Why You Should Use A/B Testing to Refine Your Online Marketing


For those of us who work in marketing, we know the value of a hunch. That gut-feeling. We use it a lot to brainstorm new campaigns, solve problems, and direct our social media posts. There’s merit to the gut-feeling technique, it’s true. But there’s a downside too – your hunch might not always be right. In reality, it may always be wrong. That’s where A/B testing comes in.

What is A/B Testing?

A/B testing is a way to compare two versions of something (an email, a landing page, an ad, etc.), so that you can use analytics to determine which version is most successful. A/B testing isn’t unique to online marketing, but it is particularly helpful in this field, and in eCommerce especially. Here’s why.

When you’re putting together a website or ad campaign, there are many subtle changes and tweaks to make along the way. You choose what color to make the “Add to Cart” button. You opt for one image over another for your PPC ads. You change the copy on your landing page slightly. These choices might seem minor, but studies have shown again and again that customer behavior is majorly affected by them.

How Can A/B Testing Help?

A/B testing is actually ideal for trying out these kinds of changes. It’s a test for refining your online marketing, not completely overhauling it. Any eCommerce whiz can tell you that even small changes to the sales funnel can make big waves on the other end. Do you want to make those changes based on your hunch of what color looks best? Or your personal opinion on which text flows better? Or would you rather test out both options so you know for a fact that you’ve optimized in every way you can?

The real problem with relying on your gut is that it’s yours. Other people react differently to colors, words, images, even fonts. Your feeling about a certain choice might not be the majority’s reaction to it, and that’s who you should be trying to please! Even minute changes can be the difference between a considerable sale and an abandoned shopping cart, and I know which you’d prefer.

Email Marketing: A/B Testing in Action

Let’s look at an example of how A/B testing can help your email marketing strategy.

For many of us, our email marketing follows a standard schedule: weekly mailers with sales/offers, monthly newsletters, follow-up emails to encourage returning customers, etc. This probably means you’re pretty set in your ways – do your emails always go out at 11 a.m. on a Monday? Do they always have roughly the same subject line? Is the format the same?

You could be missing out on a chance to maximize the sales benefit for each email you send – but you’ll never know unless you use A/B testing to try out some changes and analyze the results.

Landing page test

First, you’ll need to decide which metrics matter the most to you for determining ‘success.’ You might want to track whatever constitutes a conversion for your business, whether it’s a sale or just downloading a free white paper. Click through rates are another good measure of your recipients’ interest, or you could track how many use a discount code included in the email. If you’re trying out different subject lines or timing, your open rate might be all you need to see results. Related Class: Metrics-Driven Demand Gen in a Multichannel World

The next step is splitting your mailing list into two groups – let’s call them A and B, for obvious reasons. If you’d like to compare two new ideas, you could send new, different versions to both groups. Or if you’re just looking to see how your current newsletters stack up against a slightly updated version, you could keep group A as your control group, and send group B the new email.

The key when making changes is to keep it minimal. Choose ONE aspect to change. This is important because at the end of the day, you’re looking for actionable results that can guide you going forward. If you change half the email, you won’t be able to put your finger on the one thing that really matters for increasing sales, conversions, CTR, etc.

A few easy things to test: if you usually email at 4 p.m., try 10 a.m. instead. If you usually use a standard greeting in the subject line, try something more discount/offer oriented. If you usually include a voucher code for a percentage off, try a buy-on-get-one voucher code instead. If you usually offer 15% off for returning customers, try 20% off instead.

Google Analytics Measurement for AdWords

The last step is sitting down with a big cup of coffee and all your analytics. Did the changes improve your key metrics? Or make them worse? Did offering a deeper discount pay off overall, or did you shrink your profit for nothing? Read over your results, compare outcomes, and then form steps or recommendations based on your data. It shouldn’t be surprising that continuing your A/B testing over a longer period will help you get more accurate data, less likely to be affected by random highs or lows on a certain day.

Goodbye to the Marketing Hunch

Overall, the clear lesson here is that if you’re not A/B testing changes to your website, sales funnel, or marketing techniques, you’re just relying on your own feedback to make decisions. Gather more feedback through testing, and it’s like a free focus group for your online marketing efforts! If you don’t have the time or personnel to manage A/B testing yourself in-house, there are many tools and services that will do the dirty work for you, for a fee.

Want to learn more about A/B testing for website design changes? See it in action and play along in this class, “10 A/B Test Studies.



How A/B Testing Strategies Can Help You Make Better Decisions


A Q&A with Chris Goward, Author of "You Should Test That!"

This week, we are sitting down with Chris Goward, the author of "You Should Test That!", a book that teaches the processes, frameworks and techniques of scientific marketing to make better decisions and achieve industry-leading results. Featuring case studies of real tests plus many more examples of how companies are succeeding and failing in their websites and their marketing, we're eager to learn more.

What’s the premise behind your book, “You Should Test That!” ?

Too many businesses still use antiquated methods for decision-making with their marketing. They seek out so-called “best practices”, copy competitors tactics, and redesign their websites without A/B testing, to name just a few examples. I wanted to write a book that would provide a dose of inspiration in the new scientific marketing discipline as well as practical processes and frameworks marketers can apply directly to their marketing strategy. It really does contain detail on a lot of the methods WiderFunnel uses to consistently achieve winning results for our clients.

