Polygraph Media Blog

Social Media Measurement & ROI - the next big thing

According to The Center for Marketing Research at The University of Massachusetts.

We agree.  Link below:

http://www.customerthink.com/blog/social_media_measurement_and_roi_next_focus_of_inc_500_fortune_500

Guest Blog Posts

I thought I'd share some guest blog posts that I've published over the past few months on the Windmill Networking blog.  It is run by Neal Schaffer, who is one of the world's leading experts on B2B marketing and social media.  Neal is a great guy and friend.

How Can Facebook Get Its Mojo Back

The Unlikely Newest Member of Your Social Media Team

I've committed to Neal that I'll publish there every other month, which means I'm due a third submission there later this month.  :)

Big Social Data -- Explaining Offline Behavior

Over the past six months or more, you've probably heard the term "big data" floating around as if it is supposed to solve all your problems in business, marketing, operations, etc.  Just "access the data" and you'll be smarter than your competition.  You'll react to customer feedback.  You'll be a visionary.  Blah blah blah

All of this creates a situation where they hype is through the roof, but few people can really speak to real-world scenarios and useful applications of big data.  That's probably why "Big Data" is high on Gartner's Hype Cycle 2012 Chart.  Lots of possibilities, but not a lot of answers just yet.

We work primarily in the social data realm at the moment, although we have been getting more & more requests to integrate offline data with social data to understand patterns.  Alongside first-cousin ROI (return on investment), the big question today is whether or not social media is a scorecard for how you're doing or if it can influence offline behaviors, purchase patterns, etc.

The takeaway for us so far is that different businesses certainly have different dynamics.  Only with full access to the data can you really draw any firm conclusions.

Contact us to learn more about how we can help harness big data for your company or brand.

Data Mining... a Primer for Marketers & Decision-Makers (Part 1)

A bit of a dry post today, unless you're a data geek like we are.

Since our launch, we've entered a few customer and partner conversations that would've been best served with an introductory primer in data mining.  I would estimate that a majority of marketers don't have a firm grasp on the requirements and/or what the opportunities are in the field of data & data-driven decision making.

So here's my "business guy shorthand" on data mining, what's available today, and the opportunities all of this affords.

First of all, content on the Internet has exploded as others have chronicled over the last few years. From the linked article above: 

"...compliments of Dave Turek, the guy in charge of supercomputer development at IBM: From the year 2003 and working backwards to the beginning of human history, we generated, according to IBM’s calculations, five exabytes–that’s five billion gigabytes–of information. By last year, we were cranking out that much data every two days. By next year, predicts Turek, we’ll be doing it every 10 minutes."

How did this happen, you ask?  Look no further than the social media movement, which democratized publishing to the web via blogs, put our videos online via YouTube and Vimeo, broadcasted our short-form opinions via Twitter, and chronicled our life through Facebook.  And alongside those services are a series of other services that all collectively help us chronicle our lives online.

I personally love this infographic below that illustrates just how much data we're all creating today.  It's a far cry from when we needed a web developer to post content for us.  Additionally, check out this compendium of stats from 2011.

In addition to the revolution in self-publishing, we've simultaneously had a revolution in the collection of data in the corporate realm.  Gone are the days of Day Timers, Day Minders, etc.  In with the world of Salesforce.com.  New Point of Sales (POS) systems are no longer analog but rather "digital", which allow for the collection much more data that can be analyzed and explained. Every part of a modern business can be digitized and recorded today for data analysis -- and smart businesses are doing just that even if they don't have the analysis capability just yet.

Additionally, government agencies are publishing data to the Internet now with increasing frequency -- making records public that were once published to books, stored on microfiche, or available only upon specific request in-person.

The greater point is that we're all creating data about ourselves every day -- personally, as citizens of our locality, as employees, etc.  Although the "quantified self" movement is relatively young, we're already uncovering introspective ways that we can get smarter about the things that we're doing using data as our guide.

Through collecting and analyzing data appropriately, all stakeholder groups can benefit.  A few quick examples...

