The Social Media ROI Cookbook

The Social Media ROI
Cookbook:
Six Ingredients Top Brands Use to Measure
the Revenue Impact of Social Media
July 24, 2012
By Susan Etlinger
With Jeremiah Owyang and Andrew Jones
Includes input from 66 ecosystem contributors

Attribution-Noncommercial-Share Alike 3.0 United States | © 2012 Altimeter Group | 1
Executive Summary
Today, customers move constantly between the online and offline worlds, using a range of devices
— such as smartphones and tablets — that didn’t exist a few short years ago. Thousands of
applications and dozens of social media platforms collect and transmit an unprecedented amount of
structured and unstructured data1
, and API changes are a fact of life. The volatility of social data and
the pace of change mean that tried-and-true measurement methods are no longer enough. Social
data is different. The old rules don’t apply.
Although many organizations have established formalized social media programs2
, the vast majority
— 75% — still lack a holistic measurement strategy3
. Web analytics; social media monitoring;
social platforms; and tool, application, and ecommerce providers have rushed to fill the gaps, while
analysts at brands and agencies have borrowed accepted methodologies from adjacent disciplines
to address the unique challenges and pitfalls of social data.
As social media matures, new approaches to social media measurement will emerge to provide businesses with a
greater level of insight, but the days of certainty (if ever they existed) are behind us. As George E. P. Box4
, a noted
statistician, famously said, “Essentially, all models are wrong, but some are useful.”
In our research for this report, Altimeter Group identified six primary top-down and bottom-up approaches and
developed three case studies that illustrate how organizations measure the impact of social media on revenue. But
while these six ingredients are consistent, the emphasis each company places on them depends on the nature of
their business. There is no “one-size-fits-all” approach. The following pages aim to identify and describe — based on
business, product, media, and customer type — the most effective “recipes” for measuring the revenue impact of social
media that we have seen adopted to date.
Methodology
Altimeter Group conducted both qualitative and quantitative analyses, using a combination of online survey,
interviews, and briefings, on the ways large organizations measure the revenue impact of social media.
Specifically, we conducted:
Interviews with 38 vendors of social media technology, whose products offer some ability to
measure the revenue impact of social media
Interviews with 15 brands that are currently measuring the revenue impact of social media programs
Interviews with three agencies
Interviews with four domain experts
Quantitative study of 71 brand and agency-side professionals on measurement experiences
and practices

Table of Contents
Business Pain: Organizations Struggle to Quantify Revenue Impact of Social Media .............................................3
Problem: Industry in Transition Leaves Organizations Flying Blind ..................................................................................................3
Beyond Revenue: Improving Insight ..................................................................................................................................................7
The Six Ingredients to Measuring the Revenue Impact of Social Media .........................................................................8
Top-Down Approaches ............................................................................................................................................................................... 10
Bottom-Up Approaches ............................................................................................................................................................................. 11
Case Studies .................................................................................................................................................................................................. 13
Determining the Right Measurement Mix ..................................................................................................................................... 16
The Future of Social Media Measurement ................................................................................................................................... 21
Conclusion ................................................................................................................................................................................................... 23
Ecosystem Input ....................................................................................................................................................................................... 24
About Us ....................................................................................................................................................................................................... 26

Business Pain: Organizations Struggle to Quantify Revenue Impact of
Social Media
Problem: Industry in Transition Leaves Organizations Flying Blind
Social media is no longer optional for business; it’s a fact of life. Today more than 80% of the world’s online
population uses social media, according to a recent report by comScore5
. But social media poses a new series of
interpretive challenges for organizations, which can make it difficult to assess its impact on the bottom line. Altimeter
Group’s research identified the following primary barriers to measuring the revenue impact of social data:
A. Social Media Is Proliferating.
Although social media is still very new, Altimeter Group found in the research for our January 2012 report, “A Strategy
for Social Media Proliferation,” that companies average 178 corporate-owned social media accounts. This raises
serious questions:
Do companies know what value they are receiving from these social media properties?
Do they know what resources they are expending to build and support them?
Do they have accurate inventory of these properties?
According to the State of Social report by eConsultancy, the answer to each is a resounding “No.” In its report,
eConsultancy stated that 41% of more than 1,000 companies and agencies surveyed had “no return of investment
figure for any of the money they had spent on social channels as of October 2011.”6
B. Multiple Challenges Hinder Insight.
Fifty-six percent of brands and agencies that Altimeter Group surveyed reported “the inability to tie social media to
business outcomes” as the primary challenge to quantifying the revenue impact of social media. But other, more
granular challenges (“lack of analytics expertise and/or resources,” “poor tools,” “unreliable data,” “inconsistent
analytical approaches”) closely followed, suggesting that measurement of social media poses as much of a challenge
to organizations and processes as it does to technology.

