Gold in Them Hills: Computing ROI for Support Communities

Gold in Them Hills:
Computing ROI for Support Communities

Gold in Them Hills
© 2009 Lithium Technologies, Inc. All Rights Reserved.
Lithium Technologies, Inc.
lithium.com | 6121 Hollis Street, Suite 4, Emeryville, CA 94608 | tel 510.653.6800 | fax 510.653.6801
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Table of Contents
Purpose. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Financial Benefits of Support Communities. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Non-Financial Support Community Benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Case Deflection Savings. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Direct Deflection. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Indirect Deflection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
Decreased Support Costs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
Better Analytics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
Customer Satisfaction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Increased Sales. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Support Community Costs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Startup Costs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Recurring Costs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
Setting ROI Expectations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
About Lithium Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

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Purpose
This paper was created in collaboration with FT Works, a leading consulting firm that provides
strategy, operations, and metrics development & tracking services to support organizations. FT
Works’ extensive client list includes Google, Cisco, Autodesk, Chevron, Kodak, Hewlett-Packard
and Nokia.
This paper describes approaches used successfully by Lithium Technologies’ customers to
compute a realistic ROI (Return On Investment) for their support community initiatives. We define
ROI as Cumulative Benefits minus Cumulative Investment. You can use this paper in two ways: to
get a general education about community ROI, or to create your own custom ROI analysis.
If you only want general information about ROI, simply read through the paper. On the other hand,
if you are building your own ROI analysis you will find that you need to pause from time to time to
gather relevant data. In most cases you will find that you need to either analyze existing data in a
new light or gather data that simply does not exist today in order to complete the analysis. We hope
one of the benefits of this paper will be to inspire you to create better metrics for your business.
Our goal is to create a meaningful ROI calculation, based on solid and well thought-out data
so you can be sure that the ROI figure you obtain is correct and will continue to hold in the
future. Therefore, at every juncture of the following analysis we will encourage you to err on
the conservative side as you select data. The good news is that ROI for support communities is
typically very favorable, so even with our recommended conservative stance you are likely to find a
positive outcome for your community.
Financial Benefits of Support Communities
Support communities can provide financial benefits in several areas, depending on how they are
used. Here’s an inventory of the main categories.
Case deflection. For support communities this is typically the largest, most tangible, and
most easily tracked benefit. Customers who get answers through the community don’t need to
contact the support team for personal assistance. Since assisted support is costly, every
request that’s avoided (deflected) means a saving. Note that this applies not only to customers
who pose a question in the community and receive an answer, but also to the (typically much
larger) group of customers who don’t need to pose a question at all but find the answer
already posted in the community. This is Web 2.0 at its best.
Decreased support costs. Most savings occur via case deflection, but depending on how you
choose to deploy your community you may also experience additional savings. For instance,
the community may allow you to drop your email support channel entirely (replacing it with
the community), with attendant savings in staff and tool costs. Or you may be able to avoid
building a new support center to handle volume growth. Also, you may be able to boost the
productivity of the agents, either by leveraging the customer community as a knowledge base
or by deploying an internal community to more easily exchange information.
Our goal here is to
create a meaningful ROI
calculation, based on
solid and well thought-
out data so you can be
sure that the ROI figure
you obtain is correct and
will continue to hold in
the future.