• Self -- quantifying exercise, meals, etc. for better health. 
• Business -- quantifying operations to understand efficiencies in staff, travel, etc.  Mining customer data to understand market segments & purchase intent.
• Public Sector -- combing through the data to better isolate fraud potential.  Using data to optimize tax receipts.

The common term across all of them is "efficiency" -- using data to become more efficient.  In a hypercompetitive world, efficiency is the way to unlock more profits through decreased costs, increased revenues, and/or improved experiences.

Additionally, data can be predictive and prescriptive.  Let's say you are in a family of four and have bought two cars over the last 8 years.  You have a luxury car with 20,000 miles and an SUV with 200,000 miles.  It's a simplistic case, but the data in this example suggests that you might be in the market for an SUV soon and years away from another luxury car purchase.  That's the predictive part.

Odds are if you got the SUV serviced by a data-driven car dealership, you've heard from them recently about trading in that old clunker in exchange for a shiny, new SUV.  That's the prescriptive part -- send everyone likely to buy a new car a new advertisement.  Like it or not, but it happens all the time already... all while many corporate marketing departments are not fully optimized to take advantage of the opportunities available via data.

As we've talked with a number of companies about our work in big, social data, we've discovered a wide range of companies in terms of adoption of data analysis -- collection, normalizing, analysis, data-driven decision making.  Some are leading the way, and others still make analog decisions.  To be expected, although we do think the shift towards data is a long-term trend that will be impossible to ignore for most.

In the next blog post, I'll talk more about the mechanics of making sense of it all -- from data normalization to analysis and informed decision-making.

How Facebook can inform a Presidential Race

Today, we thought we'd use Facebook data to tackle one of the most anticipated decisions of 2012. Who will Mitt Romney choose as his running mate?  And can Facebook data be used to help make the decision?

Data is great and all, but what good is data if you can't make decisions with it?

First, a little context.  A number of studies have already shown that social media data is helpful to gauge voter sentiment:

• Crimson Hexagon analyzed Twitter data in 2010 to accurately predict a victory for Harry Reid.
• Social data (Twitter, Facebook, Google+) was also used to accurately predict Boris Johnson's victory in the London mayoral race last month (June 2012)
• Facebook themselves pointed out some correlations in the data as well following the 2010 US mid-term election.  Candidates with more fans won Congressional races 74% of the time and Senate races 81% of the time.  Not bad!

Now this field is not without detractors -- some academics have focused on the flaws in using social data to predict the future.  We agree that Twitter data is dirty relative to Facebook data, as it's easier to create dummy accounts for Twitter and many people use Twitter primarily for marketing purposes and not to share what they're really doing/saying/thinking.

But it's also sour grapes in our opinion.  Anything short of asking every single man, woman, and child is in essence a shortcut.  There are going to be flaws in using data to make assumptions about the behavior of a large audience.  There are flaws in traditional market research, statistical analysis, etc.  This is no different -- in fact, it may be better.

With social data, we have the largest self-contributed data sets the world has ever seen... on par with the financial and personal data owned by major credit card companies (Visa, MasterCard, AmEx, etc.) and marketing companies (Acxiom, Dun & Bradstreet, and Harte Hanks). Additionally, people don't really have the motivation to falsify information here as they would perhaps when talking with a market research professional.  Facebook is capturing the unvarnished truth of who everyone is.

As such, we think that Facebook data is the most accurate data set in the world.  And it's relatively unmined at present.

-- 

Anyhow, we wanted to show an example of how reactions on Facebook can give decision-makers in politics a clear sense of who is "known", what they've done, and how they've managed to keep their supporters engaged.  In that sense, politics is not that unlike what social marketers do all the time -- keep the brand front & center and something worth rallying around.

