But, the Vitamix (a high speed blender) has shifted my understanding and approach to food. I’ve learned to use different types of raw foods to fuel whatever activity I’m about to engage in (tip: try kale for mental clarity).

This shift has improved my performance and productivity both mentally and physically (some in my family even point to a sunnier disposition) — even though I never considered my nutrition to be lacking or my performance (or disposition) to be something that was holding me back.

What does this have to do with social media marketing tools? For now, all tools pretty much fall into the Aero Press category. And, what we really need is a Vitamix.

Like the Aero Press, today’s tools help marketers accomplish things they already knew they were going to do each day, like posting to various social networks and responding to customers in social channels.

These tools also help social marketers find the answers to things they already knew they needed to know – like how to time those tweets or which customers to focus on engaging. While all that is unarguably useful, there are some things this generation of tools simply cannot do, such as:

• Finding solutions for problems you didn’t know existed
• Finding answers to questions you didn’t know to ask
• Discovering insights that will fundamentally change the way that you use/approach social media in the first place

Transformative Analytics

The next generation of social media marketing tools will do more than organize, manage and spit out pretty reports full of out-of-context facts. Transformative analytics will be at the heart of these tools, meaning that the data provided will go beyond standard metrics about activity and/or a single encounter in social channels.

In fact, this next generation of tools will be applicable to not only social media, but to all marketing. Below are three characteristics I very much expect to see in next-generation tools:

1. Broader Data Synthesis: As a (former) vendor in this space, I can personally attest to the difficulty of aggregating data from different social channels and combining it with even the most obvious sources like Web analytics data. And, this is only the tip of the iceberg in terms of the data that actually needs to be aggregated.

Truly transformative analytics will require combining data from sources beyond social channels or even online sources, including data from multiple corporate databases and a very long list of third-party sources.

2. More Information On People: We’re not going to get better at marketing — particularly social media marketing — until we get a lot better at knowing more about people. Understanding the person behind the action (or interaction) is critical to innovative use of social media. The big issue here, of course, is privacy.

3. Better Ways To Work With Data: At a granular level, I’m talking about better visualization, more flexibility with queries, and a more robust set of work-bench features. But overall, what I think we need are tools that emphasize data and pattern discovery rather than tools that emphasize data confirmation. (Think “The Machine” but without the Orwellian overtones.)

In social media marketing, as in just about every information-centric field, the challenge will always be to develop actionable insights into data of ever-increasing volume, diversity and complexity.

Today’s Tools Vs. Transformative Analytics

Do shades of all of these things exist in some of the tools on the market today? Sure. But the reality is that we are a long way from truly achieving transformative analytics. In fact, there is a long list of significant barriers to overcome. (Chief among them: a viable business model that balances the expense of such an undertaking with the market’s preference for cheap tools on an SaaS basis.)

Reality aside, what’s on your wish list for a silo-busting, next-generation set of social media marketing analytics tools? Let’s combine our perspectives, because we’ll never build it if we don’t start envisioning it.

But, as I’ve pointed out earlier, social listening data is just the tip of the iceberg. The variety and volume of data available to marketers keep getting bigger — and more interesting — each day.

Agencies that know how to harness and use social data creatively will profit and grow; those that do not will be left behind.  Below are a few prominent reasons why social data proficiency is a critical competency for the agency of the future:

Multi-Channel Success

Social data will hold the key to insights that lead to optimization — not just of social media initiatives, but of marketing in other channels and across multiple channels, as well. (As a simple example, consider the use of trending topics to inform content or campaigns — but the possibilities here are endless.) In fact, at the Forrester Research eBusiness Forum, 80% of respondents said they plan to use social data more in 2013 to inform campaigns in other channels.

Understanding & Predicting Buyers

Increasingly, customers will expect you to know them. Social data can play a pivotal role in building a deep understanding of customers (and also of prospects at various stages of the buy cycle).

This sort of knowledge will be absolutely fundamental for all marketing of the future (i.e., giving people what they want, when they want it and understanding consumers well enough to develop persistent relationships and predict behavior). Without it, the fall-back option is old-school marketing tactics whose efficacy is already waning quickly.

Client Demand

According to the InfoGroup study cited above, 70% of top global marketers plan to spend more on data-related marketing initiatives in 2013; and, as noted, many companies hope to expand their exploitation of social data. But, while many tools now available are good at collecting data and producing machine-based analytics from that data, it still takes a human to tell you what to do with the data. Clients will turn to agencies and other vendors in order to apply social data to a variety of marketing activities.

Competitive Advantage

When I hear the words “social data,” I am reminded of a friend who recently took up golf. His assessment? “It’s really easy to do poorly and really hard to do well.” So, too, with collecting social data and aggregating it into a form that allows it to be sliced and diced — and integrated with other possibly heterogeneous but relevant marketing data.

It is a time-consuming and resource-intensive process. (As someone who has built a social analytics platform from scratch, I can speak to this first hand.) More importantly, analyzing social data and finding the nuggets of wisdom that drive action requires deep knowledge and a wide range of fairly rare skills. Agencies that can master these complexities and offer their own “secret sauce” will be exceptionally hard to compete against. Moreover, this type of offering will be difficult to replicate by competitors who arrive late to the game.

