Predicting my future

Posted on December 6, 2011 by Rebecca Denison

I have life-altering, ground-shaking news. Again.

OK, so I’m being dramatic, but I’m incredibly excited about this. And I have been dying to share this news with you: I’m going back to school!

Starting just a few days after the New Year, I will begin a masters program at DePaul University in Chicago. For the next two years, I will be studying predictive analytics through the College of Computing and Digital Media.

Lucky for me, the CDM campus is in the Loop, just a few blocks from the Digitas office, and a lot of my courses will be available online, too. I’m hoping to become one of those crazy people who can easily balance a full-time job, classes, course work and some semblance of a social life. We shall see.

As excited as I am, I’d be lying if I said I wasn’t absolutely terrified at the same time. I haven’t had to study or do homework for more than two years, and I’m nervous about getting back on that horse. I’ve never studied anything to do with computers, and nearly one half of my courses will be in computer science. I’m worried about how busy I may become. I’m afraid to fail.

But in the end, it will be worth it. This will help add skills and knowledge I desperately need to continue growing. I can’t tell you how many times since joining Ken Burbary at Digitas I’ve found myself saying, “Wouldn’t it be so cool if we could only….”

With my masters under my belt, I’m hoping we won’t have to wonder anymore. We’ll just be able to do it. I’ll be able to tackle far more problems and create more complex and integrated solutions.

I want y’all to know, I will still try my best to write as much as I can, but I’m guessing you’ll notice some silence around finals time each quarter. Or maybe an increase around midterms as I try to procrastinate.

Lastly, I want to give a big thank you to a few people who have made this possible. I’m so thrilled to take on yet another challenge, and I wouldn’t be able to do it without the constant love and support from my mama, daddy and wonderful gent. I also wouldn’t have any chance to take on course and homework if I didn’t have an incredibly supportive and understanding boss, so big thanks to Ken, too! And I owe a thank you to my good friend Morgan for keeping me calm and serving as my financial planner.

Posted in Digitas, Life as a senior analyst, Measurement | 16 Comments

Planning for proper attribution – how far is too far?

Posted on October 19, 2011 by Rebecca Denison

The other day I was thinking about attribution. Most folks these days agree that last-click attribution isn’t the best practice, but we’re still struggling to make sense of it. How do we make sure that the proper pieces of the marketing mix receive credit?

I stared to wonder if detailed planning could help solve the problem. If you’re using online display ads to drive traffic to your website, you can use something like Google Analytics to track how different ads are driving traffic. If you use some paid tools, you can even see traffic on a placement level.

But maybe you’re running TV commercials at the same time and you want to capture traffic from those ads, too. Maybe you give a specific URL in the commercial. But that tells you how much traffic comes from all TV. What if all of it is really coming from one spot on one channel? Can you really give different URLs on each spot to give proper attribution?

I know I’m thinking about this too much, and I’m thinking too small. But I can’t help it. How granular do you go? How many layers do you add before the additional value is no longer worth the effort?

Posted in Life as a senior analyst, Measurement | Tagged , , , , | Leave a comment

Has your memory been Googled?

Posted on October 12, 2011 by Rebecca Denison

This infographic about how Google affects our memory really got my mind turning. It claims that our ability to find endless information instantly on the Internet (specifically Google) has diminished our ability to form memories and recall information.

The theory is if we don’t care enough to put in the legwork to research something, odds are we won’t remember it. We’ll just look to Google if we ever need to remember.

I hope this isn’t true. I’d like to believe it’s not true for me, at least to a certain extent.

Certain topics are definitely easily forgotten, and I have found myself searching for the same things over and over on Google. But are these things truly important? Likely not. Would I remember them if I had to search in a book? I don’t know.

If I care so little about information that I’m willing to forget it and let Google remind me, would I even be willing to put in the effort to find it offline? I would guess not. I can instantly search for every Starbucks in the city of Chicago, but would I ever do the legwork for this information? No. Because it’s just not that important to me.