In this admittedly simplistic example, we looked at a number of factors in an attempt to narrow down the Field from a large number (8) to a top-priority running mate.  We collected data on the following:

• Current Facebook Fan count
• Percentage of “Likes” over 5 quarters of posts
• Pro or negative “Romney” in page posts
• Pace of new Facebook fan acquisitions predicted between now and election day based on previous pace (how many new Friends per day)
• Polarization – the activity of each candidate on “pro” or “against” 3^rd party Fan pages

Each of these things was selected in order to test something relevant for a national election.  Is a candidate a national or regional candidate?  Is a candidate doing a good job of keeping the base engaged?  Is the candidate extending his/her reach to a broader base of enthusiastic supporters? Does the candidate create controversy or negative passion in other voters that might improve the prospects of the other political party?

The infographic is below.  We'd love to know what you think.  Also check out our YouTube video where we walk through the findings and explain the numbers in more detail.

Video - walkthrough of our Romney Veepstakes Infographic - Facebook Data

In this quick video below, we review the recent infographic that we released about how Facebook data can be used to inform political campaigns.

 

 

Social Marketing & The Quantified Self

The "Quantified Self" movement is something you've probably heard of over the last few years -- the idea that you can quantify previously mundane activities that you've otherwise ignored to attach a number to the things that you do.  There's plenty of reading about it on Wikipedia if you'd like to dig deeper.

In real life, the movement has manifested itself in successful consumer products in/around the fitness industry, such as the FitBit, numberous nutrition apps on the iPad, Garmin products, and the Nike+ line of products.  

In fact, Nike is releasing a product specifically for basketball so you can quantify your vital stats on the basketball court.  Allow me to let the expert, LeBron James, explain it.  

 

Sidebar -- but as a 38 year old, aging weekend warrior, I just don't want to know how bad my numbers are and especially as they compare to friends... but I digress.

Others have added a social element to tap into how we respond to peer pressure and/or social humiliation -- such as Strava and the Withings Scale that tweets out your weight.  Yikes!  

Why do people quantify themselves?

• People quantify themselves when something is wrong and they want to fix it.
• People quantify themselves when they're doing something right, and want to make sure they continue to do things right.  
• People quantify themselves when they want discipline to do the right thing, even though their natural inclination is to not do the right thing.
• People quantify themselves when they want an objective measurement of how they are performing at something, relative to peers or competitors.
• People quantify others when they want to use data & milestones to understand things they cannot understand, or as a proxy for heavy-handed, micro-management.

Numbers have a way of cutting through the clutter and capturing only what really matters... outcomes.  Combining numbers from different sources can give you a quick, objective look at everything that really matters to you.

If you take numbers the next step to analysis, you can begin to draw conclusions based on the data but also including human judgment where it's appropriate.  Leave analysis to others, and you're getting their interpretation of the data.

We found it interesting that Jeff Ma, formerly of the famed MIT Blackjack team, recently ventured into this space to quantify what people are doing in the workplace with his new startup, TenXer.  Right place, right time -- like Facebook, this would've never flown even a decade ago.  But times change and now it's a brilliant idea.

We're seeing it in social marketing and we're seeing it move into other areas of marketing that were thought to be a "black hole" previously.

We're at the beginning of a bigger trend where the "Quantified Self" moves into areas beyond personal improvement, fitness, etc.  People are learning the value of numbers, metrics, and how to apply them to make better decisions.  We're happy to be here at this critical time.

"Old Media" Learning from New, Explosive Growth Companies?

Over the last five years, a number of companies have emerged seemingly out of thin air to dominate in a "three screen", computerized world (mobile, tablet, computer) and grow explosively. Think Facebook and Groupon in the publicly traded realm... in Austin we have Chaotic Moon Studios, Mutual Mobile, and AppSumo.  Of this group, only Facebook existed in 2007.  Yet all are growing like a weed.

They all have one thing in common -- they saw opportunities, a market need, and a clear path to monetization that was also capable of scale.  In each case, once they found success, they hit the accelerator rapidly.  And none of them have debilitating geographic limitations that can't easily be overcome.

A number of my friends, colleagues, and acquaintances in traditional media want to capture that lightning in a bottle -- and are now putting plans in place to do just that.  What will they need to do to succeed?