Credibility

We live in a data-driven world. Having the analytics chops to provide clients with answers will build trust. Facility with social data analytics will come to be a measure of an agency’s maturity and sophistication. Unique services offerings built around proprietary tools and algorithms will allow adept agencies to leverage and grow existing customer relationships, while also competing effectively for new accounts.

As consumers increase their personal and business activities in social channels — and leave a trail of data behind them about those activities — the data and sources available will continue to grow and become more complex. Becoming proficient in social data is not simple — it takes time. But, agencies that master the challenges and opportunities will come out on top.

What is your agency or company doing to become more social data proficient?

While there are some commonalities between companies in similar industry verticals, my experience suggests strongly that there simply is no “cookbook” for social media measurement that applies universally.

Image via Shutterstock

What this means is that you can’t simply watch what the gurus are measuring (or the competition, or that guy you met at the conference) and adopt it as your own. 

To make matters even more complicated, there is an enormous amount of data available about social media – and only some of it will be valuable to you. Sorting through all of it to find the bits that will be useful simply isn’t an option.

These challenges often lead to two common disasters: Analysis Paralysis (nothing gets measured and sound bites like “how can I measure the ROI of my mother” are bandied about in meetings) and/or Mindless Reporting (a standard set of useless reports are distributed regularly but no one bothers looking at them).

Both will have serious, long term consequences in the long run, especially in environments where:

1.) Tactical decisions need to be made quickly by people who manage programs

2.) Senior executives demand proof of business value for every dollar spent.

Does anyone in social media operate in an environment where these conditions do not exist?

Below are three steps that will help you avoid this fate and create a measurement approach that is effective, actionable and customized to your unique needs:

Step 1: Document Function, Audience & Business Goals

Social media serves many different functions in an organization. For example, Twitter might be used to conduct product research, to support customers, or to execute a viral marketing campaign designed for lead generation.

In each of these instances, Twitter is serving a decidedly different purpose. It is likely being used by different stakeholders or operational groups (PR, marketing , etc.). Even more importantly, it is being used to target completely different audiences.

Clearly, what should be measured will be different in each instance. In the viral marketing campaign, for example, you may want to collect data on retweets of the campaign by influencers in a particular niche. To find out if the campaign moved the needle among prospects, you’ll need additional data beyond Twitter activity.

In the customer support example, Twitter metrics might include things like inbound customer support tweets and response rate. Again, you will need additional data (beyond Twitter activity) to judge whether the customer support initiative is leading to increased repeat sales or other business benefits.

Create a spreadsheet that documents the various functions being served by social media. Note the audience being targeted (this will help you make metrics more specific). Next, link each entry in your spreadsheet back to the appropriate business goal (this will help to ensure that you include metrics that can be linked back to the big picture concerns of senior executives).

Step 2:  Identify Action Drivers

What you will do with the data you collect? Make a list: which metrics might prompt you to take an action or a series of actions that impact something that is a very high priority?

Here is a simple example: Let’s say you are spending a significant amount of budget on paid Facebook initiatives. Understanding which posts are being shared the most organically can help you quickly decide which ones are worth paying to promote. The ability to quickly identify (or be alerted to) posts that have higher than average sharing could prompt you to take immediate action that could improve your paid results significantly.

At the very least, thinking through the most important actions that will impact things that are very high priority can help you make tough resource decisions by identifying what is absolutely necessary and what would be nice to have, but perhaps not crucial.

Step 3:  Connect Data Sources

The data that is necessary to create useful, actionable metrics, as well as metrics that speak to senior executives, come from many different sources. If you really want to measure what matters, you will have to do some work to connect those sources. (Yes, this involves IT; I’m very sorry.) The only question is how much work will be necessary.

Once you have an understanding of the metrics, you need (Steps 1 and 2), to conduct an audit of the tools and systems you are currently using that hold the necessary data. This will include things like CRM systems, web analytics tools, listening platforms, marketing automation tools, email management systems, and SMMS tools (social media management systems).

Next, look for the low hanging fruit. What sources can be connected with minimal effort? What connections would help you create high-value metrics? Once you understand what needs to be connected and the level of effort required, you can make a long term plan.

The sad reality is that no tool on the market today (including ours) will give you 100% of the data and metrics you need. About the best you can expect is a set of tools that help you advance some distance down the road. The trick is to fully understand your unique needs before you start down that road.

Image courtesy of DepositPhotos

Remember that time long, long ago (in a land far away) when the term “web analytics” hadn’t even been coined? Fast-forward to 2013: web analytics data is the tip of the iceberg, “big data” is readily available, and many new tools on the market do the work of collecting data, storing it, manipulating it and reporting on it.

No doubt about it, Data-Land is a much sweeter place than No-Data-Land, and as marketers, we’re lucky to have arrived here. Data provides insights that enable us to market smarter, to optimize faster, and to return provable results.

And yet, a dirty little secret about Data-Land keeps the marketing world up at night (especially the night before we present our data)…

At least some of this data is probably wrong.

And that’s ok – if you know where the holes are. Understanding where data falls short will help you field questions and challenges and maybe even fix at least some of the inaccuracies before others notice them.

