued, "The primary goal, of course, is to deliver the right experience at the right time using the right channel." He then offered four tips "to help all marketers get more personal":

1. "Let data be your guide–no more guesswork!
2. "Inject personalized content into transactional messages. Transactional messages are a key component to creating a relationship with your customers–don’t overlook them. Surprisingly, in a study of the top retailers, 79% had no email personalization after an online purchase.
3. "Capture user behavior during/after the shopping process. Listen to what your customers are doing on your site to help drive recommendations or post-purchase remarketing opportunities.
4. "Make your data actionable. It's been shown that almost half of all people will completely abandon a brand's communications after only two un-personalized attempts."

Segal agrees that good personalization begins with the data. She explains, "Let the data do the hard work and decide what the most relevant content and offers are to serve the customer at the detailed level." She also agrees that content should be personalized. "Get rid of 'spray and pray' emails," she writes. She also agrees that gathering and analyzing data is essential to capture and analyze the customer's digital journey. "Identifying key points along your customer's virtual path is important," she writes, "as it allows you to decipher where conversion is highest." Nevertheless, she cautions, "While per­son­al­isa­tion may often rely heav­ily on data and analytics, it is important not to completely surrender all con­trol of customer experience management to machines. There is still a role for behavioural tar­get­ing, as long as you test against it regularly. A blend of data-led and intuitive marketing often works the best."

"'Big data' promises to be the solution to getting a 360 degree view of your customer and make more intelligent personalization decisions," writes Linda Bustos. ["Using Big Data for Big Personalization," GetElastic, 11 July 2013] Bustos' article included the following "infographic from Monetate [that] covers the big data problem, the segmentation opportunity, and 3 keys for data and segmentation success."

Alicia Fiorletta concludes, "As shoppers continue to leverage digital tools and channels to research, browse and buy products, they also are beginning to demand more relevant products and offers. With these heightened expectations, personalization is becoming an integral component of retailers' cross-channel marketing strategies." ["Retailers Across Verticals Personalize With Digital Solutions," Retail TouchPoints, 6 May 2013] Duperrin adds, "When business treat groups and not individuals, [i.e.,] trying to please everyone at the same time, [that strategy] often leads to pleas[ing] no one since the lowest common denominator is never satisfying for each person taken individually." The requirement for retail channels to become even more personalized is likely to continue. I agree with Duperrin who insists that the technology used to get know customers better must be complemented by knowledgeable and caring people who can really put the finishing touches on personalization.

Get Personal with Your Customers

"In a climate where companies send mass, generic emails to entire mailing lists on a regular basis," writes Malcolm Duckett, "consumers have become deadened by indiscriminate email campaigns." Duckett believes that "a targeted approach is the only real way to avoid damaging your company's relationship with customers and to build brand loyalty." ["Intelligent email marketing should be personalised and targeted," Fourth Source, 7 May 2013] Janet Kyle Altman, of Kaufman, Rossin & Co., basically says the same thing, but in a different way. She writes, "Your target is not 'everyone'." ["To Market Successfully, Your Customer Can't Be 'Everyone'," Business News Daily, 27 September 2013] It's obvious that you can't personalize your marketing efforts if you know little to nothing about the consumer you wish to reach. Richard Ting asserts that "brands are missing out by not fully understanding who their customers are. Let's face it: the signal-to-noise ratio is still fairly low among brands." ["The Customer Profile: Your Brand's Secret Weapon," HBR Blog Network, 11 March 2013]

Angela Wells calls the "getting to know your customer" approach Business-to-People (B2P) marketing. "B2P Marketing," she writes, "is the recognition that businesses aren't actually buying what you're trying to sell. Individual decision makers — people — are making the decisions for their companies, not impersonal disengaged companies as a whole." ["Forget About B2B And B2C - Technology Enables B2P (Business To People) Marketing," Marketing Tools: CRM, 28 June 2013] Whether your desired customer is sitting behind a desk at a business or on the couch in their home, doesn't really matter. Wells is correct that individual decisions are what you are trying to influence. Duckett insists that "saying the right thing at the right time to the right person" is getting easier thanks to technology. He writes, "The new generation of cloud-based marketing automation tools out there can help make this quick, simple and effective." He recommends a four-step approach for getting to know customers better.

"Step 1 – Create a profile: Clearly identify and classify visitors by monitoring and remembering their behaviour. There are tools that let marketers automatically record visitors’ individual behaviours as part of a 'customer history' record.

"Step 2 – Target: The marketer can set up simple targeting 'rules' (one by one as needed) so, for example, a rule might say 'target people who have looked at brand A more than 15 times', 'target visitors who have been visiting for 2 months but have not purchased' or 'target visitors who have purchased but not for 3 months'. Then the marketer will communicate to the system what content they want to try on each segment (this might include a set of email variants or even content to show in the visitor’s web page or triggers to your telesales team).

'Step 3 – See what works: Gathering this data on which content delivers the best results from this target segment (and the control group) is useful to marketers that then need to look at conversion rates, number of sale and, basket size to make their decision.

"Step 4 – Repeat and love the engagement: Keep the process going, each time building into the targeting the additional behavioural information harvested from the visitors. Your system should also include functions to ensure customers aren't repeatedly contacted with the same message or offer. This is important; otherwise customers will get wise and exploit the brand. For example, they will come to understand that if they abandon a basket one day, they will receive a discount the next – or will get frustrated when continually offered a deal they are not interested in, for example, a product they already purchased elsewhere."