You’ve become a regular speaker at the top online marketing conferences. How did you get into conversion optimization?

I’ve always questioned current ways of doing things. In the early to mid 2000’s, I wondered why marketers accepted the status quo where ad agencies used their clients’ budgets to create self-serving campaigns aimed solely at winning awards for cleverness. I couldn’t understand why digital agencies were creating websites that ignored direct response principles and really couldn’t be more than poor copies of the old TV world.

I left the agency world in 2007 to create WiderFunnel based on the belief that agencies should prove their value. Since then, we’ve been running thousands of A/B tests on hundreds of websites across all industries to discover consistent persuasion and user experience principles that maximize companies’ online profits.

Related Class: Integrating SEM, Testing, and Analytics for Improved ROI

What are the biggest mistakes you see marketers making today?

There are so many!

  • Implementing the latest “tips & tricks” they see on blog posts. I’ve already said many times why tactical marketing tips and “best practices” don’t work. The problem is that they ignore your unique business context.
  • Consensus decision-making.
  • Getting stuck behind organizational barriers. I’ve seen turf battles, silos and competing priorities hamstring some very promising potential A/B tests.
  • Acting on usability testing or other qualitative methods to make website changes without testing those insights. I’ve covered before, the many reasons that usability testing alone is not reliable.
  • Testing too conservatively.
  • Not prioritizing effort correctly and wasting time optimizing inconsequential areas.
  • Using “before & after” testing rather than correct controlled test methods.
  • Drawing conclusions from inconclusive data. Often, it’s difficult for the conversion champion to hold off the pressure to make decisions without enough data.
  • Taking advice from “experts” who don’t do a ton of testing. If their primary business isn’t testing, testing and more testing, where is their advice coming from? You might be surprised at how little testing some of the industry’s pre-eminent figures actually do.
  • Over-emphasizing optimization tool selection before developing a strategy and process for optimization. Tools don’t solve marketing problems. Smart marketers with great strategy and ideas do.

What are the biggest challenges businesses face in adopting marketing optimization as a strategy?

I’ve been running an ongoing poll of marketers asking a similar question since 2012.

Interestingly, in 2012, most respondents said they faced resistance within their organization for conducting testing. This year, that’s the least likely challenge. Companies now know conversion optimization needs to be prioritized and there’s senior-level support for the strategy.

The biggest challenges marketers face in 2014 are in getting great results from their program. They either don’t have staff with deep testing experience, don’t have a reliable process, or face technical barriers. So, it’s good to see the market evolving to having support for the strategy. Now, the challenges are more about how to get consistent results.

eConsultancy did their own survey of companies doing conversion optimization and found that those who reported having a “structured approach” to their program were twice as likely to see large increases in sales. The disciplined, rigorous process alone determines a great deal of the success.

Related Class: eCommerce Testing to Dramatically Lift Sales 

What are your favorite website elements to test?

Really, I like any testing any area that gets results. And, that can be different for every website depending on where the conversion barriers are. Every website design, structure and target audience is slightly different. Some companies are adopting WiderFunnel’s PIE Framework for prioritizing tests to answer this question based on their unique context.

That being said, however, we’re having a lot of success this year adding the “Evolutionary Site Redesign” strategy to conversion optimization for our clients.

It’s a strategy any (and I believe every) company should use. Essentially, it means we’re testing the site-wide website templates in a methodical way. It results in a redesigned website without the risks of traditional “flip the switch” epic redesign. Using A/B testing of the overall design elements, companies are finding sometimes huge revenue improvements from improved navigation, information architecture, design credibility, merchandising, etc. and the resulting design changes can be just as dramatic.

In this class, 10 A/B Test Studies, you’ll encounter 10 such tests and can guess which page won. The answers will surprise you and the knowledge you’ll gain about how to conduct these tests and what makes some pages better than others will make you a more effective marketer.   


Predictive Intelligence: The Fuel for Successful B2B Marketing


Consider this scenario: A regional bank is evaluating providers to help it migrate its financial management applications to the cloud. The cross-functional decision-making team is spread across offices and communicates heavily over tools like Skype. In addition to the time team members spend evaluating the websites of you and your competitors, they also search, read blogs and publisher websites, tweet, share research, and meet to discuss in person.

Research from Google/Corporate Executive Board and SiriusDecisions suggests this buyer decision-making process is the new normal and that means your marketing team is challenged to not only have adequate visibility into these activities but to also effectively influence each prospect across as many channels as possible. Oh, and then there is the sales team hungry for new leads down the hall…

Today, a new category of predictive intelligence beyond lead scoring provides marketers with the data, insights, and recommendations they need to understand today’s disjointed buyer’s journey and drive measurably better sales results.

It’s Not Magic, It’s Math

Through a combination of data sources and modeling methods, predictive intelligence tells marketers which companies are in the market to buy, which products and services they need, and when they are likely to make a purchase. The accounts and contacts are then scored and that information is delivered directly into systems like marketing automation, CRM, CMS, and ad buying tools for companies to take immediate action.