Here are 5 examples of potentially inaccurate numbers you may be using in your social media reports and dashboards:

Visits To Your Website From Social Channels

Let’s start with something simple – or seemingly simple. How much traffic did Twitter, or Facebook, or YouTube drive to your website?  Theoretically, you should be able to find the answer quickly and easily in Google Analytics (GA). But be careful! You may have already noticed that social traffic numbers from GA’s Social Reports (GoogleAnalytics>Traffic Sources>Social>Network Referrals) seem to under-count the amount of traffic that was truly generated by social sources.

One of the reasons for this is that the numbers in GA Social Reports don’t always include all traffic generated from links you send out with custom UTM parameters. For example, if you send out a link like this, it may not get counted in the number reported in Social Reports: http://www.examplesite.com/?utm_source=facebook&utm_medium=social&utm_campaign=winter_sale.

This happens because GA matches social referrals based on the domain name (facebook.com), so the source in your URL, “facebook,” is not categorized as a social media site by GA.  (In other words, GA counts the visit as a visit from “facebook,” but doesn’t see “facebook” as a social site.)

You can get a better count from GA by going to Traffic Sources>Referrals and searching the name of a social site, for example, “twitter.” But even this won’t provide you with a full count because the t.co referral won’t show up. (When you attach a link to a tweet that is longer than 19 characters, Twitter will wrap it in a t.co link.)

To get more accurate data from GA on social visits, try setting up an advanced filter using a RegEx (here is more background on why these issues exist in GA and how to set up the RegEx filter).

Social “Assists”

Attribution (the practice of crediting a source like social media with an “assist” if social touched a prospect somewhere along the way to becoming a customer) is a handy concept, especially for social media marketers.

Unfortunately, social media “assists” may also be significantly undercounted by GA for the same reason discussed above — i.e., only the visits or conversions sourced to “facebook.com” are credited as being referred by a social media site.  Other sources that should be categorized as social, like a URL with the custom parameter “source = facebook” or a t.co referral don’t get counted as a social media assist.

This is not just a GA problem. The number of leads and socially assisted sales reported by tools that place code on your site for tracking (for example, many marketing automation tools) often under-report for the same reason.

Clicks On Shortened URLs

If you are including clicks on links in your social reports, and the source of your data is a URL shortener (either a stand-alone shortener like Bit.ly or a shortener that is built in to your SMMS system), you may be reporting on numbers that are inflated by bots and crawlers.

Some of these clicks are filtered out in reports generated by the URL shortener you are using. However, if you compare the number of clicks reported by the URL shortener to visits data from Google Analytics, you’re likely to see a significant difference (this is the probably the primary reason behind the discrepancies in Twitter traffic noted recently in this post).

The reason for this is that the GA code placed on your website is javascript. Bots and crawlers simply cannot execute javascript, so the GA visits number won’t include them. This means that GA will generally report that you got far fewer clicks on shortened URLs than your URL shortener reports – and the GA number is much closer to the mark.

Monthly Facebook Metrics

Facebook is a key channel for many brands, so your reports and dashboards likely include some metrics that come from Facebook Insights. Here is a problem to watch out for: Facebook provides many metrics in daily, weekly, and 28 day increments – not on a monthly basis (the exception to this is post-level metrics which are reported on as lifetime values).

At least some of your reports and dashboards are probably based on monthly metrics. If so, you have two choices:

1. Use the Facebook 28 day number: the problem with this is that the 2-3 days you are missing could skew your total dramatically.
2. Calculate a 30 day metric: this is perfectly legitimate for some metrics, but not for others. Facebook metrics that are based on unique numbers cannot be turned into a 30-day number (without using an estimate). More on this here.

The key is simply to know what you are reporting on, which isn’t a problem if you are pulling data manually from Facebook Insights. If you are getting your Facebook data from a tool, make sure you understand how the metric is being calculated and pay close attention to any unique metric (People Talking About This, for example) reported as a monthly number.

Here is one more thing to watch out for with Facebook data: the delivery of Facebook data is often delayed by two days, so running a monthly report on the first of each month will generally produce inaccurate metric values.

Share Of Voice

Few, if any, social listening tools capture every single mention of your brand or keyword, especially in the Twitter environment (you wouldn’t like the price tag if they did). What does this mean? Let’s take the metric “share of voice” as an example. If you aren’t capturing 100% of the conversations that occurred, then “share of voice” is representative of only the conversations you captured. It is not an accurate measure of the share of total conversations about a particular topic or keyword.

This doesn’t mean that “share of voice” is a metric to avoid. Just be clear about what you are measuring (and presenting).

Living in Data-Land (the land of plenty) has created an expectation that data will be available, and that’s probably a pretty good bet. But whether that data is accurate or not is an entirely different matter. The best way to avoid bad data is to:

1. Be an educated consumer about the data you are using
2. Track trends over time closely

This will help you spot changes that don’t make sense and determine an expected range of inconsistencies from month to month.

The good news is that plenty of data and metrics exist. The bad news is that marketers are already awash in data and often suffer from too much noise, not enough signal. Careful planning can help ensure that measurement is meaningful and provides insights for decision making.

