Social media monitoring is perhaps one of the most widely known and used social technologies among businesses large and small. Whether using free tools like Google Alerts and SocialMention.com or paid solutions like uberVu, Radian6, Sysomos or others, it seems listening as the most important function of a business’s efforts in social media has been successfully ground into our collective conscience. At least to those of us determined to implement good social media marketing strategies.

But social media monitoring is often thought of and implemented as a reactionary practice. Find the keyword mentions, then respond. Done. Smart companies know, however, that using social media monitoring as a proactive, business driver, can make the difference between being successful with your social media efforts and not.

Arienne Holland from Raven Internet Marketing Tools knows a thing or two about proactive social media monitoring. She implements tactics and strategies around monitoring for her company on a daily basis. She’ll be presenting her experiences as well as some good case studies of other brands doing the same at Explore Dallas-Fort Worth on Feb. 17. I caught up with her last week to chat about how companies are and can use monitoring more effectively.

You won’t want to miss the business insights Arienne has to give at Explore Dallas-Fort Worth. She’ll be speaking there, along with an all-star lineup that includes Copyblogger’s Brian Clark, Zena Weist of Edelman Digital, Tom Webster from Edison Research, Nichole Kelly of Full Frontal ROI, DJ Waldow from Waldow Social and more. The event will also feature a number of excellent software providers and companies to help you navigate the waters of digital marketing. They’ll bring their knowledge to share as well as their products. This is a must-attend event, so register now!

The first 100 registrants get the full day’s content, breakfast, lunch (by Wolfgang Puck Catering) and a cocktail reception for just $250! The full price of the event is $400, so save $150 now and reserve your spot.

Explore is a five-city conference event series from Social Media Explorer and presented by Expion and Raven Internet Marketing Tools. Learn more and sign up for email updates for the city nearest you at socialmediaexplorer.com/product/events.

Altimeter Group‘s newest research report, “A Strategy for Managing Social Media Proliferation,” labeled as a “Buyer’s Guide,” is out and offers a deep look at social media management systems and how brands are using them. The report, which is free and available for download on Altimeter’s website but is also embedded below, is the first deep dive into the SMMS space which grows increasingly confusing and crowded. This report, authored by Jeremiah Owyang, will help brands better understand what is available and what platforms they should consider based on their strategic goals for social media activity. (Disclosure: I was interviewed and am included in the research for this report.)

As we’ve discussed here before, there are many different components to a complete social media management system. None of the current vendors on the market really offer everything, or at least none offer everything well. Social Media Explorer’s definition of what components comprise an SMMS platform varies from the Five Use Cases for Social Media Management Altimeter presents. Our 8 Functions (monitoring, publishing, engagement, organizational management, lead & conversion tracking, measurement, customer relationship management and social advertising management) are more practical and tactical than Altimeter’s defined use cases: Intense Engagement, Social Broadcasting, Platform Campaign Marketing, Distributed Brand Presence and Tailored Customizations. But ours fit into their descriptions well.

Perhaps the best part of the report for brand managers and marketing decision-makers is an Altimeter Radar chart comparing 27 different SMMS providers. While there are far more than 27 out there, Altimeter has defined each of these for Altimeter’s audience: enterprise clients. That factor must accompany your reading of the report because medium and small businesses don’t much matter to Altimeter. They see the world through large corporate lenses, mostly because those lenses have larger dollars signs etched into them.

Still, the comparison chart looks at these vendors and rates them on their ability to fulfill the five use cases defined by Altimeter. Syncapse, Vitrue and Engage 121, among others, come out looking very strong. But again, this is through the five use case filter. Altimeter’s definitions do not drill down to the practical applications of these platforms. So, if you’re looking for something that does good lead and conversion tracking, for instance, the chart won’t help you.