What might seem too good to be true is built on machine learning and data science. Predictive intelligence ties together data from sources like marketing automation, CRM, past bookings, buyer profiles, and web activity across your site and thousands of others. The blend of static data (e.g., company size, revenues) and behavioral data (e.g., prospects downloading white papers) not only identifies which companies are in market to buy now but also uncovers accounts previously unknown who are looking for what you sell. One SiriusDecisions ABM Campaign Of the Year award winner says these early insights on what prospects do before they reach a salesperson gives their company an “unfair advantage.”

Applying Predictive Intelligence Data to Marketing and Sales Channels

Let’s revisit our bank: Through email campaigns over the last several years you have obtained several contact records inside your marketing automation database. From what you can tell its interest is limited to a case study registration a quarter ago. And what you don’t know is that the bank’s IT team is moving closer to a vendor recommendation for the application migration. Team members attended multiple webinars in the last month, spent days researching across the web, and held a lengthy conversation on a tech forum. Is your typical quarterly investment in email, lead gen, and advertising enough to identify and create a sales opportunity with this company? Predictive intelligence can help ensure it is by tying together all the activity into one predictive score.

web analytics truths

Let’s look at some of the ways marketers can use predictive intelligence data to improve nurturing and create opportunities with companies like our example bank.

  • Call center: Create call scripts tailored to your prospect using company and category intelligence and improve lead qualification rates.
  • Marketing automation: Route prospects to the right campaign and ensure communications are properly personalized based on company size, industry, job role, and level of interest in your products.
  • Advertising: Only advertise to key companies and adjust messaging and landing pages based on purchase intent and company attributes.
  • Retargeting: Stay visible to your prospects after they reach your website. Tailor messaging according to the intent they show at your website and across the rest of the B2B web.
  • Social media: Only target ads to prospects at key companies when they are on LinkedIn, Twitter and Facebook.
  • List acquisition and lead generation: Educate and nurture prospects from key companies while building your database with net new contacts.
  • Website personalization: Make each visit as useful as possible by integrating audience data from predictive intelligence scoring into your content management system, personalization and testing tools.
  • Sales calls and conversion: Help reps prioritize the right prospects and arm them with the intelligence to secure meetings, RFPs, and close deals.

The use cases are many and the impetus is here: savvy buyers warrant savvy marketers. Before launching another half-baked campaign where your prospects run you, consider how predictive intelligence can help you gain insight into your audience so you can blow away your benchmarks.

Data sources, modeling techniques, systems integration, marketing tactics: What areas would you like to learn about most? Let us know, and we’ll follow-up in future posts.

To learn more about today's advances in predictive analytics can give marketers competitive insight on which contacts and accounts to target; what the right cadence of touch-points is; and which channels should be used for maximum message delivery impact, join the Online Marketing Institute and 6Sense on Monday, August 18th at 2:00pm ET for a free webinar, “How To Increase Your Digital Marketing ROI Using Predictive Analytics”.  



How To Use Predictive Intelligence to Target the Right Buyers and Close More Deals


With 60 to 90 percent of buyers making their purchase decisions before they hit an organization’s sales funnel, marketing and sales are turning to predictive intelligence to capture unknown prospects and target the right leads. As I have been working with enterprise companies on their lead generation pain points for over 14 years, there are several questions about predictive intelligence solutions that I’m regularly asked on the front-lines.

On July 9th, Matt Heinz, president of Heinz Marketing, and I will be leading a discussion on how you can use predictive intelligence to target the right buyers and close more deals. Here’s a sneak peek of what you can expect to learn as we address these questions during the webinar. 

How do you know you’re not just applying the tip of the predictive analytics iceberg?

Image source: Econsultancy  

Which types of data uncover the most business-growing insights?

In an interview with CMO Eric Siegel, founder of Predictive Analytics World and author of Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, he commented: “It’s the holy grail of marketing—to proactively pounce on every individual customer opportunity.” By leveraging the sheer amount and variety of data accessible today, marketers and sales can not only “pounce,” but can accurately “pounce” on data-backed leads—a significant change from traditional lead scoring, which uses only a fraction of the data of predictive intelligence. So, what types of data lead to the most accurate prediction of buyers? Heinz and I will discuss the differences between external vs. internal data; behavioral vs. attribute data; and known vs. anonymous data to help you make an informed decision.

What kind of results can you expect to see from predictive intelligence?

Early adopters of predictive intelligence, like Cisco, have already seen promising results from their initiatives. Beyond sales and marketing efficiency gains, predictive intelligence has the potential to improve your business across a number of KPIs—from conversions, to time-to-close, to revenues. I’ll be discussing what results you can and should expect from predictive intelligence, including:

-        Improvements in accurate sales forecasting

-        Growth of deal sizes

-        Closing more accounts

-        Personalization of marketing outreach

-        Maximization of budgets

What are the differences among predictive intelligence solutions?

It’s critical to evaluate predictive intelligence solutions by how they align to your specific business objectives. Different needs—for example, prioritizing existing leads vs. finding net-new leads—warrant different approaches. Here are a few guiding questions to help you gauge what sort of solution will work for your company. Prepare your answers to these questions ahead of the webinar to find out what solution fits your needs.