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Better analytics. One of the very enticing benefits of support communities is to facilitate
feedback between customers and vendors, both for existing products and for future products,
for instance via a beta community. Customer feedback can be obtained via other means, by
mining interactions with assisted support channels or by conducting customer panels for
instance, but communities make the exercise much easier, faster, and less costly.
Communities are also ideal for spotting smaller-scope, detailed feedback that may never get
voiced through an assisted support channel or a formal customer panel because customers
see the issue as too trivial to bother.
Customer satisfaction. Community users tend to be more satisfied users, tend to recommend
your products or services to others, and experience lower turnover rates. The issue for ROI is
not whether customer satisfaction is increased by the community but rather how a company
can capture customer satisfaction and translate it into financial terms. We’ll come back to
this later in this paper.
Increased sales. Although a support community may not be the first tool you think about to
increase sales, it’s an ideal mechanism to make product recommendations. Some of
Lithium’s customers capture the traffic from their communities to their online sales site and
have shown that forum recommendations are most effective in triggering not only a visit to
the sales site but actual purchases as well.
Non-Financial Support Community Benefits
Do communities provide benefits other than financial? Absolutely! Just to use one example,
community users tend to be satisfied not just with the community but also with your products and
services as a whole. So even if you are unable to measure the financial impact of the increase
in customer satisfaction, you can rest assured that there are many non-financial benefits of
communities. Because our focus here is financial we focus exclusively on those benefits that can
be translated into dollars. It does not mean that there are the only benefits you will enjoy from
your investment.
Case Deflection Savings
Case deflection usually provides the bulk of the hard-ROI benefits for support communities.
Indeed, we find that many Lithium customers don’t bother estimating other savings, not because
they are not there but because they are likely to be dwarfed by the case deflection savings (and
they are harder to measure!). If you have a small user base or you are using an internal-only
forum naturally you won’t find large savings in case deflection, but that’s the exception rather than
the rule.
Case deflection is best analyzed by separating:
Direct deflection, which occurs when a user who would normally place a request for assisted
support instead posts a question and gets an answer; and
Indirect deflection, which occurs when a user obtains an answer from the forum without
having to post a question. In other words, the question has been posed and answered already
and the customer can use the answer immediately.

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In most cases indirect deflection generates much higher savings than direct deflection. We see
ratios of 1:5 to 1:10 and beyond between direct and indirect deflection, scaling up with the size of
the user base. Communities are very much a many-to-many tool.
Direct Deflection
To calculate direct deflection you need two pieces of data:
The volume of threads that result in an answer; and
The cost of processing an assisted support request (cost per case or cost per call)
The cost per case is usually pretty easy to obtain, as it’s a standard support metric. If you don’t
happen to have it handy you can simply divide the support budget (at least the assisted support
cost) by the number of assisted support cases you handle. If your support organization typically
handles highly complex cases and you feel that deflected cases are much less complex than
average (a reasonable assumption) you may use a discounted figure for the cost per case. For
instance, you may use the cost for the average case handled within the level 1 team.
Computing the volume of threads that result in answers, and therefore correspond to deflected
cases, requires a little more effort and thinking. Clearly the overall volume of threads is easy to
capture but not all threads get answered. So how can you proceed?
If you ask users to label threads as “answered,” use the labels. You will be undercounting
successful threads (since a fair number of users may receive an answer but not bother to
mark the thread as answered) but that’s what you want: you want to be conservative in your
assumptions.
Otherwise, perform a simple manual audit. Read through the threads that were posted last
week (or just one day last week if your volumes are high) and determine the percentage of
threads that were answered. You want to use threads that are slightly old so they had a
reasonable chance to get answered; if you use this morning’s threads you will drastically
underestimate the success rate. You want to be conservative in estimating ROI benefits but
you don’t want to be thoughtless. We find that answer rates tend to remain fairly constant so
you don’t need to perform the audit more than once a quarter or maybe once a year.
If some threads are answered by customers and some by staff members, should you
distinguish between the two? If you have staff dedicated to the community, or you have a way
to capture the cost of the effort of answering community questions (perhaps via a “cost per
thread” figure similar to the cost per case figure), no worries. You will simply capture your
cost on the cost side of the ROI so you don’t have to distinguish here between customer-
answered and staff-answered. If you have staff that works seamlessly on both threads or
cases and you cannot easily tease out their cost you should segregate out threads answered
by customers (hence answered “for free” and clearly belonging in the deflected category) and
threads answered by your own staff (that are not free and do not represent complete
deflection – even if the cost of a community answer is probably less than the cost of a regular
support case.)
In most cases indirect
case deflection gen-
erates much higher
savings than direct
case deflection. We see
ratios of 1:5 to 1:10 and
beyond between direct
and indirect deflection,
scaling up with the size
of the user base.

