This is why Amazon is considering setting up some retail locations. This should be an opportunity for some of the “brick and mortar” stores. Wal-Mart comes to mind because of their expertise in logistics and convenient locations. I have purchased several items through walmart.com instead of Amazon because free pickup at the Wal-Mart store – just a couple miles away – is even handier than free home delivery…when you worry about having the item sit in your driveway all day.

Despite Wal-Mart’s advantages I suspect that their cost-cutting culture, based on “everyday low prices”, may handicap them in competition with Amazon. This problem was illustrated when I went to Wal-Mart recently to pick up an Internet delivery.

Picking up my walmart.com order

The pickup area is an unadorned room in the middle of the back wall of the Walmart store. I suppose it is in the back in order to be by the warehouse, but another goal may be to make you walk through the entire store – like someone buying milk in Kroger.

There are big negatives to the location: it is a walk, it feels remote and cutoff from the store, it is a long way to carry packages going out. In addition if you forget to get a shopping cart as you entered the store it is a hassle to go back and get one.

As noted, the room is austere. A large sign over a credit card swipe machine says to touch the screen to let an associate know that you are waiting to pick up a walmart.com order. The space is shared with restrooms and a job search computer. The effect is to make you feel like a third class customer. Several associates walked through but simply gave me a pitying look, probably knowing that I would be there a while.

I waited 5 minutes before leaning across the counter to the inside phone. I hit the page button and said “walmart.com customer waiting for assistance in the pickup area.” An associate came back fairly quickly. It turned out that only one of the two text messages I had received from walmart.com  was accurate: the second package had not arrived. The associate gave the impression that 50% accuracy was normal.

The pickup took nearly 25 minutes. In that time Wal-Mart managed to deliver half of what was promised and convinced me that I was a low value customer.

I would actually like to see Wal-Mart prevail against AMZN, perhaps out of nostalgia for the 80s, but it will take a company that cares about service to fight Amazon. Maybe Target?

Happy Day – Seeing my students graduate and getting my tenure and promotion letters!!!

If so, please go to my other blog and share your ideas!!!

Thoughts on a theory of innovation? 

Yesterday on my Facebook feed there was a serious discussion of an article from the Daily Currant claiming that Sarah Palin had advocated invading the Czech Republic to thwart radical Islam in Chechnya.

Of course the article was a fictional satire, which would seem obvious from:

1. A cursory reading of the article,
2. The article being in a publication which describes itself as political satire, or
3. Even the name of the publication – isn’t a currant a tasteless raisin?

Yet some web-savvy Facebook friends and acquaintances were seriously discussing what their European friends and the rest of the world would think… (The thread has been removed, so don’t bother trying to find the conversation…)

The Sexiest Man Alive

I was reminded of when the People’s Daily, the official newspaper of the Chinese Communist Party reported as fact the Onion naming Kim Jong Un the Sexiest Man Alive:

Where does this credulity come from?

In 1996 well-known journalist Pierre Salinger was vilified for claiming that TWA Flight 800 was accidentally shot down by a missile fired from a Navy ship, based on a document he found on the Internet. I think we have all become much more skeptical about Internet news since then.

But where does the credulity to believe an Onion or Currant article come from? I think the credulity comes from people looking for support for their biases or worldview. If you think that Kim Jong Un is a misunderstood comrade, you might be pleased to see him named the sexiest man alive. If you believe in the Tina Fey version of Sarah Palin, the Currant article may appeal to you.

This tendency is dangerous in a world were people now select that news and commentary that they are comfortable with. If you watch Fox News and seek online commentary via the Drudge Report, you see different news and opinions than a neighbor who views MSNBC and scans Kos. You may also be more susceptible to false information… There is a risk to all the choice!

How do you avoid this tendency to select “news” and information that is comforting to you??

Calculating the ROI of Social Media

In five previous posts the importance of measuring social media efforts and a broad array of metrics tied to social media activity have been discussed. All of these measures can potentially have value to assessing what is currently going on in the SM effort and trends for the organization’s social media presence. But what is the bottom line? What is the ROI of social media? As discussed in the next and final chapter of this text, organizational goals and objectives will be set based on the organization’s mission and strategy. Therefore the goals and measures used by different organizations will differ. In this section some of the possible return on investment or success metrics for a social media campaign will be discussed.