Duckett concludes, "By engaging the visitor at every stage, marketers can ensure that customers are not disappointed by their experience of the brand, either by confusing content or unnecessary adverts. The end goal is that the visitor's experience will be easy, engaging and ultimately provide the visitor and the brand with exactly what they want." As I've noted in previous posts, it's easy for online customers to jump on or off the path to purchase. That's why I agree with Duckett that consumers must encounter a good experience at every stage or touchpoint along their journey.

Ting believes that many companies don't get to know their customers better because the data they collect about them is siloed. "Combined," he writes, "this information would be enough to create the ultimate 360-degree customer profile, which would allow enhanced targeting and personalization." The different types of siloes into which data is gathered include:

• "What they're saying — social CRM. What are your consumers saying about your products and services in social media? Are your consumers' brand sentiments shifting from positive to negative or vice versa?


• "What they're buying — purchase history. What is the last product a consumer purchased from you? How often does he buy from you? What are her favorite products? Are people making more or fewer purchases?


• "What they're doing — brand interaction history. Are they using your mobile apps? How often are they using them? Are they visiting your website? Are they spending more or less time with your brand?


• "What they're liking — social interest graph. What interests do they share on social media channels, and who is in the network of people who share similar interests?"

He cautions, "It may seem simple to combine these discrete data sets into one holistic customer profile, but there are major technology obstacles brands need to get past." Integrating data is never as straight forward as people think it will be. Ting insists that a customer's lifetime value will increase "by better engaging them over the long term and with purpose. ... To surgically cut through the noise, advertisers need to develop richer customer profiles. It's not the sexiest of topics in advertising, but it's one that will ultimately allow brands to target and personalize the experiences and messages that consumers deserve." Altman concludes, "No matter what product you sell or service you deliver, more targeted marketing gives you a better return. Targeting a specific audience gets you in front of them more often, with messages that touch them emotionally. If you try to be everything to everyone, your message becomes vague and less impactful."

Wells agrees. "With the rise of social media and engagement," she writes, "it has become increasingly obvious that we are all targeting people – those people who make the decisions whether or not to purchase what you are trying to sell. These people we are targeting are consuming media like never before, across a range of social platforms such as Facebook, Twitter, LinkedIn, and so much more." It should be pretty obvious by now that none of the recommendations offered by these pundits can be achieved without the right kind of technology. The secret is to get personal with your customers without creeping them out. It's a fine line that companies must walk when making personalized offers. The right technology and a good marketing department or firm will help you walk that line.

Millennials: Getting to Know You

Back in 1951, when Oscar Hammerstein II and Richard Rogers wrote their now-famous tune "Getting to Know You," they weren't thinking about marketers' love affair with consumers. Nor did they ever dream about how intimately marketers could actually get to know consumers. Nevertheless, marketers embrace the sentiments contained in Rodgers and Hammerstein lyrics:

Getting to know you
Getting to know all about you
Getting to like you
Getting to hope you like me

As marketers get to know consumers, differences in generation product preferences quickly become clear. For example, back in 2012, Jefferies, a global investment bank, and AlixPartners, a global business advisory firm, released a study entitled Trouble in Aisle 5 that concludes there is a dividing line between baby boomers and millennials (sometimes referred to as Generation Y). ["Millennials' Grocery Consumption Patterns to Vastly Affect Food, Beverage Industry, Study Finds," SupplyChainBrain, 3 July 2012] Presumably Generation X individuals lean either towards their parents preferences or towards their children's preferences, because you don't read a lot about Gen Xers as a huge marketing target. In fact, the generation getting most of the attention nowadays is Generation Y — the so-called millennials. As the staff at ZOG Digital tells retailers and manufacturers, "Millennials are likely within your target audience." ["Marketing to Millennials: Just be Real, Dude," 3 July 2013] Here's how the ZOG Digital staff defines who is included in the term "millennials":

"The exact definition of 'millennials' varies, but it generally encompasses anyone between the ages of 18 and 30. Described as 'digital natives' by eMarketer, these consumers grew up with advancing technological opportunities. They may remember their parent's old brick car phone or beginning computer classes in grade school, but largely, they emerged from their teen years with a solid grasp on the Internet and all surrounding devices. Now, millennials are not only the creators of many social media networks, but they are – as a whole – early adopters who exemplify it. Just take a look at the average age of users on six of the most popular social networks – the typical user on Facebook, Twitter, Pinterest, YouTube, Google+ and Instagram falls within the late teen to early thirties age range. Millennials are the influencers you are looking to identify and engage with in order to increase visibility."

To learn more about "influencers," read my post entitled Do You Know Who Your "Influentials" Are? Lucia Moses notes, "Millennials are different from their parents, at least when it comes to spending. The Shullman Research Center surveyed adults with a household income of $75,000 plus on their spending plans and habits, and found that those age 18-33 were more optimistic about their financial situation and planned to spend more than their older counterparts." ["Wealthy Millennials Approach Shopping Differently Than Their Parents," AdWeek, 3 September 2013] The latest quarterly MarketPulse report from Information Resources Inc. confirmed the optimistic outlook of millennials: "The report found that 28% of millennials feel their financial situation has improved in the past year, vs. 20% of those aged 25-54 and 16% of those age 55 and older. In addition, 42% of millennials expect their financial position to improve in the coming year, vs. 26% of those aged 35-54 and 17% of those aged 55 and older." ["Shopper Sentiment Improves: Report," Supermarket News, 6 August 2013]

According to Moses, millennials are more likely to buy online but less likely to use credit than preceding generations. So what else has Big Data analysis taught us about millennials? AlixPartners analysts report:

"Based on the most recent projections by the U.S. Census Bureau, millennials over the age of 25 (the age at which income and household formation typically start to really accelerate) will make up roughly 19 percent of the U.S. population by 2020, up from just over 5 percent in 2010. These 64 million millennials will see a significant spending-power increase in the coming years as the median income for those households is expected to jump to more than $45,000 from just over $28,000. In fact, the study finds, food-at-home spending by Millennials is set to jump by $50bn annually through 2020. By contrast, the baby boomer generation, which has had an outsized influence on consumer trends for decades, will fall to below 20 percent of the population in the next eight years." ["Millennials' Grocery Consumption Patterns to Vastly Affect Food, Beverage Industry, Study Finds," SupplyChainBrain, 3 July 2012]

Brad Tuttle agrees with that analysis. "The millennial generation," he writes, "is easily the most studied demographic since ... the Baby Boomers." ["Millennial Shoppers: Big on Browsing, Not Splurging," Time, 11 September 2013] He continues:

"This is not only because Americans are always fascinated by youth culture, and that millennials are growing up during a period when technology and economic forces are changing rapidly, but also because — to put it bluntly — Gen Y represents big bucks. Roughly 80 million American millennials spend $600 billion annually, and by 2020, it's expected this generation's spending will hit $1.4 trillion per year, or about 30% of all retail sales. No wonder retailers, marketers, manufacturers, and all kinds of consultants have been trying so desperately over the years to get inside their heads and find out what it is that interests them — and what they'll pay for."

Analysts obviously don't agree on everything about millennials. As noted above, some analysts predict that millennials will spend more than older consumers; but, others claim they will spend less. Tuttle notes that recent studies about millennials have been published by "the NPD Group, Accenture, and the Shullman Research Center." He reports, "In a press release accompany the NPD report, Marshal Cohen, the group's chief industry analyst, called millennials 'the most elusive generation and the most challenging to keep engaged.' While some of the findings in the studies from NPD and others may be surprising, and demonstrate important cultural differences between how millennials and other age groups spend, simple economic circumstances can be credited for much of what sets young consumers apart. For instance, why is it that millennials go shopping quite frequently, but purchase at a significantly lower rate than older consumers? 'Because they are the most selective as well as the most economically challenged,' Cohen put it simply." Tuttle provides a few more insights about millennials drawn from these studies:

• "Millennials really love to shop. Indeed, in the Shullman study, 58% of consumers ages 18 to 33 put themselves in the 'love to shop' category, compared to 40% of adults overall. And while the data indicates that millennials are more likely to make online purchases than older consumers, young shoppers still do enjoy going to stores. According to the NPD report, 53% of millennials shop in-store at least once a week, and 81% of their dollars are spent in brick-and-mortar stores. 'Interviews conducted recently at one of America's largest shopping malls confirmed our survey findings that many members of the digital generation actually prefer visiting stores to shopping online,' the Accenture report states."

Lorraine Mirabella provides additional evidence that millennials may save brick-and-stores from the onslaught of online retailers. "Buying almost anything online may be as much second nature as texting for many in the first generation to have grown up with e-commerce," Mirabella writes, "but the millennials still do most of their shopping in stores, especially those that keep their offerings fresh and make the experience social, according to research from the Urban Land Institute." ["Gen Y shoppers, raised on e-commerce, still prefer in-store experience," The Baltimore Sun, 7 September 2013] Tuttle's next descriptive trait involves shopping frequency.

• "Millennials purchase less frequently. Young consumers may be out at stores in large numbers, but they're not necessarily buying anything. According to the NPD study, the conversion rate — percentage of consumers who actually make a purchase — is lowest among millennials. Whereas seniors make purchases 72% of the time, millennials pull the trigger only on 57% of their shopping (more like browsing) ventures. Gen X and Baby Boomers fall in the middle, with conversion rates of 66% and 69%, respectively."

Maureen McAvey, senior resident fellow for retail for Urban Land Institute, told Mirabella, "Retailers are keeping a close eye on the millennials' buying habits because it's becoming clear that they are not just a younger version of their elders, but a different shopper altogether." That's why it's so important that retailers get to know them better. Tuttle's list continues:

• "Even well-off millennials aren't big splurgers. The Shellman study, which focused on young consumers with household incomes of at least $75,000 annually, found that for 53% of higher-income millennials, their last 'luxury' purchase cost under $250. What's more, these consumers were fairly likely to wait and save up before buying anything in the luxury category: 30% reported saving up specifically for the purchase (compared to 16% of adults overall), and only 10% of millennials put the purchase on a credit card (compared to 19% of adults overall)."

Suley Muratoglu, Vice President for Marketing and Product Management at Tetra Pak, reports, "Millennials represent the fastest-growing segment of luxury goods and services purchasers, according to a recent study by American Express. Yet they are also giving rise to a new lifestyle that can be characterized in two words: frugal and green." ["Millennials’ Frugal And Green Lifestyles Raise The Bar For Brands," Manufacturing.net, 29 May 2013] Muratoglu continues:

"To splurge on the high-quality items they covet, especially just-off-the-line electronics, Millennials scrimp in other areas. But even as they look for coupons, sales and promotions and stray from well-known brands to keep their cash-strapped budgets in check, they choose 'makers and products that are socially responsible. … fair-trade and offer lower carbon footprints,' notes Ana Nennig, EVP of global consulting firm Havas PR. What's more, packaging, which has long been part of the green discussion due to concerns about food waste, sustainability and recyclability, is center stage again. But this time consumers are considering it in a more holistic way to embrace and fulfill this young group's unique views on frugality and social responsibility."

