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SOCIAL MEDIA ANALYTICSEFFECTIVE TOOLS FOR BUILDING, INTERPRETING, AND USING METRICS
By MARSHALL SPONDER
McGraw-HillCopyright © 2012 Marshall Sponder
All right reserved.
Chapter OneThe Conundrum of Social Media: Where's the ROI?
The average social media campaign requires between three months and a year to show results. What kind of numbers can be derived from social media to show if a campaign is successful? How much information is sufficient on which to base future strategy? These questions, among others, are those that users of social media want answered.
If Starbucks were to offer a $5 coupon to everyone on Twitter, it would likely get a great response—but how valuable would it be in the long run? Would such a campaign ultimately increase customer loyalty or drive long-term sales? When we need benchmarks to evaluate return on investment (ROI) effectiveness, marketing professionals first should determine the duration of a campaign and what milestones or standards they want to reach.
In 2004, vendors began developing and offering social media analytics platforms and providing data-crunching reports. As a matter of fact, the first recorded use of the term social media occurred in 2004, according to Merriam-Webster's Online Dictionary. (More reporting and analytics platforms have been appearing, almost daily.) Although these platforms were expressions of data collection through a variety of lenses, at that time, no industrywide accepted standards and practices had emerged.
With so many advances rapidly taking place, including the promise of merging disparate data (including site analytics, search traffic, geolocal checkins—à la Foursquare, Face-book Places, and Gowalla—along with customer data, such as e-mail and receipts), it appeared that market researchers and analysts would be better able to understand customer behavior stemming from social media, and businesses would be able to act on that behavior in real time or soon after, with actionable responses to the results of analytics. Through my own research, I observed a 400 percent increase in searches on "social media" in search engines and in social media monitoring tools (such as Alterian Techrigy SM22) took place in the third quarter of 2009. This increase in social media mentions may have been a direct result of Google's inclusion of Twitter and Facebook updates in search results. This news indicates a fuller and accelerated integration of search engines and social media for the foreseeable future.
In 2010, the social media analytics ROI discussion turned red hot. At the time of this writing, there were at least 8 books on the topic of social media ROI available on Amazon.com and 16 on social media analytics. What are known as social listening platforms are the collection and analysis of online mentions in Facebook and Twitter, geolocal check-ins, photo-sharing sites, blogs, message boards, forums, and online commentary from mainstream media produced by readers as well as music-sharing sites such as Last.fm and Pandora. However, there is still so much difference between the benefits and costs of social listening and information on what the platforms and tools actually can provide that there is clearly room for at least one more book—one that can provide an authoritative voice for the analyst and analytics.
Nobody has talked about the subject seriously and in sufficient depth to make enough of an impact. In the following pages, I share my own opinions regarding how analysts performing social listening tasks are regarded, how much time reports should take to create and develop, and additional costs associated with producing actionable data.
Many people have read my WebMetricsGuru.com blog over the past six years and can vouch for the fact that I know social media, search, and Web analytics quite well. It's gratifying that I'm considered by the industry to be a practitioner, a hands-on analyst, and an expert in the field. I am not a journalist or conference promoter; what I write about is the very work I'm involved in and have pondered over deeply for several years. Furthermore, if I have not been involved in something personally, I almost always know people who have been, and I've wrung the salt out of their wisdom at conferences, bars, and tweetups. I'm also close friends with many of the leaders in this field, many of whom have contributed to this book case studies and various insights you will encounter in the following pages. I'm fortunate to be in a position to see the social media metrics industry in a holistic way. As a result, I've created my own view based on personal experiences that I provide to the industry as a whole and to my readers in particular in this book.
Analytics Platforms and Their Users
The language of listening platforms has well surpassed the level of typical business users' normal vocabulary. By using arcane words that almost no one who runs a business is familiar with, the platform providers have implemented reporting and analytics that are failing to directly inform most businesses.
The disparity between vocabularies was created partly by design; using cutting-edge technology based on search engine crawling was an experiment, and companies mining Web data—getting their hands dirty, so to speak—were exploring how to gather information and what to do with it. Companies such as Collective Intellect and Brandwatch were pushing the edge of what was possible in 2004 to 2005, when the industry was first born.
The average business user, ageny owner, or stakeholder lacked (and still lacks) the understanding, patience, or sophistication to utilize these listening platforms effectively. As a result, these people hire analysts to access the platforms for them and to provide reporting data and dashboards. Dashboards are reports that give users a high-level snapshot of how their campaigns and business initiatives are performing online. Dashboards can be quickly viewed or shared. Now it seems as though analysts need to be experts on the businesses and industries they are monitoring in order to do effective listening by supplying the necessary context and perspective that are still too complex to program into a listening platform. This is similar to the way financial industry analysts or hedge fund managers need to understand the businesses they are reporting on, investing in, trading on, and profiting from in order to be effective as analysts.
