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Marisa Albanese Oct 13

Art and Data: The New ‘It’ Couple


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In case you haven’t noticed (because you’ve either awoken from a 15-year coma, raised by feral wolves, or a little of both), 2016 is an election year. Don’t worry — I will refrain from any political discourse.

The election did inspire me and two friends to take a day trip to Washington, D.C. to see the sights. We tried to venture to different types of attractions and eventually ended up at the Renwick Galley at the Smithsonian American Art Museum. One of my friends, Amanda, is an art teacher. She also possesses a crazy knowledge of all things art, so I love going to galleries with her.

The Renwick focuses on contemporary craft art — sculptures, pottery and installation pieces. While exploring, I stumbled across Norwood Viviano’s “Global Cities.” On the floor lay separate white panels with black outlines of the continents with the names of major cities geographically highlighted. The panels were arranged to provide an almost seamless view of the map. Above the panels were 29 pieces of blown glass, each a different size and shape. The glass hovered above a specific city.

The size and shape of the glass corresponded with amount of time humans had inhabited the area and how the population had grown or declined. It was a breathtaking sight. An exhibit specialist at the Renwick explained that population data was used to create the blown glass. The piece was meant to showcase the true distribution of populations through the use of a grand visual display.

This piece showed what all data nerds like me feel: Data can be beautiful.

While I stood transfixed, Amanda explained  that artists were beginning to utilize data more in their pieces. I honestly never saw the connection before her statement. Art is, well, art. It can be anything. There are no rules. Data is the exact opposite. It’s regimented and structured. Their marriage, though, has the ability to create understanding for a whole slew of people. Ergo, art is able to unlock the true job of data, which is bringing information to light.

This brings up an intriguing insight. Perhaps things we had a preconceived notion about in marketing bear a second look. Maybe an audience who was perceived as not being receptive to a message should get a deeper dive. A failed campaign re-examined to understand what went

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“Global Cities”

If you ever get a chance to check out the Renwick and this piece, I highly recommend it. You may find it as inspiring as I did. I also recommend taking as many ridiculous pictures as you can in front of the Washington Monument. Why? No real reason, except to possibly annoy everyone around you.

 Marisa Albanese is database marketing analyst at Annodyne.


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Marisa Albanese Oct 6

Win any game with insightful data analytics


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Flyers logo

It’s the most glorious time of the year. Would you like to know why? If you guessed because everything is flavored pumpkin-spice then you are dead wrong. While we’re on the subject, when did we as a culture decide pumpkin-spice was going to take our lives during fall? I feel like one year it just exploded and now here we are.

It’s the most glorious time of year because hockey is back. In one week, the start of the regular season will begin.  As I’ve mentioned in blogs past, my favorite team is the Philadelphia Flyers. Last season was a difficult year for the club, to put it mildly, as they didn’t make it to the playoffs.  When a team fails to reach the post-season, the next few months are spent in deep contemplation by management.

The Flyers were no different. But imagine to my happy surprised when I stumbled upon this article  detailing how Flyers General Manager Ron Hextall (A little trivia – Hextall was the first goalie in NHL history to score a goal) has been relying on advanced player stats to make critical decisions.

The NHL has a tight salary cap. A few years ago, under a different GM, the Flyers signed several players to lengthy and costly contracts. Some were no-brainers, like current Captain and league elite Claude Giroux. Others though have left the team in a bad situation – the inability the move players who aren’t performing. Hextall understood stats only tell half of the story. In order to know the full picture, sleuthing must be done.

The article gives an example of this new way to look at stats with the case of former Flyer defensemen Nick Grossmann. Grossmann had decent stats, particularly his plus/minus rating (if the opposing team scores a goal while you’re in the ice, you get a minus. If your team scores a goal while you’re on the ice, you get a plus). However, once further digging was completed, it revealed Grossmann ranked last among all Flyers defensemen for clearing the puck. This meant he didn’t do a great job of getting the puck out of Flyers end of the ice. The Flyers were paying him at an elite level, which clearly he was not.  In the beginning of the summer, Ron Hextall traded him to Phoenix.

This trade may have never been possible without paying close attention to the details and asking questions. Data can be a treasure hunt and sometimes, you don’t know what you’ll find. In this case, the Flyers discovered they needed to make a move in order to help their defense.

