Tag Archives: analysis

Strength in Humans – The Power of People in Social Media Marketing

When we tell brands to be “more human” it’s rare that they immediately understand how it translates on social media. Tim Howell set the stage for this blog when he asked businesses to ask themselves why it was important to “be human” on social media. In this blog, I’ll look at how businesses can effectively be “more human” while still meeting their social media goals.

I believe that part of the answer can be found by looking to Humans of New York (HONY).

HONY is social media.

More specifically, HONY is a website that gives people everywhere “daily glimpses into the lives of strangers in New York City”.

These people aren’t famous. They are normal, everyday people walking the streets of New York. And their photos and stories have transformed into something almost magical – creating news, inspiring imitators, and serving as great platforms for calls to action.

It is visual. It is storytelling. It is measurable. And at its core, it is undeniably human.

So how can companies use the magic of HONY’s humanness to inspire their brand’s social media content?

Step 1. Highlight the Human Side.

Every business has a story to tell. There may be a single person who embodies the spirit of your brand, or an entire department that spends everyday living up to your brand promise. You are a company made up of people. Embrace it – your audience will.

Step 2. Write Well. Write Often.

You are as strong as your content. If you go to a party and tell the same story over and over, eventually people will stop paying attention to you. Social media is the same way. Part of the appeal of HONY is the stories behind the photos, told through short, platform appropriate captions. New content is posted daily to multiple platforms, which brings me to the next point…

Step 3. Know Your Platforms.

You wouldn’t use YouTube to post photos and you wouldn’t ask someone on Tumblr to “Like this post!” Great content will go nowhere if it was posted to the wrong platform. The visual nature of Tumblr and the ease of sharing across the network made it ideal for HONY. Adding in the virality and reach of Facebook enhanced the reach and awareness of the brand. Before you post, ask yourself: are the capabilities of the platform aligned with the needs of my brand?

Remember: the “Robot Revolution” hasn’t happened yet. If you want to successfully communicate with humans, you need to be human. 

When she’s not working as a marketing manager for Make Me Social, Mandi Frishman drinks a lot of tea. During her time studying at The University of Florida, Mandi became convinced in the power of learning through play. She has since committed herself to playing (and learning) all day, every day.


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Romney in a Landslide: Using Facebook Data for Predictive Analysis

Election coverage is filled with plenty of subjectivity, so here’s a little more:

Based on Facebook data, Mitt Romney is set to win in a landslide over Barack Obama, claiming 391 of the 538 votes from the Electoral College. That’s not exactly matching what the media or polls are saying … so how did I get there?

The Inspiration

Facebook’s EdgeRank Algorithm says that a Like is worth less than a Comment because a Like is a more passive form of engagement, while taking the time to type something out is seen as more active engagement.

I believe that the same can be said for people who Like a Facebook Page versus those who actively join groups or type something out in the interests section of their personal Page.

Following this logic, if we use Facebook Advertising to determine the relative size of an audience in the network based not solely on likes but on interests and groups as well, we should be able to identify the number of people actively engaged on behalf of a candidate.

It stands to reason that those who care enough to actively engage on Facebook are more likely to actively engage by voting.

Additional Details

Total “Popular Votes” counted through Facebook: 25,527,910

“Popular Votes” For Obama: 12,250,120

“Popular Votes” For Romney: 13,277,790

My Electoral College Results

“Votes” For Romney: 391

“Votes” For Obama: 147

Here is a comparison of my data when examined alongside three Electoral College Maps, CNN, Rasmussen and Karl Rove.

So how do these results stand up to “traditional” thinking?

  • In 2008, young voters went against election trends by showing up and voting (see: Young voters feel less engaged this year). The Facebook numbers I’ve pulled this time around seem to indicate a return to the traditional model with older voters driving the outcome of the election. While my projections show Obama carrying the popular vote in the 18-20, 21-24 and 25-34 age categories, they do not outnumber voters aged 35 and up who favor Romney.
  • The South votes Republican and the Northeast votes Democrat.
  • California is weird. Nothing new here, but perhaps the biggest anomaly in the numbers shows Romney carrying California because of a large number of 45-64 year olds “voting” for him. In addition to California, Delaware, Hawaii, Illinois, Maine, Maryland, Massachusetts, New Jersey, Rhode Island and Washington project for Romney.

The Process

I used the Facebook Ad Manager to gather data on the number of people on the Facebook network that have either Obama, or Romney listed in their Timeline using the Precise Targeting tool.

I segmented the search information by Keyword and broke results out by State and Age Range. To be as accurate as possible, I also used the Exact Age Match feature.

Precise Targeting looks at a person’s interests, activities, education, job titles, pages they like and groups they belong to, and Exact Age Match eliminates overlap between age groups. For example if you search 25-34 year olds without Exact Age Match, the targeting engine may include 24 and 35 year olds in the audience. I used these features with the goal of creating a comparison to how we would typically look at any other brand’s audience when taking a high level pass at their potential audience for a Facebook Ad buy.