The last item on Tuttle's list addresses the frugality of millennials:

• "They’re big fans of convenience and cheap prices. It's easy to see economic forces at work yet again in light of the NPD study's findings that 'value oriented retailers within the dollar store, second hand, drug store, and off-price channels' are especially appealing to millennial shoppers. Another study, 'Millennial Shoppers: Tapping into the Next Growth Segment,' released last summer by SymphonyIRI, indicated that millennials tend to be driven more by cheap prices than loyalty to any particular brands, and that they like shopping in drugstore chains like CVS and Walgreens more than other consumer demographics."

The millennials' reputation for frugality led McAvey to tell Mirabella, "'Many people speculate this is going to be the sharing generation,' more apt to rent a zip car or ride a bicycle than buy a car or use a tie-sharing service rather than having a closet full of the accessory. ... 'It's not clear that they wish to acquire as much stuff as their parents did, and retailers are very interested in what they're going to do.'" Tuttle further reports, "The SymphonyIRI survey also showed that millennials have been resorting to classic DIY strategies in order to spend less money, sometimes — in the case of health care — to disturbing degrees:

'This group is 46 percent more likely to use at-home beauty treatments to save money, and 31 percent more likely to cook from scratch or with limited convenience foods to save money. They are also 18 percent more likely to 'self-treat' where possible to avoid spending money on doctor's visits.'

The bottom line appears to be that millennials are becoming an economic force to be reckoned with but extracting money from their clenched fists may prove more difficult for retailers than it has been to get money from previous generations.

Getting to Know Emerging Markets, Part 2

In Part 1 of this two-part series, I noted that many respected analysts believe that the future of the global economy (and, therefore, the fortunes of many businesses) depends on emerging market countries and the consumers who live there. Many of those same analysts noted, however, that companies that believe they can use a one-size-fits-all strategy for emerging markets are going to be disappointed. Not only do emerging markets have peculiarities that make them unique, consumers living in those markets also have varying taste and lifestyle preferences. The only way to discover those variations and respond correctly to them is through the collection and analysis of Big Data. In this post, I'll discuss recommended strategies for getting to know the consumers in emerging markets and the conditions in which they live.

Boston Consulting Group analysts conclude that "multinational companies have the right priorities — emerging markets are the growth spots of the future — but have not fully put in place winning practices." ["Playing to Win in Emerging Markets," by Amitabh Mall, David C. Michael, Lori Spivey, Andrew Tratz, Bernd Waltermann, and Jeff Walters, bcg.perspectives, 13 September 2013] That's because they don't fully understand the consumers living in areas in which they hope to expand. Mark Harrington, the Chief Marketing Officer at ListenLogic, asserts that Big Data now provides the opportunity to obtain that understanding. ["How Marketers Are Finally Getting to Know Their Customers," Direct Marketing News, 24 July 2013] he writes:

"Having the ability to visualize millions of consumers based on their needs, attitudes, actions, and experiences delivers multidimensional insight to drive critical marketing components, ranging from promotions to product innovation. Marketers can gain deep understanding of what prospects and customers want, need, like, and dislike without ever asking a question. And they can do this on a continual basis to track markets shift in the always-on world."

One of the tools he suggests using is ethnography. Jessica Weber and John Cheng explain that ethnography involves "studying the customs of individuals and cultures." ["Making the Most of Ethnographic Research," UX Magazine, 5 August 2013] They continue:

"Ethnographic research offers several key benefits for defining a long term, multi-channel [user experience] strategy, including:

• Identifying user needs that have yet to be met
• Testing market demand for products that do not exist
• Providing a holistic view of a problem space
• Exposing opportunities for competitive differentiation

"The principal advantage of ethnographic methods is the ability to see the impact of the physical world on factors that could drive digital design. Ethnographic research is all about discovery of the unknown — disproving assumptions about user behavior and uncovering unexpected insights. Whenever you're in the field, something you see is going to surprise you, and those surprises are almost always at the root of innovation."

In previous posts, I've noted that providing a positive user experience at every touchpoint in a consumer's digital path to purchase is important because it is so easy to opt out of a purchase decision at any given moment. Weber and Cheng add:

"The user experience can be thought of as a composite of the user, the interface, and the context; context being an amalgamation of environment and situation. In ethnography, research is conducted in the field, where users' real-world behaviors and interactions with products and services take place, so that researchers can gain insight into how context impacts the user experiences."

Ethnographic research can also take advantage of Big Data and the refined segmentation that it can provide. Weber and Cheng conclude, "To design and develop optimal user experiences, companies must answer the right questions at the right time." Big Data that is analyzed by a cognitive computer system can actually help discover some pertinent questions that might have been overlooked and test hypotheses about them. Jodie Sangster, CEO of the Association for Data-Driven Marketing and Advertising in Australia, believes that global marketing in the future is going to be data driven. ["Where Is Global Marketing Going?" Direct Marketing News, 26 August 2013] "The future of all marketing and advertising around the globe is data-driven," she writes, "and at last, the value of measurable, accountable, customer-centric marketing has been realized." Nevertheless, Sangster agrees with Boston Consulting Group analysts that companies are still grappling with winning strategies. She explains:

"As organizations prepare themselves to ride the Big Data wave, most businesses are still struggling to centralize, analyse, and commercialize their own small data sets. It's not a local issue and it's not a new one, either: The IBM Global CMO Study first identified this struggle as the number one issue keeping CMOs worldwide awake at night in 2011. Another study released in Asia Pacific last year 2012 noted that Down Under, more than 50% of organizations felt ill equipped to grapple with the challenge of how to retrieve the value that's locked away in their data. This will continue to be the case for many more years."

