Understanding the Digital Media Landscape
When digital marketing and advertising began in the 1990s, the promise of digital channels was to deliver the right message to the right audience at the right time—a game-changing upgrade over traditional media channels. Digital media has been sold as a nirvana of data collection, analysis, and measurement that would yield the most efficient, optimized programs one could hope for. Fast-forward 15 years, and we’ve learned that achieving that reality isn’t impossible but can be far more difficult than it seems at first glance.
Today’s digital media landscape is more complex than ever before. The continuous and rapid introduction of new platforms, tools, data sources, and media consumption devices (such as mobile devices and tablets) have created an environment that can make any marketer’s head spin. The challenge now lies in identifying which unique composition of all those choices is required to produce the outcomes needed to achieve your digital goals and objectives.
Digital media is great at creating data about who you are, what you like and dislike, and where you’ve been online. This book helps you work smarter by providing you with the approach and information you need to understand and utilize the data that exists across the entire digital landscape. Hopefully the original digital promise that got everyone so excited in the first place will become a reality for you, and you’ll have a better understanding of why digital channels continue to draw more investment in time and money away from traditional media channels.
Digital Media Types
From the mid-’90s until the present day, the digital media landscape has undergone tremendous change. For a good 10 years there were two dominant media types, although we’ve relabeled them through the years. The first is paid media, either in the form of paid search (think Google AdWords) or display advertising (think DoubleClick banner ads). Paid media is literally just that—digital media channels that a brand pays to utilize.
The second is owned media. This is a generic term for any media asset or platform that a company owns, controls, and utilizes to reach a prospective audience. Some of the most common forms of owned media are dot-com brand websites, email marketing to subscribers, and company blogs. For both paid and owned media, clicks still rule as the dominant data to collect and analyze. However, tracking what happens after a user clicks on a link can be useful, but it can’t answer all the questions.
In the past several years, there has been the emergence of a third media type, called earned media (see Figure 1.1). Some say it’s new; others think it’s simply a new label for what public relations professionals have historically called free media, something generated by word of mouth, buzz, or a communication “going viral.”
Figure 1.1. Paid, earned, and owned media are converging to the point where one type of media has a direct impact on the other.
Source: “The Converged Media Imperative: How Brands Must Combine Paid, Owned & Earned Media,” Altimeter Group (July 19, 2012)
With Facebook eclipsing 900 million users and Twitter closing in on 150 million, owned and earned media are now richer sources of data that include new data types that weren’t available to marketers in the past—specifically those types that involve user behaviors, intentions, and affinities. The new era of engagement has resulted in a data explosion that takes us beyond analyzing clicks, counting advertising impressions, and adding up website page views.
The data and tools available today can give you the insight you need to improve marketing and advertising performance. You can now better understand both the qualitative and quantitative dimensions of a prospective audience. You can use this knowledge to personalize user experiences and facilitate a real value exchange that meets users’ needs and expectations. Simply put, you’ve never been in a better position to generate the desired outcomes and predict future behavior thanks to the robust ecosystem of data and analytics tools. Over the course of the next several chapters we will dive into these tools, which include search analytics, social media monitoring, and social media engagement.
Each media type contains several channels that serve a purpose and play a role in your marketing mix. The data and analytics associated with each helps you determine how much or how little of a role each should play. No digital strategy can succeed based on only one media type.
Paid media is a more mature media type than some of the other digital media types. It has well-established methods of targeting, audience segmentation, and measurement. Additionally, paid media programs contain real-time measurement capabilities, which allow companies the opportunity to assess and change course if necessary. However, because the way paid media programs are executed is well-established, the models have not evolved to meet the impact of owned media channels (such as Facebook, Twitter, YouTube, and so on).
Paid search is still one of the best places to get insights and understanding about an audience. Several search engine and third-party analytics tools work with search data to identify user, behavioral, and intention insights. Read Chapter 5, “Tools: Search Analytics,” for more information on paid search data and analytics.
Paid display, otherwise known as banner advertising, is suffering these days due to “banner blindness.” Banner blindness happens for one very clear reason: utter saturation of the digital landscape with all types of banner advertising units, including standard ads, rich media ads, interactive game ads, and social ads. Consumers have become so attuned to seeing display ad units on web pages that they block them out. Banners are essentially background noise most of the time. The net effect is declining views and click-through rates (CTRs).