  1. Are you having trouble locating net-new leads? How important are they to achieving your sales pipeline this quarter or year?
  2. Are you satisfied with current lead scoring processes? What would you like to see improved?
  3. Are you struggling with low marketing-to-sales qualified lead conversions?
  4. How much return are you getting from your content marketing? Are you satisfied, for example, with your ad click-through rates?
If you work in demand generation, marketing, or sales and you’re not sure how to apply predictive intelligence to what you do, register for the webinar today to learn all about it. Have specific questions you want addressed during our webinar? Tweet them to us early at: @6SenseInc


6 Facebook Page Statistics You Need to Know, Part 2


Last week, we shared with you the first part of our blog installment, 6 Facebook Page Statistics You Need to Know, based on our conversation with Emeric Ernoult, CEO of Agorapulse. See a full recap here and the continued list below.

Facebook metric #4: Storytellers

What is it?

The “Storytellers”, called “People Talking About This” in the old insights, represents the people who have liked, commented or shared a post. The engaged users are all the users who have clicked anywhere on your post, the storytellers is the portion of these users who have clicked on like, comment or share.

As opposed to just clicking on a link, a picture or a video, liking, commenting or sharing a post will generate a story that will be published on Facebook for our friends to see.

What makes the “Storytellers” different than the mere engagement metric is that engagement in this case potentially generated a publication by that user showing his engagement to his friends.

Where can I find it?

Here again, go to your insight interface at the same place where you spotted the organic reach and the engagement and look at the “Engagement” column after having selected “likes / comments / shares” in the drop down menu. Easy.

Why it matters?

This is the “viral” metric. Going back to the roots of your motivation for investing in a Facebook page was probably the dream that you could connect with the friends of your existing fans for free! That metric is the best one to measure how many people are willing to spread the word about you to their friends.

In plain English, if a user likes, comments or share a post on your page, Facebook may publish to his friends that this user (their friend) liked, commented or shared a piece or content from your page. I emphasize the “may” because Facebook is limiting the reach of these stories very seriously. That is probably why if you used to see in your newsfeed that such and such friends had liked, commented or shared a piece of content from a page, you probably see less and less of that today.

So, even f you still need to follow that metric, don’t expect too much from it. Facebook is still the best place to leverage virality, but it’s not the eldorado it used to be.

Facebook metric #5: Clickthrough rate (or “consumption”)

What is it?

Here comes a metric that you are used to! CTR, or Click Through Rate has been around for years on the web and is used to measure the effectiveness of email marketing, banner advertising, search engine ads such as adwords campaigns or landing page quality.

The good news is that it means the same thing within Facebook. This will tell you the number of people who have clicked on a link in your content, watched your video or viewed a larger version of your photo.

Where can I find it?

Go to your page insight interface, click on the “posts” menu and you’ll find the number of users who have clicked on your content.


Why it matters?

It is nice to know how many people have potentially seen your content (the reach metric), even nicer to know how many of them were interested enough to act on it (engaged users), but the bottom line is really to know how many people were actually interested enough to pay real attention to your content. And that means watching your video, looking at your photo or checking out your link.

That is the bottom of your “content quality” funnel. Keep an eye on it.

Facebook metric #6: Negative Feedback

What is it?

Negative feedback is a “negative” action taken by a fan on your piece of content. It can be hiding that specific post, hiding all future posts from your page, unliking your page or worse, reporting it as spam. Simply put, it counts the number of users who really did not like your content or the fact that it appeared in their newsfeed.

Where can I find it?

Go to your page insight interface, click on the posts menu and look at the “Engagement” column after having selected “Post Hides, Hides of All Posts, Reports of Spam, Unlikes of Page” in the drop down menu.

Why it matters?

Since September 2012, Facebook has given much more weight to the negative feedback metric. In other words, posts with a high negative feedback will have much less exposure through edgerank and, pages with an average negative feedback that remains high will have less and less reach over time.

Needless to say that if you want to stay in the game of Facebook marketing, you need to keep that number as low as possible.

Conclusion: Measuring your Facebook page performance may seem like a daunting task if you have to do it manually from the Facebook insight interface or the Excel download, but it is good to start doing it that way to really have a feeling of where the data come from and what they mean.

Once you start being familiar with them, you can use third party tools that will help you save time and get right to the point. One free tool Emeric recommends l is the Facebook page barometer, but for more detailed metrics, you can also try the Facebook page management suite at

What metric are you paying attention to and why? Do you do that on Facebook directly or do you use a tool?

Like what you see here and interested in learning more? Join OMI and Agorapulse for a free webinar, “Facebook Metrics: Measuring Your Content’s Performance”, tomorrow  Thursday, June 12th at 11:00 am ET.


6 Facebook Page Statistics You Need to Know, Part 1


You’ve created quality Facebook content, but now what? How do you measure the performance of your Facebook Page? With so many metrics to track, it can be hard to break through the clutter. To determine the metrics that really matter, why, and what they can teach you, we spoke with Emeric Ernoult, CEO of Facebook marketing firm, AgoraPulse, for his insight on the subject.

What he’s uncovered are the 6 key metrics you need to follow to really understand how your Facebook page is doing, where to find them, and what they mean for your Facebook performance and why you should care. In Part 1 of this blog installment, we’ll cover the first 3 of the top 6 Facebook Page statistics you need to know. Like what you see here and interested in learning more? Join OMI and Agorapulse for a free webinar, “Facebook Metrics: Measuring Your Content’s Performance”, next Thursday, June 12th at 11:00 am ET.

Facebook Page Statistic #1: Fan Reach

What is it?

Fan Reach = the number of fans of your page who have seen any given post.