Advertising Measures

As discussed in Chapter 8, social media can be used as a complement as well as a substitute for advertising. Therefore it makes sense that some of the same measures used to compute success in advertising should apply to social media campaigns. Surveys can be conducted in the online community or randomly to measure advertising metrics such as:

•     Cost per impression

•     Reach

•     Frequency of impressions

•     Brand or product awareness

The cost of attaining these outcomes can be compared to standard advertising costs to get a comparative return on social media efforts in the form of any savings versus traditional advertising.

Other commonly used advertising and marketing survey measures such as customer satisfaction or purchase (or repurchase) intention should certainly apply to social media campaigns. As will be discussed in Chapter 14, Dave Evans (2012) argues that the net promoter score[i] (Reichheld 2003), based on the simple question, How likely are you to recommend this company/service to a friend?, should have special meaning for social media marketing as it is based on word of mouth[ii].

Based on the importance of WOM many organizations will closely monitor share of buzz as a success measure for a social media campaign.

Monetary ROI—Sales, Revenue, and Profits

For many B2B companies, quality leads are a scarce and valuable input. As discussed in Chapter 12, social media, particularly LinkedIn, has been shown to be good sources of B2B leads.[iii] Since many firms can assign an estimated monetary value to quality leads, lead generation through social media activity can be evaluated as a financial return on investment for some B2B companies.

In some circumstances companies may have good estimates of sales, revenues, or profits resulting from social media. As discussed earlier, through the use of custom links and/or alternative web landing pages, an organization engaging in e-commerce or fundraising can estimate revenue from social media efforts. Firms may also estimate the origin of sales by surveying customers, by asking at the point of sale (“where did you hear about us?”), or by using special coupons or discount codes on social media promotions. Social media managers should try all means to track and quantify the benefits of social media efforts.

Key Takeaways

•      Social media efforts can be assessed by metrics from surveys commonly used to measure the impact of advertising.

•      The net promoter score measures the likelihood of a community member recommending an organization or its services to a friend.

•      Revenue, sales, or profits due to social media can be estimated from survey or point-of-sale questions about where a purchaser learned of the offering, from observation of activity on a commercial web site, or for the implicit value of outcomes such as solid leads.

……………………………………………..

This is part #6 and the final excerpt about “Metrics” from an early draft of a text for teaching Social Media Marketing. Please do not copy without the approval of Flatworld Knowledge and Gary Schirr. I welcome thoughts on omissions, additions and corrections!!!

Other articles:

Teaching SMM: METRICS #1 Importance of Measurement

Teaching SMM – METRICS #2 Activity Measures

Teaching SMM – METRICS #3 Measuring Influence: Art or Science?

Teaching SMM – METRICS #4 Influence Scores

Teaching SMM – Metrics #5 Monitoring and Listening

Teaching Social Media Metrics – The Hangout (Video)

http://sfy.co/dHK4

(I failed at inserting the post into my WordPress blog…)

Monitoring and Listening to Online Conversations

There is an incredible amount of information, discussion, and “content” being created and posted on the web every day. Former Google CEO Eric Schmidt was quoted in 2010: “There was five exabytes of information created between the dawn of civilization through 2003, but that much information is now created every two days, and the pace is increasing.” Even though Schmidt may have exaggerated a bit—the exact figures are subject to some debate (Finley 2011), there is no doubt that we are living through an information and knowledge explosion. As noted several times, social media marketing is commonly referred to as “word of mouth on steriods.” Key metrics of social media efforts should logically include what is being said about an organization in social media or other online conversations.

Monitoring the Conversation

One measure of a social media campaign is the buzz, quantity of online conversations involving an organization or its services. By using Google, Google Blog, and Google alerts, a participant or organization can regularly monitor the conversations online and detect how often an organization or its products or services are mentioned. A key question is, of course, whether “buzz” seems to be increasing in line with SMM efforts and whether it changes based on new social media marketing campaigns.