Performance of banner ads varies due to many factors as well as the banner type. The average CTR for a standard banner ad unit is estimated to be around 0.1% or 0.2%, depending on banner type. This means that if 1,000 people see a banner, only 1 or 2 people click it. This is subpar performance by any standard, and it compares unfavorably to seemingly less attractive digital options, such as email (or even traditional marketing options such as direct mail).
The upside of the paid display market is its well-established methods for targeting and measurement. Publishers and ad-serving platforms have become quite advanced in their usage of cookies for collecting data and tracking an audience. In fact, it’s big business. According to a 2012 cross-industry study by Krux, data collection and audience profiling grew 400% over the prior year. This means, for example, that the average number of data-collection events associated with a single web page visit increased from 10 to 50.
Targeting is done through a combination of both first- and third-party data. What does this mean? It means the company (first party) that owns the website you land on is directly capturing data about you and your visit. Third-party collection is responsible for the lion’s share of data collection growth. In fact, the number of data collection companies has doubled, with more than 300 companies observed in the 2012 Krux study, compared to 167 the previous year. Targeting is done through a variety of creative cookie wrangling and has been aided by the integration of social technologies into owned media assets.
An example of targeting that is quite common, and yet not well known, is popular social sharing widgets such as ShareThis. It’s a simple proposition for website owners: A company can easily install a preconfigured social sharing widget to allow sharing of their brand content across major social networking platforms and/or email. ShareThis is free, and it takes little time to get it installed and running. The catch, though, is data leakage. The sharing widgets are voluntarily leaking data about users to third parties.
In exchange for freely distributing a sharing widget, companies like ShareThis target users by tracking users’ sharing activity through the network of websites that have the widget installed. They collect data about what users like, read, share, save, and more. This data is then augmented with additional targeting data and sold at a premium.
To truly understand the magnitude of data generation and collection that occurs, you can do a fun exercise using a browser plug-in. The developer disconnect.me has created a plug-in for the Google Chrome browser called Collusion that graphs in real time all the data collection that occurs during your web browsing. Figure 1.2 maps the web of data collectors associated with just 15 minutes of a web surfing session. Collusion provides an effective way to see a visual representation of data leakage.
Figure 1.2. Data Collection Map: An example of how data is collected with just 15 minutes of a web surfing session.
The end result is a robust data set that can be sliced and diced using data management platforms (DMPs) such as Demdex or BlueKai. DMPs are cookie data warehouses married to analytics engines that have massive horsepower. They are designed to clean, manage, and integrate data with all different types of first-party and third-party data that a company might have or purchase.
DMPs offer advanced capabilities to find trends and to understand and segment audiences based on user attributes, media consumption habits, and more. Many large corporations with complex segmentation needs, such as those within the Fortune 100, have migrated to utilizing DMPs to increase performance and improve efficiency through optimization and targeting.
We identify some paid media data sources that you can use to gain deeper audience insights and understanding in this chapter.
It’s not just the emergence of earned media that is new to the digital data and analytics landscape. Owned media assets offer more options than ever to gather competitive intelligence, user experience feedback, real-time site analytics, and testing for site optimization in addition to richer-than-ever-before clickstream activity analysis.
Your goal should be to tie the insights and data from each media channel to one another to tell a deeper story. These are not redundant analytics options, meant to be an either/or decision. Remember, they complement one another.
Trying to decide which of the data and analytics options to implement can be overwhelming. Your choice depends on your defined goals and learning agenda. You can read more about the details of defining clear and specific objectives in Chapter 2, “Understanding Digital Analytics Concepts.”
Developing a learning agenda is a useful technique in defining the boundaries of where to focus your analytics efforts. Such an agenda essentially defines the specific questions you are trying to answer about your audience and acts as a guide for your analysis during a project to keep you focused.
In the following few sections, we dive into each of the considerations for analytics on your owned media properties.
Keeping an eye on competitors is nothing new. There is quite a bit to pay attention to these days, and there are many tools aimed at helping you understand what your competitors are doing on both their owned media assets and social media platforms. You should use a combination of free and paid tools to access the data you need for competitive intelligence.
Free tools from Google, Alexa, and Compete can provide competitor website and audience profile data. Paid versions of these tools offer more robust data on consumer behavior data that you can use to answer specific questions such as these:
- Which audience segments are competitors reaching that you are not?
- What keywords are successful for your competitors?