I’d like to believe that information and knowledge I care about, I will remember no matter how I learn it. If I Google it or read it in a book, newspaper or research abstract, if it strikes me as odd, funny or fascinating, I’ll bet I remember it just fine.

After all, I tend to remember important facts that my mother said to me just as well as something I’ve read in a book. And isn’t asking my mother far easier than digging through a book? Maybe I’m not fully understanding the distinction between how these memories are formed, biologically speaking.

It would be interesting to see how our brains function when we read a book versus when we search on Google for the same fact. I wonder if they could tell how we were forming memories and if there was a great difference.

What do you think? Has Google affected the way you remember the little things? Have you found that you struggle to remember important details because of the way you learned them?

Posted in Life as a senior analyst | Tagged , , | Leave a comment

Searchmetrics helps bridge the social, SEO gap

Posted on September 21, 2011 by Rebecca Denison

Last week, I was lucky enough to get a sneak peek of Searchmetrics’ newest release: Searchmetrics Essentials. I also had the pleasure to speak with Searchmetric’s CEO Horst Joepen. He gave me a look at the new tool and it capabilities, and he was great about answering my questions (even the silly ones).

Searchmetrics already has a suite of tools to help analyze search, but the new Essentials tool will bring search and social together into one dashboard. Metrics like SEO visibility (visitors by search) can be compared or correlated to social visibility of branded content (reach of social mentions, such as tweets, Facebook shares, etc.).

Social visibility measures the number of folks who were exposed to a link to brand-owned content, not just mentions of the brand. Keep in mind that just because someone with 10,000 followers includes a link to branded content, Essentials will count all 10,000 followers in their social visibility metric even though we all know far fewer folks actually saw the tweet, let alone clicked the link.

While social visibility is not a perfect measure of the reach of branded content, the real value lies with the ability to see this data side-by-side with search metrics. This can easily be used as an index to understand how social media mentions may be helping drive higher SEO visibility. Ideally we’d want to be able to measure the total number of clicks, but that’s realistic with this kind of tool.

But if you see that your social visibility is increasing, followed shortly thereafter by SEO visibility, you can make a connection. It’s generally a safe bet that if more people have the opportunity to see or click a link to branded content, more folks will actually click through, right? Well Essentials can help you better understand how social is driving clicks and lifting SEO.

Another caveat to this data stems from Essentials ability to only pull data from Facebook, Twitter, LinkedIn, Google+, Delicious and StumbleUpon. The current suite of solutions is able to analyze and monitoring more than 100 search engines in 30 countries. The social visibility metric will touch on the biggest networks, but keep in mind the limitations as you work with different brands or campaigns.

The user interface was sleek and easy-to-use, and I’m honestly excited to see it again when it’s live. I won’t claim that this is an end-all solution (no tool is), but it will be really interesting to see search and social data integrated in this way.

Have you used Searchmetrics other solutions? What are your overall thoughts? Will you use Essentials?

Posted in Measurement, Search, Social Media | Tagged , , , , , | 1 Comment

The best social media measurement tool: the analyst

Posted on September 19, 2011 by Rebecca Denison

With all of the discussion lately about which social media monitoring and measurement tools to use, which ones not to use or just how to go about choosing, it seems we’ve all forgotten the biggest key to successful measurement: the analyst.

Just the other day I was reading a summary of a report on the state of Web analytics today, and one quote really stood out to me in regards to measurement tools:

“In his view, web analytics vendors have focused on making systems appeal to people who don’t really work with web analytics on a day-to-day basis. There has been too much emphasis on pretty pictures, ease of deployment, and finding ways to justify the investment. These are all signs of products that must appeal to people who won’t use the products, don’t see the point, and don’t really understand the task that the software is designed for. If you have to sell to such people, what else can you do but focus on stuff that doesn’t require any skill to understand, such as fancy graphics?”

Even the best technology and most thorough tools will never be valuable without an analyst to use them. More often than not, I find myself using data pulled from one tool or another, but I rarely use the pretty graphs or other functionality. It’s just too hard to find insights that way. I find insights by digging through the raw data and manipulating it the way I want to, not the way some interface allows me to.