In addition to the 35% of survey respondents who noted “inconsistent analytical approaches” as a barrier to insight,
several organizations we interviewed highlighted the educational requirements of social data. For example, Robert
Ross, Vice President, Interactive & New Media of the American Cancer Society, commented, “We’ve found we have
to help people understand the nature of the data and how to use it and apply it. That’s a delivery challenge.”
C. Social Data is New and Different.
As outlined in the “Executive Summary,” the complexities of social data make it substantially different from what enterprises
have seen before. Following are the most commonly cited challenges of measuring the impact of social media:
Exists in online, offline, and across multiple screens, fragmenting data capture. Avinash Kaushik
of Google7
has written extensively about the measurement challenges of the world we live in; specifically,
the chasm between online and offline and the proliferation of screens through which we interact. This is a
significant difference from the early days of the web, before smartphone and tablet devices began to grow
in popularity.
Is volatile, making measurement a moving target. Even in the heyday of traditional media, the number
of media outlets was relatively stable in comparison to the volatility of today’s social web. For example,
from January 1, 2012 to June 5, 2012, Facebook announced the completion of 14 API changes8
, while
the Pew Research “Twitter Use 2012” report found that “the proportion of online adults who say they use
Twitter on a “typical day” has doubled since May 2011 and has quadrupled since late 2010.”9
Figure 1: Brands See Multiple Barriers to Tying Social Media to Revenue
“Which of the following have been challenges? (Check up to three)”
Base: 71 respondents responsible for social media measurement in their organization
0%
10%
20%
30%
40%
50%
60%
Inability to tie
social media to
business outcomes
Lack of
analytics expertise
and/or resources
Poor tools Inconsistent
analytical
approaches
Unreliable data
56% 39% 38% 35% 30%
Source: “The Social Media ROI Cookbook: Six Ingredients Top Brands Use to Measure the Revenue Impact of Social Media,”
Altimeter Group (July 24, 2012)

Organizations don’t “own” social media the way they do their websites or other owned
properties. Unlike embedded web analytics on their own website, organizations do not have the ability
to tag and track properties on third-party platforms (such as others’ blogs, Facebook pages, or online
communities), so they have little direct insight into customer behavior on those properties.
Different apps and platforms give rise to different metrics, making a holistic view challenging.
As the old saying goes, “The trouble with standards is that there are so many to choose from.” Facebook
metrics differ from Twitter, which differ from Tumblr, communities, and YouTube. To make matters more
complicated, new behaviors and features yield new metrics (such as “pins” in Pinterest), and APIs of these
third party sites are constantly being updated.
Because social media is still immature, it is tempting to think of it in terms of known quantities such as traditional/
digital media, marketing, advertising, or ecommerce. But unlike those disciplines, social media is driven from the
outside in, and it happens whether or not we plan for it. As a result, the way we measure social media must adapt to
suit the unique characteristics of the social web. The old rules do not apply.
D. Organizations Lack Confidence in Measuring Revenue Impact.
Altimeter’s research shows that only 30% of organizations claim to be “very effective” or “extremely effective” at
connecting social media to revenue generation.
Says Ken Burbary, Chief Digital Officer at Campbell Ewald, “I feel like we’re all data chemists at this point, trying to
put a bunch of stuff into our beakers to see if it works.” Although social media has proliferated during the past few
years, there is a significant gap in the ability to articulate its value.
“On scale of 1-5, how effective is your organization at connecting social media to revenue generation?”
Figure 2: Few Are Extremely Effective At Connecting Social Media to Revenue
0%
5%
10%
15%
20%
25%
30%
35%
1
(Not at all effective)
2 3 4 5
(Extremely effective)
17% 24% 30% 16% 14%

E. Organizations Are Adapting Slowly.
Although social media activity has grown dramatically within the past few years, measurement organizations generally
remain small. Sixty-three percent of brands Altimeter Group surveyed reported that they have one or two people
tasked with social media measurement, while nearly 75% reported fewer than ﬁve people in the function.
Because of the variation in company size, structure, and strategy, these numbers may not necessarily imply that
social media measurement is under-resourced. Most organizations Altimeter Group interviewed have taken a cautious
approach to resource allocation and process improvement as they learn more about the impact of social media on
the business. Says Todd Forsythe, VP Global Marketing, EMC, “We started by saying, ‘Let’s build the organizational
capabilities, dip our toes in the water.’ Now we’re increasingly becoming more programmatic.”
Others brands reported that organizational silos hinder information-sharing, particularly in light of the “inconsistent
analytical approaches” reported in Figure 1.
3-5
6-10
11-20
More than 20
1-2
0
13%
6%
3%
4%
11%
63%
“How many employees are dedicated
to social media measurement within
your organization?”
Figure 3: Social Media Measurement Organizations Still Very Small

Beyond Revenue: Improving Insight
Organizations understand that revenue generation is only one benefit of social media and that its main business value
is to deepen relationships with customers and community. While only one of the brands interviewed for this report
admitted to embarking on a true ROI analysis for social media (analyzing the investment in, as well as return on, social
media), all reported that they are making a concerted effort to measure the revenue impact of social media, albeit in
various ways. Survey respondents reported overwhelmingly that the primary business impact of social media was not
revenue generation, but “insight that helped us meet customer experience goals.”
The next most-reported benefit was decision-making; 51% of respondents stated that social media measurement
“enabled us to make better informed decisions based on social data.” Ali Ardalan, Media and Analytics Strategist at
Intel, believes that social media has become a critical input to business decisions and to business cases. Ardalan
says, “Why do you do an ROI analysis? To justify why you should do this project vs. another. Why you need more
funding. You need to know the result; are you wasting money? Could you have done the same thing with 20% of
the budget?”
Wes Nichols, Co-Founder and CEO, MarketShare, agrees: “What we’re finding is that businesses will only move big
money once they understand what’s truly working. To do that they need a comprehensive view of their marketing
performance, not just the tactical channels.”
Companies that fail to quantify the hard and soft benefits of their social media programs and activities risk flying blind
into a storm. Those that start now to formulate a measurement strategy, as the companies in the following pages
have done, will be best positioned to succeed in this brave new customer-centric world.
Figure 4: The Primary Business Value of Social Media: Customer Insight
“What have been the primary positive impacts of social media measurement within your organization?
(Check up to three)”
Customer/
community insight
Decision-making Investment Financial impacts Organizational
development
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
84% 51% 35% 32% 26%