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If you must determine the proportion of customer-answered threads, perform a simple audit.
The percentage should remain quite stable over time unless you change your support model
so there’s no need to repeat the analysis more than once a year.
If some of your customers are not entitled to contact support you should remove their
answered threads. Yes, their questions were answered, but no case deflection occurred since
the customers could not contact support in the first place.
How do you distinguish between supported customers and others? It depends on your internal
tools. If you can match community users to support contacts the computation is pretty easy. If
you cannot, again use a small-scale audit or survey to find out. Note that there can be impor-
tant differences in the way that entitled and non-entitled customers use the community:
typically non-entitled customers are heavier users of the community since they have no other
alternatives.
As a recap of the arithmetic, direct deflection volume is computed as follows:
total thread volume * answer rate
And all you need to do to get to savings is to multiply by the cost per case
total thread volume * answer rate * cost per case
Example
ACME’s community added 5000 threads last month, 80% of which were posted by customers with
a support contract. 46% of the threads were resolved by customers, the balance by ACME support
staff (ACME has a policy to respond to each thread if it’s left unanswered for 24 hours.) ACME’s
cost per case is $20. How much did ACME save through direct deflection?
Of the 5000 threads, 5000 * 80% = 4000 were for customers with a support contract. (We
don’t count the other 1000 since customers without a contract cannot contact Support.)
Of those, 4000 * 46% = 1840 were answered by the community. (The others were answered
by Support staff so were not deflected.)
The savings are 1840 * 20 = $36,800 for direct deflection.

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Indirect Deflection
Now for the fun part: indirect deflection (or “savings through search” as some call it) embodies
the essence of communities: users’ experiences can be shared. The calculation is.
browsing visits * success rate * cost per case
Since we already computed direct deflection, that is the savings associated with users who posted
questions and received answers, we now want to focus on browsing visits, visits in which the user
did not choose to create a new thread, so the calculation can be refined to:
(visits – threads) * success rate * cost per case
A visit is not a page view. Typically customers will visit multiple pages as part of a single visit and
it would be grossly inaccurate to consider page views rather than visits. So what constitutes a
successful visit? Clearly, one during which the customer finds an answer, but how do we capture
that? There are a number of avenues depending on your specific circumstances.
If you ask community users to log in and you are able to match the logins to your assisted
support entitlement data, you will be able to determine whether community users then move
on to log an assisted support request. Naturally, someone could visit the community to take
care of one need, find the answer, and then place a support request on an unrelated topic.
However, matching up visits to support requests placed within a reasonably short window
(say, 24 hours) will give you a solid, conservative estimate of success.
Since most communities do not require browsing customers to log in, other techniques are
needed to estimate the success rate, typically through a user survey of some kind. There are
no silver bullets here. You may use a pop-up survey as users exit the forum (but it’s difficult to
capture forum exits, and in any case many users block pop-ups.) If you are able to reach out to
your users in other ways, for instance via email, you can contact them after the fact and
gather their perception of success. You could also use data from a survey about overall
self-service usage, not just communities.
The good news is that you don’t need to repeat this type of survey very often as success rates
tend to remain fairly even.
Working with Lithium customers we find that the success rates for finding answers within
communities range from a few percentage points (using very conservative estimates, to be fair)
to 30%-plus. Industry data suggest that a success rate of 40%-plus for self-service would be
extraordinarily high.
One last note about deflection savings: it takes a while to get to a critical mass of community
users, so if you’re starting out, expect to see a ramp in deflection from just a small amount at the
beginning (and mostly direct), increasing as the popularity of the community grows and indirect
deflection blossoms.
Working with Lithium
customers we find that
the success rates for
finding answers within
communities range
from a few percentage
points (using very
conservative estimates,
to be fair) to 30%-plus.