That said, there are some tools with which I can manipulate data more than others, and I tend to prefer these to others. But there is not perfect solution out there. Not yet.

I’m as guilty as the next guy (or more so) of nit picking about which tools really work and which don’t. But let’s all knock it off. For each new situation, campaign or project, there will likely be a different tool that provides the most relevant data. In every case, the most valuable and complete tool will always be the analyst.

Let’s make a pact to stop fighting, OK? We each have our own preferences and bias, but can we all agree that no tool will ever replace humans?

Posted in Life as a senior analyst, Measurement, Social Media | Tagged , , , , , , | 2 Comments

Getting around your attribution problem

Posted on September 14, 2011 by Rebecca Denison

I’ve come to the conclusion that attribution is measurement’s only unsolvable problem. There is no currently process to reliably or accurately give proper attribution. But that doesn’t mean you shouldn’t try to measure. It just means you have to skirt attribution by using indirect measures to prove value.

 

Control what you can. You can’t control word of mouth or social media, but you can control your own paid advertising and owned channels. When it’s time to find out the value of your Twitter account, for example, set up a controlled experiment.

  • Keep as many other variables as you can constant. Buy the same ad space and paid searches. Run the same TV spots. Post on the same days at the same time on your Facebook page and respond in the same fashion to complaints or questions. Be as rigid as possible (you won’t be perfect, and that’s OK).
  • Be consistent for three distinct periods of time: pre-test, test, post-test. Your test can be anything. A Twitter contest or other promotion. Maybe you will just strive to be more active on Twitter during your test period. It’s up to you.
  • Compare results for your three different time periods. Your measures will vary depending on your goals and how you define success. But overall you’re looking to decipher how your Twitter activity affected success. It won’t be perfect as you won’t be able to definitively prove that your increased engagement really drove all those extra sales, but it will be a much more compelling argument this way.

Dive into the weeds. There is a lot of data to be had, and there is no reason to collect all of it just because you can. But collecting more than you may initially think you need can be beneficial in the long run by helping you connect the dots and show value more definitively.

  • Don’t go overboard. Don’t sign up for every free and paid tool to get every single piece of data imaginable. Let me say that again: don’t try to capture everything.
  • That said, widen your scope a bit. If you’re building a new Twitter presence, for example, don’t just look at the most common metrics. Followers are important, as are retweets and mentions. But look beyond these metrics, too. Identify those you interact with most, look at who else they talk to and what they talk about. Try to understand what drives new followers. Do you notice a handful of new followers each time you interact with certain people?
  • Track small pieces of data around your campaign that may seem erroneous. Don’t take up too much time, but you never know when you’ll find yourself thinking, “I wish I’d kept track of how Twitter activity varies by day of the week!” Or something like that. You get the idea.
  • The more data you have, the easier you can make connections and draw conclusions without necessarily needing direct attribution. Remembering nuances and assumptions is important, but having more data from which to derive value doesn’t hurt.

Label everything you can. This can be specific to Web analytics, but keep it in mind for all analysis. Label and categorize all data, as much as you can. The more you can connect individual data and results with campaigns, tactics or goals, the more easily you can show success.

  • Use tags for everything. If you’re using Web analytics, add tags and make them as specific as you can without confusing yourself. This can help you to understand later whether activity on Facebook or Twitter drove more (or different) traffic to other Web properties.
  • Shorten links with a service like bit.ly and use a different shortened link like you would tags. If you share the same information on different channels, use a different link for each to analyze the difference in how consumers interact with the information across the Web. When sharing different types of information, different campaigns, or even when using different types of headlines, use a new link. Get as granular as you think will help.
  • This ties back to diving into the weeds, but include meta-data where you can. If you’re keeping track of all retweets on Twitter, for example, don’t just track a number. Collect each individual tweet as well as information about who retweeted you like their name, sex and location (as available). Again, keep this information separated by campaign or tactic.

