Who’s Mining Your Enterprise Collaboration Data?

imgresI’m not sure exactly what triggered my latest bout of insomnia two nights ago.  You can pretty much pick a card from the deck and find a reason.  So, at 3:15 am, I did what any sleep expert will tell you.  I picked up my iPad to catch up on my reading.  Because nothing says “soothing lullaby” like an irradiating screen burning your retina from six inches away.

As my head began to clear a bit at 3:25, I came across this post from Dan Brown.  He did to Facebook what many of us want to do but just can’t seem to pull the trigger, despite Sheryl Sandberg’s latest assertion.  If you are on Facebook (the 6 billion slackers that haven’t felt the rush yet can disregard), you need to read Dan’s post!

I did, several times.  After finally closing my tablet, I thought I could squeeze out another 45 minutes or so of sleep.  But, Dan’s post kept swirling in my head.  Then, I had a thought that scared the hell out of me.  Sleep was done for the night.  Here’s why.

It’s year-end prediction time all over this great big media universe we live in.  Everyone’s taking their turn putting on the Carnac get-up.  One of the most prolific predictions in the social business galaxy is that social business, enterprise collaboration, E2.0, whatever you want to call it, will accelerate in 2014 and will start to become ubiquitous in enterprise operations, strategies and business models across a multitude of industries.  Enterprise collaboration and the technologies that enable these practices will start to become the norm.  Corporate culture will shift en mass from the idea that “he with the knowledge wins” to “he who shares his knowledge and builds collaborative relationships will win”.   And, I’m all for it.  There’s no “I” in team.  Nor is there one in my name.  I am an over-the-top, open collaborator.  And have been forever.

But, in order for this enterprise collaboration to really work, for people to find and share with others in the organization through which they can create mutual value for themselves and the business, by definition, people will have to form bonds.  They will have to find some common ground upon which to forge these collaborative relationships.  In the course of this new enterprise Dating Game, people are going to share, and want others to share with them, information about themselves.  In this social media-driven world, we call it “authenticity” and “transparency”.  But, its also basic human nature.

So, what happens when the Monday morning water cooler chatter ends up in the new stream of the company’s collaboration platform?

A typical post that is already a reality might look something like this.

“Hey Bill, I’ve posted a revision of that design here for you and your team to review for your presentation”

“Thanks!  BTW, I had a great time at the Packers game yesterday.  Thanks for the tickets!”

Fairly innocuous.  Right?

Then, a couple of days later, Bill comes back from lunch and checks his news feed again.  The first post he sees looks something like this.

Sponsored Link

Get the latest NIKE NLF gear from The Packers and support Green Bay in their charge to another Super Bowl”

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Ok, that would never happen.  The Packers stink this year.  But, here’s the point.

As Dan Brown articulated, in Facebook’s eye’s, you are the product.  You are there to be sold.  Everything you do, either with your explicit permission, or implicitly because they have crafty attorneys that write privacy statements that you can’t understand and so consent to blindly, is mined, packaged and sold as data to marketers who use that data to hawk their wares to you.  In case you hadn’t noticed, your Facebook news feed is being overrun by sponsored posts and targeted ads.

So, what’s to stop your employer from doing the same?  Yes, I know.  Just like email or any other company-owned platform, whatever you say becomes the property of the enterprise.  But, this is different.  Email is email.  And while I’ve seen way too many people torpedo their careers by hitting “reply all” when sending a rant about their boss, a selfie showing too much flesh or other such stupidity, this is different.  As, organizations become more virtual and digital collaboration platforms become the default methods for all communications (if we are to believe the prognosticators), much much more will be shared across these platforms than would ever have been shared via email.

Facebook uses all this member data for one reason.  To make money.  While not even Walmart has a billion employees, some of the most progressive organizations in the adoption of enterprise collaboration are huge, global enterprises with several hundred thousand employees.  Not a bad data set for a marketer, if you ask me.