Erin Haselkorn reminds us that "collecting data and analyzing it to find meaningful conclusions has always been part of how marketers go about connecting with consumers." However, with the advent of Big Data technologies, "their strategies have improved dramatically over time." ["Data helps marketers move beyond general stereotypes," Marketing Forward, 10 September 2013] As a result, he writes, marketing teams have been able to "transition away from broad stereotyping toward better targeted forms of data mining. ... We now have the capability to zoom in on the specific customer."

Although most new global middle class consumers are found in Asia, "the middle class in Latin America and the Caribbean region grew by 50 percent over the past decade." ["World Bank: Middle class grows by 50 percent in Latin America, Caribbean region," Fox News, 13 November 2013] It doesn't take a data scientist to know that tastes and lifestyles vary greatly in Latin American, Asia, and Africa — the three areas experiencing the greatest middle class growth. Regardless of where consumers are located, local conditions and culture will play a major role in their purchasing behavior. McKinsey analysts Maria Valdeviesa de Uster, Jon Vander Ark, and Wesley Walden assert that unless companies learn how to "act like a local" they will never succeed in emerging markets. ["Act like a local: How to sell in emerging markets," McKinsey & Company, September 2012] They offer three "imperatives" that will help companies "accelerate growth in emerging markets." They are:

1. "Get on the ground. Information on customers and the market is often hard to obtain. Successful companies invest in all the data sources and expert information available, but nothing beats getting a firsthand sense of how the market works by visiting local areas and resellers. This ground-level view also gives sales leaders a clear read of where the market is heading and lets them plan for it.


2. "Overinvest in the right partners. In developed markets, a company may have many capable potential partners. In emerging markets, finding a partner is a much more strategic endeavor. With limited choice, partnerships are for the long haul, which means companies must find the right capabilities and partners that share their values.


3. "Build talent for the long term. Annual growth in emerging markets can exceed 10 percent. That pace requires sales leaders to think creatively about how they will attract and retain the talent they will need to keep up."

Although I don't disagree with the "boots on the ground" imperative, I can't help but observe that the emerging world's embrace of mobile technologies means that every day more data becomes available for analysis. That data doesn't necessarily need to be analyzed in-country. And, I as noted in Part 1 of this series, emerging markets are likely to have large virtual marketplaces to accommodate this phenomenon. In addition to the fact that smartphone use is increasing, another reason that the number of virtual marketplaces is growing is that infrastructure in many emerging market countries is lacking or sub-standard. That makes building and supplying brick-and-mortar stores more challenging. Lack of infrastructure is one of the many challenges identified by McKinsey analysts. They conclude:

"Emerging-market infrastructure is often less developed, channels are fragmented, and cultural preferences often more complex and varied. Demand can be unpredictable, making the near-term return on sales investment uncertain, even if long-term growth prospects are extremely attractive."

Some of that uncertainty can be reduced by good data collection and analysis. One thing that most analysts can probably agree upon is that companies that get a late start in getting to know emerging markets are going to have a tougher time cracking those markets in the years ahead.

Do You Know Who Your "Influentials" Are?

"Online influentials who provide sole or 'exclusive' influence over consumers are the most valuable to companies," reports Robert Berkman. ["Valuing Influentials Means More than Just Counting Connections," MIT Sloan Management Review, 10 July 2013] Berkman makes that assertion based on "the finding from research conducted by Zsolt Katona, [an] assistant professor at the Haas School of Business, UC Berkeley." Berkman continues:

"Conventional wisdom, reflected by influence-ranking sites such as Klout, is primarily to count the number of a person's connections to assess his or her ability to influence others. But Katona's research has discovered that determining the value of a particular influencer is more complex, and that finding the value of an influencer depends on several underlying factors in the network structure of that individual with the target set of consumers."

The study's results sound similar to Malcolm Gladwell's conclusion that "the success of any kind of social epidemic is heavily dependent on the involvement of people with a particular and rare set of social gifts." He calls this "the Law of the Few." [The Tipping Point] Duncan Watts, a network-theory scientist, disagrees with Gladwell's conclusion about the Law of the Few. Watts insists that influentials play "no special role in trends at all." ["Is the Tipping Point Toast?" by Clive Thompson, Fast Company, February 2008] Mark Borden describes the debate this way:

"There has long been debate about what, precisely, defines influence. Dale Carnegie, author of How to Win Friends and Influence People, described it as the ability to arouse enthusiasm in others to change their behavior. Tipping Point author Malcolm Gladwell says it derives from identifying new trends and sharing them through connected networks. Network theory scientist Duncan Watts says targeting influencers is wasted effort, that starting a trend is essentially a random act." ["The New Faces of Social Media," Fast Company, 25 October 2010]

So who is correct? The folks at Crowdtap believe that Watts is the "knockout" winner. They "found that when it comes to purchasing decisions, the most influential recommendations come from people we actually know, either through the web or in person." ["Who Are the Real Online Influencers?" by Josh Catone, Mashable, 13 June 2012] Catone's article was accompanied by the following Crowdtap infographic.

