If there’s all this great information in big data, why do we have such a hard time getting to the part with the deep business insights? One issue is related to getting a better handle on influence.  But it’s also about structuring and tagging data in a way that allows you to see connections not only between people, but also concepts, companies and innovation.  For a long time, companies have been conducting business intelligence on their internal data, but now a few start-ups are tackling the task of conducting external business intelligence using publicly available data (social media, PR reports, investment disclosures, etc.).

Quid and Recorded Future are two such companies, and they are raising money and building teams to tackle this very real problem of pulling insight out of all this digital data floating around in cyberspace.  Large corporations, especially those in the technology sector, are using their services to analyze competitor moves, trends in the sector, opportunities for growth and acquisition targets, while traders at financial firms are using these services to analyze events, media-flow, and market behavior to adjust their trading strategies.

It’s always easier to see these things with concrete examples, and there is a great example using Smart TVs on Recorded Future’s website to provide a glimpse into the possibilities.  Imagine you are a corporate strategist at Samsung trying to map out the Smart TV landscape.  You know that people are talking about Smart TVs, and you could probably use a social media or traditional PR listening tool to figure out which forums and which blogs are discussing the topic.  But then what?  What about all of the financial documents, analyst reports and predictions that exist across other channels.  And how do you figure out how it all maps out in terms of sources, relationships and timing?

These tools essentially take as much publicly available content as possible and apply complex natural language processing to identify specific references to ideas, people and events.   These references are then structured and organized by things like time, topics and concepts.  By visualizing this data onto a dashboard that can be played with and manipulated, a corporate strategist at Samsung can now quickly see which companies are currently investing in SmartTVs and where the largest sums of investment are going to.  If he or she wants to find out how soon Samsung needs to begin thinking about R&D or a possible acquisition target, that can be done as well.

As the volume of data and the speed of innovation increases, these types of services will become a necessary tool for any strategic minded professional who wants to get validated insight into the future.

While Quid is currently not available for trial, Recorded Future offers those who are curious, a 15 day trial of the service.  Even if this is not exactly your thing, it’s worth seeing where we are headed.  Pretty cool stuff.

For the last couple posts, I have focused a lot of energy into trying to illustrate the power of influence on engagement strategies.  With so many voices contributing content, how can we focus on the conversations which are going to impact our brands to the greatest degree?  By knowing who is influential, we can ensure that we are paying the most attention to the people who can influence their own audiences.  This is often about figuring out a better engagement strategy on social media, so that company messaging reaches the largest audiences.  You can also understand what people think about your current products and campaigns, and it’s much better to focus on influencer conversations than wade through a billion conversations.

Companies like Klout and PeerIndex are giving companies the opportunity to see scores of influence for every individual, and they are starting to drill down onto the topics that these individuals influence.  Professional networks like LinkedIn allow brands to find and engage people based on what they do for work, and that’s a great way to tap into interest graphs, especially when it comes to people and topics where big purchases are being made.  And then you have a whole ecosystem of companies like Radian6, eCairn and Traackr who help to filter conversations based on influencer mapping using partner or home-grown methods.

But what’s the next step?  How do we help social media conversations achieve the promise of looking into the future?  I would make the case that influence is the answer.  It is one the primary keys to getting better interest graphs.  And interest graphs will then be the key to making sense of the insights hidden in big data.  So then instead of using influence just to figure out who should be engaged, rewarded and marketed to, we can also begin to use influence to find out where we need to go.

This is more strategic than simply finding out that Taco Bell’s Black Jack taco was a bad idea, because “I hate eating black colored food”.  Once we can accurately measure influence and match it to interest, we can use big data to figure out where thought leaders across the globe think the tablet market is going.  What do influencers in fashion think will be next year’s trends?  Which innovations are CIOs excited about over the next five years, and how can that affect the long term strategy of a Google or Salesforce?

I think these are the really big strategies that we can hope to understand from big data as influence and interest graphs are better understood.  What do you think?

Over the last five years, the level of conversation on the larger social networks has increased exponentially, and when you  combine it with all of the other user-generated channels, that’s a lot of content being created on a daily basis.  But what does that mean to the quality of insights that can derived from the larger conversation ?  Is there more noise on a percentage basis or is there more insight as a result of these increases?

There was interesting point raised at the end of a recent article in the Economist that discussed the value of social media buzz, and the diminishing returns that come from an ever increasing volume of posts.