What happens when one of those smart brands approaches said progressive company and offers a lucrative revenue stream in exchange for access to it’s collaboration platform data and the ability to use that platform to pitch its products to all 400,000 employees.  What if ten brands do it?  One hundred?  One thousand?  This is potentially a temptation too strong for company leadership to resist.  Where does it stop?  The NSA is already there.  Credit agencies? Banks? Insurance companies?  Lifestyle is a significant variable in health insurance premium calculations.  What if an employer’s insurer offers discounts on group premiums in exchange for access to this data?

The past several years have seen employers spend countless monetary and human capital resources crafting social media guidelines that their workers need to follow as a condition of employment.  The focus of these guidelines for the most part has been to protect the company.  What about protecting employees’ privacy?  It’s not reasonable for organizations to incentivize, and even in some cases require employees to engage on these digital platforms and then provide them no reasonable protection from having what may seem mundane information used as input into some targeting or segmentation algorithm.

My goal in writing this ridiculously long post (sorry about that) is that someone reading this post can point me to advocacy work already been done in this area.  Or, if not, to raise awareness that this is a real and present issue that needs thoughtful dialog and consideration.  Let’s hope the dialog happens before unsuspecting employees find out the hard way.  Like Bill.

Why Driving Away Customer Contacts is the Wrong Approach

We all love IVRs!  Ok, no we don’t.  Study after blog post after twitter rant confirms that customers generally would rather take a sharp stick in the eye.

Then it’s web self-service.  Everyone wants self-service!  In fact they prefer it over human-based interactions.  Right?  Not so much?

So, why is it that, for certain individuals, words like IVR and other self-service elicit such guttural, vial reactions?

It’s not that IVR and other self-service solutions are inherently evil.  The answer lies in that, in a great many cases, these solutions have been implemented to do one thing.  Reduce the number of interactions that are handled by a human, thus reducing the cost of service.  And, over the past 30 years, that has been the overarching myopic focus of customer service organizations, regardless of industry.

Because, any company that isn’t maniacal about pushing customers to lower cost channels, driving down average handle times, burying the 800 number on the 10th page of the website and reducing the total number of customer interactions will surely not be long for this world.

Oh…wait.  Zappos, eBags, Virgin & Marriott among others do exactly the opposite.  And they seem to be doing o.k.

The fact is your company, any company, should want to talk to as many customers as it possibly can, through whatever channels your customers choose.  By this, I don’t mean talking to the same customers about the same problem or issue over and over.  Rather, cast as wide and deep a net as possible.  Why?  Because, if you make the investment in and take the time to listen to those unsolicited customer voices, the insights contained within will deliver a return far greater than the narrowly focused cost saving efforts of restricted access.

A strategy of cost containment and access reduction limits the insight into customer preferences, needs, problems to be solved and ultimately, their behavior.

Slide1

What if we looked at the service delivery model differently?  If, rather than the conclusion of the interaction being the end of the process, we need to view that step as a means to a different end.  Then the business justification becomes clearer.   Investing in more ways for customers to communicate with your brand as the means of gathering a greater volume of unsolicited customer feedback can drive innovation in everything from product development, retail experience to back office processes and everything in between.

Slide2

Pretty intuitive.  Right?

Now let me not be so naïve as to suggest that anyone in your organization, especially your CEO or CFO, is going to write a blank check for you to go out and double the size of your customer service organization, reengineer your IVR and website and dump a whole bunch of money into new channels just because of the argument above.  Sorry to say.  But, you’re going to have to prove it.  And the proof is going to be different in every organization.  So, pick an issue.  Run a pilot.  And build the business case.  If, during that pilot, you identify that you don’t have the data, can’t get to it, or don’t have the ability to analyze it, you may need help from the outside.

Also note that this model of customer service as enterprise analytics hub will likely require different skills and resources within your organization as you are changing the value proposition for customer service as an enterprise function.

We’ll explore those skills and the process for transformation in upcoming posts here.

Syndicated, Social & Customer Service Data

Social-Media-InsightsSpencer Geren, my friend and big data evangelist, made a compelling case for the incremental value created by augmenting syndicated data in Consumer Packaged Goods with social web data.  In Spencer’s example, social data provides the opportunity to understand the “why” behind the sales and consumption numbers.