 

There are so many other solutions to attribution, and until we can directly connect all aspects of our activity, we have to make do with what we’ve got. How do you deal with your attribution problem? What’s your favorite method to measure?

Posted in Life as a senior analyst, Measurement | Tagged , , , , , , , , | Leave a comment

Reporting vs. Analyzing: Know the difference

Posted on August 26, 2011 by Rebecca Denison

I just wanted to get one thing clear: reporting and analyzing do not mean the same thing. While both have to do with measurement (or monitoring), they have very different definitions.

More and more frequently I’m seeing blog posts and case studies which include social media or data “analysis.” What follows tends to be a list of metrics or observations from a data set. Let me give an example:

  • There were 1,000 check-ins at the restaurant this month.
  • Twitter followers increased 10% to 5,460 this month.
  • The Facebook community is comprised largely of women aged 45+.

These are metrics and observations being reported. It’s quite honestly simple regurgitation in most cases. Sometimes a little bit of math is required to get there, but these are reported facts and figures. This is not data analysis.

True analysis takes facts, figures, numbers, whatever you want to call them and tells you what that means. Analysis answers the questions, “so what?” or “why?” wheras reporting more often than not just tells me, “what?”

Analysis often includes context and ties multiple observations together to give a more complete picture. Instead of reporting each fact as a singular data point, connections are made and related facts are grouped to show significance. Reporting tells me what it is; analysis tells me what it means. Here’s an example:

  • There were 1,000 check-ins at the restaurant this month even though we have stopped offering a discount for each check-in. This indicates our consumers may be likely to use location-based services without an incentive.
  • Twitter followers increased 10% to 5,460 this month compared with 45% growth last month. As our #FantasticGiveaway promotion ended and mentions on Twitter fell, it is likely less visibility has caused this decline in follower acquisition.
  • The Facebook community is comprised largely of women aged 45+, which is slightly older than our core target audience. We should consider adjusting content to appeal more broadly to women in this age group.

Am I being too picky here? I feel it’s an important distinction to be made. Reporting has its value, but drawing conclusions and providing analysis are also valuable (in a totally different way).

Do you see a difference? Or is it all semantics?

Posted in Life as a senior analyst, Measurement | Tagged , , , , | 1 Comment

Is the whole greater than the sum of its parts in data analysis?

Posted on August 18, 2011 by Rebecca Denison

When we talk about social media analysis or monitoring, most of us think of something along the same lines. Analyzing mentions in social media to try to find insights, sales leads and the like. The focus is on finding mentions of a brand or its products in channels like Facebook, Twitter, blogs and forums.

There a few, however, already thinking up ways to use social media data for a very different purpose. Walmart is planning to use your social media habits to provide better and more relevant product recommendations. If I buy the latest album from Bob Schneider from Walmart.com, and you Google “top new music releases,” Walmart wants to show you an ad recommending the album your friend (me) just bought. Cool (and creepy), right?

The next big wave in social media data analysis is coming, and it has little to do with brand mentions. It has everything to do with you, the consumer. It would seem the next step is to move away from brand-focused search to customer-centric data aggregation.

There would be far more value in a brand mention if you also knew what brands the mention-er liked on Facebook or who their friend’s recommend to them. While we can derive a great deal of insight from pouring over singular mentions of our brand or our product, there is so much more to be learned from understanding the whole consumer, not the whole conversation.

Think about it this way: if I say, “I have to hand it to Duke, they’ve got a great squad this year!” does that mean more to you than if a Duke alum says it? (For the record, I would never say such a thing. Go Heels!)

If I’m known for disliking a specific brand or loving a specific brand, mentioning a competitor should have much more weight and meaning than a person who has never been part of the conversation before. In today’s world, it’s hard to connect those dots.

I’m sure this is someone out there developing a great new (creepy) tool that will let me not only see who is talking about my brand but follow those folks every move. And I cannot wait for the day that I will be able to use those kinds of insights in my work.