Where can I find it?

The Fan Reach metric is now available in the Facebook statistics interface. The “Fans reached” metric is easy to spot in your Facebook insights. In the posts menu, click on the top left arrow and select “reach: Fans / Non-Fans”. Then, hover to each graph and you’ll see the number of fans reached for the concerned post.


Why does it matter?

The Per-post-Fan-Reach is the most important metric because it is a key indicator of your content’s appeal to your audience and the quality of your audience. The higher the quality of your audience and the more interesting your content is, the greater the increase in percentage of fans reached will be — and vice versa.

Facebook Page Statistic #2: Organic Reach

What is it?

Organic Reach = the number of people, fans and non-fans, who have seen a given post.

Where can I find it?

From your Facebook Page, go to your insights, click on “posts”, scroll down and you’ll see the “reach” number for each post. Hover your mouse on the bar chart for “organic” and you’ll see the Organic reach number for that post.


Why does it matter?

Organic Reach can replace fan reach in the metrics you are interested in, but only if the average difference between organic and fan reach is not too high in your case.

Otherwise, it can help you identify ways to improve your content’s organic visibility. For example, an organic reach that is very close to a fan reach typically means that someone cannot be exposed to your content if he or she is not already a fan. If you have a website, a blog and a newsletter and no or very little difference between your organic and fan reach, it probably means that you are not attracting a new “non fan” audience to your content. If that’s the case, try to better promote your page on these other channels and you should see your organic reach going up.

Facebook Page Statistic #3: Engagement

What is it?

Engagement = the number of people who clicked anywhere in your post. That means liking, commenting and sharing, but also people who’ve viewed your videos, clicked on your links and photos, and also, clicked on a commenter’s name, liked a comment, clicked on your page name and even those who gave negative feedback by reporting your post.

Reach tells you how many people have potentially seen your content, whereas engagement is the number of people who have acted on that content.

Where can I find it?

Go to your Insights at the same place where you spotted the organic reach. The number of people who “engaged” with your content is in the “Engagement” column. To see the total engagement though, you’ll have to add the number of post clicks and the number of likes, comments and shares.


Why does it matter?

Engagement, whether it implies “acting” on your post by commenting, liking or sharing it, or is “passive” such as watching the video, zooming on a photo or clicking on a link, is probably the second most important metric to focus on if you are serious about measuring your page’s performance.

It is not enough to be viewed by a lot of people, you need to make sure that what you offer them as content will trigger some kind of interest. And engagement is the only measurable sign of interest. Stay tuned for the next installment of this series,  6 Facebook Page Statistics You Need to Know, Part 2.

Interested in learning more about the tools and techniques that can help you fine-tune your Facebook Marketing Strategy? Join the Online Marketing Institute and AgoraPulse on June 12th at 11:00am ET for a free webinar, “Facebook Metrics: Measuring Your Content’s Performance”. View the event here for more details and to register!


Not All Big Data is Created Equal


“In 2014, big data will finally be put to good use as marketers stop waiting for insights to reveal themselves and start finding actionable paths through the information.” - Forrester Consulting

Industry experts are saying that 2014 will be the year for data-driven marketing, especially for B2B marketers. While the more sophisticated and technology-enabled marketers (read: B2C) are actively using solutions that turn data into insights, a recent CMO survey showed that 63 percent of marking projects still don’t leverage marketing analytics to inform decisions. It’s like shooting an arrow without aim.

Barriers to quick uptake could very well be the daunting task of deciding what data to analyze and beginning data accumulation and analysis in earnest. The good news is that the big data marketing landscape for B2B is rapidly evolving, and with that comes a wealth of opportunities for marketers to use technology and predictive analytics to improve marketing efficiencies and predict sales.

If you’re eager to get started (it’s OK, it’s only May!), there are a several things you need to consider deeply before you decide to embark on big data analytics.

Related class: Using Big Data to Support Managing Marketing Performance

What Data Do You Want to Capture? 

It is easy to become lost in the possibilities of big data, and so it’s critical to pinpoint what insights you want to be able to capture and why. For example, do you want to simply understand more about your target audience profile through data? Or is your organization looking for a better conversion rate? Do you want to optimize media spend? Does your team want to be able to deliver better qualified leads from its campaigns?

To that effect, not all data is created equal. Certain marketing goals require a more thorough engagement with a more complex type of big data.

Identify Your Data Sources

Booz & Company does a good job of differentiating between structured and unstructured big data. Structured data refers to data that is compiled (via a survey, for example), provoked, created, and transacted. Structured data is descriptive in nature, forming a basis for categorization of an audience, such as position, age, title, organizational employee size, etc.

On the other hand, unstructured data is user-generated and must be captured. It’s good to think about unstructured data as “digital breadcrumbs” that reveal behavioral patterns of target consumers and predict those consumers’ next purchase, among other insights.

While the role of descriptive data is paramount to any marketing initiative, behavioral data is the key to solving some of the more in-depth marketing challenges, such as understanding the timeframe your customer is likely to buy in or who else might be involved in the decision-making process. Think about it: by aggregating the digital footprints of a potential buyer (unstructured, behavioral data), you can accurately pinpoint when the buyer will purchase, what he will likely purchase, and even the potential value of the purchase. The possibilities are incredible.

What’s Next?