- What sources are driving traffic to your competitors’ websites?
It’s not difficult to gather competitive intelligence data when it comes to social media. Most of this data is freely available to anyone who is interested in it. Quick-and-dirty approaches using free versions of tools such as SimplyMeasured can provide a wide range of competitive intelligence across several social platforms, including the following:
- Facebook competitive analysis
- Facebook content analysis
- YouTube competitive analysis
- YouTube channel analysis
- Twitter profile analysis
These higher-level reports do not always provide the depth you need. To get more information, you can use specialty tools that focus on particular social platforms and can provide more detailed data and metrics. For example, EdgeRank Checker focuses exclusively on Facebook analytics for a specific industry and compares them to your brand page. Reports like the ones you get from EdgeRank Checker provide analysis and insight into post-grading, page recommendations, trending of post performance over time, and keyword engagement analysis.
Clickstream (Web Analytics)
Counting onsite activity using web analytics is the oldest form of digital analytics. (Remember log file analysis of website hits?) Thankfully, web analytics tools have come a long way since those days and now offer a full suite of advanced measurement and analytics features, including the following, among many others:
- Custom dashboards—Leading platforms offer the ability to create custom dashboards, personalized to your site and conversion events, including threshold notifications for key events and custom key performance indicators (KPIs)/goal definition.
- Content analytics—Content is king. Identifying best- and worst-performing content is invaluable. You cannot optimize what you don’t measure, and content analytics gives you a window into what content users are consuming and interacting with most (and least). Internal page analytics and local site search reporting also provides useful insights into what users are looking for.
In addition to content analytics, several leading web analytics platforms, such as Adobe Omniture and Google Analytics, also allow for content experimentation. This feature gives you the ability to test variations of content and user experience on your website pages in order to determine which specific permutations yield the most conversions and highest user satisfaction.
Mobile analytics—The mobile web is in the midst of an explosion, and it hasn’t yet reached critical mass. Mobile analytics is no longer only a nice-to-have feature; it’s a core requirement to provide an effective mobile experience, whether through a mobile-optimized site or mobile application. Web analytics tools have incorporated mobile support, and they offer a robust set of features to measure any mobile content across any mobile device. Mobile analytics provides answers to common questions such as these:
- Where is my mobile traffic coming from?
- What content are mobile users most interested in?
- How is my mobile app being used? What’s working? What isn’t?
- Which mobile platforms (and versions) work best with my site?
- How does mobile users’ engagement with my site compare to traditional web users’ engagement?
Your website exists for a reason. More specifically, it exists for a set of specific conversion events. Leading web analytics platforms provide insights regarding this key area and answer questions about how onsite user behaviors lead to conversions (regardless of what those may be—sales, registrations, leads, and so on).
One of the most advanced capabilities offered in the area of conversion analytics has to do with multichannel funnel attribution. You’re no longer limited by the “last click” attribution problem. You can now gain insight into how much each digital marketing or advertising channels are contributing to specific conversion goals, including paid search, paid display, social marketing, email marketing, and more.
Another useful feature is user experience path visualization, which enables you to determine the highest-performing visitor conversion paths. What are the most common and highest-performing entry points onsite? Where are users getting stuck along the path? What step in the user experience journey causes the most abandonment? These are all key questions involved in optimizing the user experience.
Finally, some leading platforms, such as Blue Fountain Media, offer attribution modeling. Want to build predictive models to attribute conversions to specific channels to better gauge your channel mix and investment? Now you can.
Custom segmentation enables you to personalize your web analytics in the way that’s most relevant to your business. It allows you to define custom variables and classify individual user segments or groups.
Analyzing your traffic in aggregate might be interesting, but it isn’t advised. As Avinash Kaushik—one of the foremost experts on all things web analytics—has repeated over the years, data in the aggregate is useless. You must segment or die. This has never been more true than it is today. It’s one of the biggest issues we currently face with social platforms and the data they generate. Most social platforms provide vast amounts of data, but in the aggregate, which is not terribly useful. Facebook, for example, provides basic segmentation by certain demographics, such as age, gender, location, and a few others, but as of this writing, it doesn’t allow page administrators to segment their audiences in a meaningful way.
With custom segmentation, you can divide your audience into segments that mirror your customers and prospects, and this enables you to optimize and personalize the user experience for each. Custom segmentation also enables you to drill down into specific subsections of a site, such as visitors that converted or paid user behavior versus organic user behavior.
