A Brief History of Social Media Measurement, and a Prescription for Web Analytics

Architecting Better Data-driven Digital Experiences

A Brief History of Social Media Measurement, and a Prescription for Web Analytics

The Challenge
Common sense asserts a wealth of marketing opportunity residing in the correct analysis of consumers’ publicly shared (and digitally documented) interests and interactions. However, there are significant challenges in separating valid information from noise, then structuring that valid data to draw actionable insights with the same level of confidence that businesses expect from their market research, web analytics insights, and other Business Intelligence functions.

The first generations of social media measurement and analysis have addressed these challenges as best they could. To advance beyond pseudo-science into the realm of truly actionable business analytics, the next generation of analysis will need to draw from the established standards and best-practices of organizations’ existing analytics functions such as web analytics, with established competency in building data-driven management practices from digital analytics.

Current State
Current approaches to social media measurement come in two forms: 1) content-based monitoring or “listening” evaluates the content of conversations to assess current state perceptions, and guide future engagement. 2) Context-based “social graph” analysis evaluates relationships and interactions within and across the social graph to assess networks and their capability to drive business objectives.

Businesses are currently trying to apply these two forms of measurement in various combinations for several objectives; to avoid or respond to brand crises, to build brand awareness and affinity, to enhance customer experience and loyalty, and even to influence sales.

The first real corporate attention to social media emerged around some high-profile brand crises. As these were crisis communications problems, PR/communications was the natural organization to step in and address the crisis management strategy through social media channels.

This initial touch-point with social media prompted PR teams to propose movement into proactive attention to communications, particularly with a focus on “influencers” and communities, a logical extension of PR’s expertise in placing content with outlets that could generate impressions within relevant audiences.

The initial reactive crisis management objectives fueled a social media monitoring technology industry, which then quickly adopted the “influencer” idea to sell services supporting proactive social communications. Today many existing social teams have grown from PR practices, and are striving to deliver value through proactive social engagement of various levels of influencers.

Around the same time, another natural extension of the organization into social media measurement emerged around customer support. In many organizations, the business value of investment in social communications were not immediately apparent, (after all, how can you ever prove that a crisis was avoided?), so managers strove to find another driver of value, and the potential to address customer issues uncovered through social media was the most apparent candidate.

This emergence of this approach saw the overlap of call-centers and PR within these efforts, since a reasonable argument could be made that a visible public complaint was indeed a PR issue. This overlap, though often political and raucous for those involved, have helped to establish the need for the removal of organizational silos and a more holistic notion of customer experience, which seeks to generate engaged advocates for the brand through proactive experience and brand building and responsive customer and relations.

Missing Links
As this first round of social media for business has evolved, several established practices that would seem to have a natural fit with social media measurement – namely Customer Intelligence and Market Research, Direct Marketing, and Web Analytics – have come late to this first round of aligning social media with business.

The hesitancy of these organizations to adopt the first round of social media measurement practices has likely been rooted in the nature of the social media data available to them. While PR has long been accustomed to working from measures that at best extrapolate and estimate the potential impact of their work across broadly defined public constituencies based on volumes of impressions, the general audience served by an outlet, and sentiment of coverage, these other disciplines are built around clearly modeled and structured data collection (a fired tag, a closed-ended survey response) and well-defined and validated segmentation of existing and potential consumers using demographic and behavioral data.

Thus, while the first generation of social media measurement allowed PR to gain more granular insight (and entry) into public conversations about the brand, it did so with what was typically a non-representative sample of a company’s overall market, without verifiable means of segmentation of the sample population, and with meta-data derived from qualitative tools like sentiment engines that were highly inaccurate.

Thus web analytics’ slow move to social media measurement has also been rooted in the nature of the data available – in essence, web analytics has viewed social media as just one potential referrer amongst many, and for many large firms, certainly one of the least performing channels compared to email marketing, organic and paid search, and online advertising.

In terms of understanding customer opinion and behavior, web analytics has been able to use cookies and site tagging to collect detailed information on site visitors’ behaviors on the site across the web. If a customer has willingly provided additional personal information, then the tracked behavioral data can be coupled with demographic and psychographic data to give insights around very specific segments of users who are known to be using our site. For the purposes of managing experiences on a website, available forms of social media measurement have had little applicability compared to this sort of data.

Getting Social
Increasingly though, web analytics functions are mirroring the interconnectivity of the digital world with a more holistic approach to serving digital marketing. This evolved function is what Critical Mass calls Marketing Science, which takes an integrated view of how digital measurement can work beyond website performance metrics to provide integrated insights that serve to optimize the comprehensive digital experience that spans from objectives through awareness to a comprehensive digital experience, and ultimately to conversions.

From a content measurement standpoint, Marketing Science should approach social media monitoring and measurement with the same mindset it is bringing to advanced web analytics functions such as testing and optimization. As social media may be an important step on the path to conversion, web analysts must understand how to properly attribute social media to conversions, and must help guide the optimization of social media in that context.

The context measurement approach to social media measurement fits even more strongly with the strengths of web analytics. By drawing social graph data directly from primary and secondary social network APIs, analytics functions can use structured quantitative data to derive the types of objectives-oriented ratios and KPIs delivered through current digital analytics reporting and dashboards.

Web analytics has an established competency in building a data-driven management culture and providing business insights from digital data. Thus, marketing science is a natural candidate to advance organizations from the raw (and dumb) volume or “count” metrics such as “Followers”, “Likes”, “Views” etc. to give managers integrated performance insights from ratios such as “comments/post”, “comments/page likes”, “links followed/re-tweet” and “conversions/social click-through”, which will be even more valuable when used in conjunction with the content analysis mentioned above.

Finally, as new solutions begin to align social media profile, content and relationship data with existing CRM databases, Marketing Science has a clear role in developing digital strategy and performance insights from these combined data-sets.

Many disciplines have faced significant challenges with emerging technologies, methodologies and organizational readiness to bring social media measurement to its current state. Web analytics must now help advance the cause by bringing its competencies, experiences, requirements and standards to bear on the next generation of tools and approaches.