Katona's study, which is entitled Competing for Influencers in a Social Network, concluded, "The most valuable person influences consumers who are not influenced by any other influentials online. A company that wants to invest time or resources in cultivating an influential person online should focus on those where the target consumers are being influenced in that product/service arena only by that person and not by anyone else." Do such influencers really exist? The study concedes, "Often, though, an influencer does not have an exclusive relationship with a set of target consumers. In these 'non exclusive' relationships, influencers who are most valuable are those where the sought after consumer/set of consumers has a very small set of additional competing influencers." Berkman reports that there was an interesting twist discovered during the study. "The next most valuable influentials are those who influence target consumers who have a very high number of additional competing influencers. ... The reason: if the target consumer has a high degree of additional competing influencers, a company will not need to invest as much money or resources to reach those consumers because they already have so many incoming connections informing them about all the options and they will buy the product that is best for them regardless of the firm’s efforts."

Berkman reports that those with "a middle range of additional competing influencers" were the least influential. Katona told Berkman that high, medium, and small were relative terms that "depended on the specific parameters set up by his model." Berkman then asks the $64,000 question: "What, then, are the practical implications of this study for social media marketers?" He concludes:

"The most important one is that firms should not just look at the number of connections an influential has when determining how many resources to devote to that person. Instead, they need to find out what the target consumer market's relationship is to the influential by taking into account their connections with any other competing influencers. Although widely available customer-influence network analyses sites and services like Klout do not take into account competing influencers and this overall network structures of influentials, Katona says that some telecom firms are now analyzing the connections between their customers and their competitor's customers on their own, and he says that it won't be long until other firms begin doing these analyses as well."

Jose Capelo is one pundit who believes in the power of influentials. He writes, "Social media influencers are fundamental to drive awareness and popularity for brands." He defines an influential as "a person or group of people, usually experts in a particular subject, which have gained recognition and credibility through their actions on Social Media. These actions include: frequent posts and of good quality, say what they think, and overall exerting personal persuasion. The influence is achieved by adding a personal brand, trust and experience." ["Importance of Social Media Influencers," Marketing Query, 18 July 2013] Russ Henneberry is another author who believes that some people have more online influence than others. He reports, "A study from Forrester Research confirms that 13.4% of U.S. adults online create 80% of the content that influences people. And 6.2% of these web users are responsible for 80% of the influence in social media." ["How to Find Influential People With Social Media," Social Media Examiner, 17 October 2012] Of course, not everyone who is in the 6.2% group of influencers is going to have influence in the same area. So, for any one industry or market, that number is considerably smaller. Henneberry asserts that "there are tools and processes to help you reduce the amount of noise in social media. You can use these to concentrate on the key influencers who can move the needle for your business. The goal is to find these key influencers and create a filter that allows you to communicate with them. This helps you develop a positive relationship with the influencers, which can grow your business."

Clearly, some consumers are influenced by "trusted strangers" they follow online. Although I tend to agree with Watts that the closer a consumer is to an influencer (e.g., a family member, friend, or associate) the greater the influence that person has on the consumer.

Targeted Marketing and Predictive Analytics, Part 2

In the first segment of this two-part series on predictive analytics, I discussed the potential of analytics for providing a better ROI for marketers as well as how to select the right databases to analyze and what to do with them once they were identified. McKinsey & Company partners Jonathan Gordon, Jesko Perrey, and Dennis Spillecke report:

"Some companies are already turning that Big Data promise into reality. Those that use Big Data and analytics effectively show productivity rates and profitability that are 5 – 6 percent higher than those of their peers. McKinsey analysis of more than 250 engagements over five years has revealed that companies that put data at the center of the marketing and sales decisions improve their marketing return on investment (MROI) by 15 – 20 percent. That adds up to $150 – $200 billion of additional value based on global annual marketing spend of an estimated $1 trillion." ["Big Data, Analytics And The Future Of Marketing And Sales," Forbes, 22 July 2013]

Andrew Gill, CEO of Kred, was first impressed with the potential of predictive analytics when he saw a presentation about how law enforcement organizations were using Big Data to predict potential criminal activity and then used those predictions to make arrests leading to convictions. It convinced him that "the marketing community can use cues from social big data and purchase history big data to predict future purchase patterns." ["Using Big Data to fight crime and predict what products consumers might purchase in the future," London Calling, 4 June 2013] He concluded:

"I believe that if individual brands start to harness the power of big social data (and that means becoming a social business), then they can start to pull ahead of their competition. Angela Ahrendts, CEO of Burberry, was quoted in a Capgemini consulting report recently as saying 'Consumer data will be the biggest differentiator in the next two to three years. Whoever unlocks the reams of data and uses it strategically will win.' Placing a bet on big data is not for the feint hearted. Those brands that will lead the big data race have already started though."

Alex Bulat offers "some practical ways of applying predictive personalization." ["Predictive Personalization as a Way to Increase Conversion," Template Monster Blog, April 2013] His first suggestion is to "provide relevant content." Targeted marketing (i.e., the implementation of predictive personalization) is all about providing the right offer to the right person at the right time in the right circumstance. In other words, it involves both content and context. Concerning content, Bulat writes:

"Website personalization simplifies the search of the content. This technology adequately identifies key characteristics of each visitor, and categorizes them based on predefined rules. At the same time, visitors feel that website is personalized and enjoy the benefits of 'noise reduction' (irrelevant information) and see only most interesting content."

Targeted marketing, of course, involves more than website content. It also includes targeting advertising. On that subject, Bulat writes:

"This technique means building up ads depending on customer's needs, based on the history of their interaction with the website. It sufficiently increases customer satisfaction and leads to an increase of conversions. While the history of user interaction with the site accumulates, this data can be used to develop unique, relevant offers in [the] future, as well as group visitors with similar interests."

Bulat believes that "all personalization techniques can be divided into two categories." Those categories are:

• Rule-based and user segment personalization.
• Personalization based on predictive analytical algorithms.