The Six Ingredients to Measuring the Revenue Impact of Social Media
While we identiﬁed no “perfect” solution to measuring the revenue impact of social media, several best practices have
emerged that are bridging the gaps between what is possible today and what may be possible in the future. Altimeter
Group identiﬁed six primary ways that organizations currently measure the revenue impact of social media, which
should be used as a guideline to determine the most effective measurement mix for your business. The following are
brief descriptions; more detailed descriptions follow.
Anecdote
Specific examples where social media was known to influence a sale or sales.
Correlation
Comparing two data sets (for example, number of likes vs. revenue) to determine whether
there may be a relationship. Note that most correlations are quite simple, although companies
such as MarketShare are working on far more advanced social econometric models.
Multivariate Testing
Comparing one group exposed to social media content with another that was exposed
to different or no content.
Figure 5: Six Ways of Measuring Revenue Impact of Social Media
Links and Tagging
Links refer to short links, such as bit.ly, goo.gl, or custom links embedded into content.
Tags (and cookies) refer to a piece of code that is embedded into links or URLs for the
purpose of conversion attribution.
Integrated
Integrated refers to apps or Software-as-a-Service (SaaS) offerings with integrated analytics,
such as those offered by Buddy Media, Wildfire, or Facebook apps for Timeline.
Direct Commerce
Addition of an ecommerce storefront to a social platform such as Facebook; frequently
referred to as “fcommerce.”
1. Anecdote
“
2. Correlation
3. Testing
A
B
C
5. Integrated
4. Links and Tagging
6. Direct Commerce
Source: “The Social Media ROI Cookbook: Six Ingredients Top Brands Use to Measure the Revenue
Impact of Social Media,” Altimeter Group (July 24, 2012)

The chart below reﬂects both the immaturity of social media measurement and the resourcefulness of brands trying
to understand its impact on their business in a holistic way. Top-down approaches are as widely used as bottom-up
approaches; anecdote and correlation tied at 44% as the most popular ways to measure the revenue impact of social
media, while links were a close second with 42%.
What is important to take away from this data is that, while top-down approaches provide business context and
bottom-up approaches provide granularity, they are most valuable when viewed in context of each other. The case
studies that follow illustrate how three very different organizations orchestrate these methods to provide insights that
help drive decision-making.
0%
5%
10%
15%
20%
25%
30%
35%
40%
44%
45%
50%
Figure 6: Brands Blend Top-Down and Bottom-Up Measurement Approaches
44% 42% 37% 32% 17% 16%
“In which ways does your organization measure the revenue impact of social media?”

Top-Down Approaches
Figure 7: Top-Down Revenue Measurement Approaches
Type Deﬁnition and Usage Considerations Sample Vendors
1. Anecdote Examples of relationship
between social media
and sales; information
is often shared verbally,
sometimes entered
manually into CRM.
Seen in large, often B2B
companies with high
consideration and long
sales cycles
Lightweight and practical
for some companies
Manual
Cannot scale
No ability to share broadly
You can use anecdotes
from any and all social
media service or product
vendors. This may
take verbal or written
form, depending on
the company. See the
SAP case study for an
example.
2. Correlation Correlation refers to the
ability to compare one
data set with another to
identify patterns. It can
be as simple as chart
overlays comparing
likes and sales to highly
complex econometric
models that take into
account external data,
such as gas prices,
interest rates, jobless
claims, etc.
Properly applied,
provides insight into the
relationship between
social strategies/tactics
and business outcomes
Well accepted by the
industry
Requires trained analysts
who can control for
variables and interpret
data to minimize
irrelevancies and
distortion
Manual (therefore not
scalable)
Whatever tool you are
using — web analytics,
email service provider —
usually imported into an
Excel spreadsheet. Tools
such as MarketShare
and Compass Labs
perform more advanced
correlations. Expect this
to become more common
as tools mature.
3. Testing (A/B,
Multivariate)
In statistics, multivariate
testing or multi-variable
testing is a technique for
testing hypotheses on
complex multi-variable
systems, especially
used in testing market
perceptions.10
Used by digital marketers
to compare performance
of tactics across
different populations;
examples could include
news headlines, social
content of any sort
(video, image, text). Also
used by multichannel
organizations with both
online and brick-and-
mortar presence.
Properly applied,
provides insight into the
relationship between
social strategies/tactics
and business outcomes
Well accepted by digital
marketing
Requires trained analysts
who can control for
variables and interpret
data to minimize
irrelevancies and
distortion
Manual (therefore not
scalable)
You can compare the
performance of any social
content to any other
social content, either
within the tool itself or
from tool to tool. Note
that source data may
come from a variety of
tools, such as listening
and monitoring, social
media management,
or any other tool with a
social data output. Some
organizations download
data into an Excel
spreadsheet.11