It makes me happy my favorite team is now invoking this methodology. May Lord Stanley’s Cup come back to Philadelphia.

Marisa Albanese is database marketing analyst at Annodyne.


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Marisa Albanese Jul 23

In Search of a More Perfect Algorithm…


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Today, we’re going to discuss erroneous algorithms in machine learning (this term is used to describe computer-based predictive analytics). To set up the context, I’m going to share a little something I learned back in my political science days as an undergrad. OK, something I learned besides where on campus was the best place to take a nap. (For any Temple University students — SAC, upper level, near the conference rooms. You’re welcome.) There is a central question nearly everyone has asked within the poli sci realm: Is there a perfect form of government? Short answer: No. I will not bore everyone to tears by detailing why not but there is a very simplistic way to understand this dilemma: Government was created by people, people are flawed and, therefore, government will naturally be flawed. Side note: Please do not turn the comments section into a political thunderdome over this proclamation.

This brings me back to the topic of algorithms. Recently, The New York Times published an article that pulled from various studies completed about bias in online marketing ads based on algorithms. An algorithm is a formula. It’s what Google uses when a person types in “best running shoes for beginners” to produce search results. A person creates algorithms, using the principles of predictive analytics, usually some calculus and a dash of black magic. Machines, however, learn from human behavior and adjust algorithms over time. This is known as a learned algorithm.

The Times article gives a great example. When you type into Google or Bing “best running shoes” it auto-completes the thought. But the crux of the article was how search results are being corrupted by the negative, and deeply stereotypical, side of society. For instance, ads targeting applicants for high-paying executive jobs appeared in the search results for men over double the rate as they did for women. A separate study revealed ads for arrest records appearing in searches for African-American-centric names.

People are leaning on machine learning data and calculations because we see this way as the ultimate truth. Machines have no prejudice and will just report the facts. But if they are implanted with bad search algorithms, not necessary created with malice but lack of social understanding, this is like building a house on a cracked foundation.

This sets up the discussion “Oh my God, this is how Skynet started” (this is a reference to the storyline for the “Terminator” series). The machines are learning without us! Artificial intelligence! Before you start building that underground bunker, keep in mind a few things. For starters, data scientists are still trying to understand this phenomenon. It has been suggested if an algorithm shows signs of this behavior to rewrite it. These signs would be present during testing. Ah, yes! That magical thing I suggested a few blogs ago: Always create a test plan.

Test your algorithms. Then test them again. Also, I’m going to drop some additional poli sci knowledge. Niccolo Machiavelli, who wrote The Prince, did not fake his own death. He simply wrote about it. So to everyone who thinks Tupac Shakur faked his own death because he named one of his posthumous albums Machiavelli, this is wrong. But “California Love” is still an awesome song.

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This cat is re-creating my most common activity during college.

 Marisa Albanese is database marketing analyst at Annodyne.


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Marisa Albanese Jun 9

Data Transparency is a Really Big Deal


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I consider myself many things — dedicated Flyers fan, irrationally fearful of monkey attacks, the most fabulous person you’ll ever meet, and wickedly humble. But I am foremost a massive proponent of data transparency.

So when I read this article in The New York Times recently, I was appalled. The article is about Michael LaCour, a political science grad student at UCLA, who had a fascinating question: Can canvassers with a personal stake in a political issue directly change the opinion of a voter?

He picked the best time to study this query — it was 2012 and California was in the midst of trying to legalize same-sex marriage. He decided to study canvassers who self-identified as being part of the LGBTQ community and measure how voters responded after their interactions.

A study of this magnitude takes a few things, starting with funding and clout. Mr. LaCour found the latter in Dr. Donald P. Green, the Godfather of modern policy on field experiments in political campaigns. In 2013, their study was published in the journal Science.

This is why it’s kind of a big deal. I’ve spent my entire academic career studying the social sciences (my undergrad is in political science,) and I can attest to mainstream science giving no credence to the social sciences. The major reason is some social science theories cannot be properly “tested” by the scientific method.  I won’t annoy everyone with my standard “there are other ways to test a theory” tirade (ahem — Meta-Policy or Third Wave Evaluation approach — ahem). To present such a landmark study in such a prestigious journal as a graduate student? It’s the academic equivalent of when Sidney Crosby became eligible for the NHL draft — everyone would want you.