I was happy to see Expion, an SME client and Explore sponsor, highlighted in one of the case studies presented in the report. Spredfast, Argyle Social, Shoutlet and Awareness, all companies I have client or sponsorship relationships with here at SME are also well represented. But I was disappointed to see campaign-centric applications like WildfireApp still listed as SMMS platforms when campaign gadgets like them provide very few of the qualities an SMMS platform should have. There are also a number of platforms left out of the report’s per view, probably because Altimeter doesn’t define them as being suitable for enterprise clients. HubSpot, Raven Internet Marketing Tools and many others provide more robust functionality than many of the platforms analyzed, yet weren’t included.

Still, this report is a must-have companion for the digital marketing decision-maker. The social media software universe is vast and confusing. Even a small business can look at the information in this report and have a better understanding of how businesses are using social media management systems, what systems are out there and what business can use SMMS for. Altimeter continues to do valiant work in researching and interpreting the social technology space for us all, even if we’re not big enough to be in their target audience. For that, I’m thankful.

In early November you may have read the interview I did here with Seth Grimes on the Future of Sentiment Analysis. Seth provided some great insight into describing the current state of the sentiment analysis space, where it is headed and what role social media plays in the grand scheme of things. Soon after that post, I was able to attend the third annual Sentiment Analysis Symposium, founded by Seth, in San Francisco.

I understand the basics and importance of sentiment to marketing and data mining, but it was interesting to listen to many of the most passionate experts in this field discuss the nitty gritty of this growing area. Here are a few of my take aways from the event:

Sentiment analysis is extremely dependent on social media.

Just about every presentation, no matter what the topic, referenced social media as the primary fuel driving modern sentiment data. Every status update, tweet, blog post, product reviews, etc., … social media is providing data at an unprecedented level. Social media is oozing sentiment rich data. As the amount of data increases the patterns, trends and context that can be extracted from it will become more important for businesses of all sizes.

Twitter is an ocean of sentiment data.

Of all the social networks, Twitter was mentioned most frequently by speakers. The rushing river of 140 character or less posts provide the most conversational data on the web by far. A single tweet on its own may have some value when building a sentiment data set, but when you analyze the hundreds of thousands of tweets that are posted each day there is much more meat on the bone to chew on. Also consider that most of the information on Twitter is public in comparison to networks like Facebook which is primarily private. It all makes Twitter a very attractive place to gather and analyze sentiment.

There is much more to sentiment data than what we find in text.

Although sentiment analysis is usually associated with extracting information from the emotional context of text, the social web is much more than just text. Although NLP (Natural Language Processing) plays a huge role in the current technology used to gather and assess sentiment it is not enough. No matter how accurate software gets at understanding the emotional meaning in text on the web there are other elements that need to be factored in. How should you treat a “like” on Facebook? How about if the data you captured is a retweet rather than an original tweet? Can a sentiment score or value be given to a social action like this? Even more difficult are the potential complexities of trying to extract meaning from an image or a video. Imagine trying to understand the emotional context of a powerful photograph making rounds on Facebook. We only scratch the surface by understanding the textual data.

Sarcasm is sooooo cool!

No, not really. Understanding sarcasm continues to be a tough nut to crack, but analysts and technology providers are getting better at it. Understanding the context around key words or phrases is critical in accurately assessing the emotional value of the content. Context is equally important in being able to understand if something that seems to be positive is negative and vice versa. Take my heading for example “Sarcasm is sooooo cool!” At first blush it might be identified as saying something positive, but when the context within the rest of the content is read there is evidence that my intention is to express the opposite. This happens more often than one would think. Being able to effectively pull apart sentences and phrases piece by piece to identify the subject, the context and the sentiment is likely the direction many technology vendors are going to take. By my observation, some of them are already doing it now.

It all must tie back to business goals and existing processes.

Ultimately, as with social media marketing, you need to consider how your efforts are going to tie back to business goals and processes. Are you gathering the data to help you understand what people feel about your brand or are you leveraging it to help you better understand an emerging problem you may be able to solve with a new product?

There are a number of reasons you might consider gathering and analyzing sentiment data, but you need to think ahead so that the data you gather is inline with your desired outcome.

