Social Media

For starters, I wanted to briefly clarify my personal position/perspective on social media. On Groundswell’s Social Technographics Ladder, I would qualify as a Specator. That classification is almost exclusively owed to my somewhat regular habit of checking out certain blogs and forums. But I am likely to never climb the ladder and become a Joiner because of my pretty deliberate avoidance of social networking sites like Facebook, Twitter and MySpace.

To oversimplify, it seems there are two primary uses of these sites – professional vs. personal. And to be honest, I can see value in both uses – to an extent.

From a professional standpoint, I can see tremendous value for companies who can more effectively target, and communicate with, current and prospective consumers. And from a personal standpoint, these sites have clearly made it much easier for people to maintain contact with friends and family.

However, often times it just seems so excessive. People seem to think that social media is everything…and everything is social media. As a result, I think it is often difficult to separate the signal from the noise. I guess I think that like many other things, social media is good in moderation. A lot of the advances that make social media so effective can also make it very annoying – specifically, attributes like speed/frequency of communication as well as the amount/type of information communicated.

So, given my selective participation in social media, I would not consider myself an expert. Additionally, I really don’t have any idea what companies are making particularly effective use of these tools. So rather than try to make sense of my limited experiences, I chose option two on this assignment. I was curious about these social media research tools and wondered what exactly they could deliver. I first decided to use these tools to determine what the buzz is around the latest news about Goldman Sachs. Then I also tested out some celebrities who are often in the news like Sarah Palin and David Beckham, as well as regional celebrities that are not currently being talked much about like Mack Brown.

I found the most interesting tool by far was the one providing website information. Understanding how many people are visiting, what else they are looking for, and what other places they stop seems extremely valuable…and also very interesting. Additionally I enjoyed the Google blog search. It very quickly provided access to the most recent and most read blogs on a particular person or topic. The volume was obviously considerably higher for Goldman Sachs who are all over the headlines right now. And the sentiment is overwhelmingly negative. In contrast Sarah Palin also generates a high volume of activity but the commentary is clearly mixed. This tool seems like a great way to quickly get a pulse for what people are saying about a particular topic.

I had higher expectations for the trending tools. At times it was interesting to view by geography – somehow David Beckham is hot in Nepal right now – and at other time it was difficult to extract anything specific. For example, where in the US is this information most sought after? Additionally, it was interesting to view the growth or “hotness” of a person or topic in relation to their category. This seems to have potential for brands or companies that are interesting in gauging level of response to their product in general, or response to a particular advertisement or promotion. But it seems further detail would be necessary for this information to really be valuable.

It seems what is most helpful is to set up alerts and notifications to ensure that information on whatever topic might interest you gets into your hands.

As a business school student it is nearly impossible to escape discussions about Walmart. Whether you are talking about real estate, supply chain, sustainability or anything in between, the retailing behemoth rears its head in most conversations. And given the fact that Walmart maintains 460 terabytes of data – more than the entire internet! – we would be remiss to ignore them when considering the topic of customer insights. But despite their relevance in all of these different spaces, when it comes down to it Walmart is mostly about one thing and one thing only – Every Day Low Prices. This mantra is woven into the culture at Walmart and influences all business decisions.

Having spent a summer working for a supplier to Walmart, I am keenly aware that each grocery store or mass merchandiser operates using a different business model. EDLP is clearly Walmart’s source of competitive advantage. They thrive because they can offer lower prices than any other retailer. In contrast, a supermarket like Publix focuses more on shopper experience. Things like cleanliness, friendliness, flexible return policies, and many other characteristics combine for a higher quality experience. Additionally, loyalty programs are in place to provide benefits to Publix customers.

So, at first thought, it doesn’t make sense to me that Walmart would spend so much money on data mining technology. After all, reducing costs is what allows Walmart to offer such low prices. So, why pay so much ($4 billion) for this technology? I would much sooner expect someone like Publix to make an investment like this to further enhance their shopper experience. But, on second thought, Walmart seems to be successful in using this information to manage inventory costs – a major challenge for retailers. So if this investment in customer information allows them to better manage costs and continue to offer low prices, then in a sense it does contribute to their competitive advantage…and in turn create a better customer experience – assuming that those customers prioritize low prices above everything else.

However, as the article discusses, Walmart isn’t all that concerned with the demographics or psychographics of their customers. They just want to know what goes into their baskets when they shop. This being the case, it is troubling that they have access to so much information on customers – specifically information that has no relevance to grocery shopping. I don’t mind if Walmart wants to know how much beer and Pop-Tarts to stock on the shelves in advance of a hurricane. I certainly wouldn’t want to be caught in a hurricane without either. But knowing that they could reference mortgage payments and bank info seems like an invasion or privacy.