Dr. Green agreed to co-author the study because of the importance and timeliness of the subject matter. Mr. LaCour also assured Dr. Green his funding was solid, although Dr. Green never did find out where Mr. LaCour secured said funding. Also a bit perplexing is the fact no one, not even Dr. Green, saw Mr. LaCour’s raw data.

The paper published in Science reported a 12 percent response rate among participants. That’s a fairly high response rate for something that is voluntary and multifaceted. Mr. LaCour did report he was paying participants, which would account for the increased numbers. Paying participants is a standard data collection practice and something widely used in marketing data collection. However, when fellow researchers tried to replicate the same results in a similar political setting in Florida, they yielded only a 3 percent response rate.

Due to this failure to replicate, Mr. LaCour’s raw data was requested by several people. He claimed he deleted his data files to protect the identity of respondents. For the analysis projects I have worked on for Montgomery County Community College, I am given raw prospective data. This contains sensitive information. I am cognizant of this fact and encrypt my files. I backup as well. I also have an open-door policy about my raw data, particularly with my colleague Simon Lindsay, who acts as my Svengali during analysis projects. So, frankly, I don’t buy Mr. LaCour’s excuse, and I find it downright upsetting.

The article suggests Mr. LaCour really wanted his theory to be right, and it may have caused him to make some career-limiting decisions in the process. It also may have sullied the reputation of a well-respected scholar (who should have been more proactive but readily admits it in hindsight). This further illegitimatizes social science research within the scientific community.

Transparency should be a top priority when conducting any analysis, particularly with surveys. Data tells a story, and sometimes it may not tell a story your client would like to hear. However, it is your responsibility to hold yourself accountable. If someone does call into question information, that’s why the raw data is there. Have I made mistakes in my calculations? Yes. But I always had someone there to vet my data before it was presented. I cannot stress the importance of data vetting. But vetting cannot be effective unless the entire picture is shown.

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I’m on to you, monkey! I know you want to randomly attack me.

Marisa Albanese is database marketing analyst at Annodyne.


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Marisa Albanese May 5

In-Security Issues


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I have a very good friend named Denise whom I’ve known since we were 8 years old. Dee and I have a long, tangled history of incidents and adventures, some of which were amazing and others not worth repeating in polite company. When we were 11 years old, Denise got the Internet. A little context, this was 1996, when the Internet was still dial-up and everyone got those sweet AOL CDs offering free Internet. Remember when we had to pay by the hour for the Internet? Dark and evil times, my friends.

Anyway, during one of our marathon phone conversations, Dee was regaling me with tales of Internet browsing. We decided to create a Yahoo Geo-Cities page (oh yeah, this was real old school). Here’s how the conversation went down:

Denise: “Aren’t the Spice Girls amazing? Hey, Macarena!”

Me: “Dee, too legit! But we need to focus. I stopped reading YM for this.”

Denise: “Sorry. What should we call our page?”

Me: “Hmmmm. How about The Web Page of Marisa Albanese and Denise Clarke?”

Denise: “No! You can’t put your name on the Internet! That’s how people find out where you live!”

I may have paraphrased the beginning of the conversation, but I clearly remember Dee having a conniption over my title suggestion. While we can all chuckle over this now, tween Denise was offering some sage wisdom — data security is an ongoing problem.

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This was Denise back in the ’90s. After this blog, post I’m pretty sure our 22-year friendship will be history.

In February  2014, the University of Maryland’s IT department detected a breach in one of its databases. It was revealed a hacker had accessed the personal information of 300,000 student and faculty records. These records went back to 1998 and contained names, addresses, and Social Security numbers. The university stated the security around its databases was strong and that it was a “sophisticated” attack. They offered victims a free year of credit monitoring and the president of the university, Dr. Wallace Loh, even posted a video on YouTube providing updates on the data hack. Everything was under control.

Then David Helkowski made a post on Reddit.