Also think about how this data might empower existing processes and departments. Is there value in connecting sentiment data to your existing CRM so you can see what previous experience a customer may have had with your brand and why he is unhappy with you? For instance, I saw an example of a company analyzing the transcript of a customer service phone call. The gentleman on the phone was clearly unhappy and because they knew who he was they were able to pull records of previous interactions he has had with them which pointed to why he was voicing his discontent. Does that make the customer service rep better at making the situation right? Likely.

In general, the tools, trends and best practices for sentiment analysis have a lot of room to grow. Social media will continue to play an important role in how quickly this space grows and ow we apply it to business. If you want to check out some of the sessions from the Sentiment Analysis Symposium you can find videos of most of the sessions here. For those of you who enjoy sarcasm, just imagine trying to analyze the conversation in the video below. Enjoy.

Have You Registered For Explore Dallas-Fort Worth?

Don’t miss a day of intensive learning with some of the leading thinkers and practitioners in the digital marketing and social media marketing space. Copyblogger’s Brian Clark, Edison Research’s Tom Webster, Edelman Digital’s Zena Weist and more headline one of the leading digital and social media marketing events of 2012, February 17 in Dallas, Texas! DON’T WAIT TO REGISTER! The first 100 to do so get an incredible discount! Reserve your seat today!

No doubt you’re either in the Black Friday shopping scrums, or smugly congratulating yourself for dodging the melee. (Or maybe, like me, you’re watching the kids while a significant other is tossing elbows in an attempt to get one of the five loss-leader gadgets meant to lure shoppers…)

From an online marketing perspective, however, I’m more interested in Blank Friday.

That’s the day Facebook made a big shift that changed our search volume:

Takeaway? It’s wise to periodically review your analytics. Most businesses are still searching for the right baseline from which to measure their activity and efficacy — now we see that those baselines are subject to radical seismic shifts. If you’re not careful, you might become tied to benchmarks that have become irrelevant or even impossible to achieve.

If you have a story about your own “Blank Friday” moment, please share it in the comments.

Warning: The crux of this post surrounds the word “shit.” It’s not used to be vulgar or profane, but to show what consumers are saying about brands online. If the word offends you, please move on. If you don’t and it still offends you, you were warned.

Talking with the folks at NetBase in preparation for Friday’s 11 for ’11 Webinar (see below), we came up with a fun little experiment to see A) How good NetBase is at really distinguishing between very similar phrases with very different meanings and B) Which brands are winning and losing in the online sentiment race … at least within these very small parameters.

There’s a major definition difference between saying something is “shit” versus saying something is “the shit.” They are, in fact, polar opposites. But having a sentiment analytics or online research tool that can automatically decipher which is which is tricky. We put NetBase to the task and found that it not only worked, but there are some brands out there that could use some help getting their online audiences to add the word “the” to the phrase.

Here are the brands that lost in the online battle of who is “shit” versus who is “the shit:”

Notice how dominant Blackberry is in being called “shit.” Odd also that all the major phone carriers are there. Maybe it’s not the phone carriers themselves, but just the technology in general that sucks.

Now here are the brands that “won” because they were called “the shit:”

My only questions as interpret this data are A) McDonald’s? Really? And B) I’m thinking Taco Bell might be listed because it gives you “the shits.” So we may need to go decipher the data a bit. Then again, White Castle didn’t make it, so maybe I’m wrong. Heh.

Silly as it might be, these are potentially interesting bits of data for brands to have. So even though we focused on a little bawdy language today, know that there are online tools out there, like NetBase, that can help your company find and distinguish between the two.

As for the webinar, the last (11th) in the series is this Friday, (11/11 at 11 a.m PT, even), the NetBase gang thought it would be fun to have me do a webinar on my book. If you haven’t had the opportunity to hear my stories from the book talk, please join us! NetBase is giving away 250 copies of the book during the webinar, so just being an attendee gives you a chance to win.

Register for the webinar on the NetBase website and then block your calendar off for this Friday, Nov. 11 at 11 a.m. PT/2 p.m. ET for some good fun.

See you Friday!

As Jason has reported before here, sentiment analysis is a tricky thing. Even humans disagree on sentiment 15 percent of the time, so how can a computer create something more accurate? As technology evolves, sentiment analysis gets better, or so we’d like to think.