Here are three things to consider as you create a measurement plan for your content marketing initiatives:

1. Where Are You Measuring?

Will you measure at the program level, the content level, or both?  If you are being asked for an ROI number, measuring at the program level makes sense and is fairly straightforward.

Measuring the ROI of a blog, for example, can be done by calculating the investment (number of hours multiplied by an hourly cost that includes overhead, plus costs for design, hosting, etc.) and comparing it to return (50 leads generated per month multiplied by lead conversion rate, average lifetime value and average profit margin).

However, if you want to understand which content types, topics, authors, or formats to focus on, or if you want to measure financial impact of different types of content, you will need a more granular analysis of each piece of content you create. Measuring at this level is decidedly more complicated.

The first step is to create a system for organizing content, including a content identification number, tracking tags, and descriptive tags such as content topic, content type or format, author and/or other criteria that will help you pinpoint the magic formula.

Keep in mind that there is a limit to the number of records an Excel sheet can hold, so if you are creating a significant amount of content, you will need a database.

2. What Counts As “Content”?

Let’s say you write a blog post. Then you tweet it out. Is the tweet a distinct piece of content? Or is the blog post the only piece of content?

This is only one example of the difficulties inherent in defining “content,” and there is no right or wrong way to do it. The point is that how you define content will impact what and how you measure, the data sources required, and in some cases, the way metrics are defined.

Using the example of status updates versus pages, let’s take a closer look:

– Status Updates (example: a tweet or a Facebook post): Engagement and exposure metrics can be tracked via social channel data; many social media management systems also provide this type of data.

Keep in mind, however, that the exposure and engagement metrics used for a status update are not defined in a way that is consistent with metrics used for pages.

Conversions (leads and even transactions) generated by individual status updates can also be tracked through Google Analytics, provided that you use a URL with campaign parameters (example of source/medium/campaign) and a call to action in the update.

– Pages (example: a blog post):  Visits, conversions, and engagement metrics such as time spent can be tracked through Web analytics programs.

Some data about page sharing is available through Google Analytics (however, this data is incomplete since Facebook and Twitter sharing are not covered).

If you are using a sophisticated CRM or marketing automation solution, you may be able to track which content was consumed by prospects and customers across multiple touch-points. (Note: Be sure to clarify how data is collected in whatever system you are using.  Measurement is never perfect, but you should at least understand where the holes are.)

It is possible to group status updates with the content those updates link to (much like a Google AdWords group) for measurement purposes. This can only be done if there is a link from the status update to content that exists on an owned media property.

In order to create groups like this, you must use URLs with UTM parameters (example: www.example.com?utm_source=yahoo&utm_medium=link&utm_campaign=FathersDay).  Free tool: URL tracker/manager

3. What Is Your Content Supposed To Do?

If you have a structured content marketing plan that outlines who each piece of content is designed for and what it is supposed to do, creating an effective  measurement plan is a much easier task.

For example, your content marketing plan might include a group of content items such as a “How To” Ebook designed to create awareness among prospects in the early phases of consideration. Goals for this type of content might include:

• Exposure for the brand or product
• Sharing and engagement (which creates additional exposure)
• Conversion to an email subscription or event (for future nurturing of a prospect who may become a lead someday).

Awareness content is doing its job when it accomplishes these goals, so measuring mentions of the Ebook, retweets, reach of the Facebook post about the Ebook, and soft conversions sourced to the Ebook are appropriate metrics.

Other types of content call for a different set of metrics. For example, content designed for prospects who are in the preference or purchase stage will likely require measuring the hard conversions generated by that content (for example, a demo request or a price quote).

The important thing to remember is to stay focused on the goal of the content and the measurement plan will flow naturally from there. Once you have this laid out, you can create a realistic plan to use the data you can get and to get the data you don’t have.

Of course, perfect measurement is not possible. For example, you will not be able to fully capture the reach of an infographic that was shared across multiple social platforms.

And this leads to the last (and perhaps most important) consideration: What is your tolerance (or the the tolerance of the person you will be presenting your data to) for imperfection? If low, you may want to stick to numbers that are more defensible, even if these numbers don’t fully make a compelling case for the value of content.

So, what’s a marketer to do?  Here are five tips to help you work with the data you have, get the data you need, and make your case effectively.

1. Translate

While it is certainly true that marketers don’t usually have all the information senior execs are looking for, part of the problem is simply the way things get communicated.

Take some time to translate what you are trying to achieve with social media, as well as your metrics, into language senior executives will understand.  For example:

• If your goal for social media is focused on customer service, don’t talk about improving customer satisfaction. Talk about driving new sales from existing customers.
• If your goal is awareness/exposure, don’t talk about reach. Translate reach into a cost metric (cost-per-impression, cost-per-visit) and focus the conversation on comparative cost savings.

2. Shift Your Focus

Don’t lead with a losing hand. For most companies, social media isn’t going to compare favorably with channels like PPC on the basis of last-click transactions.

So, turn your attention toward measuring social media’s contribution to filling up the prospect funnel, the quality of a social lead, and/or how socially connected customers differ in terms of value and purchasing habits.

Yes, this will require connecting the dots between data sources, but if you really want to measure business value, you will eventually have to do this. You might as well get started now, even if you can only take baby steps. (Note: For a thorough discussion on this topic, see Nichole Kelly’s excellent new book, How To Measure Social Media.)

