© 2010 Mike Moran Mike Moran www.mikemoran.com What Are Customers Saying About You? Mike Moran for MENG NJ November 2010.

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Presentation transcript:

© 2010 Mike Moran Mike Moran What Are Customers Saying About You? Mike Moran for MENG NJ November 2010

Mike Moran © 2008 Mike Moran © 2010 Mike Moran Social media volumes are staggering 126 million blogs (900,000 new posts each day) Source: BlogPulse, January million tweets per day (two billion per month) Source: Twiter, September 2010 Half a million Facebook apps Source: Royal Pingdom, January 2010 YouTube serves one billion videos per day Source: Royal Pingdom, January

Mike Moran © 2008 Mike Moran © 2010 Mike Moran 3 Social media now makes marketing a conversation Readers comment on your blogs They change your wikis The create blogs of their own They create hate sites if they dont like you Web 1.0 users were consumers Web 2.0 users are participants

Mike Moran © 2008 Mike Moran © 2010 Mike Moran 4 Message boards have long been complaint centers Would you have spotted this comment? Would someone know how to respond? What if that is one my competitors?

Mike Moran © 2008 Mike Moran © 2010 Mike Moran But now all you need is a phone Your customers look at reviews before going into your restaurant Or writing a review while they wait for the check 5

Mike Moran © 2008 Mike Moran © 2010 Mike Moran 6 This isnt so newits what the Web is about You always wanted to attract links to your site You always had hate sites for those with a tin ear

Mike Moran © 2008 Mike Moran © 2010 Mike Moran 7 Marketers do not have message control We dont control the message Maybe we never did The message is changed, rebutted, and misconstrued by our audience We must modify what we say in response

Mike Moran © 2008 Mike Moran © 2010 Mike Moran 8 Are you ignoring the conversation? Others are talking Are you listening? Do you speak the language? Are you commenting?

Mike Moran © 2008 Mike Moran © 2010 Mike Moran Ford contains a potential disaster A Ford fan site goes public with a Ford cease and desist order that goes viral on the Web Scott Monty of Ford tweets not good when he first hears the story Later, his legal team explains that the fan site was selling counterfeit Ford items and he tweets that Within 24 hours, the story is dead, with Fords reputation intact 9

Mike Moran © 2008 Mike Moran © 2010 Mike Moran Graco handles a recall online Imagine the nightmare of baby strollers recalled for safety reasons Graco jumped on Twitter and responded to every nervous tweet, requesting serial numbers and providing advice Afterwards, as many stories praised Graco as slammed them 10

Mike Moran © 2008 Mike Moran © 2010 Mike Moran Dell goes from embarrassment to leadership Then: Bloggers took Dells service to task with Dell Hell Now: IdeaStorm builds new products from customer ideas 11

Mike Moran © 2008 Mike Moran © 2010 Mike Moran Comcast did the same thing Comcasts first exposure to social media came from a YouTube video of a service man sleeping on the customers couch They later became one of the first companies to pioneer customer service on Twitter 12

Mike Moran © 2008 Mike Moran © 2010 Mike Moran Starbucks also solicits ideas from customers 250,000 people voted one million times for 84,000 different ideas 48 ideas launched in Starbucks restaurants 13

Mike Moran © 2008 Mike Moran © 2010 Mike Moran 14 How will the companies of the future work? Imagine a fictitious mid- size manufacturer and direct seller of telephone systems called telecom.com that sells to consumers, SOHO, and larger businesses Dorothy is the Marketing Executive for all telephone systems telecom.com

Mike Moran © 2008 Mike Moran © 2010 Mike Moran 15 Problems for our heroes Dorothy is checking her reputation dashboard when she sees a bad story From an important blog Reputation Dashboard Results from Reputation Scan 1 to 10 of 37 stories | Next> Telecom 2617 Review …Telecoms new 2617 digital switch surpasses the competition… Another Winner from Telecom …2617 exceeded our benchmarks … Questionable Telecom TCO …causes us to question Telecoms low TCO claims… Monitor Todays Telecom Talk Concepts

Mike Moran © 2008 Mike Moran © 2010 Mike Moran 16 Dorothy checks the story The story says that anecdotal reports indicate that Telecoms products are costly to repair It quotes two unnamed Telecom customers Todays Telecom Talk Reputation Dashboard Monitor Concepts Create Concept Questionable Telecom TCO Have you heard Telecoms claims of low TCO? We have too, but weve also heard from two Telecom customers, which causes us to question Telecoms low TCO claims. If you believe the customers we spoke with, Telecom products can be costly to