Word of mouth does not follow the old Hollywood public relations dictate that all publicity is good publicity. Certainly all word of mouth is not good. It would be useful to track positive word of mouth separately from negative WOM. Again by using Google, Google Blog, Google alerts, and the social media search engines, or the paid services to identify the comments, an organization can regularly monitor the conversations online, collect and store all comments and mention of the organization, and then periodically rate comments as positive, neutral, or negative. Metrics related to positive/negative buzz include:

•     Daily or weekly levels of positive and negative buzz

•     Percentage of an organizaton’s buzz that is positive (percentage positive buzz)

•     Percentage negative buzz

•     Share of buzz by an organization

•     Trends in all of these levels

Share of buzz is a common goal of social media efforts as an increasing share of the total conversation within the defined market space or topics is seen as winning the WOM battle. A firm may wish to compare its share of buzz to its market share of products or services within the same competitor group.

How does an organization collect and analyze the data and compute the share of buzz? Small businesses or specialized B2B business may be able to simply find the comments using Google, Google Blog, and other search engines, copy and check for relevancy, classify and compute the numbers, ratios and trends. There also are services that specialize in tracking SM and online conversations. One free service to track the total numbers of conversations is SocialMention™. For a fee there are numerous tools such as Radian6™, BuzzLogic™, TNS Cymfony™, Sysomos™, Cision™, and Buzzmetrics™ that will collect the data from online conversation and compute some of the analysis including share of buzz, computing the number of comments about an organization to the total number of comments about the organization and its competitors. Buzz, share of buzz, and trend of buzz are all interesting ways to view the WOM effect of social media efforts. Some organizations view “share of buzz” as the key measure to judge their social media efforts. Some monitoring services employ algorithms to classify negative and positive buzz or even perform basic ethnographic analysis such as combined comments of similar themes or looking for trends.

Listening to the Conversation

An article in the Journal of Marketing reported research showing that good ideas for product innovations on automobiles were developed from observing the actions of an auto maker’s online community of customers and prospects, when looking at options for cars.[i] The customers were limited to alternative choices on the site: imagine how much richer the data would be if they were freely conversing and had more choice of options to discuss. In the blogs, forums, on the website, FB, Twitter, and LinkedIn, customers may be conversing about their thoughts, opinions, and feelings of an organization, its products and customer service, and its competitors. The possibilities for useful market research are endless—think of a 24/7 focus group without the observer and group effects that so limit new ideas in a group[ii].

Consumer products firms, such as P&G, Nokia, Coca-Cola, and Nike, have for years hired trained anthropologists to watch and listen to users to find out their deep thoughts, feelings, impressions, and creative uses of their products. Ethnography is a deep study of a cultural phenomenon without limited preconceived ideas using observation, interviews, and other primary data. Marketers have used ethnography to help understand how to sell cell phones in poor villages in China and India, what urban youths value in sneakers, why some insect spray customers wanted to see the pests die, and many other valuable product and marketing insights. The insights are often surprises, which is why the observer or researcher seeks to limit preconceived notions. Now an organization may not have to send researchers into the field to observe interactions and conversation: Similar rich data may now be available simply by listening online. Someone in an organization can be observing prospects and customers having detailed technical discussions on forums or groups; venting anger on Twitter or blogs; or sharing short Facebook comments.

The observer effect, the change of the phenomenon being measured because of interaction with the researcher/observer may be eliminated in online data. However an issue with the researcher being invisible is the application of the principle of informed consent, the basis of ethical research for qualitative research and human subjects. Subjects of human research and ethnographic research have the right to know that they are the subject of research, what the research is about, and to freely choose whether or not to participate. It may seem reasonable to consider Tweets as public data not subject to requirements of informed consent (an argument can occur even here) but what about other networks where there is at least some pretense of membership or privacy? The ethics of such research will be an area of concern and attention as online qualitative research grows. An organization should adopt a policy for online qualitative research that considers this issue of informed consent.

Kozinets (1999) uses the term Netnography to describe ethnography using online data, although other social scientists prefer to simply refer to online ethnography[iii]. Kozinets advocates gathering and analyzing the data with the same care that anthropologists or sociologists use in studying offline phenomenon: in fact, using trained social scientists to do the analysis if possible. If a firm does not current have the budget or priority to hire an expert analysis of the online information, it can still be valuable to have a knowledgeable insider monitor the data, looking for trends or insights.

Key Takeaways

•      Buzz should be monitored in a variety of ways: number of daily comments about your organization, trend in the number of those comments, changes with different SM campaigns, positive versus negative buzz, and share of buzz.

•      Beyond simply counting mentions there is rich content and information online about an organization, its customers, competitors, and marketplace in blog posts, forums, comments, as well as SM conversations in the data available online.