I also used the hashtag feature in front of the candidate name to collect all possible interest categories, and get the broadest base of support.

The age ranges used were based on Voter Data as measured by the US Census, 18-20, 21-24, 25-34, 35-44, 45- 64 and over 65.

I then used an Electoral College calculator to allocate votes in the Electoral College based on the number of “active voters” for each candidate.


The data set is limited and only shows what it shows based on the Facebook definition of Precise Targeting and Exact Age matching. There are a lot of outside factors that influence the data. For instance, younger audiences may be engaging more actively on other platforms, like Tumblr or Twitter.

User activity by age range is a big takeaway. People in the older demographic groups are actively using Facebook when they encounter something that fits their needs, or interests. While a younger person may update their Status or Like a Page, an older person seems more likely to join a Group or update their Profile information to reflect their voting behaviors.

The 45 and up categories generate more targetable activity than the younger demos and are ripe for smart marketing.

For a closer look at the data pulled, I’ve made it available here as a spreadsheet: https://docs.google.com/open?id=0B6O00up2QT8RQ2NGSlhJZVJEMTA


JOSH JORDAN is the Founder and President of Make Me Social. Josh has spent the majority of his career blending his passion for people, technology and community development to create real relationships for brands and their message. Josh and his wife Jennifer live in St. Augustine, FL where they volunteer their time and energy to support the local arts and children’s charities and spend endless hours keeping their 19 month old son, George, entertained.


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As the Kings of Content Battled, The Digital Revolution Continued: Why Viacom and DIRECTV Fought the Wrong Battle, A Social Media and Marketplace Analysis

The recent battle between Viacom and DIRECTV captured a lot of attention this month. By focusing on the issues that Viacom and DIRECTV were addressing in their negotiations, it was easy to miss the larger issue: that winning this battle would not win them the war. We turned to social media analytics and market research to examine the big picture, and ask: can the Kings of Content survive the Digital Revolution?

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Sources and Content Creation

“Don’t think so hard. You might hurt yourself.”

I can’t remember the name of the teacher who interrupted me during an exam with that message, but I’ve never forgotten their words.

Each month we host an internal training for all members of our content team. This month we focused on ways to find inspiration for content curation and creation, and the presentation was heavily inspired by the sentiment behind those words.

In the interest of sharing and all that is social, we’ve decided to make portions of that training available to the public. Enjoy!

When she’s not working as a marketing manager for Make Me Social, Mandi Frishman enjoys finding that her degree is relevant to her life. During her time studying at The University of Florida, Mandi became convinced in the power of learning through play. She has since committed herself to playing (and learning) all day, every day.

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The Unfocused Focus Group: The Power of Social Media Monitoring

When I was in high school I participated in a focus group about deodorant. I sat in a room with a bunch of girls that I had never met and was asked to share my memories of deodorant and give feedback on the smells that I enjoyed. The most memorable part of the experience was a girl who shared that she began using deodorant after her mother told her that she smelled like, “A meatpacking plant.” Her delivery was excellent – completely straight faced with no hint of emotion. It was the highlight of the focus group, although I’m pretty confident that the company who paid for that focus group did not enjoy it as much as I did.

Now this was “back in the day” (within the past 10 years) but not so far back that I don’t remember how much I was paid. For less than two hours of my time I made $60 and they gave me cookies. There were probably 5-7 girls in the room with me, each of whom were given $60. We were not the only focus group and I can only hope that they got something more than “girls will use deodorant when shamed by their mothers” out of it. But why all of this talk about how much we were paid? ROI, my friends.

Let’s fast forward to the glorious present, where teens tweet, brands want you to like them, and public content is indexed for your searching pleasure. How could that company get better information today? How could they expand their focus group while refining their data, and without paying for every bit of feedback? Two words: social media.

Your focus group is out there, tweeting, posting, and blogging about their deepest darkest desires, offhand thoughts, likes, and dislikes. They’re talking about your industry, your brand, your products, and even your employees. The social media listening tools that are available are incredibly powerful and allow brands to monitor whatever keywords they desire. For the first time, you have an opportunity to get unfiltered feedback, offered up in real time and without prompting.

If you’re reading this with a questioning mind, and I hope you are, you’re probably thinking: “What happens if that deodorant brand wanted to know what got young women between the ages of 13 and 18 to wear deodorant for the first time? Is it possible to move from monitoring to engaging in order to ask specific questions of specific audiences?” (I love it when you ask questions.)

Let’s respond to your questions by asking three questions:

  • Does this brand have a Facebook Page?
  • Does this brand have the ability to purchase Facebook Ads targeting females between the ages of 13 and 18?
  • Does this brand have the ability to build a campaign soliciting stories through a branded landing page?

If the answer to any of these questions is yes, the brand can take their focus group from 5-7 girls uncomfortably answering questions for money, to thousands of girls answering questions for fun. People will contribute to your market research without expecting payment if you position the ask properly. Less cost, more quality – and high quantities of – information. ROI, my friends.