“Most commentary on social media ignores an obvious truth—that the value of things is largely determined by their rarity. The more people tweet, the less attention people will pay to any individual tweet. The more people “friend” even passing acquaintances, the less meaning such connections have. As communication grows ever easier, the important thing is detecting whispers of useful information in a howling hurricane of noise. ”

While the value of each individual tweet will inevitably be reduced by the sheer volume of tweeting, the high volume of created content actually can help to improve overall insights.  Based on our work with clients, we notice that general trends and insights are in fact better and more substantial when the volume of conversations go up.  But as the article states, “Everyone will need better filters—editors, analysts, middle managers and so on—to help them extract meaning from the blizzard of buzz.”

Filtering conversations based on purchase intent and measurable business value can allow companies to get a better handle on what their customers think of their services and products.  In fact, it could be said that the promise of using social media for business intelligence has not been fully realized because there is still not enough volume to do everything that we hope for.  The time for companies to start working and testing their data filters is now, because we’re not too far away from the day where everyone really is talking.  And then there’s going to be a lot of data to sift through, and less time to experiment.

Having a listening solution that works “out-of-the-box” maybe be a bit of an illusion given the high expectations of deep social insight, however we are seeing many clients who are buying social media monitoring only to be frustrated that these tools don’t work as advertised.  The problem is not that these tools don’t work, but rather we were all really hoping for some magic.

Good business intelligence that comes from social media is a little like having a crystal ball.  Tell me the current trends in my industry.  Tell me why customers buy.  What should I do to engage?  But can you really just take a crystal ball from your local magic store and expect it to give you insights about your future?  Two things are going to happen: either the crystal ball is going to tell you something pretty generic or you’re not going to be able to figure out what you’re being told.

Sound familiar?  Many of the insights that come out of social media monitoring tools when set up internally, often are generic or filled with noisy data.  And generally, the problem is not that the tools are useless.  Rather, these tools work best when they are set up by individuals who have worked with them before and know how to get the most of out them.  While most vendors and many consultants provide this service, few clients actually pay the extra money to have a solution that has been calibrated to their business needs.

While some current social monitoring tools may not be as sophisticated as Cognos or Microstrategy business intelligence solutions, they still aim to bring back insights that can affect marketing, crisis communications, customer service, product design, campaign development and more.  Trying to save the initial setup and quarterly fine-tuning costs after committing to a hefty monthly licensing fee almost seems absurd.  Keywords that drive the filtering in these tools can be easy to come up with, but it’s a lot harder for teams to put together profiles that bring back clean data focused on business needs.

Rather than throw out your expensive crystal ball, spend the extra cash and have someone calibrate these tools so that you can use them to learn more about your industry, your competitors and your customers.  You will feel better about the tools, and you will actually be able to use the insights to inform business strategy.

As influence becomes a coveted metric among those who measure and analyze social media data, many are beginning to segment content creators into one of two groups: those with influence and those without.  But considering that our ability to measure influence with true precision is still relatively limited, this may not really be the most effective to way to think about influence.  Rather we may be better served by breaking influence into its component parts: reach and relevance, and then examining the individual business purpose for wanting to know influence.

Reach is about numbers.  How many fans and followers does an individual have across all of his or her online properties?  This is often the easiest way to measure influence, because it is objective and public metric.  Some will say that this metric doesn’t always tell the right story since “tribes” are influenced by very specific people.  However, it can still be a relevant metric, especially when we think about social customer service within retail and consumer products/services.  It doesn’t matter if Justin Bieber has zero relevance to the pizza business and is not an influencer to that industry.  If he says that he hates Dominos, that’s going to have an impact on the brand, and customer service professionals with access to social monitoring and social CRM tools need to pay attention to the absolute reach that each person has online.

Relevance is about topics and interest graphs.  This is a little harder to measure, but  there are already a number of vendor tools that are trying to crack that nut as well.  We’re starting to see Klout scores incorporated into many of the leading social media monitoring tools, and a combination of social mining with topic level influence is going to make this type of analysis important for brands trying to influence the influencer.  Unlike reach metrics around influence which are essential for real-time response and crisis avoidance, relevance metrics can help a brand quickly figure out who is influential to their particular brand or industry and then target that person for outreach.  A food blogger who could potentially rave about the new Dominos pizza sauce is a much better candidate to engage with than a B-list celebrity who never talks about food but technically may have more fans and followers.

Linking reach and relevance clearly allows brands to have a better understanding of influence for customer service, outreach and trending analysis.  But because the methodology of determining accurate relevance is still in its infancy, it may be a bit premature for brands to automatically combine reach with relevance.  Rather, we encourage organizations to look at both reach and relevance individually, and to bring together reach metrics with relevance data and interest graphs when appropriate.