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Example
Let’s reprise the ACME example above and focus on indirect deflection. The ACME community
enjoyed 50,000 visits last month and is estimating a 20% success rate, based on its survey of
self-service (20% is a fairly high number but ACME seems to pay close attention to self-service,
including posting answers to all community threads, and that’s paying off.) How much did ACME
save through indirect deflection?
The number of browsing visits is 50,000 – 5000 = 45,000 (removing the visits where a
thread was created.)
The number of successful visits is 45,000 * 20% = 9000.
The savings totals 9000 * 20 = $180,000 for indirect deflection. Note how the number is a
lot higher than the direct deflection number and how it could be even higher if the user base of
the community were larger.
Decreased Support Costs
Clearly communities decrease support costs because they decrease the number of support
requests, as we just described at length. But they may also have other positive impacts, usually of
smaller scale, that we will explore here.
Increased productivity. You may find that using communities allows your support agents to be
more productive, namely to resolve issues faster and to be able to handle more issues without
escalating to the (always costly) next level. The productivity increase may occur with level 1
agents if you find that they can leverage the customer community as a knowledge base
substitute or add-on. The productivity increases may occur with agents of all levels if they
have access to internal forums that facilitate quick dissemination of information amongst the
staff.
The math to compute increased productivity savings is not too difficult, although you will need
detailed data on resolution time and cost by level of agent. You will also have to ensure you
are not double-counting savings if, as is common, there are multiple savings at multiple
levels. The savings will be expressed by the following formulas, one for savings achieved
within a particular level of the organization:
time saved * cost per minute
and one for savings related to lower escalation percentages:
escalation avoidance * cost at next level
Be careful not to be too optimistic with productivity increases. If you start a customer
community a common consequence is that the technical complexity of support requests
increases as the easier issues get resolved within the community so your agents may spend
more time on each case on average, reflecting the increased complexity. You would still
experience savings since the overall case volume is lower so the aggregate amount of effort
required to solve all cases decrease, but the “savings” for this particular category would
be negative.

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Decreased support agent costs. To be sure, decreased support agent costs are more elusive
than increased productivity, but they may exist in your context. They would include:
•• Lower compensation if you can use less-skilled agents who leverage community
knowledge (internal or external forum). Your savings equation is
compensation savings per head * headcount
•• Lower facility costs if community sharing allows you to use home-based agents. The
savings are
facility savings per head * headcount
•• Faster ramp up. Using the community as a knowledge creating and sharing mecha-
nism may translate into tangible gains in how long it takes to train new agents. The
savings add up:
time saved * compensation * headcount
•• Lower turnover. Agents who feel they have good tools tend to stay longer. As we
know, turnover means much higher recruiting and training costs so if you can link
community use to lower turnover you will see tangible savings.
turnover decrease * cost of turnover
Strategic savings. In some instances communities may serve as a substitute for other, costly
investments. For instance, they may allow you to skip investing in the following areas (in each
instance, the savings are simply the avoided cost of the investment):
•• Support for multilingual customers. Supporting multilingual customers is often
expensive, requiring hiring new, multilingual employees, and often opening a new
location where such people can be found. It may require translating extensive
amounts of documentation and training materials for agents. Instead, you may
be able to direct customers to a community and avoid or delay the investment in
people and facilities.
•• Support for long-tail products. It can be very expensive to maintain a trained work-
force to support low-volume, perhaps older products or releases – the statistical
“long-tail” of support demand for any mature company. Tapping the knowledge of
your customers is the best way to meet this demand. The savings would equal the
investment you would have to make otherwise.
•• Business continuity solutions. While we would always recommend having a robust
business continuity (backup) plan in place for your support centers, it’s very
expensive to build complete redundancy, especially for major, uncontrollable
events such as natural disasters. If your customers can use alternate support
avenues such as a community during the disaster recovery time frame they will
be much more tolerant and understanding of the failures, especially if you can be
candid about the source of the problem.
It can be very expensive
to maintain a trained
workforce to support
low-volume, perhaps
older products or
releases. Tapping the
knowledge of your cus-
tomers is the best way
to meet this demand.