Mr. Helkowski worked as an IT security consultant for the university. Over the course of a year, he discovered several “backdoors” on various databases containing student and faculty information. A backdoor is when someone hacks into a system and creates a way for themselves to access it. The hacker can get in and out quickly, without drawing attention. (Backdoors are created for large databases for legitimate IT purposes, too. Do not get concerned if one of your analysts uses this term.) If what Mr. Helkowski is alleging is true, that means the university’s databases had been previously hacked.

Then the February breach occurred, and Mr. Helkowski was not happy with how his warnings had fallen on deaf ears. So, he hacked into the newly “secure” database and posted Dr. Loh’s Social Security number on Reddit. He then bragged about what he did to his co-workers via the gamer site Steam (so there was a nice transcript of his conversation). He claims he did it to prove how unsecured the database was. I can’t wait for the film version of this to be made. I hope they get Ryan Gosling to play David Helkowski because God knows that man needs to be seen more.

All joking aside, what he did was stupid (and got him in trouble with the FBI because hacking is a federal crime) but he made some solid points. He also pointed out something very troubling — college databases are deep troughs brimming with valuable personal information, and they can be very easy to dismantle.

What’s the takeaway from all of this? Data security is a complex business. Take every necessary step when securing a database. If you use an IT security professional, which I highly recommend, take his or her recommendations seriously. Get educated. I truly believe the reason why these things happen is a lack of understanding. IT has its own language, but understanding what’s good and what’s bad isn’t hard. So invest in data security.

Or you could use the money to hire a PR rep to describe a data breach as a sophisticated test. Your choice.

Marisa Albanese is database marketing analyst at Annodyne.


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Darcy Grabenstein Apr 1

Don’t Be Fooled By Metrics – Focus on Quality, Not Quantity


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Jester

Every year, my family tries to pull off an April Fools’ Day joke with other family members and friends. Last year, my son (it helps that he’s a lawyer) drew up a very detailed eviction letter from his condo association (including the letterhead) and sent it to his roommates. The letter cited various lease violations, such as having a grill on the balcony (guilty as charged). His roommates fell for it, hook, line and sinker.

When it comes to lead generation, however, misinterpretation of metrics is no laughing matter. You’re only fooling yourself if you take the results at face value.

It’s important not to be shortsighted when analyzing your organization’s leads. The tendency is to look at immediate results, make a determination as to the lead’s quality, and move on to the next lead. In doing so, you may be bypassing leads that could convert down the road.

When tracking leads, you must look at them throughout the marketing lifecycle. Only then will you be able to accurately classify them as poor or promising prospects.

Another pitfall that many marketers fall into is the numbers game. If you’re running a promotion and generate a huge number of leads, don’t consider it a success. You’ve got to weed out the dead-end leads first. Once you do, you’ll then be able to follow up on the solid leads and calculate conversions. That’s what determines the true success of any campaign.

You’ve also got to take into consideration the goal of your campaign. Is it to build brand awareness? Grow your database? A sweepstakes may be great for brand building, but if you’re using it to grow your database, think again. You may be surprised at how many new email “subscribers” unsubscribe once the sweepstakes is over.

At Annodyne, we emphasize the importance of lead scoring with our clients. Using our proprietary Annotrak™ technology, we help clients track and manage leads to determine the best prospects and reveal the marketing channels they use. By distinguishing “hot” leads from “cooler” ones, clients can make the best use of their time, following up on the most promising leads.

Don’t be foolish. Analyze your data carefully, then implement the campaign changes necessary to optimize your lead generation and conversion.

Darcy Grabenstein is senior copywriter at Annodyne.

photo credit: osseous via photopin


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Marisa Albanese Mar 3

Data Segmentation is the Bee’s Knees at SXSW


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In March, two big events will happen – the opening of the SXSW Music and Arts festival in Austin, TX, and my 30th birthday (March 13, mark your calendars). I’ll send a link to my Amazon Wish List to anyone who is interested (hint, hint — I’m a devoted fan of the Philadelphia Flyers and could really use a Sean Couturier jersey).