Bottom-Up Approaches
Figure 8: Bottom-Up Revenue Measurement Approaches
4. Linking and
Tagging
Using a piece of code
(a short link, ROI tag, or
cookie) to identify the
source of a conversion or
sale
At the simpler end: short
links; at the sophisticated
end, ROI tags, such as
those available as part of
web analytics solutions
Broadly applicable to any
online property in which
an item or service is sold
directly to a customer
(direct B2C) or a piece of
social content culminates
in a desired action,
such as a contest entry,
white paper download,
application submission, or
other desired conversion
action/lead
Industry standard for
conversion attribution
Enables tracking from
click to conversion
Facilitates (measurable)
social spreading
Only work on owned
online properties
Don’t (always) work
across screens
Don’t account for
macroeconomic or
business factors (price of
gas, earnings, etc.)
Only works for single-
browser sessions. Links
may break easily or may
not be passed through
Vendors below use links,
tags, and/or cookies to
identify the source of
social content. While
revenue attribution is
a shared feature, they
represent a range of
services, from web
analytics and digital
marketing optimization to
social analytics and social
ecommerce.
Adobe Omniture
Argyle Social
Awareness Inc.
Badgeville
Bazaarvoice
Buddy Media (acquired by
Salesforce.com)
Campalyst
Exact Target
Expion
IBM Coremetrics
Interpreter
Meltwater Buzz
Offerpop
Power Reviews (acquired
by Bazaarvoice)
Revinate
ShopIgniter
Vitrue
WebTrends
Wildﬁre Interactive

5. Integrated Analytics integrated into a
social media app, widget,
SaaS solution, or service
installed on a social
platform
Broadly applicable to
any online property but
requires development
of an application or
purchase/use of a tool/
service, such as those
listed under “Sample
Vendors”
Highly measurable (if the
conversion occurs within
the app)
Requires development or
purchase
Managing complexity
(multiple apps with
different analytics)
Metrics may be siloed or
inconsistent with other
metrics
Argyle Social
Awareness, Inc.
Buddy Media
Exact Target
Facebook (Apps for
Timeline)
Lithium
Momentfeed
Moontoast
Offerpop
Proprietary Tools
Shopkick
Webtrends
6. Direct
Commerce
Addition of ecommerce
storefront to a social
platform (typically
Facebook, “fcommerce”)
Broadly applicable to any
online property
Highly measurable
Limited if you don’t track
full engagement
8th Bridge
Moontoast
Offerpop
ShopIgniter
Spiceworks

Case Studies
Case Study: SAP
Business: Direct and indirect sale, mixed online and ofﬂine
Conservative culture but with support for test-and-learn approaches
Product: Very high consideration, very long sales-cycle product/service
Media: Mixed paid, owned, and earned
Customer: Business customer
The power of anecdote: Social media frees SAP sales team to focus on lower-funnel activities, improving
productivity and close rate.
Given SAP’s size and highly metrics-driven culture, one would expect that the company would insist only on
quantitative metrics to evaluate the success of its social media initiatives. But SAP values both qualitative
and quantitative measures. While it does track more granular metrics (such as numbers of white paper
downloads or webinar sign-ups) for lead generation purposes, the company also values qualitative measures
that contribute to institutional knowledge. Todd Wilms, Senior Director/Evangelist, Communities and Social
Media, reports strong support for social media within SAP: “We have been extremely fortunate from a culture
perspective,” he says.
At SAP, one of the goals for programs groups and SAP-branded channels is to drive leads. Wilms says that
social media has changed the point at which many sales professionals begin to engage with prospects,
because it helps prospects to “self-qualify” by engaging with others in SAP communities early in their
decision process.
As a high-consideration, business-to-business product with a long sales cycle (months to years), SAP is able
to track many of the factors that contributed to a single sale. The company has a well-developed customer
community (which generates its own far more granular and empirical metrics) with which prospective
customers can freely engage. Prospects self-report that they were able to answer their questions and educate
themselves through a variety of SAP social channels before engaging directly with the SAP sales team.
As a result, says Wilms, “Our sales people can now get involved later in the sales process; they don’t have to jump
into the pipeline as early, which has enabled them to have deeper conversations with fewer clients. Then, when they
do engage, they want someone to walk them through that last step of ﬁne-tuning SAP into their organization.”

Case Study: EMC
Business: Direct and indirect sale, mixed online and offline
Culture supports test-and-learn approaches
Product: Medium/high consideration
Medium/long sales-cycle product/service
Media: Mixed paid, owned, and earned
Customer: Business customer
Using a mix of quantitative and qualitative methods to prove cause and effect at EMC
EMC is taking a holistic approach to measurement, but with quantitative measures at the core. Says Keith
Paul, Chief Listener at EMC, “We’re trying to figure out the revenue impact of social. We’re building an
integration and media lab to align everything: social, advertising, search, and marketing sciences.” At the most
tactical level, this means working with marketing teams to develop consistent usage of Omniture codes and
bit.ly short links. At a strategic level, it means a shared approach to understanding the impact of social media
on revenue, as well as on other business goals.
Paul has already seen benefits to evangelizing tagging throughout the organization. Recently — using Adobe
Omniture codes and bit.ly links — he was able to prove that social media was responsible for generating
30% of the viewership for simulcast of a major product launch. Says Paul, “Web analytics is becoming more
strategic again.”
At the same time, the company has set its sights on a more ambitious goal: building an ecosystem with use
cases and tools that can eventually be used in concert with other enterprise data. Says Todd Forsythe, Vice
President, Global Marketing, “What we’re hoping we can do is connect linking and listening to action in a
streamlined way and track — on a real-time basis — the impact of social on business.”
In the longer term, this will mean more integration of “Big Data,” specifically, advanced correlations of customer
behavioral data, leads, transactions, and service experiences. While EMC is still in the process of making
measurement more programmatic and scalable, the end game, say Paul and Forsythe, is for social data to
become fully integrated into enterprise data and business strategy. Says Forsythe, “We always have taken the
approach of ‘Plant a thousand seeds, and let the flowers bloom.’”