3. Sell Them On Staged Investments In Measurement So You Can Give Them What They Want

Instead of asking for budget to execute more programs, ask for a small investment in measurement. You aren’t likely to get a green light on anything that is expensive or resource intensive (at least in the beginning), so the key here is to start small.

Remember that the perfect should not be the enemy of the good. The goal here is to get enough data, and enough connected dots, to show progress.

4. Avoid Questionable Data 

The last thing you want to do is create more uncertainty — or worse, mistrust — so, don’t ask for trouble. Make sure the data you present are defensible.

For example, if you are using conversion (goal) values, base the values on a data set of past performance that is statistically significant (e.g., 3% of Request a Price Quote submissions convert to a sale based on an analysis of many sales over time), and validate that number frequently.

If you are dealing with a skeptical audience, you may only want to present this type of data alongside details of your last validation attempt (e.g., “Last quarter we presented goal value estimates based on a 3% close rate; we validated that 3% number at the end of the quarter so we are comfortable that goal values based on a 3% close rate are accurate estimates.”).

5. Don’t Try To Redefine ROI

Metrics like “return on conversation” may be interesting and even useful to some stakeholders, but they won’t be accepted as a substitute for ROI (not by this crowd, anyway).

These types of metrics raise more questions than they answer and can divert the already short attention spans of the people you need to convince. And, at the end of the day, you will still be left with the difficult task of defining the value piece of “creative” metrics in hard, financial terms. This can be just as difficult and time-consuming as chasing the elusive ROI number. 

Measuring the business value of social media can be difficult, no doubt. On the other hand, it is likely to be easier than talking senior executives out of a business value assessment.

Senior executives are focused on sales, revenue and costs — and, most importantly, on the two or three things that are most likely to move the needle on sales, revenue and costs. Trying to talk them out of that focus simply won’t work, so why not take the bull by the horns and start working on getting the answers they want? Even if you aren’t completely successful, it may help your cause to demonstrate that your approach is squarely focused on business outcomes.

Image from Istockphoto used with permission.

Social media marketing can be an effective way to generate exposure among potential new customers. Done right, that exposure can be translated into engagement, interest, and eventually, a sale.

Unfortunately, social media doesn’t always get the credit it deserves for that sale, especially when transactions do not take place on the web site.

Here are two approaches to tracking the business value of social media marketing in this scenario:

Create Goal (Soft Conversion) Values

If a site visitor orders a catalog, asks for a price quote, or signs up to receive email communications, these are promising indicators that a sale is possible in the future. Once you establish the rate at which these types of actions result in a sale, you can assign an estimated value to them.

Here is an example:  

ABC Truck Leasing publishes a blog about fleet management and promotes blog content through a variety of social channels. ABC tweets out a new blog post and gets a visitor from Twitter.

After reading the blog post, this visitor begins exploring the ABC web site and eventually fills out a “Request a Price Quote” form (either during the original visit, or on a subsequent visit). The form submission is recorded in ABC’s CRM system.

An analysis of data from ABC’s CRM system shows that 3% of all “Request a Price Quote” submissions eventually result in a sale and the lifetime value of a customer is about $6000.

If 100 “Request a Price Quote” leads are generated and 3% of those can be expected to convert to a sale, the total value of the leads generated is $18,000.  But what about the average value of each lead generated?  Armed with this information, ABC can perform the following calculation:

Now, through Google Analytics Social Value reports, ABC can see the total number of all “Request a Price Quote” conversions that came from social media sources, both assisted conversions (meaning that social media referred at least one of the visits leading up to conversion, but not the last visit) and last click conversions (meaning that social media referred the visit that immediately preceded the conversion). Even better, ABC can see an estimate of the average value of each lead generated from social sources.

Note the word “estimate”.  The average number of people who fill out the “Request a Price Quote” form and subsequently buy is an average. The average number of people who convert to a sale is likely to change over time. Hence, the social value number in Google Analytics is an educated guess.

To avoid being accused of fuzzy math and/or measurement fantasy, the marketing team at ABC should validate the 3% average conversion number on a periodic basis. (Note: The volume of conversions and sales must be high enough to be statistically significant.  In other words, an average of 3% based on 100 “Request a Price Quote” submissions and 3 sales would be highly questionable.)

Note that this can be done as a post-campaign analysis as well.  For example, online coupons that are downloaded and redeemed in-store can be analyzed after the campaign is over. In this case, the final number would not be an estimate; it would be an accurate total count and value.

Connect The Dots Between CRM Data And Analytics Data

If goal value estimates won’t fly with the powers that be, there is a way to connect the dots between actions taken on your site and an eventual sale. It requires integrating the data in your CRM system with web analytics data.

Here is how it works:  When a site visitor fills out the “Request a Price Quote” form, this information is passed to the CRM system.  In most cases (even with many free CRM tools like Zoho), you can configure your CRM system to issue a unique ID to the visitor who filled out the form.