I visited the SXSW Facebook page to get information on speakers, performers and the planned events. Before I begin, I need to point out I am not being paid by SXSW to say any of this. If SXSW wanted to pay me, though, I would not be opposed. The bands assembled are pretty amazing. Vanessa Bayer (one of my favorite SNL performers) will be hosting the SXSW Film Awards and, oh yeah, a panel discussion on the economics of celebrity culture with Paul Krugman and Win Butler, the lead singer of Arcade Fire. This panel should be renamed “People who Marisa Albanese must have dinner with before she dies.”

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This was me as I was reading SXSW’s Facebook Page.

Due to my age, general interests and social media habits, I know I’m part of the target audience for SXSW. But I put on my data analyst hat and thought, “How are they measuring who exactly is coming to SXSW?” Since the festival happens over a few weeks, with so many events, you cannot measure if someone is going to SXSW. You would have to measure what events people were planning on attending.

Apparently, the organizers of SXSW had the same thought process. They employed the help of a data analysis company called Umbel, based in Austin. By developing a special RSVP tool for SXSW, Umbel was able to produce audience segments based on genomes (online profiles). You can read all about it here. Event organizers were able to see who made up their audience and what their interests were. Most importantly, the audience can be segmented by any number of variables. For an event hosted by an independent record label, one could segment the audience by those attending to see specific artists or general interest in indie music. Genomes can contain geographical locations and email addresses. Let’s say the same record label is hosting an event in Seattle. Their data crunchers can access the genome data from SXSW, filter anyone who listed their home city as Seattle (and areas within driving distance), and send out specific emails based on their interest.

You’re getting goosebumps, right? Data is sexy.

This reminds me of what the Project Horizons Office is doing with analyzing prospective students who are interested in Montgomery County Community College. We are segmenting by specific variables — gender, age, location and program of interest. Through this, we drill down. We have found a strong correlation between female prospective students and an interest in health sciences. From trying to get people to attend an event or to enroll in college — data segmenting is a valuable tool that can easily be utilized.

Also, SXSW is hosting several big data information panels ranging from its use in business, the music industry and healthcare. Umbel is hosting a separate panel today on converting fans into customers through data analysis. And I will be patiently waiting for my Couturier jersey.

Marisa Albanese is database marketing analyst at Annodyne.


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Marisa Albanese Feb 13

Love, Community College Style


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Once upon a time, in a land not so far away from Annodyne, lived a young girl. This girl knew she wanted to gain more knowledge. She worked really hard at her studies and was accepted into a big, fancy university. The girl was so happy!

But then, the evil troll of financial reality came by and said, “Foolish girl! Do you have any idea how much this big, fancy university is going to cost!?”

And the girl was sad because the evil troll was right; the big, fancy university was going to be a small fortune. But the girl was lucky because, just as she became forlorn, the fairy Godmother swooped in and said, “You there, being forlorn, just go to Montgomery County Community College! You’ll get a quality education at an affordable price.”

The girl, for once, paid attention and did just that. And she lived happily ever after.

The story you just read is true and that young girl is me. Shocker!

This is my humorous way of detailing why I love my job – because I get to give back to the place that gave me so much. Like a vast majority of young people seeking a higher education, cost was a high concern for me. I turned to Montgomery County Community College because it was the cost-effective choice.

But I got a bit of a surprise; I fell in love with the College. I had professors who cared about me, advisors who always went the extra mile, and I received some great support both academically and personally. I also was pretty active socially. You’re looking at a former treasurer of the Student Government Association. Yes, contain yourselves.

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This is me on the day I graduated from the College in May 2006.

It was at Montgomery County Community College that I discovered how much I loved research. This passion carried over to my undergraduate and eventually graduate studies. Montgomery County Community College helped me lay the foundation, through academic exploration, for my future career as an analyst. A career that has taken me back to the place where it all started. Now I get to use the same skills the College once helped me hone to give back to both current and future students. Some would call me a hero, which I totally am, but this isn’t the time or place.

This carries into my work and commitment to not only the College but to all of our clients. Annodyne helps institutions reach people so they can better their lives. This is something that gives everyone here immense pride. Also, my experience as a former student gives a new perspective to the work the Project Horizons Office is completing.

So I guess this girl really did live happily ever after. OK, that may be taking it too far. Let’s just say I’m very fortunate and will continue to work tirelessly to retain said fortune.

Marisa Albanese is database marketing analyst at Annodyne.