To illustrate the danger of combining these metrics: a food blogger who talks about pizza with 5000 followers is obviously a better candidate for outreach than a food blogger with 500 followers.  But the reality is that we don’t know if we have captured all of the individuals who are relevant to Dominos by focusing just on food bloggers who write content about pizza.  Data analysis of social conversations is still generally keyword based, and there can be large gaps in the types of relevant influencers that automated tools bring back.

We recommend using both methods of measuring influence, but using them separately and as appropriate.  Reach for customer service.  Relevance for influencer engagement and trending.  It’s not always black and white, but it can help focus analysis to those metrics that will have the most impact for your specific business goals.

With the ever increasing volume of data flowing through the blogosphere, we constantly hear from clients about the challenges of sorting through conversations that will have an impact on their interest graph and those that are just casually commenting about a topic or brand.  In other words, can we isolate only those conversations and individuals that will influence a brand, so that we’re not listening, analyzing and responding to a lot of random chatter?

Many of the leading  tools in the market have already begun to assign influence through a combination of variables including: conversation volume, keywords and high level scores partnering with companies like Klout and ComScore.   Focusing on the conversations of the more influential people can often provide better insight towards trends.  And it can also make the process of engagement more efficient.  As we think about how this relates to Social CRM, a true determination of influence helps to provide an additional layer of knowledge around customer and vendor relationships.  The next step will be mapping the relationships and similarities among the most influential voices to determine how people are interconnected and what that can mean to the business.

One vendor who is working on this today is a company called eCairn.  I sat down with Dominique Lahaix, eCairn’s CEO, a few days ago to go through a quick demo of the product.  Rather than having to find influencers from scratch, eCairn has already identified over 300,000 bloggers who belong to some 300 different “tribes”.  These tribes include everything from people who talk about nails to bloggers interested in healthcare.  Looking at specific topics and conversations within these tribes, a company can listen and quickly put together an influencer map that identifies connections between groups and uncovers relationships that may not be obvious at first glance.  Over the years, I have seen the painstaking process of building similar influencer maps, and the option of having a head start on this type of work is something that should help many strategists.

As we move forward, the need to filter social media conversations based on influence, urgency and impact will become more important to social business.  The more that we can automate the ability to do this, the easier it will be for organizations to develop strategies and processes for business units to take advantage of this additional layer of data.

If you use other vendor technologies that help look at influence, I would love to hear about them, so please comment below.

There’s a new book out by Aaron Shapiro called “Users, Not Customers: Who Really Determines the Success of Your Business“.  Listening to an interview with him promoting the book, I realized that this is one of the fundamental things that a lot of our clients need to consider.  Traditionally, we always think that it is the customer who determines a company’s success.  And we define it as someone who buys or actively interacts with the brand.  It’s a very specific place on the purchase funnel.  But what about all of the people who are not yet customers?

According to Shapiro, a user should be defined as “anyone who interacts with a company through digital media and technology.”  Combine that with a recent Forrester study that says that 48% of all offline retail purchases are researched or conducted online (reaching 50% next year), and it becomes pretty obvious that the pool of people reading, curating and sharing messaging is much larger than “customers” in the traditional sense.

So when we think about trending analysis from social conversation data, we need to stress the importance of understanding what users are thinking about the brand, its products and its services before they become customers.  What factors drive users to go with our brand over a competitor?  Are there specific forums or sites that people rely on to make decisions?

When it comes to users, it is often more important to see the bigger picture and to understand the drivers of high level perceptions.  By accepting this new reality and analyzing conversations with this in mind, we can be better prepared to provide content and interactions that meets the needs of both customers and users.

Active listening across social media channels and responding directly to questions and comments across these channels is a lot different than in-depth trend analysis which can influence business strategy.  But as we work with our clients, we are noticing that there is a push towards engagement over analysis.  And it makes sense due to the immediacy necessary for responding to customer queries, but it may also indicate a dangerous sign from a governance and leadership perspective.

For the last two or three years, many of the social media reports hitting the desks of the C-level have been cluttered with generic volume charts and a hodgepodge of social media mentions from Twitter and Facebook.  In general, these reports (either developed in-house or by a third-party) do not address business KPIs nor do they help executives understand the parts of their business that social is truly affecting.  With few business metrics to analyze, many executives are forced to take away the operational numbers that they are given: increase in Facebook fans, total posts, total interactions.  But what does a higher volume of fans, posts or interactions really mean, if deep statistical analysis is not performed on the conversations?