It’s time to unfocus your focus group.

When she’s not working as a marketing manager for Make Me Social, Mandi Frishman enjoys perusing the internet for mentions of her dog, Emma. During her time studying at The University of Florida, Mandi became convinced in the power of learning through play. She has since committed herself to playing (and learning) all day, every day.


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Black Friday by the Numbers!

Fact: Black Friday is the biggest shopping day of the year. Millions of dollars are spent on ads to get people in the stores and make them aware of the doorbuster deals.

Using foursquare data publicly shared on Twitter we can get an idea of how well some major retailers did this Black Friday. Users that share their Foursquare check-ins on Twitter are a consistent group and as a result statistical patterns can be established. These same users are also giving away branded impressions at no charge.

The 6 Black Friday pushes that were evaluated using Foursquare check-in data were:

Target, Walmart, and Best Buy: These are the obvious 3, every year they expressly go after tech savvy shoppers with their discounted TV’s, video games, and cell phones.

Gap and Kmart: Very different stores with the same strategy: be open when everyone else is closed.

Macy’s and Kohl’s: Both spent a lot of money this year attempting to drum up excitement about their offerings via TV ads.

Sports Authority: Sports Authority actually ran a Foursquare promotion, making for an interesting case study. Every hour they were giving away $500 gift cards to their store via Foursquare. They didn’t broadcast it much other than leveraging their database and they didn’t provide many outrageous deals.

The Question: Which retailer had the biggest spike over their average on Black Friday? 

The baseline: Which brand got the most check-ins?

This data consists of public check-ins within the 5 days of black Friday. Walmart clearly dominates check-ins, with Target a close second. On the surface level it would appear that Target and Walmart are the big winners.

However environmental effects need to be considered:

– Consumer preference

– Technology proficiency of a consumer group for a given brand

– Average Age of the consumer group and corresponding technographic profile

– Income: can the group afford smart phones/smart phone plans?

– Number of distribution centers

In short we need some more significant data to work with….

The next level: Trending- Were there actually any spikes?

This graph is a little more telling. Clearly, there were spikes by all 6 brands on Black Friday. It is also clear that Walmart averages the most check-ins for this sample group. Finally and most importantly for the purposes this analysis, the samples are fairly consistent.  In almost all cases the standard deviation was less than 20% of the mean. Only Macy’s had a Standard Deviation large enough, above 80% of the mean for the 30 days leading up to Black Friday, to create measurement questions/require deeper analysis of outlying data.

This trending graph doesn’t fully explain which brands had the largest percent of success. How much did Walmart or Target actually improve above their daily average on this Black Friday? This graph doesn’t give us that information.

Actual analysis: The mean is an important number statistically, it’s like the foundation of a building. The mean often gives more information about a sample than we care to realize and needs to be expressly included in analysis. Walmart averaged 1305 check-ins shared on Twitter every day for the 30 days leading up to Black Friday, Target averaged 1035, Best Buy averaged 358, Macy’s (adjusted) 238, Gap averaged 86, K-Mart had 76, Sports Authority got 27, and Kohl’s had a very small 14 .

It is important to note that these samples don’t include Black Friday data, which would skew and destroy the sample. As will become apparent later, Black Friday as a set are super-outliers for all brands.

Which brand actually did the best?  

It is interesting that Kohl’s was one of the biggest winners. On Black Friday they  averaged 31 times their normal standard deviation. I would question the base sample size if no other brands were close to multiplying their standard deviations to that extent. However, Best Buy, who had one of the largest, and most consistent, regular samples sizes had a LARGER multiplication of standard deviation. Again these numbers were very normative when compared to the mean against each other. Kohl’s and Best Buy were within .01% of percentage standard deviation against the mean. Both Kohl’s and Best Buy were within 2% of Target’s and Walmart’s standard deviations compared against the mean. Only Macy’s required further analysis, after which the data falls right in line with Walmart and Target. Macy’s averaged around 15 times a normal standard deviation, when points greater than 2 standard deviations (outliers) were excluded from the sampling.

What does this all really mean? 

#1 Apparently this ad worked…

#2 Best Buy is the place to go if you are a tech savvy shopper

#3 Target, Walmart, and Macy’s averaged about 6 times their average check-in traffic on Black Friday. Most likely they had similar foot traffic spikes.

#4 Keeping a store open on Thanksgiving doesn’t generate a tremendous lift. Kmart and Gap both had strong returns, however, both stores were still on the bottom of total Black Friday checkins, and had some of the weakest returns.

#5 A Foursquare promotion doesn’t skew data just because it exists. Sports Authority needed better media support.

Mike Handy has been working in Social Media since Facebook was only for college students. He started his first blog in 1999 when most people were still figuring out this “Internet thing”.  These experiences paired with his background in advertising and data-centric approach provide him with a unique view of social media. When he isn’t working he is probably watching, playing, or doing something hockey related.

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