I think the main point is that customers would be willing to share information that will create benefits for them. Whether those benefits come in the form of low prices, fully stocked Pop-Tart aisles, or loyalty cards from Publix. But when information is used without customer knowledge or without customer benefit, it seems a breach of privacy and/or trust.

The sheer size of Walmart obviously grants them huge power over their suppliers. For many manufacturers, Walmart represents nearly 30% of business. As a result, often times suppliers have no choice but to adhere to the strict policies Walmart puts in place. For example, products being stocked at Walmart must have a certain level of velocity or be at risk of getting booted off the shelves in the following month or quarter. And often times just to get stocked, manufacturers margins are getting squeezed to the point of loss. Now, there are examples of Walmart using its power for good – forcing Procter & Gamble to change packaging on liquid soap. But I imagine most examples are not quite as noble as this and result in reduced profitability rather than increased efficiency.

Babel Fish

On February 8, 2010 Fast Company ran an article entitled “Will Google’s Translator Phone lead us to Babylon or Babel On?” The article revealed Google’s plans to design a smartphone that can translate between two languages. The article points out, only half kidding, that this Google product is not all that dissimilar from the Babel fish proposed in The Hitchhiker’s Guide to the Galaxy, where you could literally stick a small yellow fish (see below) in your ear and be able to communicate with all other species, including aliens. On a more serious note, the author went on to debate the merits, as well as the dangers, of such an invention. Regardless of where you stand in that debate, the fact that Google is moving in this direction is interesting. As Thomas Friedman wrote, the world has become flat. With foreign cultures/markets becoming more accessible, the motivation to learn a foreign language has increased drastically.

Learning a second language is of particular interest to me. My wife is French. She has relatives in France that we visit on a fairly regular basis. And though her parents are here in the US, most conversations we have with them typically take place in French. So clearly, there are many occasions in which I would benefit from being fluent in French. For the past several years, I have utilized a combination of classes, tutors, flash cards, podcasts, subtitled movies, and computer software to attempt to learn. Unfortunately, I’m still not proficient in French and probably have a ways to go before I’m there.

I suspect that there are many people out there who share my frustration. And unless, or until, Google solves this problem for each of us, we are left with the usual suspects in terms of language acquisition. But I would venture to guess that someone out there can build a better customer experience for those of us motivated to learn a new language.

Perhaps it is Rosetta Stone. On January 26, 2010, Rosetta Stone opened an “experience store” in Times Square. The store is designed to allow customers to fully engage in their dynamic immersion method of teaching a language. Or perhaps it will require a new approach entirely. BusinessWeek ran an article on February 19, 2010, entitled “Second Language Comes Faster When Taught in Own Accent.” The article argued that using native accents, which is common, is far less effective of a teaching method. For better results, languages should be taught using the learner’s own accent. This is quite different from anything I’ve seen or heard.

For my paper, I would like to explore whether the generative research concepts we discuss in class could be applied to language acquisition products in order to improve the overall customer experience. As the Fast Company article demonstrates, there is sufficient demand for these types of products. And as the BusinessWeek article proves, there are insights to be gleaned that can improve the customer experience. How do we learn best? Are there better methods for different ages? Are there better methods for people with certain backgrounds? Is there a combination of tools that could be used for greater results? Are some people just not able to grasp a second language at all? There is a boatload of questions that could steer us in the right directon. Many of these topics have been addressed in scholarly papers – the importance of language, perspectives on teaching and learning. But I’d like to more fully explore the strengths and weaknesses of current approaches within the context of our class learnings.

Myopia

Throughout my career I have worked in sales and marketing for both products and services. In each of these experiences I have had (some) exposure to the new product development process, as well as the methods used to derive customer insights. So I have had the opportunity to conduct in-depth interviews, facilitate focus groups, and administer surveys. These traditional methods were fairly boring, but so were the product and service ideas that they we were evaluating. If only attempting an incremental change to your product or service, customers are more likely to be able to articulate their wants and needs. However, as Gladwell points out, when considering a truly revolutionary idea these traditional tools are often “too blunt.”