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•• Spike handling. In the same vein, it’s awfully hard to be completely ready to handle
sudden spikes in volume. By using the community as an overflow mechanism you
could save significant dollars.
•• Substitute support channels. Some Lithium customers have been able to simply
do away with providing email support by offering community support instead
(yes, their communities are monitored by internal staff, but the savings are still
significant due to the many-to-many nature of communities).
•• Delay in strategic investments. Is there a new support center in your future to
handle increasing volume? Deploying a community solution may help you avoid the
steep costs associated with a new venue.
Decreased online maintenance costs. If you are converting an existing community to a
Lithium-powered community you may well find that Lithium’s features allow you to save on
administration costs. Customers tell us that they can save in three ways: forum maintenance,
forum administration, and the ability to repurpose information gleaned from the forum into
the knowledge base (an active community is a wonderful knowledge-
mining site).
Better Analytics
While issues may take days to percolate through the support centers (typically much longer than
it takes to resolve the cases to which they gave rise, since root cause analysis rarely starts until
cases are closed) community input can be used much faster. Let’s consider both reactive benefits,
through better root cause analysis, and proactive benefits, thought better customer input.
Product issue identification. If you are able to identify product issues by mining forum data
and resolve them, your savings will amount to
# issues * cost saved by discovering issue
While this technique can apply to all kinds of product problems, communities are
particularly suited for spotting low-grade issues, issues that may not be identified through
assisted support for a long time because the agents fail to identify their full scope: after all,
all the customer had to do was to reboot. But as we know a large volume of small annoyances
adds up to a sizable cost, not to mention lots of frustrated customers.
Product Feedback. The other, more advanced idea is to use communities as product feedback
mechanisms. Seeking customer input for new or future products is not easy or cheap, and
communities can be a great avenue for gathering data quickly and
inexpensively. The savings will be the cost saved in focus groups and surveys.
(# focus groups * cost) + (# surveys * cost)
If you can go one step further and track the adoption rate of the product, you can capture
increase in adoption rate * product price

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but it’s probably difficult to track all the way through. See the Increased Sales section at the
end of the paper for more suggestions around sales benefits.
Customer Satisfaction
The customer satisfaction benefits of support communities are undeniable: customers love
communities and their enthusiasm seems to carry over to the very products supported in the
communities. The challenge is not so much measuring customer satisfaction, but rather
translating increased satisfaction into a financial benefit. Most organizations have no established
method to do that, and if that’s your situation that’s fine: simply concentrate on measuring the
other benefits.
In the organizations we’ve worked with who have quantified the financial impact of customer
satisfaction it’s typically the Marketing group that has led the effort, showing that an increase of
X points on customer satisfaction can be matched to an increase of Y dollars in revenue. Other
companies assign a token (and completely arbitrary) value to customer satisfaction, such as $1 for
each increase of one point. If you have such data, you can apply it to the
following areas:
Customer satisfaction with communities themselves.
Customer satisfaction with specific topics that are well-served by the communities, better
served than through assisted support. For instance, communities are typically an
excellent medium for sharing best practices.
Customer satisfaction with support in general. Customers typically appreciate communities
as part of the total support experience
Customer satisfaction with the product or brand. Community users often report higher
overall satisfaction
You may also be able to measure the impact of the community on reputation: how community
participation may inspire your customers to be active advocates for your products and your
company. While we believe that community participation does indeed encourage customers to
become active cheerleaders it’s a challenge to capture exact numbers. If you choose to venture
into this area you may want to look at two aspects:
Independent recommendations. Community users tend to recommend products associated
with the community to others. Benefits would be computed through the volume of influenced
purchases (You can tell how difficult that would be to track: see the next section for another
way of looking at sales influenced by community usage).
Better brand value. Community users are more likely to positively influence the brand. Again
this is a difficult metric to tease out.
Seeking customer
input for new or future
products is not easy or
cheap, and
communities can be a
great avenue for
gathering data quickly
and inexpensively.