This ID can be passed to Google Analytics via ecommerce tracking (Note: Your site must be set up as an ecommerce site to do this).  By doing this, you are no longer constrained by the fact that Google Analytics gives you only an aggregate number of price quote requests sourced from social media. You can now put people and actions together, like this:

Using this data, you can calculate a number of rich social media metrics, such as:

• The percentage of socially-referred visitors who submitted a price quote and eventually bought, compared to visitors from other sources.

• The average time to close a social media lead (Request a Price Quote lead) compared to other sources.

• The lifetime value of socially-referred leads who became customers compared to other sources.

Note that both of these approaches have advantages and disadvantages. In the first approach, the impact of social media can be seen further up the funnel (via assist data).

In the second approach, social media is tied to an actual sale, but only last-click sources are included in the analysis. Fortunately, these approaches are not mutually exclusive. In fact, some of the best examples of creative and successful measurement approaches are the result of experimentation with data generated in various ways from different sources.

Remember that even if you can’t formally integrate data sources like CRM systems and web analytics, you can still use data from these systems to make manual calculations that may help you make the case for social media investment.

For example, if you know that the LTV of a new customer is $6,000 (Source: CRM system) and you spend $18,000 per month on social media, your social media efforts must generate 3 sales per month to break even. If 3% of your leads convert to a sale, this means you need to generate 100 leads (Source: Google Analytics) from social media per month.

Happy calculations!

Low Hanging Fruit

Basic social media metrics are readily available, easy to get and generally cheap (or free).  But if you are serious about measurement, you’ll have to break a sweat and stretch beyond simple metrics that serve as “gain” indicators (traffic, buzz volume, fans, etc.).

It isn’t that “gain” metrics don’t have value — they serve as useful pieces of important calculations. But by themselves, they can’t answer questions about the business impact of social media. As Olivier Blanchard put it “…bread and ham may individually be part of the ham sandwich but ham alone is not a ham sandwich”.

RESOURCE: 101 Success Stories, YES, 101 Examples of ROI, NO, Here’s Why

Aimlessness

If you don’t know where you are going, how can you possibly know when you arrive? Goals are a prerequisite for any type of measurement.

Goals tell you if you are on the right path and how far you have to go before you get *there*.  Hint: The more directly your SM measurement goals can be shown as related to your core business goals (think: increased revenue,  decreased costs…),  the greater your chances of being taken seriously by senior management.

 RESOURCE:  The One Social Media Element Marketers Miss

Silos

One of the key reasons we are data-rich and insight-poor is that potentially useful social media data lives in many disparate places.

Call it “spreadsheet fatigue” perhaps, but many marketers and analysts tend not to look at the data as often, and thus are less likely to follow up on hunches or insights when it takes too much time (and elbow-grease) to bring the really useful data together into one place for analysis.

Effective measurement can’t happen until you de-silo the most common data sources for social media (web analytics, social channels, CRM systems, social media monitoring systems).   

Note: This doesn’t mean that you can’t start measuring social media until you completely rebuild your organization’s IT infrastructure. It does mean that you will have to find ways to create “data windows,” or views into the data you need. Think “forest”, not “trees.”

RESOURCE: Social Media Metrics Secrets (see chapter 2 section on “Assembling a Panoramic Perspective”)

Disorganization

Measuring social media is hard enough. Measuring a haphazardly-executed social media program is near impossible.

If there are inadequate systems and processes in place for managing your social media marketing program, you won’t be able to collect and organize all of the data points needed (and it won’t matter because you will be so busy running around like a chicken with its head cut off that you won’t have time for analysis anyway).

If this is your problem, fixing it won’t happen overnight, but one simple thing you can do right now is to organize campaign URLs used in social media campaigns. This makes for simpler, cleaner, faster analysis of social media campaigns.

RESOURCE: Free campaign URL Tracker

Impatience

If you want to generate meaningless, highly questionable reports that are packed with pretty charts and graphs, then 30 days and a handful of metrics will work just fine.

Sure, two points is all you need to draw a line. But gaining insights about cause and effect and/or building predictive models requires tracking data trends over time.

Many of the most insightful “ah-ha!” moments in measurement come out of correlations and trending over the long term, so don’t expect immediate and obvious answers as soon as you hit the “on” switch and start collecting data.  The more perspective you have at your disposal, the more compelling your results can be.

RESOURCE: The ROI of Emily

Naysayers

There will always be someone in the room who points out that what you are trying to measure can’t be measured (and/or probably shouldn’t be measured). Ignore these people (or find ways around them).

Sticking with what’s tried and true (and what you know how to do) will take you only so far in these times. In a tumultuous, frenetic field with no benchmarks, no settled industry standards and no baselines, you’ll need to be creative, experimental, and unfazed by obstacles.

Trust the “experts,” if you like, but trust yourself and your creative intuitions even more. Translation:  Pioneers needed in social media measurement.

RESOURCE: 4 Unique Approaches for Measuring Social Media ROI

Un-translated Data

Senior executives understand business goals. They do not get (nor do they want to get) follower to following ratios, average engagement per post, or true Twitter network size. (And, no, they are not likely to laugh if you throw out that cute little sound bite about calculating the ROI of your mother.)

If you do not translate measurement into a context that can be understood by senior management, you lose credibility (and possibly even your job).