We are whole people. We are more than just singular mentions, and I can’t wait to learn more about the folks who are talking about brands and companies I care about. Imagine the kind of knowledge you will be able to learn.

Do you focus on mentions or do you focus on people? Have you considered mining and aggregating data this way?

Posted in Life as a senior analyst, Measurement | Tagged , , , , , , | 4 Comments

How Klout could make +K better (and less game-able)

Posted on June 21, 2011 by Rebecca Denison


I know what you’re thinking. I’ve never really had a nice word to say about Klout. And I’ve been too critical of them.

Klout is trying to measure something that is inherently impossible to quantify. But they are giving us all a head start, and their algorithm and methods are pretty good. They’re not perfect, and I still would never recommend using Klout as an end-all for anything, but they’re not evil or anything. :)

With the release of +K, Klout added a new layer for influence measurement. Now your peers can help boost your influence on certain topics. Topical relevance is extremely important when measuring influence, but does this method really do what it needs to do? It’s a great idea in theory, but in practice there is a chance people will game the system.

If you give me a +K on rainbows, I’ll give you a +K, too! (No matter that I’ve never influenced you on anything, let alone rainbows.)

One way to improve the +K system and maybe discourage gaming would be to make one +K more valuable depending on who gives it. If someone influential in a topic gives you a +K for that topic, that should mean more than a +K from someone random, right?

The more you influence other influencers, the more influential you are. That is a confusing sentence, but it’s true!

If I’m one of the foremost influencers on rainbows, then if I give you a +K on rainbows, that must mean you are also pretty darn influential. If your mom gives you a +K, it may not carry the same value, but it will still boost your influence.

Those who may not be as well-known, but have a small and loyal audience will still get extra points for every +K they receive. And  in theory, these +K’s should help to propel you and get you attention from the so-called “big guys.”

That’s just my theory, though. How this could be accomplished and built into the current algorithm, I really don’t know. But I think it would help.

What do you think? How would you improve Klout or the new +K system?

Posted in Influence, Measurement, Social Media, Social media influence | 9 Comments

PR measurement was never meant to be an exclusive club

Posted on June 16, 2011 by Rebecca Denison

Originally posted on PRBreakfastClub.

OK, maybe I have a biased opinion about this, but I don’t think PR measurement was ever intended to be an exclusive club.

I remember learning about measurement during the first week of my first PR course in college. We even learned an acronym that included research and measurement: RACE (Research, Action, Communication and Evaluation). Research and evaluation were engrained in me right off the bat.

Perhaps this made me wrongly assume that measurement was already an integral part of the PR industry, and I’m still continually surprised by how few professionals talk about it.

Not to say there aren’t a handful of incredibly knowledgeable folks out there who always share amazing thoughts and advice, but c’mon, y’all!

I know it’s been said time and again, but measurement has to be a part of each and every campaign or project. Whether it’s as simple as tracking an increase in fans or followers, or an intricate equation balancing numerous metrics, measurement is required to show success.

Think about how you determine success, and I don’t just mean at work. How do you determine whether or not you’re successful in your personal life, too? You set goals, right? And you measure against those goals in real outputs.

If you want to run a marathon by the end of the year, odds are you will measure your success based on whether or not you complete a marathon. Easy enough, right?

So why when it comes to measuring a PR campaign does everyone run for the hills or try to pass the buck? Measurement does not have to be complicated. It can be as simple or extensive as you want it to be.

It may require one extra step or keeping track of a few numbers here and there, but I promise you, anyone can measure. You do not have to have a background in advanced mathematics or be an Excel spreadsheet master. But if you know that 2+2=4, you can measure your next PR campaign.

Let’s step it up! We’re always talking about it in theory, but I want to hear more about how you’re using measurement in your every day life. There shouldn’t so few voices talking about PR measurement.

What do you measure every day? What do you keep track of? Do you find personal metrics can be applied to your job, too?

Posted in Measurement, PR metrics, public relations | 2 Comments