Social media has been maddeningly short on evidence. While there are plenty of social media true believers, there aren't yet a lot of truths. And, because social media is contextual—the right tools and the right use of them depend very much on the user, intended audience, and desired outcomes— it can be difficult to figure out which social media tactics best align with an organization's marketing strategies and measurably advance its operational objectives.
So, how can you figure out which tools are right for your needs? How can you separate truth from belief? By using a scientific approach to social media.
All scientific inquiry starts with questions: Why? How? What? Scientists answer those questions by applying the scientific method, a series of steps designed to produce evidence that reveals whether a proposed answer to a particular question — a hypothesis — is, in fact, true. We can use the same approach to provide customized, repeatable, and documentable answers to our questions about social media, and to produce the measurement we need to support our efforts.
So grab your lab book (you'll need it!), and let's get started.
Defining the question provides a framework on which to build the rest of the approach. The question can be broad ("How can we best use social media in our business?") or granular ("Is podcasting an effective way for us to generate prospects?), but it likely already exists in your head ("What is all of this stuff about, anyway?").
To answer that overarching question, you need to understand the environment to which your question applies. That happens through listening to if and what your current and potential customers and competitors are saying, and watching where and how they interact with various social media tools.
Investigation provides the framework for your experiment, by defining and documenting parameters for the scope, audience(s), content, tools and resources, desired outcomes, and basis for measurement.
Scope. Your observations likely will provide clarity about where it makes sense to get started. So, what is that scope? Will you be answering the question as it relates to your whole organization? A department? A specific initiative or cause? An individual?
Audiences. For that scope, what audience(s) make the most sense? Where are they? What tools are they using? What are they saying about you? How do they perceive you?
Content. For your defined scope and audience, what are the best types of content? On what topics? What content already exists? What do you need to generate?
Tools and resources. For your scope, audiences, and defined content, which tools and tactics make the most sense? What else do you need to use them effectively? People? Time? Money? How will you get what you need?
Outcomes. What do you want to have happen? The classic marketing funnel can be useful here: Are you trying to achieve awareness? Comprehension? Participation? Loyalty? Support? (And no, "all of the above" isn't an option!) Defining your desired outcomes up front materially changes what the rest of your experiment will look like.
Measurement. What does success in your desired outcome look like? How will you measure it? And how will you tie those measures to concrete business results?
A hypothesis proposes an answer to the question you defined in Step 0 and sets the stage for your social media experimentation. It states the specific strategy you're testing and the measurable results you expect it produce. Thankfully, after the work of observation and investigation, this one's easy.
For [SCOPE], the [CONTENT] from [SOURCES] used
across [TOOLS] will produce [MEASURED][OUTCOMES]
with [AUDIENCES].
This step has two phases: design and execution. In design, you're outlining the steps you intend to take, when, and how — and at what point you'll declare the experiment over so you'll know when to stop and assess your results. In execution, you implement the steps you've outlined.
As in any proper experiment, document the steps as you take them. If you didn't end up taking a planned step, note why. Note if a step happened sooner or later than intended, and why, as well as other significant events (a media outlet referenced an article on your blog, for instance). As you execute various parts of your plan, log your impressions and immediate results. Check regularly on your measurement data points and document those, too.
The work of all the previous steps leads here, to figuring out if your hypothesis — your proposed answer to your Step 0 question — was correct or not. In other words, how did you do? What were the results? Did they meet, exceed, or fall short of your expectations?
To answer why the results are what they are, overlay your results with your outlined steps and significant events (launched blog, media mention, conference appearance, etc.). Do changes in your measurement points seem to relate to any of the steps or events?
Aligning steps and results with data helps us play one of the scientist's most important roles: the skeptic. When looking at your results, look closely at the "other significant events" as you explain what you see. Are there events, beyond your control that could explain positive or negative movement in your measurements?
Ultimately you will either confirm your hypothesis or disconfirm it. If you've confirmed your hypothesis, it's time to define a new question. Perhaps you want to explore a change in scope, or how best to move from one phase of the consumer cycle to another (For example: "People know we exist, but aren't clear about what we do. How can we best use social media to aid comprehension?")
If you weren't able to confirm your hypothesis — either because the desired results weren't there, or the causal relationship to your efforts isn't clear — your analysis will have identified areas for further exploration, which will lead to a revised hypothesis, a new experiment, and further analysis.
The gaining of knowledge is an ever-evolving process. Your involvement with social media should be the same. People change, tools change, norms change, behaviors change, attitudes change — there will always be new questions to answer.
But there's a reason the scientific method has been around so long: It sets out a rational approach to tackling even the most complicated questions with clearly defined terms and clearly defined measures of success. And, as a social media scientist, you'll have the tools to separate truth from belief.

Tamsen McMahon is Director of Digital and Strategic Initiatives at Sametz Blackstone Associates, a Boston-based, brand-focused consultancy that integrates strategy, design, and digital media to help mission-driven organizations better navigate change. She can be reached at This e-mail address is being protected from spambots, you need JavaScript enabled to view it .
This article, in substantially the same form, originally appeared on iMedia Connection.