Case Study: Eventbrite
Business: Mostly online; service
Metrics-driven, adaptive culture
Product: Short sales cycle
Low(er) consideration service
Media: Paid, earned, owned
Customer: Mixed B2B/B2C
Highly social consumer and business customer
Integrating social media into the product provides clarity for Eventbrite.
Eventbrite is a company in which social media — in this case, Facebook — is deeply integrated into the
product itself, making it highly measurable.
This wasn’t always the case. “When it was first built, Eventbrite was focused on SEO optimization to drive
traffic,” says Vice President of Marketing Tamara Mendelsohn. “Then in about 2008, we saw that Facebook
had popped up as a top referrer of traffic. Two things were happening: first, event organizers were creating
events and including links back to Eventbrite to buy tickets. Second, attendees, once they discovered the
event, were sharing the link either pre- or post-purchase. Those two behaviors pushed more traffic.”
Eventbrite reached out to Facebook, which opened up the event API to them. It then incorporated sharing
features into the product itself. Within a few months, Facebook was the top traffic referrer, which it remains
today. Recently, says Mendelsohn, Facebook’s mobile site (m.Facebook) began to show up in the top 10
referrers as well. While the product is integrated with Facebook, Eventbrite still must use some of the simpler
techniques, such URL tracking, to measure business outcomes. While purchases may originate in Facebook,
the transactions themselves occur on Eventbrite.
The online nature of the business, and the integration with Facebook, means that the company is able to
produce clear, quantitative metrics that demonstrate the relationship between social media and revenue. For
example, Mendelsohn says, “We can see how many shares and clicks occur and how many of the clicks
convert. And that’s how we derive a dollar amount. Our main financial metric is gross ticket sales. Our top
social metrics are total dollars driven by sharing divided by total shares, and total visits driven by sharing
divided by total shares.”
But transactions don’t tell the complete picture. Says Mendelsohn, “The transaction is the most sacred part of the
funnel, but we’re optimizing all parts of the funnel. For example, if you look at total attendee sharing, 60% of sharing
occurs after the purchase. One in 100 people who look at an event page before purchase share it, while 1 in 10
share it after purchase. And a post-purchase share drives 20% more ticket sales than a pre-purchase share.”
Ultimately, says Mendelsohn, the question is how to increase the number of shares, especially post-purchase.
“If 10% of customers are sharing after purchase,” she says, “how do we make that 20%?” While Mendelsohn
is philosophically against incenting people to share — for fear of promoting spammy behavior toward friends
— there is still a lot of room for optimization and growth as Eventbrite looks for effective and authentic ways to
optimize the relationship between social and sales.

Determining the Right Measurement Mix
There is no universal recipe for measuring the revenue impact of social media. While social media measurement is
still nascent and organizations are still experimenting with approaches, we found that the most advanced companies
consider the following four factors to determine the appropriate measurement mix:
Business: the nature and structure of the business
Product: the nature and type of products or services offered
Media: type of media being used
Customer: the nature and type of customer(s)
As social media matures, we will see deeper integration and industry benchmarking that will provide more guidance
for organizations of different sizes and types. For now, however, best practice measurement approaches use the
above decision criteria.
The following pages provide guidance on how to determine the measurement mix that is most appropriate for
your organization.
Figure 9: Decision Matrix – Assessing the Measurement Mix That’s Right for You
1. Identify Business
Type
4. Identify
Customer Profile
3. Factor In Your
Media MiX
2. Assess Product
Type

First, Identify Your Business Type.
The way your company goes to market largely drives what is possible when it comes to revenue measurement.
If your business is … The most appropriate primary
metrics are …
Best Practices
Exclusively online
(e.g., Zappos, Eventbrite)
Links and tags measure revenue
impact at all stages of the
purchase path.
Awareness: views, impressions
Consideration: engagement
(re-tweets, likes, shares)
Conversion (downloads,
purchases, registration,
transaction)
Integrated: Apps and services
offer integrated metrics that you
can use to better understand
impact of specific content,
channels, or campaigns.
Build in measurement at the
beginning of every significant
campaign or program.
Clearly define goals and metrics
at all stages of the path to
purchase.
Map volume metrics (views,
shares, retweets, likes, fans, etc.)
with the appropriate stage of the
purchase path to ensure your
metrics have business context.
Review analytics provided with
apps and services you are
considering. The analytics should
be a critical purchase criterion.
If you are using multiple apps
and services, correlate metrics to
better understand relationships.
Multichannel
(mixed online/offline)
Correlations will help you
understand relationships between
online and offline activities.
Where practical, use mobile apps
to bridge the online and offline
experience and collect data on
in-store/offline behaviors.
If you are using QR codes and
barcode scanning, correlate
their analytics with other online
sources.
and services as many companies
do, correlate metrics among
similar apps to better understand
relationships.