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Increased Sales
Do community users buy more than others? It seems from Lithium customers’ experiences that
the answer is yes, and that the only obstacle to capturing that data is a good tracking mechanism
to track the behavior of community users, typically by analyzing the origin of online purchases
to determine whether they come directly from the community. Look for additional sales in the
following areas.
Product sales. This is commonly seen when forum posts recommend specific items. The
increased sales will be:
# of additional purchases * product price
Support sales. Community users may purchase or renew support contracts more readily. The
increased sales will be:
# of additional support contracts * contract price
Lower churn. Community users tend to remain as customers longer than others. If your
industry experiences high churn that would be a very high value. While difficult the measure,
the conservative increased sales will be (calculated assuming the average retained customer
stays one additional year):
# retained customers * avg. annual sales per customer
Support Community Costs
Support community costs fall into two categories: startup costs and recurring costs. If you are
preparing an ROI analysis for an upcoming purchase you will likely concentrate on the startup
costs such as project management for the implementation, but you must also consider recurring
costs such as the compensation of the community manager.
If your community is way past implementation stage, it’s not too late to create an ROI analysis. You
will likely focus on the recurring costs since startup costs have long since been expensed.
Startup Costs
Here’s an annotated checklist for startup costs:
Launch fee. This is the fee you pay to Lithium.
Cost of other software. This refers to optional, complementary software for communities
such as analytics software.
Do community users
buy more than others?
It seems from Lithium
customers’ experiences
that the answer is yes,
and that the only
obstacle to
capturing that data is a
good tracking
mechanism to track the
behavior of
community users.

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Project management costs. This is typically an internal cost although you may choose to hire
a third party to handle the rollout. It can be difficult to estimate internal costs but do give it a
try. Especially for larger-scope initiatives internal costs can be significant. Estimate the
headcount (or portion thereof) required and multiply by a weighed labor cost.
headcount or % * fully-loaded cost
Integration costs. If, for example, you are integrating the community with your CRM system or
enabling single sign-on, Lithium will assess an integration fee in addition to the launch fee.
Design work. Integrating the new community with your existing support web site will require
some amount of work, either internally or through an outside agency.
Process design work. Adding a community means adding new roles (such as moderators) and
often new tasks (such as forum data mining.) The process creation and revision work is
usually done internally.
Internal IT resources. Although Lithium is a SaaS solution, some amount of IT resources may
be required if you are implementing a single sign-on solution or other integration.
Data migration. Migrating user IDs to Lithium may be handled by internal resources or a third
party as part of the initial rollout.
Reporting setup. Perhaps inspired by this paper, you will want to set up a reporting environ-
ment for your communities such as web metrics.
Administrator training. Lithium provides complimentary training but you should take into
account the time required for the administrators to attend the training.
Training for forum moderators. Here again it’s a matter of the time investment rather than
out-of-pocket training fees.
Marketing rollout to customers. You will probably want to tell your customers about the new
community. For instance, you may need to invest in an email campaign.
Recurring Costs
So much for the startup costs. What about recurring costs?
Usage fee. This is the monthly fee you pay for Lithium’s software. Your ROI calculation should
project increases related to higher usage (which will be matched by increased
case deflection.)
Software maintenance. If you purchased add-on software as part of the rollout you will be
paying maintenance for it.
Reporting recurring fees. Your IT organization or third-party provider may charge you
regular fees for creating the reports – and it’s likely you will want to update the reports every
once in a while.
Ongoing IT support for integrations. Again this is for CRM or other integration.