Mike Moran © 2008 Mike Moran © 2010 Mike Moran 17 Dorothy decides to see if more talk is happening Are others talking about high costs? She highlights TCO and presses the Create Concept button Reputation Dashboard Monitor Todays Telecom Talk Concepts Create Concept TCO Questionable Telecom TCO Have you heard Telecoms claims of low TCO? We have too, but weve also heard from two Telecom customers, which causes us to question Telecoms low claims. If you believe the customers we spoke with, Telecom products can be costly to

Mike Moran © 2008 Mike Moran © 2010 Mike Moran 18 TCO talk comes in many flavors She selects the related phrases that she wants to include She presses the Save Concept button Reputation Dashboard Monitor Concepts More Phrases: Big repair bill Big training costs Big training expenses Costly repairs Costly training Expensive to fix Expensive to repair More… Concept Editor Current: TCO Add additional phrases from list at right Save Concept

Mike Moran © 2008 Mike Moran © 2010 Mike Moran 19 Dorothy matches the concept with her products She cares about this talk only when it relates to her own products She chooses Brand names and Product names and runs it Reputation Dashboard Monitor Concepts Telecom Brand names Executives Locations Product names Concept Editor Save and Search Competitors Brand names Executives Locations Product names Current: TCO Add additional concepts from list at right

Mike Moran © 2008 Mike Moran © 2010 Mike Moran 20 Dorothy sees what all the chatter is about Dorothy sees that some of these same costly repair stories are popping up on message boards And product reviews Reputation Dashboard Results from Message Boards 1 to 10 of 17 phrases | Next> expensive to fix (6) big repair bill (5) high maintenance costs (3) More… Monitor Todays Telecom Talk Concepts Results from Product Reviews 1 to 10 of 12 phrases | Next> pricey service (2) expensive repair (1) More…

Mike Moran © 2008 Mike Moran © 2010 Mike Moran 21 Do competitors have the same problems? Dorothy checks the same concepts found for competitive names She chooses Brand names and Product names and runs it Reputation Dashboard Monitor Concepts Telecom Brand names Executives Locations Product names Concept Editor Save and Search Competitors Brand names Executives Locations Product names Current: TCO Add additional concepts from list at right

Mike Moran © 2008 Mike Moran © 2010 Mike Moran 22 Many of the same phrases come up Dorothy sees that some of these same costly repair stories are popping up for competitors In message boards and in product reviews Reputation Dashboard Results from Message Boards 1 to 10 of 57 phrases | Next> high maintenance costs (23) expensive to fix (19) expensive repair (15) More… Monitor Todays Telecom Talk Concepts Results from Product Reviews 1 to 10 of 62 phrases | Next> costly service (13) expensive repair (11) More…

Mike Moran © 2008 Mike Moran © 2010 Mike Moran 23 How do todays companies listen to customers? Google Alerts are free and easy Set up a search and follow the s or an RSS feed Perfect for small businesses and unique search keywords

Mike Moran © 2008 Mike Moran © 2010 Mike Moran But other companies fail with search algorithms T-Mobile will be found quite easily Sprint not so much Verizon Wireless is also not easy to isolate 24

Mike Moran © 2008 Mike Moran © 2010 Mike Moran Algorithmic listening also misses details [Negative for Treximet Cardio Side Effects] I did a little research of my own, and was a bit alarmed to come upon a forum of migraine sufferers who had tried the drug and reported tightness in the chest and other indications of cardiac disturbance. I decided to leave the Treximet in the desk, untouched. Blog.lazyharpy.comBlog.lazyharpy.com, published on [Negative for Treximet Cardio Side Effects] I did a little research of my own, and was a bit alarmed to come upon a forum of migraine sufferers who had tried the drug and reported tightness in the chest and other indications of cardiac disturbance. I decided to leave the Treximet in the desk, untouched. Blog.lazyharpy.comBlog.lazyharpy.com, published on [Positive for Treximet Effectiveness] …I popped a Treximet, slanted my shades, closed and locked my office door, and put my head down for fifteen minutes. When my alarm went off, my head was perfectly clear. That was four hours ago. Blog.lazyharpy.comBlog.lazyharpy.com, published on [Positive for Treximet Effectiveness] …I popped a Treximet, slanted my shades, closed and locked my office door, and put my head down for fifteen minutes. When my alarm went off, my head was perfectly clear. That was four hours ago. Blog.lazyharpy.comBlog.lazyharpy.com, published on [Positive for Cardio Side Effects] For some reason, today I picked it up. I did a quick web search for adverse side effects of Imitrex, which I have used for years, and felt surprised to see the very same descriptions as those accompanying the Treximet. Since Imitrex has never bothered me,.. Blog.lazyharpy.comBlog.lazyharpy.com, published on [Positive for Cardio Side Effects] For some reason, today I picked it up. I did a quick web search for adverse side effects of Imitrex, which I have used for years, and felt surprised to see the very same descriptions as those accompanying the Treximet. Since Imitrex has never bothered me,.. Blog.lazyharpy.comBlog.lazyharpy.com, published on Do you care if the whole post is positive or negative? Or what the specifics are for each issue? Do you care if the whole post is positive or negative? Or what the specifics are for each issue? 25