Second, Assess Your Service or Product Type.
The key criteria that drive revenue measurement strategy based upon service and product type are sales cycle
and whether the product/service is a high- or low- consideration item. The longer the path to purchase, the less
reliable clickstream data becomes, because there is generally so much elapsed time and so many variables between
awareness (the reveal of a new car, for example) and purchase (going to the dealer and buying it).
Google Analytics has a good way of looking at this challenge from a measurement standpoint. It has divided conversion
attribution into two types in their “Social Reports” products. They refer to referrals that lead to conversions immediately
as “Last Interaction Social Conversions,” compared to what they call “Assisted Social Conversions,” in which a “referral
from a social source doesn’t immediately generate a conversion, but the visitor returns later and converts.”12
If your product/service is … You should … Best Practices
A lower-consideration item (event
tickets, pet food) or has a short
sales cycle
Use links and tags to measure
revenue impact at all stages of
the purchase path.
Awareness: views, impressions
Consideration: engagement
(re-tweets, likes, shares)
Conversion (downloads,
purchases, registration,
transaction)
Integrated: Apps and services
offer integrated metrics that you
can use to better understand
cause and effect.
based on path to purchase.
Review analytics provided with
apps and services you are
considering. The analytics should
be a critical purchase criterion.
and services, correlate metrics to
better understand relationships.
Longer sales cycles and higher-
consideration items (cars, real
estate)
Experiment with correlation, as
these items are frequently sold
through channels.
Use linking and tagging for calls
to action such as white paper
downloads, webinar registrations,
dealer/agent referrals.
Don’t disregard anecdote as a
tool to connect the online and
ofﬂine worlds, especially if you are
able to log customer verbatims in
a CRM system. While this is not
scalable, it may yield insight when
you aggregate the data.

Third, Factor In Your Media Mix.
The type of medium (Paid, Owned, Earned13
) also inﬂuences your measurement method, as you can only tag online
properties that you control.
If the media you are using is … You should … Best Practices
Paid Use links and tags to measure
revenue impact at all stages of
the online purchase path.
Print can be linked and tagged
via bar or QR codes, while
broadcast media generally
cannot, and must rely on
conventional metrics (or use
correlation, as UFC has done).
A/B testing will show you which
media perform better than others.
based on path to purchase.
Start now to build connections
between the digital and social
analytics teams.
Earned Because earned media cannot
be tagged, you must use
correlations and trend analysis to
understand patterns.
Owned Owned media (as available via
video, blog posts, social posts,
microsites) can be linked and
tagged, although only across the
same browser.
“Jumping” between screens
(phone, tablet, desktop/laptop)
breaks these connections, which
requires the use of other top-
down methods of measurement.
See “Paid,” above.

Finally, and Most Importantly, Consider Your Customer Profile.
Ultimately, the customer or consumer profile will influence what measurement is possible.
If your customer is … You should … Best Practices
A business customer Look at forums, blogs, and
communities to see where
customers congregate and what
you can test and learn from
their interests, questions, and
behaviors.
Factor in known social media
behaviors (Socialmetrics), as well
as behavioral and demographic
data, to help determine how best
to engage.
Test lightweight links and tags in
forum replies (as consistent with
the behavior of the community)
to better understand interest and
consideration.
A consumer The decision to use direct
ecommerce (a storefront)
should be driven by the type
of relationship you have with
your customer base. That said,
the deeper the integration of
social and commerce, the more
granular the analytics.
Correlate behaviors at different
stages of the funnel as Eventbrite
has done, so you can better
understand pre-purchase and
post-purchase sharing and
conversion.
Highly social Correlating shares with sales
will provide insight into how
and whether the online social
experience drives sales.
Integrating apps and services
on your Facebook brand pages
yields deep analytics. The key
is to translate volume metrics to
insights and actions (i.e., people
who do X tend to do Y).
A/B testing social posts against
the same content elsewhere
(Facebook, YouTube, your
website) will provide insight into
how and where people consume
your content and where they go
(and what they do) from there.
Be mindful of the balance
between authentic and spammy
behavior before incenting
customers to share.
Look at referrers in your web
analytics to find new and trending
sources of traffic (Pinterest,
Tumblr, others).
Finally, remember that no one set of measures can tell you everything; they all come with trade-offs. But looking at
your granular bottom-up data in context of broader trend data will deliver a more representative view of the revenue
impact of social media than either can in isolation.

The Future of Social Media Measurement
The ways organizations used to measure web behavior in the past are no longer suited to today’s realities. The
fragmentation of the customer journey (across screens, apps and, platforms) combined with heterogeneous data
streams make it near-impossible for organizations to trace “digital breadcrumbs” from a transaction to its source.14
The challenges, as Avinash Kaushik has articulated them15
, are straightforward: connecting the customer from online
to offline and connecting the customer across multiple screens. To this I would add another challenge: the need to
integrate social, enterprise, and external data for a holistic view of behavior and trends. Following are some of the
trends we should expect to see emerge in the next few years.
Mobile technologies will bridge the online and offline worlds.
Mobile Smartphone and Tablet Apps. While still relatively nascent, smartphone applications such as Shopkick and
Checkpoints, which use mobile and geolocation technology to deliver insight on in-store behavior, illustrate the
possibilities of mobile technologies to connect the dots between online and offline interactions.
Scanning and Visual Search. Whether it is QR codes, Microsoft TAG, bar codes, or eventually Google Goggles,
technologies will continue to emerge that add metadata to offline experiences and enable organizations to view the
customer experience more holistically. While we are now in a period of feverish development, eventually we will start
to see standards emerge in this area. In the meantime, however, the challenge for business will be to select vendors
that provide the most reliable and stable features and integrations and manage the new data streams these devices
create without creating undue complexity.
Emerging technologies will connect the customer across multiple screens.
Matching and Authentication. One of the greatest challenges for brands is the proliferation of browsers and screens,
from tablet devices to smartphones, laptops, desktops, and television. In fact, a recent study conducted by Boston’s
Innerscope Research found that “digital natives” switch screen 27 times per hour.16
Many web analytics vendors aim to connect the social customer using attribution algorithms, while Facebook
Connect, Klout, and apps like Empire Avenue attempt to encourage users to self-authenticate so that brands
can “know” them across social channels and platforms. Identity brokers, such as such as Gigya and Janrain and
technology startups such as Fliptop are uniquely focused on this issue, offering solutions that aim to authenticate and
connect customer identity across the social web.
The ability to authenticate identity across the social web also offers an intriguing promise — the ability to connect
transactions to social and interest graphs to better understand social influence on the path to purchase.
Data will be the true predictor of influence.
As authentication and attribution capabilities improve, the question of who influences whom will become much
clearer. Actual influence (seeing which customers, and customer types, tend to influence other customers to buy)
will overtake potential influence (algorithms that predict influence based on fans, followers, and frequency of social
activity) as a critical business metric. As a result, influence vendors will need to integrate with other transactional data
sources to validate their predictions. The winners will be those who use machine learning based on actual business
outcomes to refine their algorithms.