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Administrator or community manager. Every community has a manager. This is often a
part-time commitment from someone who has other responsibilities in marketing, support,
or product management.
Moderators. If you are using Lithium’s moderation services or have a full-time internal
moderator, this recurring cost is easy to calculate. If you are using part-time internal
moderators (such as asking support agents to contribute a portion of their time to monitoring
the community) use your best estimate of the time spent on this task. The “time online” metric
in the Lithium solution can help you quantify how much time individuals are spending in the
community.
As mentioned in the discussion around deflection, if support agents are seamlessly working
on cases and community threads you may be better off separating out their answers from
customers’ rather than performing complicated calculations at this point.
Support costs for community escalations. In our experience we have found that only a tiny
percentage of community users ever need escalation-handling. If you feel that it’s important
to include, estimate a recurring cost for community issue management.
Super-user program administration. In most communities, a small number of users answer
a large percentage of all questions. Successful communities usually have programs in place
to recognize and support these “super-users” with various rewards, including gift
certificates, free admission to conferences, and free products. The costs are usually small,
but make sure you are capturing whatever you spend, plus the cost of management time
related to super-users.
Setting ROI Expectations
The two most popular questions we get are: How soon will we reach positive ROI on our
investment? And, how will overall benefits compare to overall costs over the long-term? The
answer to both is a resounding “It depends.”
You will reach positive ROI very soon
Working with real customers, we have been surprised (and so have they!) to find companies
reaching positive ROI on their initial community investment in as soon as a few months, when the
communities still felt very new. This is because the startup costs for communities are relatively
small (and indeed larger communities that require more upfront work may take a little more time
to reach positive ROI).
Your mileage will vary
Working with customers who have established communities that are considered successful
by them and their customers, we see the ratio of financial benefits to costs varying greatly,
from 2:1 (that’s a 200% overall return) to 10:1 and up. There are many reasons why a particular
community’s return will be much larger than another, including how well you can capture accurate
metrics, so rather than shooting for a particular number or ratio let’s reaffirm a few critical
Working with
customers who have
established
communities that are
considered
successful by them and
their customers, we
see the ratio of financial
benefits to costs
varying greatly, from 2:1
(that’s a 200% overall
return) to 10:1 and up.

Gold in Them Hills
15 of 15
success factors.
Size matters
The communities with the larger user bases have the largest returns. This is because the indirect
deflection savings are enormous for large communities, even if the success rate of using the
forum is relatively low. So if you have a small user base either work to increase it or be content
with a more modest return.
Follow community best practices
The most successful communities, without exception, follow a small set of best practices (for
some of those practices, see our whitepaper entitled Online Support Communities: Best Practices
and Deployment Tips for Reducing Costs and Increasing Overall Customer Satisfaction). For instance,
successful communities carefully cultivate and reward community participation.
Get better metrics
We find that the largest obstacle to creating successful ROI analyses is not that there’s no ROI
(there almost always is!) but rather that support organizations have a hard time coming up with
accurate, reliable data. For instance, many organizations simply do not track success rate for
forum usage. We hope that we have inspired you to capture a few key pieces of data on a regular
basis, starting with success rate.
Conclusion
This paper was created based on the complementary expertise of Lithium and FTWorks, combined
with the real-world experience of Lithium’s customers. Whether you are building the business
case for a proposed support community, or assessing the ROI of an established community, this
paper provides you with a robust framework for conducting your analysis.
About Lithium Technologies
Lithium is the leading provider of Social CRM solutions to power enterprise customer networks.
Lithium solutions combine the power of online customer communities with the broader social
web and traditional CRM business processes to inspire customers to innovate, promote, and
support on the company’s behalf - measurably improving marketing and sales, accelerating
innovation, and increasing customer satisfaction. Lithium’s platform is proven in high-volume,
growth environments and provides the security, analytics, APIs, and multi-language support that
enterprises demand.
About FT Works
Lithium is the leading provider of Social CRM solutions to power enterprise customer networks.
Lithium solutions combine the power of online customer communities with the broader social
web and traditional CRM business processes to inspire customers to innovate, promote, and
support on the company’s behalf - measurably improving marketing and sales, accelerating
innovation, and increasing customer satisfaction. Lithium’s platform is proven in high-volume,
growth environments and provides the security, analytics, APIs, and multi-language support that
enterprises demand.

Gold in Them Hills: Computing ROI for Support Communities

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