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Marisa Albanese Jan 9

Back to the Future: Predictive Analytics Edition


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This year will mark of 30th anniversary of the classic film Back to the Future. I think this presents the perfect opportunity to talk about two things: how predictive analytics is the best trend ever and my anger over the lack of hoverboards. More on the hoverboards later.

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Predictive analytics sounds a bit mysterious. I’m going to take the mystery out of it. It’s analyzing data to make healthy predictions about future trends. If used correctly, predictive analytics can be frighteningly accurate. Want to see this in action? Take a look at the Target example. To those in the TLDR category, I’ll summarize – Target data analysts studied the purchasing habits of female customers on the company’s baby registry. They compared this data against female customers not on the baby registry. Using the information, they are now able to catalog where a woman is in her pregnancy based off purchases and send her weekly flyers highlighting these products. This information is so accurate that it informed a man his teenage daughter was pregnant, based on the flyer mailed to her, before she did.

The vast majority of predictive analytics does not have the 1984 quality like I just described. But it can we very useful when looking at something like student enrollment data. My colleague Simon Lindsay and I are doing this right now. We’re working with MCCC on different ways to present data. One such way is generating regression models with current and past enrollment numbers to predict three things: best case, worst case, and most likely case scenarios. The best thing about using a regression model is it can be updated in real time. As you obtain more present data, the numbers produced for future trends become more accurate.

In using predictive analytics this way, we can determine if the College will meet their enrollment quota well before the end of the semester. How great is that? Instead of being reactive, the College can now become more proactive. This tool brings me back to the subject at hand – we have software to use the past to see into the future. So, we’re going back to get the future. Get it? Don’t give me that look, I thought it was funny.

Any organization can benefit from this type of analysis work. I would love to hear how you have used this for various projects. Also, does it annoy anyone else we don’t have hoverboards? I can turn on the lights in my house from my cell phone but I can’t defy gravity?

HOVERBOARD

 Marisa Albanese is database marketing analyst at Annodyne.


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Marisa Albanese Dec 4

New Year’s Resolutions – Expand Annodyne’s Analytical Capabilities and Sign Up for a Yoga Class


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December has just begun and I’m already thinking about my New Year’s resolutions. It’s the analyst in me; I’m always assessing a situation, identifying the problems, and working out a viable solution. As you may have guessed, this makes me a blast at dinner parties. But it’s also what led me to Annodyne.

I was brought on board to help Annodyne engage in a long-term project with Montgomery County Community College regarding the enrollment and retention of current and potential students. Annodyne has maintained a successful relationship with the College, providing SEM and SEO services. But the College recognized it needed to fully understand the needs of its students in order to progress as a top-notch educational institution.

The College has the data needed to find the solution to this challenge. It turned to Annodyne to help sort it out. This was a first for Annodyne. The agency determined someone was needed to dedicate the bulk of his/her energy to sorting, cataloging, reporting and providing data feedback. Someone dynamic, engaging, analytical, with a superior intellect. Well, they couldn’t find that person and instead got me.

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There may be a question of why this type of research is even essential. Over the past several years, there has been an increased examination of the value of a college education. Students are asking themselves, “Is college really worth it?” Colleges are no longer marketing just the academic experience. On a recent trip to New York, I passed this billboard on the New Jersey Turnpike for Neumann University.

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It caught my attention. There is not one mention of program offerings or a beautiful shot of the campus surrounded by sun-burnt fall foliage. It’s just about the affordability of the college and a very happy student who isn’t blowing through her parents’ retirement fund. How did Neumann know this would be effective?

Analysis! Straight up, hardcore data analysis.

Back to my resolution. In joining Annodyne, I came to understand something. Within the marketing industry, you either evolve or perish. Annodyne saw the chance to pioneer an entirely new specialty and embraced it with vigor. Over the course of the next year, my resolution is to take a page from this strategy and focus on two things: analyzing the college’s data to create comprehensive student profiles and crafting a case study for Annodyne to use with future clients.

Has your organization used an analyst for complex data work? Tell me your experiences. Oh, and if anyone could recommend an intro yoga class in the lower Montgomery County area, that would be great, too.

 Marisa Albanese is database marketing analyst at Annodyne.


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