I caught up with Seth Grimes recently. He is an analytics strategist with Washington, D.C.-based Alta Plana Corporation and a contributing editor at TechWeb’s InformationWeek. He is also perhaps the leading industry analyst covering text analytics. Seth consults, writes, and speaks on business intelligence, data management and analysis systems, text mining, visualization, and related topics. With such an expert on the subject with my reach, I asked him the following:

In layman’s terms, how would you describe/define sentiment analysis?

Image by Seth Grimes / Alta Plana via CrunchBase

Sentiment analysis is a set of methods, typically (but not always) implemented in computer software, that detect, measure, report, and exploit attitudes, opinions, and emotions in online, social, and enterprise information sources. (As an aside, what makes it “analysis” is that you’re doing it systematically, with some goal in mind.)

I’ll add is that sentiment analysis much more than simplistically subtracting the number of “negative” words from the number of “positive” in a document or message in order to produce a score.

What does sentiment data and analysis mean for marketers and brands? Is it only about analyzing social media conversations or does it have broader applications?

Yup, it can involve social conversations and also direct and indirect feedback (such surveys, contact-center notes, and warranty and insurance claims), online news, presentations, even scientific papers: Any information source that captures subjective information.

Sentiment analysis lets marketers (and market researchers, customer service and support staff, product managers, etc.) get at root causes, at explanations of behaviors that are captured in transaction and tracking records. Sentiment analysis means better targeted marketing, faster detection of opportunties and threats, brand-reputation protection, and the ultimate aim, profit.

What role do companies like Facebook, LinkedIn, Twitter and Google play?

Interesting choice of platforms. Facebook and Twitter are major sources of sentiment (and also of complementary social connectedness data). Facebook and Twitter accounts have profile data attached to them, but nothing that matches the detailed, usably-structured information you can find on LinkedIn. Google is the ultimate information-access engine, capable of bringing together information from a huge variety of disparate sources, including sentiment information such as product, restaurant, and hotel ratings, although when corporations wish to find, mine, and exploit sentiment they need to turn to deeper BI and analytics tools.

There’s no one-size-fits-all sentiment solution, not Google or one of the several as-a-service solutions out there or any of the capable analysis workbenches or social-media analytics tools. Instead, there’s a whole spectrum of sentiment sources and analysis possibilities.

What are some of the most exciting break throughs that you are seeing in the technology or methodologies related to sentiment analysis?

Wow. First off, there are beyond-polarity solutions, which look at emotional categories — for instance, angry, happy, sad, frustrated, satisfied — that offer much greater business insight and usability than positive/negative/neutral scoring systems. And leading edge solutions are going beyond text, to detect sentiment in speech and even in images and video. On the methodological front, some of the best systems are linking sentiment with transactional records (sales, inquiries, payments, Web clickstreams), including with location correlation, to move us toward a world of integrated analytics.

Can you share an interesting example of a brand or organization has successfully used sentiment?

Let me point you to an article I wrote in February, 2008, where I profiled the use of sentiment analysis (by my friend Tom Anderson of Anderson Analytics) as one analytical component of “triangulation” strategy around the Unilever Dove-brand pro.age campaign. I quote Catherine Cardoso of Unilever in the article: “We were very pleased with the results and the depth of insight. The results were helpful beyond understanding reactions to our campaign. We also gained an understanding of what motivates people on discussion boards, which issues are most important to women in our target group, and how to create better products and messaging for them.”

In your opinion, what is the biggest obstacle keeping sentiment analysis from reaching its true potential?

Misperceptions, also inflated expectations, fostered by low-grade tools that are keyword based and lack any mechanism to link sentiment to actual business outcomes. On the one hand you get low accuracy, and further there’s a “decision gap.” You get a colorful dashboards, but because the tools are working in isolation, treating social and survey sources as information silos, you can’t reliably know what sentiment is important, and what sentiment really means to your business in the sense of driving transactions, boosting satifaction, and so on.

Companies like Radian6, (recently bought by Salesforce), SM2 and others have included sentiment as part of their social media analytics/monitoring tools for some time now. How will the future of the technology and method to using the data be different than what is available now?