Concerning rule-based and user segment personalization, Bulat writes:

"This type [of personalization technique] is based on the rules (i.e., the practice of using history data, behavioral data and environmental data for creating unique proposals based on those predefined rules). Typical personalization rule takes the following form: 'If a visitor makes a follow-up, show the X offer.' One example of easily tracked and segmented client's characteristics is geographic location. If a customer visits the site selling cloths in New York, user will be offered personalization ads based on his IP address and will see coats and jackets, but if the IP address belongs to Las Vegas they will be offered sandals and slippers."

The location-based example that Bulat provides is a good example of why context as well as content matters. However, some location-based "personalization" has created angst for the companies using it. As I noted in a previous post, Staples, the office supply company, became the poster child for this kind of personalization strategy when Jennifer Valentino-DeVries, Jeremy Singer-Vine, and Ashkan Soltani revealed that "the Staples Inc. website was displaying "different prices to people after estimating their locations. More than that, Staples appeared to consider the person's distance from a rival brick-and-mortar store, either OfficeMax Inc. or Office Depot Inc. If rival stores were within 20 miles or so, Staples.com usually showed a discounted price." ["Websites Vary Prices, Deals Based on Users' Information," Wall Street Journal, 24 December 2012] The article noted that Staples wasn't the only culprit, other companies mentioned included: Discover Financial Services, Rosetta Stone Inc. and Home Depot Inc. The revelation was generally met with consumer outrage. The reporters were quick to point out that "offering different prices to different people is legal, with a few exceptions for race-based discrimination and other sensitive situations." On the subject of personalization based on predictive analytical algorithms, Bulat writes:

"This presumes the use of mathematical systems to monitor visitor behavior to develop predictive models and deliver most relevant content for each visitor. In contrast to the targeting strategy based on rules, algorithmic targeting creates and connects larger, and potentially infinite number of computer-generated micro-segments all of which develop when the model learns."

Cognitive reasoning systems are being developed that take advantage of machine learning. As these systems mature, predictive analytics will undoubtedly play an ever-larger marketing role. Nevertheless, Bulat cautions, "In behavioral targeting there is no such option as 'set and forget'. All targeting efforts should ... be checked at regular intervals and periodically compared to the control group (which was not personalized to verify the effectiveness of your efforts)." Brian Kardon, Chief Marketing Officer for Lattice Engines, agrees that predictive analytics will become more important. "Right now," he writes, "virtually all of our marketing data is backward-looking. Clicks, Web visits, open rates, downloads, and tweets all happened in the past. What if we could take this data and use it to predict what customers were going to do next?" ["Predictive Analytics: The Power Behind Next-Gen Marketing," CMO.COM, 14 August 2013] He continues:

"It is not science-fiction. Right now, the marketing organizations at companies such as ADP, Dell, SunTrust, and Microsoft are doing just that. They are using a variety of statistical techniques to analyze current and historical data to make predictions about the future. It's called predictive analytics. ... Fields as diverse as baseball, insurance, national security, logistics, and (thank you, Nate Silver) presidential elections can now be predicted with stunning accuracy."

Kardon believes that "predictive analytics is gaining traction for three main reasons." The first reason is that so much data is being created. He writes:

"Simply put, until recently we didn’t have enough marketing data to confidently predict the future. The amount of data the world produces every two days is equal to all the data produced from the beginning of civilization up to 2003. Today, companies and individuals are spewing out massive amounts of information in social networks, on the Web, and in internal systems (such as CRM and purchase histories). The sheer volume presents an unprecedented opportunity for businesses to gain insights on current and future buying behavior."

The second reason that predictive analytics is gaining traction is that new technologies are being developed every day to take advantage of Big Data. Kardon explains:

"Advances in technology now allow us to cost-effectively capture, store, search, share, analyze, and visualize data. There have been giant technological advances in computer hardware–faster CPUs, cheaper memory, and massively parallel processing (MPP) architectures. New technologies (Hadoop, MapReduce, and text analytics) can process both structured and unstructured big data. Today, exploring big data and using predictive analytics is within reach of more organizations than ever before."

Kardon's final justification for why predictive analytics will find greater future use in marketing has to do with "the democratization of the math." He explains:

"Until recently, big data and predictive analytics were almost exclusively the domain of highly skilled data scientists. Today, software makes even the most exotic of techniques within sight–from simple linear and multivariate regression to classification and regression trees (CART), conditional mutual information algorithms, random forests, and neural networks. While the range of statistical techniques had widened, the availability of graduate students and software has made it more accessible to more organizations. You do not need a small army of PhDs, but you will need to have some familiarity with these methods."

Kardon concludes, "The next generation of marketing leaders will be those who effectively harness the power inherent in big data, and the early adapters are already embracing predictive analytics. If you were an early adapter of marketing automation, then I predict that you'll also be an early adapter of predictive analytics." In the future, don't be surprised when you're shown an offer for something you didn't even know you wanted, but, once you've seen it, fall in love with. That's the power of predictive analytics.