Take your metrics and data points and turn them into calculations that speak to the business goals understood and valued by senior executives. For example, do some calculations on the leads and customers generated by social media.

Do social leads convert at a higher rate?  Do customers who are connected to your brand through social channels have a higher life time value?  Do they cost less to acquire?

RESOURCE: 7 Things You Need to Know to Measure Social Media

At least once a week I run across an article or blog post about tools for measuring social media. Headlines like “5 Social Media Measurement Tools That Save Time and Money” or “Six Free Social Media Measurement Tools for B2B” have become as common as graduation parties in June.

While it is encouraging to see so many measurement options emerging, the wide range of products in this space can be confusing. Part of the problem is that the term “social media measurement” is used to describe tools designed for many different types of users and tasks.

I keep a running list of many different types of tools that can help users measure social media in some way. My list is divided into five categories based on the primary function or use of the tool.  Here are my five categories:

Listening Tools

Listening tools are commonly referred to as social media monitoring, buzz monitoring, or social media analytics tools.  Their primary function is to monitor social media channels for conversations that are relevant to a particular brand, product, or topic.  Although tools in this category span a broad range of sophistication, the analytics component tends to be fairly in-depth across the board.

Primary Use:

• Used by PR to gain insight into brand or product perception, credibility and awareness
• Used by marketing to track word of mouth/buzz about the brand and about specific campaigns
• Used across multiple departments (customer service, PR, marketing) to identify engagement opportunities with customers, prospects or Influencers in social channels
• Used by customer service to find and respond to questions or complaints

Metrics Examples:  Listening tools generate metrics that capture the depth and breadth of online conversations, or “buzz”.  Some examples include conversation volume, positive brand mentions, share of voice, competitor buzz.

Variations/Subcategories:  Many areas of specialization; sophisticated versions use advanced natural language processing for deep analysis, customer and product research, topic categorization.

Workflow/Management Tools

These tools are not designed primarily for measurement; rather, their main purpose is to manage and organize social media marketing activities across multiple people and departments (for example, posting content to multiple social sites and accounts).

Many of these products incorporate a social media monitoring feature (typically not as robust as tools in the Listening category).  Workflow tools almost always include at least an analytics component; some tools in this category provide an extensive set of metrics.

Primary Use:

• Used across departments to manage multiple social profiles, schedule posts/messages/Tweets to various social media communities
• Used by social media marketing staff to track and organize assignments, content calendars, and the activity (number of posts for example) of individual users

Metrics Examples: Workflow tools generate metrics about usage (for example, posts assigned, posts per user, posts by team, etc.).  Most workflow tools also provide some or all of the standard metrics available through social sites like Twitter and Facebook (for example, likes, followers, Twitter reach, Facebook People Talking About This, etc.).  Workflow tools that include a monitoring feature provide a set of “listening” metrics (brand mentions, positive buzz, etc.).

Variations/Subcategories: New tools designed to facilitate the time consuming task of content development, e.g., content-curation tools, tools that manage outsourced writers and editorial planning, etc.

Site-Specific Tools

Many of the tools in this category are Twitter-specific and are not primarily used for measurement and analytics (for example, tools that help the user find the right people to follow or discover hot/trending stories on Twitter). But some focus heavily on analytics and measurement.

Facebook Insights, for example, provides in-depth analytics data for brand pages and a number of tools provide unique metrics for Twitter (true size of a follower list, extended reach of a Twitter network, psychographic profiles of Twitter followers.)  Free options are plentiful; vendors often provide free tools in this category as a way to demonstrate broader capabilities.

Primary Use:

• Used by community managers to grow and manage an engaged community
• Used by social media managers to maximize time, streamline process, gain insights, and/or research or get insights on a specific community like Twitter or Facebook

Metrics Examples:  These tools generate some unique metrics that are not commonly available, such as Tweet Density, True Twitter Network Size, Follower Churn Rate, Community Growth Rate, YouTube Audience Retention, Facebook Interaction Rate.

Variations/Subcategories:  Tools for managing Facebook ad campaigns; tools that facilitate management of branded social communities (with analytics built in).

Influencer Identification Tools

A growing number of tools focus on the ability to identify online influencers your brand may want to engage with through social channels. Tools in this space span a broad range of sophistication in terms of how influence is defined (from size of network to algorithms that attempt to determine influence in terms of the impact an influencer might have on others).

Many tools in the Listening category include some type of influencer identification mechanism; however, stand-alone tools that specialize in Influence identification and measurement are becoming more common.

Primary Use:

• Used by PR to inform various brand awareness activities and to manage online reputation
• Used by marketing to grow social communities and connections and to expand reach/exposure
• Used across multiple departments to identify highest priority engagement opportunities and brand threats
• Used by customer service to monitor high-priority questions or complaints

Metrics Examples:  These tools generate scores and rankings of people or properties that qualify as “influential” (definitions and criteria for influence vary). Some types of buzz metrics are also usually included, like influencer brand mentions, positive/negative influencer buzz, or influencer penetration.

Variations/Subcategories:  Community mapping (identifying connections between people), brand relationship assessment (intensity of a person’s connection to a brand in social channels), topic affinity analysis, value assessments (i.e., potential value of influencers and their networks).