Let’s name names. I was incredibly disappointed when I get an SM2 briefing from Alterian. I saw, earlier this year, primitive sentiment capabilities and analysis interfaces that resembled those of BI tools circa 2000. Check out what I wrote last March in an article, “What I Look For In A Social Analysis Tool.” There are other tools with similar, serious deficiencies.

Radian6, as an example, illustrates two routes forward. First, Radian6 provides a framework for plug-in of dozens of disparate extensions, including text and sentiment analysis from at least four different providers, AlchemyAPI, Clarabridge, Lexalytics, and OpenAmplify. This sort of openness and inter-operation is a benefits the solution providers and their customers alike. Second, the acquisition of Radian6 by Salesforce.com should further users’ ability to link customer-relationship data captured in Salesforce — profiles, transactions, interactions — with customer attitudes, emotions, and opinions, posted on-social and online and analyzed via Radian6, related to products and services offered by Salesforce customers and their competitors. This would mark the end of social as a silo.

What impact will mobile technology and the context that it provides (IE: location specific data) have on collecting and analyzing consumer sentiment?

Mobile creates the opportunity to solicit and collect feedback on the spot, at the point-of-service, and to understand peoples’ choices as they do whatever they’re doing. (Of course you have to consider privacy regulations and expectations.) And by collecting location and time data along with sentiment, linked to activities, you get additional analysis variables that can feed more capable, more accurate predictive models. Mobile is huge, in many, many ways.

You are one of the organizers of the upcoming Sentiment Analysis Symposium. Why do you feel an event like this is needed now? What are you hoping to accomplish?

The up-coming symposium, November 9 in San Francisco, is actually the third, following on April 2010 and 2011 New York events. The events are designed as a meeting ground for technologists and business users. They’re designed for education, for new and experienced folks alike, and to create networking and deal-making opportunities.

Folks should check out the Web site, sentimentsymposium.com, also the optional, pre-symposium tutorial (for people just getting started) and research session (for advanced users and developers).

How can people find out more information about how sentiment analysis is being used for business?

I’ve written quite a bit on the topic myself, and you can also learn from solution providers. Ask them for case studies and customer references. But I also recommend just taking a shot yourself. There are two factors that support this approach –

1) You’re working with natural language, with material you can understand directly, and it’ll be pretty clear whether the tools you’re trialing are doing a good job.

2) You have a variety of choices available including hosted, as-a-service solutions that can be used without a large up-front investment, also social-analytics and survey-analysis solutions that embed sentiment analysis without imposing a heavy technical burden on users.

I’m happy to field questions. Folks should contact me via Twitter at @sethgrimes at 301-270-0795 or grimes(at)altaplana.com.

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Use the code FOAF for a $100 discount your registration to attend the Sentiment Analysis Symposium on November 9th.

Sysomos announced this morning that it now integrates Google+ into its platform, becoming the first social media monitoring platform to integrate the newest of the big social networks. The Sysomos MAP product now monitors Google+ data and pulls it into its monitoring and analytics suite. MAP is the more advanced of Sysomos’s two major products, with Heartbeat being their entry level monitoring product. Yes, this means you’ll have to pay more to get access to it. Expect that to change as other competitors offer Google+ in their base offerings over time or as Sysomos rolls in more features with Google+.

Sysomos MAP users will be able to use their boolean searches to mine and pull mentions of keywords and keyword phrases. They’ll also be able to use the handy BuzzGraph analytics feature with Google+ data as well. This means the content will also be run through Sysomos’s sentiment analysis engines to offer up that perspective on the data, too.

While you have to applaud Sysomos for being first … the early bird gets the worm … expect other platforms to add it soon and make it part of their base offering … the second mouse gets the cheese. Not to say Sysomos doesn’t have a bit of an edge here, at least for the time being, but putting it in the MAP product, which is more of a business intelligence and analytics platform, rather than Heatbeat, their core monitoring platform, is a mistake, I think. Though Heartbeat pulls much of its data from MAP, they’re going to need to soon switch it over or they’ll get left behind when the Radian6′s of the world offer Google+ with their core packages.