Visual overlays are a nice-to-have but useful method for viewing web analytics data in a visual format. This typically includes overlays in the form of heatmaps, clickmaps, and geomaps that show physical locations of website users.
We live in a world of application programming interface (API) integration. Mashing up one data type with another can reveal new and incredible opportunities. Thankfully, leading web analytics tools provide APIs for precisely this purpose. The ability to connect website user data with other types of data is a reality. Chapter 23, “The Future of Digital Data: Business Intelligence,” touches on this topic.
Social Media Reporting
Some people like to categorize any social profile in the earned category, but we disagree. There is a difference between real “earned media” through word of mouth, buzz, and so on and direct investment in maintaining a brand presence on a social platform. Maintaining a brand presence requires investing time and money on behalf of a brand, which is why we have included social reporting in the owned media category.
Many web analytics tools now provide varying degrees of social analytics reports. These channels do not exist in silos but must work together. Converged media is the future. In an effort to measure the specific effect that social activities have on the metrics and goals that matter, we see these tools in the early stages of social attribution. There are indeed limitations now, but they offer the ability to
- Identify which social referral sources send the most engaged visitors to your site.
- Learn which brand content social visitors engaged with most and what visitors are sharing most.
- Learn how users engage with your brand content offsite, on websites that are not your own.
- Segment and measure the performance of individual social media campaigns.
- Create custom segments for users on individual social networks, such as Facebook and Twitter. This is a useful feature because segmentation enables you to truly understand the differences between your user groups and provides you with insight to optimize and personalize the user experience.
- Identify which user-generated content is responsible for amplifying brand content; this contributes to true “earned media.”
These social report integrations for web analytics tools do have some shortcomings. Data quality concerns, reporting inconsistencies, and overall data coverage are issues. For example, Google Analytics currently supports some major social platforms in its tracking, but it excludes others. This creates blind spots and can lead to questionable analyses and decision making, based on a false view of user behavior and the digital landscape.
Although an integrated solution containing both web analytics and social analytics is ideal, at this point you are better served by using best-of-breed tools for each. The social analytics landscape is immature, fragmented, and, frankly, a mess. There is too much choice, there are too many redundant tools with little to no differentiation that have created an incredibly frustrating and difficult experience for buyers. The future holds more mergers and acquisitions to reduce these problems, much as it did in the early days of digital with the early web analytics vendors.
User Experience Feedback
There are tools that enable you to gather very specific qualitative user feedback through onsite surveys. Some call this “voice of the customer,” and others call it “visitor feedback.” All these tools share a common functionality, which is a continuous and consistent measurement of the user’s website experience.
Clickstream analysis can provide insight into the volume of activity by page and conversions. It’s a starting point, but it provides an incomplete picture of overall site activity, and it’s why companies try to collect specific feedback. User experience feedback can be crucial for answering the following questions and determining how users feel about the overall website experience:
- How would you rate your overall website experience?
- What was the primary purpose of your visit?
- Were you able to complete your primary task?
- Could anything about your website experience be improved?
Site-survey solutions, such as those from iPerceptions and ForeSee Results, provide additional benefits, such as web analytics integration, threshold-based alerts to notify you about significant changes, and benchmarks of vertical industries for comparisons.
The combination of quantitative clickstream analysis to determine what is happening onsite and qualitative user experience feedback can answer many questions about what is working with an owned media asset and what needs improvement.
Real-Time Site Analytics
The newest kid on this block, real-time analytics, overlaps with traditional web analytics in terms of technical capabilities, but real-time analytics runs at hyperspeed. Real-time analytics is all about what’s happening on your website right now.
Real-time solutions from companies such as Chartbeat and Woopra were created to solve problems for those on the frontlines who are responsible for managing publishing and media sites, but they’re useful for just about any company. The assumption is that the end users are in sales, marketing, or content roles and aren’t looking to immerse themselves in data and reports. They’re focused on optimizing the user experience for each audience segment in real-time.
Real-time analytics tools provide analysis and reporting of what users on your site are doing on a second-by-second basis. You can use these tools to determine how active your users are on a page, what page interactions they are most engaged in, and what content topics and types are most consumed, shared, and ignored. Whereas web analytics focuses on clickstream analysis, real-time site analytics focuses on everything else that happens between clicks.