Fill the toolbox with relevant products -- think about what the target market wants and offer it to them.  There is a revolution going on in mobile and social media.  Hop aboard!  For mobile, that might mean offering apps, mobile advertising, and mobile optimized web sites.  For social, it means helping people keep their sites & social properties up to date, social advertising, how-to webinars, and metrics to be the ultimate scorekeeper of what is working and what is not.

Modernize the sales force & think creatively about the sales process -- Your sales force is perhaps one of your biggest assets, and a huge differentiator from other entrants who have no sales force.  But all too often, they're not motivated to modernize.  Progress means selling new things *and* maintaining cash flows from the old cash cow businesses.  Sometimes your sales force can be a part of this transition, but in other cases they just need to be disrupted.  Broaden your thinking of what a sales process is -- it might make sense for your reps to change, and/or future product sales may not even require a sales rep after all.

Invest in true innovation -- they say in technology that you have to skate to where the puck is going to make good bets for the future.  What pain points will your customers endure in a few years?  That's where they're likely to spend money.  Give thought to it, and plant seeds there alongside existing opportunities.  Some of those new things are tomorrow's stars, if you commit to them as the examples above did.  But they also will never graduate if you don't give it a real chance.

Make geography irrelevant -- Geographical constraints are expensive -- forcing you to invest in on-site salespeople and/or support staff.  Try to make geography less relevant over time to both generate new leads and to find sources of revenue that are not necessarily in your specific locale. This may force you to do some things differently, but that's OK if you can be truly geographically agnostic.

Embrace the potential of a services organization -- For bigger businesses, non-profits, and other customers, you may find that you can make more money providing support or fulfilling maintenance contracts than you would selling your core product.  A services organization, built and integrated into the sales process in the right way, can be a highly profitable yet valuable part of your product offering.

Interestingly, many services organizations and agencies are aggressively moving in the direction of offering products.  They're reinvesting cash flows to compete.  It's a smart move, but it means that old media is getting another round of competitors -- probably the last thing it really needs to stay on top.

Crowdsourced ideas for using Social Data Mining & Analytics

Happy Friday, everyone.  We launched Polygraph 2 1/2 weeks ago, and have been floored by the response.  Clearly, a lot of people have wanted access to & analysis of Facebook Page data but haven't known exactly where to go to get it.  And as "the wisdom of the crowd" would indicate, you (collectively) are a lot more creative and a lot smarter when it comes to uses of Polygraph Reports -- either as currently packaged or as you have requested we make the data and analytics available in a customized manner.

Not mentioning any names, companies, or other identifying characteristics, here are a few of our favorite ideas:

Real-time campaign & community management analysis -- Community managers have responded particularly well to Polygraph, citing its affordability and its easy to understand interface.  We've been told repeatedly that it is a "community manager's dream" although I can't personally verify that, as I'm not a community manager. ;-)

Next generation market research -- Market research used to be conducted entirely over the phone or in person.  But now, people are telling us their preferences in social media updates.  This data can be aggregated and can accentuate more traditional market research methods.

Deep competitor/industry analysis -- Several of our customers at launch are systematically pulling down reports on all the major players in their highly competitive industry.  One has already requested over 1,000 reports to survey the target market for his product/service. 

Watching trends -- Social data can be used to watch broader trends among consumers.   This data can then be applied to other data sets -- both public and private -- to better inform business and investment decisions.

Measuring offline advertising lift in social -- Marketing today is a multi-screen, multi-dimensional activity.  Social certainly gets a lift anytime you do things in other areas, and vice-versa.  Marketers around the world are trying to better understand the interplay of different marketing activities to better understand purchase intent.

I mention these really to exercise your creativity.  If you could analyze mountains of social media data, what would you do?

Interview in Texas Tech Pulse

Here's a recently published interview in Texas Tech Pulse about Polygraph and its origins.  

http://www.texastechpulse.com/interview_with_chris_treadaway_polygraph/s-0043095.html