But bravo to Nick Koudas and Nilesh Bansal and team for the work. Sysomos continues to stay on top of the monitoring world in terms of reaction time and offering features users want.

What do you think? Is Google+ worth paying extra for now? Will it set Sysomos apart? For how long? The comments are yours.

Last month I paid a visit to Dreamforce, the user conference for Salesforce.com, in San Francisco. As you may know, Salesforce.com recently acquired Radian6, one of the leading social media monitoring platforms. This was the first time the Salesforce.com and Radian6 team was together at Dreamforce and they put on quite a show.

Because many of the sessions at Dreamforce were focused on social media and social business (here’s an audio recording my talk on the ROI of Social Media), the Radian6 team was not only the star of the exhibition show floor, but cranked up the community team to listen, amplify and triage mentions of both brands, as well as others Dreamforce had purchased over the year, and show off it’s ability to be responsive and nimble despite a high volume of conversations on and off line.

To do this, Radian6 and Salesforce.com set up a command center at the Mosconi Center. They invited me in to check it out. While I was there, I not only got a chance to film what they were doing and show it off, but talk to Genevieve Coates of the community team about their efforts at the show and beyond.

As you’re growing your community team, you’ll hopefully find that example useful. It’s neat to think of building out a war room type setup in your physical location where individuals focusing on various pieces of your business are communicating across silos and routing issues to the right people quickly. Certainly, there are other examples, but looking at Radian6 and Salesforce’s temporary setup for an event gives you a good idea of where the concept can go.

How are you preparing to handle command of your social data and interactions? How many people are you devoting to the effort now? Please share your experiences in the comments so we all might learn. The comments, as always, are yours.

Valuevine released a study today that indicates keyword based social media monitoring platforms may leave as much as 82 percent of the online content about a brand out of the data it reports back to brands. The information was collected by analyzing what CEO Neil Crist told me was “following best practices” for keyword-based social media monitoring solutions like Radian6, Sysomos and the like, and comparing it to the data his tool collects from location- and local-focused check-in, ratings and review sites.

Valuevine focuses its analytics product, Valuevine Connect, on source-based searches. So instead of plugging keywords in and indexing sites to find mentions of your brand, it instead identifies the location-specific pages on sites like Yelp, CitySearch, Foursquare, Twitter, Facebook Places and more, and reports user information gleaned from those pages.

Essentially, Valuevine focuses on your known quantity of online conversations. Keyword search engine platforms like Radian6 (and frankly most social media monitoring platforms) just search for those keywords, regardless of source.

While Valuevine’s data is shocking — one brand they tested in a keyword search only revealed 18 percent of the data Valuevine derived from source-based searching — brands using keyword-based tools need to be upset … perhaps.

First, let’s level-set expectations.

“Some of these sites, specifically Yelp, have legal issues with crawling them,” Nilesh Bansal, Chief Technical Officer and Co-Founder of Sysomos told me. “Their copyright explicitly prohibits such crawing. Also, there are technical limitation with some platforms that choose not to provide APIs.”

What this means is that social media monitoring platforms can’t legally index content on many of these sites.

Crist explained how Valuevine does it by saying this:

“There are two levels of data granularity that we can bring to into the view for our clients. The baseline is that we use a search engine indexing partner that works with many sources in accordance with standard search engine policies. In turn, we follow standard search engine display behavior. For instance, we we only show snippets and ultimately drive activity back to the source pages. In that scenario those services win with the eyeballs of merchants. For some partners, we have deeper access and partnerships.”

Regardless of whether or not Valuevine is collecting information in ways other services aren’t, the simple fact remains that for brands, this is likely the first time they’ve been alerted to the fact that the security blanket they thought social media monitoring services were providing is mighty small.

Think about it. If I check-in on Facebook Places and say, “I really love this restaurant,” it likely doesn’t trigger any keyword searches the brand has in place in its monitoring software. For that matter, volumes of information could be shared by consumers about a company without alerting any of the keyword scans.