However, the model of analyst as business expert is directly at odds with the current staffing practices at many types of agencies covering the spectrum of marketing, public relations, communications, and even large and medium lines of business that have not yet understood the best applications of the technologies being employed, or what they lack.
Using a group of interchangeable analysts, shifting them across reports, and thereby making analytics a "report factory" is an example of a common practice based on a fundamental misunderstanding of how effective listening and analytics work, and it is a poor way to perform actionable reporting or analysis. In this book I delve into why and how the current practice should be turned around by explaining how listening systems actually work.
All indications are that within the next couple of years, business models and listening platforms will mature, eventually converge, and then become integrated. This is yet another reason why it is the right time for a focused look at social media analytics.
The ROI Dilemma
Social listening platforms have recently begun to come up with ROI calculations and dashboards designed to meet the needs of business users who want this level of reporting. Without the ability to accurately measure social media, however, it's hard to see how accurate ROI calculations can be done well. While many people may be willing to settle for "good enough" measures and estimates of the value of a tweet or Facebook fan or friend, in the coming years businesses will desire more than "good enough" proxies for, doing calculations of ROI. They will want, and are even now asking for the hard numbers with all the data, much like a financial statement.
As you will read in later chapters, point of sale systems, commonly termed POS systems, will become ever more relied upon to capture social media transactions directly to cash registers. It makes perfect sense that the cash register be enabled for social media, especially because all the technology to make that happen is already here.
In the Apple store, there are no cash registers, and all transactions are done from iPhones and iPods with specially equipped POS system devices; we will be seeing more businesses moving over to mobile POS systems, and those systems will increasingly interface with social data, allowing for more accurate and actionable ROI reporting.
The social media listening platform Marketwire Sysomos created a program called Sysomos Audience, which is designed to match visitors to Web sites a business cares about (such as competitors or other interesting outlets) and then to score those data in the form of visitor value (in currency). This information can help business owners decide where to spend their marketing budgets and where to focus their social media outreach.
Sysomos Audience is an attempt to merge Web and social media data to produce superior ROI metrics—the kind that, up until now, we have not had in social media—and when available data are merged intelligently, patterns will emerge that would otherwise have remained invisible. Once all the necessary data are assembled and defined in a lexicon a business owner can relate to, the data become actionable.
Social Media Enablement Audit
Although social media ROI is hard to track and most businesses are just beginning to realize the level of investment in analytics required for the necessary tracking, the business climate and analytics platforms are maturing. One of the goals of this book is to map the landscape of the playing field for social media analytics and to help business owners and organizations decide how and what they should invest in. With the rapid increase of mobile technology and geolocation, much more data and the insights derived from them need to be collected, processed, and understood so a business owner can act on the information.
According to Hubspot's Kipp Bodnar, "If you are a marketer, Facebook Places demonstrates location-based social networks are transforming from a trend into a mainstream feature of social networking."
Also, a new feature was added to Facebook allowing business owners to check in the same way users and customers do. This method will make it easier to show social media ROI because mobile devices, geolocation, quick response (QR) codes (a form of mobile bar code), and point of sale systems are rapidly becoming instrumented to keep track of social media outreach. When a customer checks into a location, the opportunity to engage with the customer directly increases satisfaction and loyalty; it also provides actionable information for social media analytics and can feed directly into ROI calculations that businesses often seek to measure.
The rapid increase in QR codes extends the concept of monitoring social media campaigns into the three-dimensional world, much as webpages have been monitored for several years using Web analytics from such platforms as Google Analytics, WebTrends, and Adobe Site Catalyst.
The New York City—based restaurant Havana Central conducted a series of social media analytics projects in 2010 with Cecilia Pineda Feret, the community manager, who managed social media outreach for the restaurant chain. With the results, we collaborated with Compete.com to create a white paper and webinar on how to find ultraviolet data to show social media ROI as a result of community outreach and other marketing campaign initiatives that can be tracked all the way to the cash register. "Ultraviolet," in this context, refers to data that are often not being tracked for business value and can be uncovered and made trackable (thereby adding business value to the data a business already has) by using an audit process I devised to identify and enable the missing analytics tracking.
An issue that sometimes arises in discussions regarding social media analytics is how to capture streams of rich data that usually exist in silos. In many cases the data necessary to determine outcomes or analyses come from separate, disparate sources or analytical tools. I also refer to this fragmentation of data, often necessary from a business perspective, but a roadblock from the analytics perspective, as "ultraviolet activity."
As a result of this line of reasoning (that all information can be tracked if we care enough to collect the data), I created my Social Media Enablement Audit process and spreadsheets. This product allows any business, marketer, or analyst to customize an audit around business data sources (vertical) and campaigns (horizontal).