Companies will integrate social, enterprise, and external data for a holistic view.
Social media should not be a data silo; it must be tied to business strategy. The challenge is to normalize social data
to the extent possible and integrate it with other enterprise data (such as business intelligence, CRM, and market
research) and external sources (such as industry and economic data) to build sophisticated econometric models that
can be used for modeling, scenario planning, and decision support.
We are already seeing movement in this area via industry consolidation (Salesforce’s acquisitions of Radian6 and
Buddy Media), Oracle’s acquisition of Collective Intellect, Involver, and Vitrue, and SAP’s partnership with NetBase,
although it will take some time to realize the full beneﬁts of these acquisitions.
Ultimately, social data, in context of other enterprise data, will become a standard input into business decision-
making. The winning technology vendors will be those who seek to solve the whole business problem, rather than
looking at social as a silo.

Conclusion
Social media for business is still immature, and the mechanisms by which we understand its impact are still evolving.
Even if it becomes possible to “match” the majority of people using the social web across platforms, there will always
be those who, for personal, cultural, age-related, security, or political reasons, cannot or will not be identiﬁable.
For that reason, most organizations should expect to use a combination of rigorous top-down and bottom-up
measurement methods for the foreseeable future, and — to solve the ROI puzzle — will need to start quantifying their
investments in social, as well as their returns from it.
Whatever ingredients you choose for your measurement mix, the important point is that the organizations that
have been most successful at understanding the ﬁnancial impact of their social media programs share several
characteristics: They are customer-centric, value experimentation, accept that social media is in its infancy and, most
importantly, have the courage to learn from — and the generosity to share — their experiences.

Ecosystem Input
This report includes input from practitioners, vendors, and market inﬂuencers who were interviewed by Altimeter Group during the course of this
research. Input into this document does not represent a complete endorsement of the report by the individuals or companies listed below.
Brands (19)
American Cancer Society, Hilary Noon, VP Customer Insight and Experience
American Cancer Society, Robert Ross, Vice President, Interactive & New Media
Cisco Systems, Petra Neiger, Senior Manager, Digital and Social Media
eBay, Sudha Jamthe, Social Media Strategist
EMC, Keith Paul, Chief Listener
EMC, Maria Mariotti, Sr. Marketing Programs Manager
EMC, Todd Forsythe, VP Global Marketing
Eventbrite, Tamara Mendelsohn, VP Marketing
Hallmark, Camille Lauer, Social Media Insights Manager
IBM, Ranjun Chauhan, Digital and Social Intelligence Strategy
Intel, Ali Ardalan, Media and Analytics Strategist
SAP, Todd Wilms, Senior Director and Evangelist of Communities and Social Media
Starbucks, Alex Wheeler, VP Digital Marketing
Starbucks, Ryan Turner, Director of Global Social Media
The Coca-Cola Company, Vincenzo Piscopo, Global Director Knowledge and Insights
Thomson Reuters, Jaime Punishill, Global Head, WM Digital Distribution and Content Strategy
Ticketmaster, Kip Levin, EVP, Ecommerce
Ultimate Fighting Championship, Kristin Adams, Social Media Manager
Whirlpool, Stacy Lukasavitz, Social Data Analyst
Vendors (38)
Agencies (5)
Domain Experts (4)
Acknowledgements
With thanks for support from: Jon Cifuentes, Asha Hossain, Charlene Li, Rebecca Lieb, Chris Silva, Brian Solis, Jaimy Szymanski, Christine Tran,
Alec Wagner, Alan Webber, and Susan Wu.
33Across
Adobe
Argyle Social
Attensity
Awareness Inc.
Badgeville
Bazaarvoice
Buddy Media (acquired by Salesforce.com)
Campalyst
Compass Labs
Converseon
Crimson Hexagon
Exact Target
Expion
Fliptop
Google
Lithium
MarketShare
Meltwater Buzz
Microstrategy
Momentfeed
Moontoast
NetBase
Networked Insights
Offerpop
Power Reviews (acquired by Bazaarvoice)
Revinate
ShopIgniter
Shopkick
Simply Measured
Solariat
Spiceworks
Topsy Labs
VinTank
Visible Technologies
Vitrue (acquired by Oracle)
Webtrends
Campbell Ewald, Ken Burbary, Chief Digital Ofﬁcer
Edelman Digital, Dave Fleet, VP
Edelman Digital, David Armano, EVP
Edelman Digital, Aniz Ruda, Team Lead, Measurement & Analytics
WCG, Chuck Hemann, Director of Analytics
Matt Hixson, Co-Founder and CEO, Tellagence
Marshall Kirkpatrick, CEO, Plexus Engine
Nitin Mayande, Chief Scientist, Tellagence
Jim Sterne, Founder, eMetrics Marketing Optimization Summit;
Digital Analytics Association