Web Analytics Tools

If you are a digital marketer, web analytics tools need no explanation. These tools offer users information on traffic, leads, transactions, etc. driven by social media marketing.

Unfortunately, much of the data needed for measuring social media comes from sources outside of the web site — sources not covered by web analytics tools. But with the increasing availability of social media modules/components for standard web analytics platforms (Google Analytics Social Reports for example), these tools are beginning to offer much more robust intelligence about the impact and performance of social media marketing.

Primary Use:

• Used by marketers and analysts to measure performance or results based on actions taken by visitors to a web site that is owned by the web analytics subscriber
• Used to enhance user experience and improve effectiveness of a web site against multiple types of goals
• Used by social media marketers to track actions taken by visitors driven to the site through social channels

Metrics Examples:  Some key metrics that relate to social media performance specifically include assisted social media conversions (assisted by social media) and conversion value, last interaction social media conversions and conversion value, traffic to socially shared pages.

Variations/Subcategories:  Business Intelligence, predictive analytics, CRM integrations.

Social media measurement is still in its infancy, so the steady flow of new products and vendors (and perhaps new categories!) will likely continue for some time. To determine the fit that is right for you, start with your measurement goals and work back from there to find the product or products that deliver the right combination of metrics, data sources, and features.

For social media marketers, this means that it is more important than ever to understand what content will resonate with target groups and which will fall flat.   Without good ways to identify the content preferences of target groups,  the only option is to throw marketing mud against the wall and hope that it sticks — an approach that is costly, more likely to fail, and may damage the credibility of budding social media programs in the eyes of senior management.

Measuring the social engagement elicited by different types of content can help social media marketers pinpoint what is effective — and what isn’t worth precious time and budget.  Here are three ways to do it:

1.) Track Cross-Channel Social Interactions

Some social sites, like Facebook, provide engagement data for each content item posted. This is important information because it helps you determine what content works best within the closed walls of a specific site or community.  But how can you determine which content works best overall, across the multiple social channels in your mix?

First, develop a system for keeping track of content.  You may already have this if you are using a social media management tool (some provide a content ID number), but an Excel spreadsheet will also work.  At a minimum, your spreadsheet should include an ID number for each content item.  You can also include additional data, such as date released, post title, and content type (link, photo, video, blog post, etc.).

Next, create a rubric.  A total count of engagement actions (sharing, commenting , liking, etc.) may be enough for your purposes, but if you want to distinguish between different types of engagement, you’ll need to create a rubric for organizing metrics into consistent categories.  For example, metrics like Facebook comments, Blog comments, and Twitter @replies can be grouped into a category called “communications”.   Metrics that represent different types of sharing activities can be grouped into a “distributions” category.  You can come up with your own categories and assign metrics in way that makes sense for you.

Your spreadsheet will look something like this:

This DIY method of tracking engagement takes time and elbow grease (so you may want to limit the analysis to a specific time frame), but it can go a long way toward helping you determine which content topics and formats to focus on.

One word of caution:  This will work best if the content you are using is highly targeted to the audience you are trying to reach.  If it isn’t, engagement levels may not be a good indicator of what your audience wants.  For example, a funny picture posted to your Facebook page might be widely shared by people who are not interested in your product or services.   Consequently, high engagement numbers for this post would not necessarily indicate that this type of content works well with your targeted groups.

If you question whether engagement is occurring among the right people, web analytics data can provide important clues…

2.) Analyze Traffic And Site Behavior of Visitors To Shared Pages

If engagement and sharing in social channels drive traffic and high levels of interaction with your website, it’s a good sign that the right folks are engaging.

True, not all of the content you share in social communities links back to a page on your site, but if it does, measuring traffic to — and interaction with — shared pages can yield valuable insights into which content is worthwhile.

The new Google Analytics Social Reports makes this much easier by providing data on traffic to shared pages, visit duration, and even the number of times the page was interacted with out in the social world (“Data Hub Activities”):

Two important notes about the new social reports: First, Facebook and Twitter are not included in the Data Hubs tracked by GA, so for many social media marketers, the total number of interactions, or Data Hub activities shown will be under-reported.

Second, don’t focus solely on traffic to shared pages.  Even if traffic numbers to shared pages seems low, remember that quality can trump quantity in the ROI equation.  One well-qualified visitor who is eager to consume your content is worth far more than ten unqualified visitors who leave the site immediately.

Bottom line: content that leads to deeper engagement within the site is successful content, so pay attention to visit duration and pages visited.  (You may also want to set up Advanced Segments in GA to further analyze the behavior patterns of visitors to shared pages.)

3.) Calculate Interactions Per Referred Visit

So far, we have looked at two ways to judge content performance:  engagement activity in social channels and website activity generated by shared content.

These two methods can be combined by calculating “Interactions Per Referred Visit”, a metric that captures social engagement relative to traffic.  Interaction Rate is calculated by dividing total interactions or engagement actions in social channels by visits to the shared page.   You can add this metric to your spreadsheet:

Ultimately, how people respond to your content can’t be fully captured by any single number (or even a set of numbers).  However, as is often the case, analyzing the data is an excellent place to start!

Are you using engagement tracking to identify high value content?  If so, what techniques and tools do you use?