As background, Dion Hinchcliffe made a very good baseline case here for the value created by combining big data and social media.

While you can make the argument that this root cause level data is already available via customer surveys, focus groups and other such methods, there are key differentiators that make the pursuit of Spencer’s concept worth the investment.  A few differentiators that this strategy provides include:

  • Unsolicited vs solicited consumer feedback: unsolicited feedback especially peer-to-peer, gathered via social chatter is more authentic.  And, by not forcing answers to specific questions, potentially leads to unexpected yet more valuable insights. 
  • Timeliness of insights: social data provides a source of more real-time feedback to brands compared to the typical time delay associated with syndicated data alone.  Actions taken in that time compressed state can translate into significant sales and market share impact.
  • Why is always more actionable than What: As Spencer noted in his piece, social data provides insights on the behaviors and real-time reactions that will drive the consumption numbers in the future.

So, as a customer service guy, I of course look at this issue through that lens.  Multi-channel customer service data provides even greater value along those three elements above.  Multi-channel customer service data, by definition:

  • Is unsolicited
  • Is timely
  • Provides the insight into customer behavior

The point here is two-fold.  First, marketers and market researchers should be tapping into this customer service data as a value added tool in their quest to predict future customer behaviors.  Secondly, as I argued in my recent post on Salesforce.com’s blog, customer service as an enterprise function has the opportunity to use social, multi-channel and other big data sets to reinvent itself from traditional reactive processes to a proactive deliverer of customer insights.

Reflections from Call Center Week 2013

I had the pleasure of sitting down with Jason Boies from Salesforce.com the other day to chat about our observations from Contact Center Week, held in Las Vegas in June.

His interview of me is here at Salesforce Marketing Cloud blog.

If you have a different perspective on where the industry is going, click back here and let me know in the comments.  I’d welcome some different perspective.  Thanks.

 

The Big Data History Lesson

imagesI just got done listening to a keynote from McKinsey’s Matt Ariker on big data at the SOCAP Spring Symposium.  As I was listening I was struggling to find something more interesting to write than just reporting the highlights of his talk.  Then, about two thirds of the way through the hour long session, I got it.  Rather than ruining my own punch line.  Let’s see if you can figure it out.  See if you come to the same conclusion.

Matt started out challenging the audience with some good questions to ponder.  Like big data, what is it?  Why now? Why should you care?  One answer?  According to Tech Crunch, big data will drive $232 billion in spending by 2017.  So, yeah.  We should care.  Good so far.

Matt went on to share some other stats and also some of the key questions that his clients are asking on the subject.  Then, his presentation outlined what he believes, or is observing as some of the critical pains that organizations are currently experiencing with respect to big data.  In summary, they were as follows:

  • Lack of clarity on the vision and roadmap for big data.  Everyone wants all the data they can get there hands on without having the business questions identified first.
  •  Enterprise culture and mindset are not aligned.  There is not 100% buy-in and commitment from the C-Suite
  • Ineffective use of data and tools.  Data project scope creep is deadly.  Too many think “if I can get more data, why not?”  There ends up being too much time and resources spent on acquisition and aggregation at the expense of analysis and solving business problems
  • Ineffective integration of big data projects into business processes.  Internal stakeholders are not engaged in development nor accountable for delivery
  • Too much focus on technology and not business processes
  • Misalignment of required enterprise skills to execute on these projects. The focus is largely on technical skills, or in repurposing other skills and resources.

Did you figure it out?  This is history repeating itself.  Haven’t we seen this before?  Many, many times?  ERP.  CRM.  Virtually any big, enterprise technology initiative over the past 20 years has faced these same set of challenges.  You could take this post and do a find and replace.  Insert “ERP” or “CRM” in place of “Big Data”, date it 1995 or 2001 and the issues would be still relevant.

So, like back in 2000, there are companies that are doing it right.  So, perhaps the best place to start, the first mile of your roadmap, should be to find those examples and do what they are doing. Imitation is the sincerest form of flattery…and it just might save your career if you’re the one writing the big data checks in your organization.