•      Organizations should both “monitor” and “listen” to online conversations.

•      Internet ethnography is challenging and may need to be done by algorithms for consumer brands and large firms, but many organizations, such as B2B firms, small companies, and local nonprofits can benefit by studying information in-house.

This is part #5 of an excerpt about “Metrics” from an early draft of a text for teaching Social Media Marketing. Please do not copy without the approval of Flatworld Knowledge and Gary Schirr. I welcome thoughts on omissions, additions and corrections!!!

Other articles:

Teaching SMM: METRICS #1 Importance of Measurement

Teaching SMM – METRICS #2 Activity Measures

Teaching SMM – METRICS #3 Measuring Influence: Art or Science?

Teaching SMM – METRICS #4 Influence Scores

Teaching Social Media Metrics – The Hangout (Video)

………………………………………………

Influence Scores: Interactivity, Performance or Nothing?

At the time of this writing, the growing influence of influence measures has generated considerable controversy. There are stories of otherwise qualified candidates allegedly turned down for jobs because their Klout™ or PeerIndex scores were less than 90th percentile level. Mark Schaefer (2012, p. 1) begins his book on influence measures with a story of a marketing expert who was turned down for a job because of a Klout score of 45. After a “tweeting rampage” to game the system, his Klout score reached 70 and he started received unsolicited job inquiries. Some applicants with high Klout scores have begun including the scores on resumes. This raises a fairness issue: Should people be evaluated for jobs and special marketing offers based on an ambiguous score generated by a secret algorithm?

There have also been outcries when Klout adjusts its algorithm. In October 2011, a change in the Klout algorithm resulted in many participants with high scores seeing the measure drop ten to twenty points literally overnight. This caused an online uproar and a call for people to opt out of Klout. However there seems to have been little long-term change except that some organizations began to follow at least one additional influence measure besides Klout.

A big issue is: What is it that these services actually measure? What is really happening when someone “Likes” or “retweets” someone else? Should anyone have confidence in secret algorithms measuring occurrences that may or may not signal influence? For example, it seems hard to believe that Justin Bieber had more clout or influence than anyone else in the world, including President Obama; yet until Klout made a revision Justin was the only 100 by Klout’s measurement. Defenders of Klout are quick to point out that Klout and the other influence measures are only measuring online influence. But that doesn’t explain why some celebrities like Oprah Winfrey have high scores despite following few people and being relatively inactive. Clearly there is a celebrity effect from offline activities.

Ferenc Huszár, data scientist at PeerIndex, pointed out to me that influence is the type of latent social measure that generally requires multiple items and weightings driven by the data for measurement. Ferenc compared influence measures to IQ measures; IQ measures are similarly attacked for imprecision and imprecise definition, but have proven to be predictive. To further the comparison he noted that the top IQ scorer, Christopher Michael Langan, a horse farmer and former nightclub bouncer, seems to be the same sort of anomaly for IQ scoring as Justin Bieber is for influence measurement.[i]

A basic issue is what kind of “influence” these services measure. Klout, PeerIndex, or Kred influence seems to be a very weak sort of “influence.” Getting someone to click a link or like, retweet, or favorite a message is a long way from getting someone to buy something or contribute to a cause. One SMM expert even advises people wanting to be more effective on social media to avoid asking followers to actually do anything[ii] (Schaefer 2012, p. 121). An example: I posted a very favorable video review of the Tao of Twitter by Mark Schaefer. In order to measure the impact of the recommendation, I sent out five tweets to the video which had a private Amazon link on it and another five tweets simply recommending the book with the Amazon link in the tweet. With high influence scores and 50,000 Twitter followers, I was disappointed with only eight visits to the Amazon site and two purchases of the book resulting from the campaign. Of course some may have bought it another time or gone to another online service but eight visits and two purchases did not make me feel very influential! According to results cited in ROI (Schaefer 2012, p. 119–120) these results were not bad relatively: an author of a different social media book arranged for recommendations and tweets from a social media superstar with 1.2 million followers and then a services of influential SM experts with an aggregate of 1.5 million followers and as a combined result sold only one book. Influence to persuade others to follow, retweet, like or favorite may not directly lead to sales or donations.