Targeted Marketing and Predictive Analytics, Part 1

Seth Gottlieb believes that using predictive analytics to target customers "is going to feel invasive" as it becomes more common. However, he continues, he is "hoping that predictive analytics will help marketers target their message to receptive customers who can genuinely benefit from the product or service. Maybe this science will even help companies discontinue programs that nobody would want." ["Predictive Analytics for Marketing," Content Here, 25 March 2013] There is always going to be the risk of a "creepiness factor" when targeted marketing is employed. But implemented tastefully and ethically, the creepiness factor can be muted. Alex Bulat reminds us that back in 2002, when the movie Minority Report was released, it contained a scene where passengers riding the subway viewed "large wall-sized screens" that showed each rider a different advertisement tailored to their preferences and tastes. "When the film was shot," he writes, "this type of advertising sounded quite Sy-Fy, the product of a distant future, but today, 11 years later, predictive personalized advertising is absolutely real." ["Predictive Personalization as a Way to Increase Conversion," Template Monster Blog, April 2013] Bulat provides this definition of predictive personalization:

"Predictive personalization is defined as the ability to predict customer behavior, needs or wants – and tailor offers and communications very precisely. Social data is one source of providing this predictive analysis, particularly social data that is structured. Predictive personalization is a much more recent means of personalization and can be used well to augment current personalization offerings … [and] discover highly relevant content requiring minimal effort to find. Both bet that people still value content and try to serve up good stuff for those moments in which they have nothing else to do. Both attempt to provide a machine-augmented curated media experience."

Bulat believes that "predictive personalization improves the quality of our lives"; but, he also understands that privacy concerns are going to temper any consumer enthusiasm for Big Data analytics. In the end, he believes the benefits will outweigh the concerns. He concludes, therefore, "Marketers who see the future in personalized ads should not fear. [Since] predictive advertising helps consumers save money, such ads will be called for and will be really effective." McKinsey & Company partners Jonathan Gordon, Jesko Perrey, and Dennis Spillecke assert, "Big Data is the biggest game-changing opportunity for marketing and sales since the Internet went mainstream almost 20 years ago." ["Big Data, Analytics And The Future Of Marketing And Sales," Forbes, 22 July 2013] They go on to note, however, that many marketers don't know how to make it happen.

Meta S. Brown, an analytics consultant, writer, and speaker, believes that the best place to start is choosing the right data sets to analyze. ["Selecting Big Data Sources for Predictive Analytics," SmartData Collective, 8 April 2013] She writes:

"The value of any dataset is determined by the quality of information you can extract from it. The key to value in big data is the detail. In other words, the value of big data is in the small stuff. ... The promise of big data is in the details. You want the data to give you the information you’d get if you observed each customer in person. You want to know what each person does. You want to know how each responds to a variety of things – products offered, pricing, presentation, and so on. You only realize value from data if you do something valuable with it."

So how do you go about selecting the right data sets? Brown suggests that you must first answer the question, "What do you want to accomplish?" She explains:

"You must know what kinds of action you have the option of taking. Can you offer new products, change the selection you offer, or must you work within the bounds of what you have now? Can you develop new ads, new offers? Now, imagine that you have the same goal, and the same options, in a face-to-face situation. What information would you want? Knowing that, you are ready to look for data sources that meet your needs."

When addressing the topic of where to look, Brown recommends staying close to home. "Start with the data you already own," she writes. "Your transaction records are a treasure chest of behavioral data." She continues:

"You know when each transaction takes place, what is purchased, at what price. If you have a loyalty program or house credit card, then you also know who was buying. Your own data is more valuable to you than anything you could buy, and it's already paid for. And this data is yours alone, giving you a unique information advantage over your competitors. If you do business online, get an understanding of the information collected in your web activity logs. These logs contain revealing details about shopping behavior, including details on the behavior of non-buyers. Only when you’ve thoroughly investigated the possibilities of your internal data sources should you look beyond your walls. Once you have a clear idea of what you want to know, and the limits of your own data, can you shop selectively, and shrewdly, for information that fills in the blanks."

Gordon, Perrey, and Spillecke agree with Brown that data is important, but they note, "Data on its own ... is nothing more than 1s and 0s." Their research shows that "companies that succeed today do three things well" with that data. The first activity involves analytics.

"1. Use analytics to identify valuable opportunities. Successful discovery requires building a data advantage by pulling in relevant data sets from both within and outside the company. Relying on mass analysis of those data, however, is often a recipe for failure. Analytics leaders take the time to develop 'destination thinking,' which is writing down in simple sentences the business problems they want to solve or questions they want answered. These need to go beyond broad goals such as 'increase wallet share' and get down to a level of specificity that is meaningful."

It's clear that many of the questions that Brown suggests should be asked when selecting data are also valuable when it comes to setting up the analytics for that data. The McKinsey partners assert, "Using data to specifically unlock new opportunities requires looking at data in a new way." Their second recommendation deals with a customer's path to purchase.

"2. Start with the consumer decision journey. Today's channel-surfing consumer is comfortable using an array of devices, tools, and technologies to fulfill a task. Understanding that decision journey is critical to identifying battlegrounds to either win new customers or keep existing ones from defecting to competitors."

They indicate that "marketing and sales leaders need to develop complete pictures of their customers so they can create messages and products that are relevant to them." For more on that topic, read my post entitled "The "Person" is the Most Important Part of Personalization Marketing." The McKinsey partners conclude, "Personalization can deliver five to eight times the ROI on marketing spend and lift sales 10 percent or more. Becoming ever more effective with this kind of targeting, we believe (and hope), will mean the death of spam." Their final recommendation is to keep your approach simple. They write:

"3. Keep it fast and simple. Data worldwide is growing 40 percent per year, a rate of growth that is daunting for any marketing and sales leader. Companies need to invest in an automated 'algorithmic marketing,' an approach that allows for the processing of vast amounts of data through a 'self-learning' process to create better and more relevant interactions with consumers."

Gordon, Perrey, and Spillecke call this "a pivot-point moment for marketing and sales leaders. Those who are able to drive above-market growth, though, are the ones who can effectively mine that gold." I'll finish the discussion about how to mine the gold in the next post.