“Buyer behavioral data remains the greatest untapped marketing asset,” according to the Forrester Consulting report, and so you definitely don’t want to leave any stone unturned.

Be a part of the “biggest » big data prediction of 2014 and start using behavioral data to your advantage.

Want to learn how to leverage big data for improved marketing ROI? Watch Online Marketing Institute's class, Using Big Data to Support Managing Marketing Performance and learn what the term "big data" means, and why it is important for marketing when it comes to strategy, product and pricing decisions.


5 Approaches for Making Sense of the Data Kaleidoscope


Today’s marketers have a nearly infinite amount of data at our disposal, and to be successful we must have the ability to analyze the millions or billions of bits and pieces of raw data and produce patterns. While reflecting on how to collect and analyze this immense amount of data, I recall fond memories of using my mother’s heirloom kaleidoscope as a young child. As she made small turns of the tube, we'd peer inside and marvel at the amazingly intricate patterns produced by the bits and pieces of colored glass at each turn.

Conducting data is required in order to understand data and identify patterns that will affect your business. However, unlike my mother's kaleidoscope, in which every pattern was beautiful, we need to apply a more discerning eye on the patterns produced from the massive amount of data we can now collect.

Today we can gather far more data than we can easily digest—because nearly every transaction or interaction creates a data element we can capture and store. How do you know which patterns are meaningful and worth action? The sheer scale of data can make for extremely complex data relationships and subtle patterns.

Related class: Measuring What Happens Through Attribution

That is why data mining has become an essential part of pattern detection. Data mining is used to simplify and summarize data. The next step is to apply various techniques to tease out the meaningful patterns.

There are five common types of pattern detection every marketer should be familiar with:

  1. Anomaly detection
  2. Association learning
  3. Classification
  4. Cluster detection
  5. Regression

Anomaly detection is useful when you are trying to determine whether something is significantly different from the expected picture. You might use this approach to monitor customers at risk.

Association learning can be used to reveal customer-purchasing patterns. For example, you might learn that customers who purchased Product A and Product B also purchased Service X. Then you can create offers to target those specific customers.

Classification allows us to use data mining to classify new data into pre-determined categories, allowing marketers to create and apply rules. You might use this approach for opportunity scoring and qualification. Once the opportunity scoring model and categories are established, new opportunities can be appropriately classified and actions planned.

Cluster detection is a good approach when you have a primary category and need to create subcategories. Let's say we have a particular group of power users of a product. It's possible that there are actually relevant and distinct subgroups of power users. Cluster detection reveals the subgroup patterns.

Regression is a type of data mining that helps with constructing predictive models. For example, being able to predict the future engagement of a customer based on past behavior requires regression. By understanding regression, marketers can use the models to determine which content elements, channel, and touch points lead to increased conversion for a particular set of prospects.

Hopefully you've come to an important conclusion—knowing which approach to use starts with asking the right question. The power of patterns begins with knowing what you want to know. And here is where the randomness of the kaleidoscope parts ways from the purpose of data mining.

As marketers, it is our responsibility to frame the question. Questions such as these (and many more) fall within our domain:

  • What data sets match with which customer segments, and how can these distinctions be used to create customer buying and usage personas?
  • What products are most preferred by a particular customer segment?
  • Which opportunities convert faster and under what conditions? And the flipside of this question: Which opportunities remain "stuck" and what do these "stuck" opportunities have in common with those that convert and, more importantly, how are they different from the opportunities that convert?
  • What product segments have the fastest traction and adoption, and what is unique about those segments compared with where the traction and adoption is lagging?
  • How can the "usage" rates, renewal rates, and upsell/cross-sell opportunities be categorized by customer segment?
  • Which touch points and channels resonate with that customer segment or persona?

Marketers need to proactively frame the question, gather and analyze the data, decipher the patterns, and—most importantly—come to the table with a recommended plan of action.

The marketers who are able to distill patterns into something meaningful and actionable are the ones who will succeed in today's data-driven business environment.

Ready to learn how to better understand how much data you have access to and how to make that data actionable? Watch Online Marketing Institute's Class, Measuring What Matters Through Attribution, and understand how much you have, what you can source, how to make it actionable and who else is making a profit from it.


Facebook Tools Guide: 9 Platforms to Improve your Fan Reach


Over the last few weeks you will probably have noticed that your reach is going down on Facebook. This means your updates may not be delivered to as many people as before.

One solution to this problem is to spend money on advertising.  But while this will solve your problem, it’s an expensive solution.

An alternative is to focus on your analytics to see what is working and not working for you or your competitors.  The key is to learn from your mistakes and capitalize on what is clearly working already.

Facebook does provide analytics on your page’s performance via Facebook Insights, but there are limitations to the information they provide.  In this article, we’ll take you through a range of 3rd party Facebook Analytics tools that not only provide better analytics on your page’s performance but also provide added value such as competitive analysis against other pages.

RELATED CLASS: 7 Elements of Highly Effective Facebook Marketing

Here are 9 analytics tools that are worth considering.


Agorapulse provide a full management tool for Facebook which includes a CRM module, a range of Facebook  applications (such as competition apps) and finally an analytics module.  

If you want analytics as part of your overall management application Agorapulse is worth considering.