Schaefer (2102) defines the online influence measured by these services as the ability to create content that is moved through the network and creates reactions. When Justin Bieber tweets, his multitude of followers pay attention and react to his content. This is very specific type of influence, but is still important. As noted in earlier chapters, there are many success stories in social media marketing. For example ticketing site Everbrite.com notes that each Facebook share of an event is worth $2.52 in average sales, a LinkedIn share $.90, and a Tweet $.43 (Rowan and Cheshire 2012). Nicolas Christakis, the author of the book that only had one sale through the high-influence/high-follower promotions, found greater success with a social media promoter who had a smaller, more focused following, leading him to the conclusion that “a small group of attentive follower may be more easily influenced than millions following a famous name” (Rowan and Cheshire 2012). Klout, PeerIndex, Kred, and likely other influence-measuring firms are studying and reporting influence in niches, such as topics, interests, and hobbies.

In an interview posted on YouTube, Azeem Azhar, founder and CEO of PeerIndex, said that marketers should focus on influencers in the “mighty middle” of PeerIndex scores, 35 to 65 (Remember from Table 5.3 that although 35 to 65 is the middle third of PeerIndex scores, which run from 1–100, the distribution of scores is skewed toward lower scores, so SM participants scoring 35–65 are actually in the 75th–98th percentile of all Twitter users). Ries (2012, p. 15) cites Kami Huyse, CEO of Zoetica Media, who believes that those with the very highest scores may be jaded and prefers to target influencers in the “magic middle…who are more serious, consistent, and eager to engage.”[iii] Morgan Brown (2012) compared two marketing campaigns by his firm and concluded that it is better to market to the Klout masses than the very top influencers, suggesting that the very top influencers get too much attention already.[iv] These comments suggest that when an organization attempts an influencer campaign, it should experiment with different levels of influence levels.

Example: The Author’s Influence Measures (August 2012)

I have been active on social media, especially Twitter and a blog, for several years. As noted elsewhere my online community helped me design my social media marketing courses. In Table 5.4 my influence ratings on five of the leading influence measuring services is compared to three social media personalities who I consider my “mentors” or aspirant group in social media. All four had TweetGrader scores of “100” higher than 99.5 percent of Twitter participants according to that algorithm, while the four ranged from the 93rd to 99th percentiles in the Twitalyzer influence measure. The four have many followers and are active users which, as noted, are rewarded in those measures. Recalling from Table 5.4 that a Klout score of 53, PeerIndex score of 45, and Kred score of 670 placed a participant in the 90th percentile for the respective measures, all four participants are at or above the 90th percentile in those rating schemes.

Source: From http://www.klout.com, http://www.peerindex.com, http://www.kred.com, http://www.tweetgrader.com, and http://www.twitalyzer.com (08/22/2012)

There are divergences in relative scores for different measuring services. Even though each service is attempting to measure social media influence primarily by analyzing interactions and communities on Twitter and Facebook, the relative scores are not consistent. Mentor 3 has a Klout Score that puts him below the 95th percentile of participants, while TweetGrader indicates 99th percentile. Similarly there are discrepancies in ranking the four SM users: Mentor1, who has written two popular books about social media and has an award-winning blog, has a higher Klout score than me, while I have a slightly higher PeerIndex score; among the four compared in the table, I was third on Klout, Kred, and Twitalyzer, but second on TweetGrader and first by the PeerIndex measure. Another free site which only uses Twitter data, TweetLevel™, ranked the four participants in the same order as Klout and Kred, but the top three all had high scores in the 80s. This probably reflects the fact that Twitter is the dominant SM platform for these SM participants.

Readers are encouraged to check out their own social media influence measures on the services discussed here and some of the others listed in Appendix B of Schaefer (2012), as well other new services that have been established by the time this is being read. For personal scores it is useful to compare scores with a referent group of people of similar interests or an aspirant set of social media participants. As shown in Table 5.4, I gauge my scores against those of three prominent social media marketing people. For organizations it is logical to look at ranking compared to competitors as well as “best practice” organizations in social media.

Marketing To and Through Those with “Influence”

As noted in Chapter 6, an organization employing a word-of-mouth marketing strategy may seek to leverage individuals with influence. Companies can provide product or services to individuals whose Klout, PeerIndex, Kred, or other influence score indicates an attractive level of influence. Klout and PeerIndex have public rewards systems under which individuals with a given score level and area of influence can claim free benefits. The services also provide private outreach services for companies who seek to privately contact influencers who are influential on given topics or interests for special offers or gifts.