 

Disney’s Data Deluge

mickeydataLast week, I threw out some ideas here on how Disney could leverage social and mobile technologies to enhance the guest experience.  And while, if you go back and read that post, there might be some specific reasons why they have a vested interest in keeping guests standing in some lines, the opportunities to leverage big data in the guest experience is just as compelling.  I’m just going to throw out three personal examples.  I’d really like to see what you all can think of too.

First, I would guess I’ve got to look like somewhat of a frequent guest or loyalist, whatever you want to call it.  I don’t have the exact count.  But between business and pleasure, my best guess is that I’ve stayed at Disney resort properties somewhere in the neighborhood of 25 times.  Of those 25 or so times,  I’ve only actually stayed at five different properties.  Yet, I’ve never had any engagement with Disney either through direct marketing or other interaction that would suggest that they know I’ve demonstrated an fairly predictable pattern of where I prefer to stay.

With respect to Disney Park attendance, I’m pretty predictable there as well.  Of the four major theme parks, my order of preference is Magic Kingdom, Hollywood Studios, Epcot then Animal Kingdom; with about 40% of my time spent at the Magic Kingdom.  And, in all the time I’ve been going to Orlando, I’ve never once attended one of the water parks.

Lastly (apparently I’m a creature of habit), when I dine at Walt Disney World, 60% of my sit-down meals have been at the same four restaurants over the past five trips there.

Combine all that information with my demographic information and there is definitely a profile there. Also, if you’ve ever been to Disney World, you know that everything you do is tracked through your hotel room key, if you’re staying on a Disney Resort property.  Every dollar spent.  Every park entered.  Every FastPass acquired.

I’m not a data scientist.  Not by any stretch.  But, like last week, I wonder what Disney is doing with this information.  And, how could they use it to make my visit even more magical?

CRM 5 In 5

[We’re not all pretty yet over here.  But, I have things to say.  So, the window dressing will come later]

What better way to kick off my new home than with a reflection back at a story posted around this time last year.

The start of the new year is inondated with predictions of all sorts.  I wonder.  Are there more predictions than resolutions?  Does a similar portion of the predicting population go back and revisit their thoughts as do those that make resolutions? In other words, woefully few?

Well this is a tale of a different sort.  This story started in January 2011 with a post called the CRM 5 in 5, modeled after IBM’s annual 5 in 5 look into the future of technology.  In that post, Lauren Carlson from the site Software Advice asked some leading CRM thinkers for their views on the next 5 big trends in CRM.

In this follow up post, the Software Advice team went back to this panel for their follow up thoughts on crowdsourcing, mobile, curated data, open APIs, NLP & personalized predictive analytics:

  • Denis Pombriant, CEO of Beagle Research Group LLC
  • Brent Leary, owner of CRM Essentials
  • Esteban Kolsky, principal and founder of ThinkJar
  • Brian Vellmure, CEO and founder of Initium LLC / Innovantage
  • Paul Greenberg, owner of 56 Group LLC

Additionally, as a follow up to last year’s topics, Rachel Ramsey of the Software Advice team send me this commentary on the convergence of gamification and crowdsourcing.

Gamification was a huge buzzword in 2011. Companies providing these technologies promised increased community engagement, productivity and other improvements by layering in game-like tools such as leader boards, badges and virtual scoreboards. While popular, there was varying opinions about  success of these platforms at the time.

 In 2012, our group foresaw gamification moving from buzzword to business strategy. These programs proved real results increasing customer loyalty, brand advocacy and engagement. We touched on that topic again this year, but through the lens of crowdsourcing.

In my mind, that’s a pretty good list.  And who am I to argue with the group above?

I will add this though.  My prediction (and this is more like history repeating itself.  So, you have a better than average chance of being in the money if you bet on this one) is that a significant portion of the projects in the categories above will fail to deliver customer or business value, if the CRM table stakes are not addressed first.

What are those CRM basics?

  • Customer value, strategy and business process first
  • Technology second
  • Focus on customer insights, not data

My brain can only think in threes.  So, that’s all I got.  What’s your prediction?