Mike Moran © 2008 Mike Moran © 2010 Mike Moran But Google Alerts treats all mentions the same 26 Doesnt aggregate volumes or show competitors Doesnt differentiate by venue Doesnt separate positive from neutral and negative

Mike Moran © 2008 Mike Moran © 2010 Mike Moran Who are the current leaders in social listening? Forrester Wave

Mike Moran © 2008 Mike Moran © 2010 Mike Moran Sentiment analysis shows opinions Top Five Tech Pundits in Smart Phone Conversation Blog URL Net Sentiment (toward Brand) RankTraffic EngadgetA Venue falls in the top 1% of highest trafficked, most influential sites Gizmodo A Venue falls in the top 1% of highest trafficked, most influential sites Electronista B Venue falls in the top 10% of high trafficked sites UberGizmo B Venue falls in the top 10% of high trafficked sites Switched C Venue falls in the bottom 90% of trafficked sites 28

Mike Moran © 2008 Mike Moran © 2010 Mike Moran Algorithmic sentiment analysis misses sarcasm Oh, the iPhone is a beautiful girl, no doubt. The automated sentiment analysis failed to identify the sarcasm and coded the entry as positive for iPhone, while failing to understand the author was actually saying there was no value for the iPhone beneath its flashy exterior 29

Mike Moran © 2008 Mike Moran © 2010 Mike Moran Algorithmic sentiment analysis misses nuance You know that these are negative, but there is no word to tell the algorithm These would be marked neutral by most algorithms 30 I waited on line for my entire lunch hour at my Wells Fargo branch today. State Farm never told me I had no flood coverage. Amazon wouldnt refund my money.

Mike Moran © 2008 Mike Moran © 2010 Mike Moran Algorithmic sentiment misses context The same words mean different things An unpredictable movie is good, but unpredictable food quality, not so much We like small cell phones but not small hotel rooms Faded jeans are good, but not faded photos Frozen computers are bad, but frozen margaritas are good 31

Mike Moran © 2008 Mike Moran © 2010 Mike Moran 70% accuracy on relevance 70% accuracy on sentiment 70% times 70% = 49% The problem: Algorithms alone fall short 32 Oh, the iPhone is a beautiful girl, no doubt. The best algorithms seem to fail half the time

Mike Moran © 2008 Mike Moran © 2010 Mike Moran If you need the data to be right, you need people to check the machines The machines collect the data and make the easy calls, and they suggest the answers for the tough ones, but humans make the final decision Human analysts can correct the algorithms 33

Mike Moran © 2008 Mike Moran © 2010 Mike Moran Visualizations make the data understandable 34

Mike Moran © 2008 Mike Moran © 2010 Mike Moran The same information is needed organization-wide 35

Mike Moran © 2008 Mike Moran © 2010 Mike Moran Workflow distributes insights 36

Mike Moran © 2008 Mike Moran © 2010 Mike Moran Workflow also allows engagement 37

Mike Moran © 2008 Mike Moran © 2010 Mike Moran Listening tools are growing up Volume Word counts/tag cloud Entry timeline High-level topics Venue analysis Influence Drill-down to entries 1.0 Monitoring 2.0 Mining Sentiment Topics and subtopics Voices/participants Key influentials Incident-level reporting Custom reporting elements Human analysis 38

Mike Moran © 2008 Mike Moran © 2010 Mike Moran Read all about it Buy this book, read it, and then read it again. -- Chris Sherman, Search Engine Watch Updated at each printing The search marketing best seller For more information about the books, and for the free Biznology newsletter and blog: Miami Herald: A Top Biz Book of 2007 Great book. -- Robert Scoble, Scoblizer blog Act now and read it. -- Bryan Eisenberg, Author of #1 best seller Waiting for Your Cat to Bark? 39