Influencers receiving free products and services have an ethical and legal obligation to disclose the benefits when writing, blogging, or even tweeting about them. Organizations running influencer campaigns should make that responsibility clear to their targetted influencers. Of course, typical standard disclosure language would not easily fit Twitter’s 140-character limit for an entire message!

Contextual Influence Measures

The influence measures discussed so far are widely known since they are open to the public and in most cases depend on individuals registering, so they can track multiple social media sites for a participant. Ries (2012, p. 43) differentiates between this previous set of influence measures whom she refers to as “personal influence measurement tools” and a separate group of measures that are discussed in this section which she calls “contextual influence measurement tools.” These contextual influence measurement tools will not generate as much buzz in social media sites as the public measures, but may be of keen interest to marketers.

For contextual analysis a powerful search engine that allows researchers to focus on a complex topic or idea is a starting point of the analysis. Ries (2012, p. 44) mentions three firms that have developed such search capability along with a scheme to measure participants contribution to the conversation: MBlast™, TRAACKR™, and SpotInfluence™. Using these search tools an organization can identify participants with influence within specific topics and interests the firm identifies. These tools may also track conversations and actions of these key subject-influencers in real time. These contextual tools can help an organization track and guide key online conversations and key participants while the conversation is occurring.

Appinions™ (http://www.appinions.com) aims to revolutionize influence measurement by going several steps further in evaluating the online (and offline) world. Like the other contextual analysis tools, Appinions effectively integrates online and offline accomplishment by including Internet references, such as newspaper or other articles or citations, into their online analysis. The focus of Appinions, though, is on opinions and opinion-shapers. Based on a decade of research at Cornell University on semantic patterns of opinions and sentiments in text, Appinions scores authors and publishers (Ries 2012, p. 52) on opinion influence within a topic based on:

1.   Preference—Who is picking up opinions?

2.   Imitation—Are other people duplicating those opinions?

3.   Trendsetters—Topic or discussion originators.

The ability to monitor opinion-makers in an organization’s market or key topics in real time has obvious implications for WOM marketing. Organizations can actively monitor the conversations and decide when to join in. Another interesting capability of Appinions research is to note what other topics are of interest to those key opinion shapers. Observed joint interest could shape marketing approaches.

In a discussion of current trends in influence measurement, Mark Schaefer, author of ROI, stated that Appinions will have a major impact on influence measurement[v]. I believe Mark’s statement could be an understatement: If the semantic analysis of opinions proves accurate, this form of influence measurement, monitoring, listening, and reacting should have a huge impact on marketing in the years ahead.

Summary of Influence Measuring

Influence measurement is rapidly evolving. There will certainly be new influence measurement services and new approaches to measurement when you read this chapter, and still other approaches six months hence. Two interesting ideas to take away from this discussion are to explore (1) marketing to the “magic middle” influencers as measured by the personal influence measures and (2) the use of contextual influence measurement tools to impact the online conversations of interest real time. These measures are controversial and raise privacy concerns but they seem likely to be employed even more by organizations going forward. According to Ries (2012, p. 5) the four major uses organizations make of influence measures today are to:

1.   Prioritize customer service by influence of the customer.

2.   Provide promotions and product samples for influencers.

3.   Court influencers with ongoing public relations efforts to get the organization’s message out.

4.   Manage the brand reputation and long-term plan.

There is some controversy attached to these uses of influence. The ethical and legal issue of promotions and samples for influencers and the need for disclose was already discussed. There is also a fairness or discrimination issue from special offers and gifts to those with high influence scores. How will customers react when they realize that they are pushed to the end of the queue for customer service because they don’t Tweet very often? Organizations must plan to address the fairness issue as they make such use of influence scores and discover new applications.

This is part #4 of an excerpt about “Metrics” from an early draft of a text for teaching Social Media Marketing. Please do not copy without the approval of Flatworld Knowledge and Gary Schirr. I welcome thoughts on omissions, additions and corrections!!!

Other articles:

Teaching SMM: METRICS #1 Importance of Measurement

Teaching SMM – METRICS #2 Activity Measures

Teaching SMM – METRICS #3 Measuring Influence: Art or Science?