End Notes
1
Social networking is the most popular online activity worldwide accounting for nearly 1 in every 5 minutes spent online in October 2011, and
reaches 82% of the world’s Internet population, representing 1.2 billion users around the globe. Source: comScore: http://www.comscore.com/
Press_Events/Presentations_Whitepapers/2011/it_is_a_social_world_top_10_need-to-knows_about_social_networking.
2
eConsultancy State of Social Report: http://econsultancy.com/us/reports/state-of-social.
3
http://www.kaushik.net/avinash/multi-channel-attribution-definitions-models.
4
Source: Facebook Developer Blog, https://developers.facebook.com/roadmap/completed-changes.
5
Source: Pew Research Center, “Twitter Use 2012,”1
http://www.pewinternet.org/Reports/2012/Twitter-Use-2012.aspx.
6
In statistics, multivariate testing or multi-variable testing is a technique for testing hypotheses on complex multi-variable systems, especially
used in testing market perceptions. Source: http://en.wikipedia.org/wiki/Multivariate_testing#cite_note-0.
7
For a good overview, see ClickZ, “A/B Testing for the Mathematically Disinclined,” http://www.clickz.com/clickz/column/1704390/a-b-testing-
mathematically-disinclined.
8
Source: “Capturing The Value of Social Media Using Google Analytics,” http://analytics.blogspot.com/2012/03/capturing-value-of-social-media-
using.html.
9
See Jeremiah Owyang and Rebecca Lieb, “The Converged Media Imperative: How Brands Will Combine Paid, Owned and Earned Media” for
more information. http://www.altimetergroup.com/research/reports/how-brands-must-combine-paid-owned-and-earned-media.
10
Altimeter Group explores these themes — The Dynamic Customer Journey, The Adaptive Organization and The Sentient World — in our
research. For more about these research themes, listen to our webinars on the topic here: http://www.altimetergroup.com/research/research-
themes.
11
See Avinash Kaushik, “Multi-Channel Attribution: Definitions, Models and a Reality Check”: http://www.kaushik.net/avinash/multi-channel-
attribution-definitions-models.
12
Source: Time, Inc.: http://www.timeinc.com/pressroom/detail.php?id=releases/time_inc_study_digital_natives.php.
Open Research
This independent research report was 100% funded by Altimeter Group. This report is published under the principle
of Open Research and is intended to advance the industry at no cost. This report is intended for you to read, utilize,
and share with others; if you do so, please provide attribution to Altimeter Group.
Permissions
The Creative Commons License is Attribution-Noncommercial-Share Alike 3.0 United States at
www.creativecommons.org/licenses/by-nc-sa/3.0.
Disclosures
Your trust is important to us, and as such, we believe in being open and transparent about our financial relationships.
With permission, we publish a list of our client base on our website. See our website to learn more:
www.altimetergroup.com/disclosure.
Disclaimer
ALTHOUGH THE INFORMATION AND DATA USED IN THIS REPORT HAVE BEEN PRODUCED AND PROCESSED FROM SOURCES BELIEVED
TO BE RELIABLE, NO WARRANTY EXPRESSED OR IMPLIED IS MADE REGARDING THE COMPLETENESS, ACCURACY, ADEQUACY, OR
USE OF THE INFORMATION. THE AUTHORS AND CONTRIBUTORS OF THE INFORMATION AND DATA SHALL HAVE NO LIABILITY FOR
ERRORS OR OMISSIONS CONTAINED HEREIN OR FOR INTERPRETATIONS THEREOF. REFERENCE HEREIN TO ANY SPECIFIC PRODUCT OR
VENDOR BY TRADE NAME, TRADEMARK, OR OTHERWISE DOES NOT CONSTITUTE OR IMPLY ITS ENDORSEMENT, RECOMMENDATION,
OR FAVORING BY THE AUTHORS OR CONTRIBUTORS AND SHALL NOT BE USED FOR ADVERTISING OR PRODUCT ENDORSEMENT
PURPOSES. THE OPINIONS EXPRESSED HEREIN ARE SUBJECT TO CHANGE WITHOUT NOTICE.

About Us
Susan Etlinger, Industry Analyst
Susan Etlinger (@setlinger) is an Analyst with Altimeter Group, where she focuses on social media analytics
and strategy. Previously, Susan was a Senior Vice President at Horn Group, where she pioneered the agency’s
social strategy offering. Susan is a published translator and has a bachelor’s degree in rhetoric from the
University of California at Berkeley.
Jeremiah Owyang, Altimeter Partner, Digital Strategy Analyst
Jeremiah Owyang (@jowyang) is a Partner with Altimeter Group, where he focuses on social business and
disruptive technologies for customer strategies. Previously, Jeremiah was a Senior Analyst at Forrester
Research, Director of Corporate Media Strategy at PodTech Network, and Manager of Global Web
Marketing at Hitachi Data Systems. He writes the Web Strategy blog (www.web-strategist.com).
Andrew Jones, Senior Researcher
Andrew Jones (@andrewjns) is a Senior Researcher at Altimeter Group, where he focuses on social
business strategy, including how brands can manage social media proliferation. He also follows broader
emerging technology trends such as mobile payments and the implications for governance and third-world
development. Andrew previously worked in digital marketing and served in the Peace Corps.
Altimeter Group is a research-based advisory ﬁrm that helps companies and industries leverage disruption to
their advantage.
Contact Us
Altimeter Group
1875 S. Grant Street, Suite 680
San Mateo, CA 94402-2667
info@altimetergroup.com
www.altimetergroup.com
Advisory Opportunities
Email: sales@altimetergroup.com

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