Feature highlights for Facebook:

  • Page and timeline level analytics overview and more detailed reports.  Graphs display breakdown of paid, organic and viral reach.
  • AgoraPulse Barometer – Free access to 8 competitive analysis statistics which compares performance of your page against other pages of a similar size to yours that also ran the barometer.   This gives you an idea of reach of other pages so you know what you should be able to achieve.
  • Useful analytics related to moderation of posts and content.  As moderation of content happens through AgoraPulse they can report on this, for example, average time to respond to comments. Very useful for community managers and agencies.  If you’re not responding to comments quick enough this could lead to less comments which leads to less reach.


BlitzMetrics is an analytics tool that provides metrics for all your main social channels such as Facebook, Twitter, YouTube and Instagram.

Feature highlights for Facebook:

  • Reporting available over 7 day, 30 day, year to date or you can select specific date periods.
  • Provide customers (depending on licensing) direct access to the data so they can use business intelligence tools such as Tableau, Microstrategy, Domo, Cognos, etc. to report on the data.  This can give you a different view to what traditional analytics will provide.
  • View graph reports in various formats, for example, graph view, list view.  View overview graph for each statistic and then select this to view a larger graph.
  • Overview reporting available for groups of pages (e.g. if you have 10 company pages you can see an overview report for all).  This is very useful for larger companies.
  • Demographic reporting with split of PTAT  (People talking about this) amongst male/female
  • Provides trending of a few dozen metrics, including all metrics available for export from Facebook insights.


Komfo provide a full social media marketing suite (including a suite of Facebook apps) with analytics as part of this.  Similar to Agorapulse if you are more interested in a full management solution Komfo provides this.

Feature highlights for Facebook:

  • Post analytics on individual posts with categorization provided to allow you to clearly identify posts that were viral, spammy, engaging or penetrating.  This helps you clearly identify the best performing posts.
  • Shows performance for the last 30 days for up to 100 posts for the free version of the tool.  This limit does not apply if you have a subscription to Komfo’s social media marketing suite
  • ROI calculation and display in graph format split up into paid, organic and viral.
  • Fan activity and influencer leaderboard
  • Useful and simple competitor comparison chart with proprietary scoring which makes it easy to rate.

Post Acumen

PostAcumen (from the founders of EdgeRank Checker) aims to examine the “why” and the “how” of competitive social analytics.

Feature highlights for Facebook:

  • Detailed competitive analysis which gives good actionable insights.  The actionable insights gives you specific actions you could take to improve your reach.
  • Monocle real time viewer – If you are really active on your Facebook page you can monitor real-time the activity.
  • A great feature is the analysis of photos where photos shared on a page are displayed in a visual with the most popular ones appearing on the top of the page.


quintly helps to track, analyze and benchmark Facebook, Twitter, YouTube, Google+, LinkedIn and Instagram profiles.

Feature highlights for Facebook:

  • Market Benchmarking – Benchmark your page against competitors to compare performance.
  • Customizable Dashboards – Set up customizable dashboards to monitor key metrics for you or your competitors.  The dashboards can be converted to PDF’s.
  • Automatic Reporting – Based on your dashboards you can set up automatic reports to be sent to relevant people within your organization.
  • Facebook Insights Integration – You can import all your Facebook analytics data to the tool.
  • Mission control – This is a live dashboard where you can monitor changes live up on the wall.


Scoreboard Social

Scoreboard Social provides simplified competitive and benchmark reporting for Facebook, Twitter and Instagram.

Feature highlights for Facebook:

  • PDF reporting to your inbox – Get a weekly PDF which outlines the performance of your own, and/or your competitor’s pages.
  • Create multiple watchlists – A watchlist is a collection of pages.  You can create multiple watchlists based on different categories of pages you are targeting.  You can also have the same page in multiple watchlists.
  • View snapshot of performance – Based on the competitors in your watchlist you can view a quick overview of the top 2 posts for your competitor over the last 24 or 72 hours.  If your competitors are getting good reach maybe there are similar posts you could also try.
  • Create watchlists to track your page or your competitors


Socialbakers provide a suite of social media management tools, one of which is an Analytics module for Facebook, Twitter, YouTube, (Russia’s #1 social network), and more recently Instagram and LinkedIn.

Feature highlights for Facebook:

  • Facebook page Country Breakdown – Overview of country level statistics such as number of Facebook fans
  • Industry benchmarking – compare your page by industry and region.  If you are under performing in reach it may be related to your content as opposed to Facebook changes.
  • Competitive analysis – compare performance of page versus other competitor pages
  • View key influencers that are interacting on the page.
  • Good reporting options, for example, side by side comparison with multiple competitors.


SumAll is a free online software that guides your decision making by connecting all the services you use such as Facebook, Twitter, Instagram, PayPal, Google Analytics, and many more in one interactive chart.

Feature highlights for Facebook:

  • Cross platform analytics – View your Facebook analytics in conjunction with other analytics.  This will help you understand the correlation between channels (e.g. does more Facebook interaction lead to website traffic?).
  • View side by side analytics with multiple pages.
  • Adjust date view to whatever date you require
  • Can track as many Facebook pages as you want. Really useful for agencies with a large number of clients.


Wisemetrics Stream is an advanced social analytics and reporting solution, currently focused on Facebook but with Twitter coming in Q1 2014.