For Valuevine’s scan of Starbucks, what that meant was that 68 percent of online conversations — mostly tied to brick-and-mortar locations where the consumer is at the point-of-sale — are potentially not being seen. This information is perhaps more critical to the brand than that being found by keyword searches because it’s 100 percent relevant to specific stores and brands. You could essentially develop an entire quality assurance effort around this data.

“We do source-based listening,” Radian6 CEO Marcel Lebrun assured me. “If I want every post on Dell.com regardless of what they say, I can get that in addition to the keyword searches with Radian6. In fact, most listening platforms do both.”

Sysomos confirmed for me they offer the same functionality. They label it “Domain Filtering,” but it operates the same way.

But can these systems do location page filtering — focusing on just a single location’s UrbanSpoon page, for instance — rather than a domain-wide search? No one really wanted to jump at the opportunity to say yay or nay because of the terms of service issues with respective sites. My guess is that they can do it, but don’t want to get into trouble.

So that brings us back to Valuevine’s data. Crist said they applied best practices to do a keyword search but wasn’t specific on which keyword engine they used. If it was internal, then comparing it to a robust and several-year-old platform like Radian6 would be unfair. He did indicate that of the clients and agency partners Valuevine worked with on the analysis, none of them seemed to either be aware their keyword-based solutions could do source-based monitoring, or they didn’t know how to use it.

The bottom line is that the huge gaps Valuevine’s data shows are probably mostly driven by the fact the social media monitoring platforms don’t index ratings and review sites. If they did, the gap would likely close. But where does this leave brands?

Beating up their social media monitoring platforms to do what Valuevine does or using both.

To his credit, I asked Crist if he thought brands should question their use of keyword-based tools.

No way!” he responded. “They absolutely need it. It’s fundamental for all brands. But for the subset of brands that have a brick and mortar location, keyword-based solutions are just one set of solutions you need. You also need to monitor the location-specific information keyword tools don’t see.”

That I agree with. And I’ve always been impressed with Valuevine’s offering, even before they became an analytics solution rather than a franchise management tool. It aggregates location-specific information into a nice, franchise-wide data set, but then allows you to drill down by location to get store-specific insights and metrics.

Another point to consider, as Vladimir Oane of uberVu deftly pointed out, is that working with location-based data is not the same as looking at topic-based streams. So adding it to keyword search data is apples-to-oranges.

“The data is structured differently, displayed differently and you interact with it a different way,” he told me. “Not to mention you need different metrics because old ones don’t apply.”

Sounds reasonable. You don’t count check-ins, mayorships and four-out-of-five star ratings when pulling information into your reporting from Twitter or some random blog. But that’s limiting your concern to the analytics. The real-time review of what people are saying on your very own brand pages being left out of monitoring services just smells wrong, doesn’t it?

The Valuevine research is, of course, accompanied by a nifty marketing play. They’re offering up a free calculator for companies who want to see how much of their local data is being missed by keyword tools. All you have to do to use it is plug in the keywords you’re searching for with your monitoring service (which may not be easy for most people), identify your business or brand and within a few hours, maybe even a day since the tool will be over-used for a few days, you’ll get a scorecard back.

But be warned: The data simply can’t be considered chapter and verse. Haphazzardly plugging in keywords to an online calculator isn’t efficient and we don’t know how Valuevine’s keyword searches compare to real keyword-based monitoring solutions. Plus, how Valuevine collects its data is — at a minimum — now going to come under scrutiny from the sites it pulls from.

For more on the Valuevine research, check out their full report on the Valuevine website.

But tell me what you think about the possibility that brands are now realizing their monitoring solutions were missing so much? Will this affect the way you look at your monitoring solution provider? Should it? Aren’t ratings and review site and location-based information sites perhaps more important than other data collected from random sites around the web?

I’m very interested to know your thoughts on this potential blind spot for brands. And what other solutions exist to ensure we’re getting what we expect from social media monitoring. The comments are yours.

Life is astonishing. Be grateful for every tiny aspect of it!