As demonstrated by the Kenna example, asking people to make an evaluation based on listening to 30 seconds of a song over the telephone is myopic. It seems akin to asking Mr. Magoo to be your co-pilot on a cross-country trip. In both instances, the experience created is going to be out of focus, without context, and potentially dangerous. Coke learned this lesson the hard way – the packaging is part of the product…and therefore should be part of the evaluation. Although, I wonder exactly where the packaging ends and where bias begins. How much is too much? A coke can is not just a can…it is hundred of billions of dollars in advertising to create a brand image. What if listeners knew that Kenna became a grammy nominated artist in 2009? And what if we gave them a positive review from Pitchfork or Metacritic to read? I suspect many people become aware of facts like this before they make their own judgements about music – much like many consumers are bombarded with advertising as they make their judgements about cola. What exactly is part of the package, and thus should be evaluated?

The generative research methods that we’ve discussed in class resonate quite a bit with me. For example, Zaltman’s ZMET process is one that I am somewhat familiar with. I really like the fact that this technique acknowledges the vast amount of information that is communicated non-verbally. These observations are often where the valuable information lies, and these gems can be lost using standard qualitative methods. As an MBA student, I find these methods extremely fascinating and would be anxious to put them into practice. But my professional experiences suggest I might be met with resistance. I can easily imagine people regarding these methods as academic, esoteric, and not statistically significant. I suspect there are a lot more Magoos out there than there are Zaltmans.

On a somewhat related note, I find it interesting that Gladwell’s article discusses the music business in detail, given our class discussion on the (forced) evolution of the industry. As outlined with Kenna, record labels historically promoted a relatively small number of artists that they expected to appeal to a relatively large number of listeners (Top 40). Thus, the market research phase was an important step in reducing risk. Only artists that were a “sure thing” would get backed by the labels.

However, with the dawn of the digital era of music, outlets like Amazon.com and iTunes have demonstrated that long tail economics can also be profitable. Thus, there is a place in today’s music industry for people like Kenna, despite their “dismal” results in market research testing. The internet’s ability to instantly provide widespread distribution and reach niche areas of the market changes the game. It has opened the door for so-called do-it-yourself artists to make a splash without the support of big labels.

Long tail economics is still being debated and perhaps the music industry is an exception – but supposing it is fairly easy, and profitable, to reach the long tail, does that change the value of market research? Is it more or less necessary?

Persona

Below is a vignette that might be useful in Phase 2 of the Persona Lifecycle: Persona Creation and Gestation

-A day in the life of “Brad”

It is Monday at 10:00am. Brad enjoys a slow wake-up. He told himself he would definitely wake up at 8:30am this morning to get a jumpstart on the week, but when the alarm sounded, there was nothing that seemed particularly pressing, so he rolled over. But now, Dawg the dog has lost all patience and is ready for a walk.

So after a toasted English muffin, Brad grabs his iPod and slips out of his two-bedroom bungalow style home in Hyde Park. Brad has just assembled his new “A List” playlist, so quickly sets the shuffle as Dawg starts to pull him towards the park they visit most mornings. Twenty minutes pass - Dawg is satisfied with the exercise, Brad is satisfied with his new band discovery after perusing iTunes for hours the night before.

Back at home, Dawg is lounging and Brad breaks out his laptop to check up on email. Considering he last checked emails before hitting bed at midnight, it’s no surprise that there is no new news. But still, Brad manages to kill some time on ESPN.com and a handful of other sports blogs that keep him informed on the hometown teams he left behind to pursue an MBA. Still more time is killed as Brad tweaks the rosters of his various fantasy sports teams.

Once convinced that he can’t effectively procrastinate anymore, Brad grabs his backpack and heads to class. With one more semester of grad school remaining, Brad’s thoughts often center around job searching, house hunting, and the like. Today is not much different and as he jumps on the bus, Brad starts daydreaming about where he and his wife might travel after graduation. They are always looking to explore newplaces. As he walks towards class, he switches his thoughts towards how he might celebrate the 30^th birthday that approaches.

We next catch Brad as he gets home from school and cracks open the beer he’d been thinking about during the bus ride home. Currently Brad’s fridge is full of a homebrewed stout that he recently bottled with a friend. After a few sips, Brad settles down in front of his laptop once again to attempt to learn some French. He loads up the Rosetta Stone French disc and slogs through the lessons he couldn’t squeeze into the morning routine.

As he finishes up, his wife walks in from her day’s activities and conversation turns to dinner. Tonight they are going to meet some friends to check out a new place on the East side. Despite adhering to a tight student budget, Brad and his wife thoroughly enjoy a good meal. After that, they will probably get home and try out the new Netflix movie that went unwatched over the weekend. Or perhaps early to bed tonight, as Brad has an 8:00am tee time tomorrow morning with a few buddies.