Feature highlights for Facebook:

  • Save time on reporting with monthly PowerPoint export of all reports – a very visually appealing PowerPoint report provided as a full presentation.
  • ROI (Return on Investment) evaluation
  • Benchmark performance against competitors
  • Country by country metrics for global pages – This means you can break down a page by a particular country and see information related to fans for that country.
  • Historical reporting – You can report back to when the page was launched if required, this is not available within Facebook.
  • Supports integration so if you include links, Wisemetrics Stream will track clicks on these links.
  • Algorithm is used for monthly reports to provide a fairly good estimate of your unique users reached or engaged for a whole month (instead of 28 days as provided by Facebook).


Reach is a problem for most of us, but if you invest the time in doing some analysis of your page’s performance this can certainly give you some insights into how you can improve your reach by focusing on what’s working.

How have you improved your reach?  Do you use any of these tools or do you use other tools?  If so, we’d love to hear from you. 

This information is part of a much more detailed Facebook analytics guide sponsored by Online Marketing Institute.


5 Ways to Turn Big Data Into Insight and Action


As it has been shown in a variety of ways over the past decade or so, the days of math-less, mindless, off-the-hip marketing have long set sail. So how do the once gun-slinging marketers of the past begin to tackle the voluminous unstructured data that is collected from nontraditional sources to harness the power of analytics? Big Data, derived from blogs, social media, email, sensors, photographs, video footage, etc. is and has always been the answer. Although Big Data isn’t new, most marketers are still wrapping their heads around the transformation of raw data into action. RELATED CLASS: Big Data, Big Analytics: Measuring What Matters

Data vs. Insight

In today's data-rich and data-driven environment, we are predisposed to gain our insights from data. But action doesn't always follow collection. A survey of 600 executives by the Economist Intelligence Unit found that 85% of the participants thought the biggest hurdle to unlocking value from data was not grappling with the sheer volume, but analyzing and acting on it. And gleaning the insights from the data is what makes the data valuable.

Merriam-Webster defines insight as the power or act of seeing. Keyword: Seeing. We must use the data to identify and see—to see patterns, trends, and anomalies. And once we gain this insight, its value is proven by the actions we take as result. Data that doesn't help you see isn't useful. So, in this instance, more does not always translate into better insights. In fact, according to the recently released 5th annual Digital IQ Survey, consulting firm Pricewaterhouse Coopers (PwC) found that 58% of respondents agree that moving from data to insight is a major challenge.

In 1990, Stephen Tuthill at 3M helped make the connection between data and wisdom. His The Data Hierarchy outlines four important concepts: data, information, knowledge, and wisdom, with data being the raw items or events. Once we have the data, we can sort and organize it into information. Knowledge is then derived from the patterns that result from understanding the relationships between the data and other factors. Wisdom comes when we understand what to pay attention to—what has meaning for us.

So, rather than focusing on more data, we need to focus on capturing the right data and then analyzing it in a way that gives us the power to see (knowledge) and act (wisdom). Bernard Marr from UK-based Advanced Performance Institute reminds us that to get the most out our data "you need to know what you want to know." Once you know what you want to know, collect and organize the data.

Now what?

Getting From Data to Insight

1. Bring data to life with visualization

Having the data is one thing, analyzing and synthesizing it is another. Synthesis is where we begin to see the patterns. Once the synthesis is completed, you will need a way to bring the data to life. Data visualization greatly aids in this part of the process. Data visualization presents analytical results visually so we can more easily see what's relevant among all the variables, capture and communicate important patterns, and even support predictive models. Visualization is an important step for exposing trends and patterns that you might not have otherwise noticed.

2. Discuss patterns and the potential implications

Not all patterns are germane. Take the time to review and discuss each pattern and its potential implications. Talk about why you think each pattern is important and what it means. This is an essential step for going from information to knowledge.

3. Articulate the insight that emerged from each pattern

In one simple statement, articulate the insight that emerged out of each pattern or point of synthesis. We find it is helpful to capture insight on a Post-it Note and place it on a wall or flip chart to easily track each insight and see the "big picture" that may be emerging as we go.

4. Incubate the insights

Give yourself and your team at least a day away from the "board." When you and the team return you can take a fresh look and decide whether to make any changes.

5. Get reactions from others

Do the insights resonate? Once you are comfortable with the conclusions/insights you've captured, involve other people who were part of the initial steps to gain their reactions. Be sure to give them the context. The point of this step is to decide if the insights resonate and are compelling enough to make or affect key decisions. That is, to determine whether you have acquired the wisdom you need to act.

The success of this approach is contingent on the quality (not necessarily the quantity) of the data set, then following a process proven to identify core insights to support strategic decisions. Just like traversing your daily route to and from work, gaining insights from data becomes innate. Although intuition of the traditional sense is still a valuable tool to modern marketers, data has become the insurance policy in understanding our customers. Our ability to “read in numbers” has become paramount. For more information, read VisionEdge Marketing’s White Paper, From Intuition to Wisdom: Transforming Data into Models and Actionable Insights.

Take your web analytics practice to the next level.

Watch the OMI tutorial, 5 Fundamental Web Analytics Truths for a Data-Driven World with Feras Alhlou, and learn how to develop a web analytics practice that enables you to optimize what matters most to your business, and ignore the rest. Access it FREE with a 7-day trial to the Online Marketing Institute. Activate trial now.