Social technologies and Web 2.0 applications change us more than we realize. Internet access, connectivity, and social media have changed the landscape of  nearly everything we do.  In the blink of an eye, connections are formed, possibilities become realities, and new relationships are formed.

It’s become almost common that something created  or discovered at breakfast over a scan of a tweetstream can become a “can’t live without” tool by dinnertime.

It is important that in the midst of our daily digital lives, we take some time to realize how lucky we are. I look at my life in the last 24 hours, and none of it would have been possible even a decade ago.

Here’s what is astonishing to me:

I am actually creating this blog post while sitting in the back corner of  La Guardia International Airport.  It’s 8pm.  I love New York, but I am not supposed to be here right now. I am supposed to be home in Iowa where I am scheduled to give a virtual presentation to clients on the the East Coast.  (At least, that was the plan.)

Because of social media and a few strategic MacGyver moves , I found a quiet, “temporary office” right here on the backside of the terminal. (As long as I move  every 30 minutes or so when the elevator opens up with a new crew of passengers, it has served me.)

I am not going to miss work or this weeks deadlines because I am plugged in, hooked up, connected, and ready to stay productive.

Using my iPhone, iPad , and my MacBookPro, I am getting more work done here, than I would just about anywhere else in my house.  I have cleared through a pile of email, caught up on two days of reading, finished three  ebooks, and as luck would have it, I just got a text from my virtual travel app; Trip Advisor alerting me that “I GET TO” keep writing this blog post to you because I’m going to be here another two hours!

I’m accessing the Internet through through my USB card, so I can tweet, FB, and message my friends and family without worry of costs incurred. And, with a few clicks of a button this crazy story will go out to thousands of people who will be reading it from who knows where on who knows what.

Social media gives us the power to do magic things; things that could not have been done even five years ago. We are privileged beings. We have access to this amazing space, we can glean insight from the world’s greatest minds, and we can have life changing relationships with individuals who we may never have a chance to meet or work with face to face. If that is not worth a thank you every once in a while; I am not sure what is.

So, say WOW with me today! Let’s not let one another lose sight of the fact that we literally have the world at our fingertips. Give thanks to what we are capable of doing because of this thing we call Social Media.

Take just five minutes today and take stock of what social media has afforded you.

What are you most thankful for?

Do tell!

Related articles

• MORF Is a Crowdsourced Database of MacGyver Tips on Your Phone [App Of The Day] (lifehacker.com)
• Using Social Media the Right Way (bigthink.com)
• Vonage Co-Founder on the Social Revolution (webpronews.com)
• The Ultimate MacGyver Recipe Book Rounds Up All of Mac’s Clever Hacks [MacGyver] (lifehacker.com)

On Thursday I’ll lead a webinar for my friends at NetBase around the topic of research and pulling insights from data. It’s really kind of a fuzzy topic for me because while I know how to do it, I don’t know that I’ve ever tried to explain it to others. But moving through the ideas and trying to come up with some recommendations for folks has been a neat exercise.

You should certainly register for the webinar and join us live, if you can. If not, the event will be archived on NetBase’s website, so you’ll still be able to access it. It kicks off at 2 p.m. ET/11 a.m. PT Thursday, May 12. It should last 45 minutes or so. And as of right now, it’ll be a fast and fun talk. I’m not planning on a lot of PowerPoint slides but rather looking at data and just walking folks through what I look for and see.

In preparation, I’d love to hear from some of you who sift through research, particularly those of you who focus on social media data you might glean from monitoring solutions, web-based research tools and the like. I’ll be sharing some ideas on how I try to pull insights from keyword research, anecdotal conversation points and more. But I’d love to hear from you:

• What do you look for when reviewing surveys, monitoring information, keyword research and so on?
• How do you decipher anomalies from potential trends?
• What type of data do you weigh heavier than others?

I’d love your thoughts and ideas on how you find the needles in the haystacks. I’m certainly not the first, only or even best person out there to explain how to pull insights from social media information. Your ideas would be a welcome addition to the conversation.

Come see us on Thursday. In the meantime, drop a comment and let me know how you find insights in the data you see.

Disclosure: NetBase is an online research partner of Social Media Explorer.