Listening and reacting to social media posts is extremely important.  There is no question of that.  But organizations need to begin going through the exercise of defining what they want to see from social media conversations and interactions that are going to drive actions, sales and innovation.  From a trending perspective, you might want to find out how things have changed over time and how that affects your business.  What are people talking about in Q3?  Is it different than Q1?  Do we want to influence the conversation to change it, or are there things that we can learn to make marketing or customer service better?

A tactical approach is necessary to engage with your customers and let them know you are listening.  However, a business focused approach to listening analysis can deliver insights that can be actionable across the long term.  It’s not something that needs to be done daily or even monthly.  But once every two or three months, if done right, an aggregate analysis of social media conversations can provide a view of your customers that is extremely hard to see from the trenches.

Yesterday, after the Oscars, the general news media from CNN to the New York Times began speculating on the way that micro-media like Twitter could change the way that national broadcasts are produced. Richard Robbins, the director of social innovation at AT&T, was quoted from a tweet as saying, “In future, live show producers should have contingency plans to make on-the-fly changes when social media chatter shows trainwrecks.”

It’s a great pie in the sky idea, but let’s face the facts. Most businesses do not move at this speed, and probably should not move at this speed anyway. It may even be a little short sighted to make strategic decisions for a television show (… or a product or service) on the fly. Just In Time (JIT) businesses like Zara and Toyota are quick to meet consumer demands, but they are not that fast. Reportedly, Zara takes about 2 weeks, compared to the traditional 6 months, to develop a new product and get it into stores. But it may be unrealistic to think that businesses can provide valuable product at the speed of thought.

One of the problems with over-hyping social media is that many companies are ignoring some of the most valuable parts of this form of communication as a result of these unrealistic ideas. It may be a safe bet to assume that next year’s Oscar telecast will not include a contigency plan for negative feedback from social media, but we are finding that this often leads companies to ignore aspects of this data that could help them.

After a major event, campaign or product launch listen to the conversations leading up to the launch and right afterwards. We would advise the Academy to figure out what messages the overall conversation conveyed. Not just single posts, but the WHOLE conversation. Segment those trends and volume reports across different time periods and for different aspects of the event (presentation, red carpet, nominees, etc.). From these segments, the Academy can begin to understand what works and what does not.

For the next event, campaign or product launch, use learnings from the previous analysis to start out on the right foot. Social media is about experimentation, and the second experiment should be better than the last. Analyse the whole conversation again three months, two months and one month before the next launch, and continue to change the way you market and to whom.

Navigating social media marketing can be difficult and unknown territory. If individuals are talking about your organization on these channels, they are providing something valuable. But social media is not a one-size-fits-all type of medium. Match the speed of your business with the level of data you collect. Not only will the task become more manageable, but strategies will be more coherent within the context of your business.

For most of our clients, social media is a no-brainer. Let’s face it. Even the mom-and-pop deli below the office has a Twitter and Facebook page. But what is scary is that companies with millions/billions in revenue, multiple locations and many more employees are often not taking their strategy much further than Mr. Kim who makes kimchi tacos on Battery Street.

In Mr. Kim’s case, he gets feedback from his customers everyday. He’s not marketing on billboards or sending out flyers. He is communicating with his customers, and they are telling him what they like and what they don’t. They tell him by generating revenue at his deli, and they also tell him verbally that they wish he would make a kalbi burrito with two eggs instead of one. It’s a two way method of communication (sounds like social media, doesn’t it?).

It’s been said more than one, but social media is only a communication tool. Since the customers of large enterprises cannot necessarily show up in the “deli” to hear their customers, social media is becoming the next best thing. Of course, people will still send complaints and feedback through email, phone, and maybe even… mail. It is not only about marketing, but it is also about understanding what the customer wants out of your products and services. And there is a lot more data flowing through the pipes now. Not just through your own Facebook, Twitter, and other user generated channels, but ALL social channels. We’re talking about more than 9 billion pieces of content created everyday. And it’s growing.

What we find is most often missing within companies is the organizational structure to pass along messages to the right business units which can actually act on questions, feedback or complaints. Mr. Kim knows that he only needs to go home and tell his wife that they need to buy more eggs for burritos, but are your community managers telling your product guys that there are tweaks that would be great on the next redesign? Do you know that people are asking why the new cinnamon twists taste strange? Are you getting messages from prospective buyers to your sales team?

Regardless of the volume that your organization is seeing outside of owned channels, this is the time to put together the workflow necessary to pass messages along to the right people in your company. Audit the types of conversations that are occurring today, and begin to categorize how these conversations should be addressed as they occur in real time. Insightful ideas are floating around in the ether, and if your organization doesn’t listen to them, someone else will.