Teaching Social Media Metrics – The Hangout (Video)

I think of the old Miller Lite commercials… Visualize the large crowd in a full session yelling: Great Talks! Switch the camera to the crowds at the TweetUp or after party who shout: Live Networking! …. Great Talks! Live Networking!!

Great Talks

When I go to a one or two-day conference, I generally deem it a success if there were two good sessions, one of which I consider worth the price of admission. Once again I put nearly every session in that category at Social Slam – and not just because the price is reasonable!

I am a huge fan of the “slam” format that gives the conference its name: a speaker has ten minutes to present 10 good actionable ideas to improve social media performance. Three of the five presenters adhered to the slam format, so we were treated to great ideas on how to better participate on Google (@shanerhyne – LOVE the hats!), Facebook (@JenKaneCo)   and Pinterest (@KimGarst). I WILL sign up for Google Author, have a FB plan, and try creating a “resources” board on Pinterest! Worth the admission!

I sort of hate the breakout sessions because I know I am missing something…but the two I attended were great. The new realities of SEO with @jfloyd, @ericpratum, @seanmcginnis and @rhogroupee provided solid advice on using organic real content to improve search results. Worth the admission! (One interesting insight: results are getting so personalized that objectives like top three in keyword search are almost meaningless.) How to build your Personal Online Brand with @markwschaefer, @kimgarst and jeffbullas was inspiring.

Amy @HowellMarketing did a great job of MC – and at promoting Memphis! Jason @jasonfalls got everyone excited about the program. As a struggling blogger, I really appreciated the 15 solid ideas provided by @jeffbullas. I will share three: try out negative headlines (things not to do), new research, and numbered lists – for more go buy his book! Clearly worth the admission!

I enjoyed the “fireside” chat with and the stories from three social media marketers in the trenches about how to reach the public. It was important to remember when they dissed Google+ and LinkedIn that they were all focusing on B2C…

And the conference closed on a high note with a good discussion of the value of qualitative research (why?) by @webby2001 and @tamadear; and on the future of digital marketing by @ducttape… Once again, worth the admission!!

Live Networking

What can you say about the opportunity to meet and talk with @jeffbullas @seanmcginnis and @jasonfalls? To finally meet twitter friends like @kerrygorgone in person? And to renew ties with the likes of @markwschaefer, @HowellMarketing and many others?

I vote Live Networking! …but it is a close call. (I will probably say more about networking in a later post…)

I have heard smartphones referred to as “rudephones.” They certainly have coarsened behavior in the non-virtual world. Who hasn’t been stuck in a line behind someone telling the cashier to “wait a moment?” while they finish messaging or talking? Or been cutoff by a minivan or truck driving who seems to be texting while driving?

I know of a preschool that sent a note to parents saying that “The high point of your child’s day is when you pick them up after school. Please do not be staring at a screen or talking when they first see you. We will not release children to a parent who is using their phone.”

On the sidelines of children’s soccer games, in the pews at church, in the booths of nice restaurants, and in the front row of classrooms people are “descreetly” messaging on Face book or texting. (Why are they staring at their laps?) And of course what is a nice meal out without someone allowing the children at the next table to game or play YouTube videos – with the sound on.

My favorites of all are the smartphone users in movie theaters! They may want to multitask during the movie, but why do they assume we do also?

What is your favorite rude smartphone use example?

STUPID – Paying $500 to acquire a learning disability

This past Saturday I braked for a biker who veered into my lane: he was messaging while pedaling his bike on Main Street Blacksburg! Driving while messaging or texting is a great STUPID example but I argue that the effect of smartphones on intelligence is more pernicious.

Current research on learning indicates that attention is the most important factor in learning and multitasking of any sort kills attention and learning. In the book, The Shallows, studies are cited showing that  hyperlinks to citations in the text of a paper impair learning. Imagine having Facebook and YouTube in your control bar while you are trying to take lecture notes! 

For students and anyone interested in learning, buying a smartphone may essentially  amount to paying $500 to acquire a learning disability. The students eerily smiling while look down at their lap and the seminar attendees glancing at their cell phones will less and more slowly. But they will know what their friends are up to.  

As rampant multitasking causes us to learn less will smarter smartphones come to our aid? 

(Cycle of dependency?)