The Social Media Enablement Audit doesn't solve the problem of capturing missing data as much as it leads to solutions that can be put in place to capture pertinent data. Once the data are captured and put into a usable form, you can decide what to do with them. Better yet, this helps indicate which social media metrics or social media ROI formula to plug the data into. Without the right data no ROI formula will be of much help. That's why the measurement of social media ROI is not easily achieved.
One of the goals of the Social Media Enablement Audit is to help determine which data inputs are required to truly calculate ROI. When essential data are missing, such as a common key (a customer name or e-mail address), then what is collected is often unusable. I designed the audit as a productivity tool to assist both in acquiring information and in providing an ROI outcome for analysis of social media metrics.
In April 2010, the Altimeter Group and Web Analytics Demystified released a social marketing framework to answer an industry challenge of business owners who could not measure social media ROI. They aligned some of the smartest minds in Web analytics—such as John Lovett (an ex-Forrester analyst) and Eric T. Peterson (an ex-Jupiter analyst), both of the Web Analytics Demystified firm—along with Altimeter founder Charlene Li's (another ex-Forrester analyst) and developed self-funded research for a social marketing analytics framework. They made a collective effort to examine the best ways to measure the rapidly changing social media marketing landscape.
While testing the social marketing framework on Havana Central (using Radian6 and Sysomos I found there was not enough guidance within the Altimeter framework to effectively apply the formulas to real marketing problems or test if the formulas were correct. It also seemed that too much of the data necessary to populate formulas was missing or ultraviolet. There will have to be more solutions to measuring social media, and there will have to be more specific guidance for how to apply them in order to provide actionable insights.
Guidance for Social Media Analytics
Social media analytics is an emerging field, emanating from the boom of connectivity and interactive tools and sites associated with lifestyles and activities in the digital realm. Perhaps an established organization such as the Web Analytics Association (webanalyticsassocation.org) and the Internet Advertising Bureau (iab.net) is the right place for the formulation of guidance and standards for the practice of social media analytics: both widely represent industries for which social media analytics is crucial. The IAB, for instance, did wonders for online video monetization by coming up with the VAST (Video Advertising Standards Template) standard.
Based on my experience as a board director at the Web Analytics Association from 2007 to 2009, I know firsthand that standards are necessary for the social media analytics field to mature to the point where it can interoperate with other business research disciplines. To that end, the UK-based IAB Social Media Council has launched an initiative with a focus on standards drafting. Richard Pentin's "New Framework for Measuring Social Media Activity" defines the four A's of social media measurement: awareness, appreciation, action, and advocacy. Pentin's paper proposes defining and measuring core key performance indicators by social media platform, marrying soft metrics with hard financials.
However, even in the absence of industrywide standards for social media measurement, there are other means available to attain more complete Web data, but they are vendor-specific. One supplier of such a service is Medallia, a company offering what it calls "360 degree analytics." Medallia reached out to me in mid 2010 to demonstrate its efforts in this respect. Medallia's solutions are more thorough than what Web analytics normally produces, providing several surveys along with deep dives, or custom analysis, that explore a site issue or problem closely in order to create a personalized customer-experience page for each visitor, along with real-time problem solving (for example, dealing with an irate customer).
Among the operational data Medallia handles are customer-relationship information such as call-resolution time, financial data such as purchase history, and Web analytics data such as data from later or earlier visits. Medallia alerts stakeholders immediately regarding unhappy customers and supplies customer-recovery workflows to help organizations address many at-risk relationships.
On yet another social media analytics front, metrics from Flash and Rich Media creative content have been among the most difficult to capture. Many sites employ animations or Flash movies driven by a programming language called ActionScript. ActionScript requires additional site analytics enablement by a creative-content developer working with the site analytics group, and for many reasons this is hard to coordinate and put into place. For example, the Flash and Ajax elements of a Web site do not generate the page view information that most Web analytics platforms require in order to track visitor activities. In addition, although Flash content can be measured with additional scripting, it may be expensive to keep in sync with site analytics tracking, or there may be Flash elements of a site that were developed previously and the original programmer has moved on, making it unclear how to update these assets.
Another reason for Flash elements of a Web site being ultraviolet: site owners are often ignorant of tracking requirements and don't know what to do with the data when they collect them. Widespread adoption of the HTML 5 standard may solve some of these problems, but that is still a few years away. As a stopgap measure, in 2009 Google released a tracking specification for Ajax code that allows any site to track Ajax pages by creating an additional static page for that content. Still, creating content that is fully trackable by analytics is a formidable challenge that few organizations have fully met.
Excerpted from SOCIAL MEDIA ANALYTICS by MARSHALL SPONDER Copyright © 2012 by Marshall Sponder. Excerpted by permission of McGraw-Hill. All rights reserved. No part of this excerpt may be reproduced or reprinted without permission in writing from the publisher.
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