The document provides a statistical analysis of live chat performance benchmarks based on data from thousands of LogMeIn customers. It finds that chatters are much more likely to convert than non-chatters, with proactive chat further increasing conversion rates. The acceptance rate for proactive invitations is on average 8.5% but varies widely. Expected chat volume depends on site size and use of proactive chat. The analysis also examines unavailable, unanswered, and abandoned chats as well as pre-chat surveys, chat satisfaction rates, and differences for higher traffic sites.
2. Introduction
Highlights
• Thousands of customers,
worldwide
• Reliable 99.99% uptime
• The industry’s best value
• Rapid deployment
• 24/7 support
• Proven installs across vertical
markets
Contact
BoldChat, a brand of LogMeIn, Inc.
2024 N. Woodlawn
Suite 350
Wichita, KS 67208
Phone: (866) 753-9933
(316) 462-7190
Email: info@boldchat.com
Website: www.BoldChat.com
In the fall of 2009, we published a benchmarking report which queried the data
across our entire customer base in order to produce statistics related to live chat
usage. Prospective customers, members of the media, analysts, and existing
clients had asked for data from the vantage point of Internet retailers, e-service
providers, and other website owners who use live chat software for sales and
services engagements. The initial publication marked the first time that a
leading live chat provider openly shared statistically relevant benchmarking
data and, as expected, the report was immediately popular. The document,
entitled Live Chat Performance Benchmarks: A statistical analysis remains
one of our most popular collateral pieces.
Because our products are provided through a software-as-a-service model, our
infrastructure includes aggregated data from thousands and thousands of live
chat customers. With tens of millions of chat records, hundreds of millions of
website visit records, and billions of unique page-URL recorded visits, we have
access to one of the largest live chat user communities in existence. This massive
base of real-world data has enabled us to extract the findings presented in both
the original report, and this follow-up version. While many of the goals of this
analysis remain consistent with the inaugural version, there are three additional
goals which themselves were born from readers of the initial report. The original
goals remain:
1.
Present benchmarks for a wide variety of live chat
operational practices
2.
Uncover implementation differences affecting
key live chat operational issues
3.
Test the statistical causality of live chat
operational best practices
The additional goals in this updated version are:
4.
Monitor and report on changes to key benchmarks
since the first report
5.
Calculate benchmarks for higher traffic sites
6.
Identify and present benchmarks for “elite” users of live chat
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3. These last two goals are worthy of discussion. In the first
benchmarking report, we noted that the key determinant
related to many critical live chat statistics was quite
simply the amount of website traffic a business had. As
the volume of visitors went up, the averages and ranges
associated with the benchmarks shifted in meaningful
ways. Higher traffic sites, rightly, have asked us to
contemplate benchmarks for them distinctly and in this
updated report we do so explicitly.
The last goal comes from the fact that many of the benchmark ranges presented in this type of analysis are, by
their nature, very wide. In many engagements with
customers and others familiar with our benchmarking
report, we’ve had conversations that began mostly like
this: “Thanks for providing these benchmarks; it’s helpful
for us to understand the ranges one could expect on
average. But, we don’t want to be average! We want to
be exceptional! If we apply best practices and rigorously
test things as you suggest, then what can we expect?”
In this new version of the benchmarking analysis, we
attempt to provide guidance here. In several sections
throughout the report, we analyze the “best of the best”
– smaller groups of customers achieving exceptional
results – so that readers can discover not only what
average is, but what’s superlative.
In several sections throughout the report,
we analyze the “best of the best” – smaller
groups of customers achieving exceptional results – so that readers can
discover not only what average is, but
what’s superlative.
A Note About Privacy
BoldChat takes the privacy of its customers seriously. We
are bound by our privacy policy and as such, protect our
customers’ information. In accordance with this policy,
the data presented in this report is entirely summative.
Unless we have a customer’s specific and written permission, we do not reveal individual statistics or information.
Terminology
For those unfamiliar with live chat technology some key
terms are defined here which will help readers to better
understand the data in this report. Other terms related to
customer groupings are also defined.
Conversion: The BoldChat system includes a conversion
tracking mechanism allowing customers to specify and
report on customized conversion types. For this analysis,
only financial conversion types were considered (i.e.,
purchases).
Pre-Chat Form: A set of questions posed to a potential
chatter before the chat starts but after they click a chat
button or accept a proactive invitation.
Unavailable Email Form: A form presented to the website
visitor after they click on a chat button during a time in
which no chat operator is available to answer the chat.
Reactive Chat: Chats initiated by website visitors by
clicking on a chat button.
Proactive Chat: Chats which occurred due to a website
visitor’s acceptance of an invitation to engage in a chat.
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4. Unavailable Chat: An attempt by a website visitor to
initiate a reactive chat during a time in which the
website’s agent is not available to answer the chat.
Abandoned Chat: A chat that makes it to the pre-chat
form, but never actually starts.
Unanswered Chat: A reactive or proactive chat begun by
a website visitor but never responded to by a website’s
agent.
Higher Traffic Sites: The group of websites in our
customer base that are well trafficked. These sites, on
average, experience almost four times the website traffic
as our average customer.
Elite Customer Segments: A smaller group of websites
for which traffic is significant and for which all the sites in
the segment exhibit benchmark performance at the
highest level.
Benchmarks vs. Best Practices
While the data provided in this report is certainly aimed
at making customers more successful, they cannot themselves be called best practices. Certainly, part of this
project aims to uncover areas that can positively
influence a live chat implementation, but best practices
are not only derived mathematically. There is a human
component – an expert human component – necessary
for any best practice to yield results. So, while the data in
this report may inform best practices and even uncover
new areas that can become best practices, they cannot
be labeled as such.
There is a human component – an expert
human component – necessary for any
best practice to yield results.
While “benchmarks” is not an entirely accurate term either,
it does more correctly describe the statistics presented
herein. A benchmark is a snapshot of data against which
progress can be measured over time. Using aggregated
metrics of thousands of customers should give new and
existing live chat users alike something against which they
can compare their own performance.
Approach
To create this report, we employed three tactics iteratively.
Common Questions
During sales and professional services engagements, our
staff is frequently asked a similar set of questions. Again, we
are able to answer these questions based on expertise
developed over years of firsthand experience, but the questions themselves were directionally useful as we crafted
specific queries to our vast databases of information. Some
of the most influential questions posed to us are:
• What kind of chat traffic can our company expect?
• Does proactive chat positively influence conversion?
• What percent of chatters will convert to sales?
• What is the best time to engage a visitor proactively?
• Should we start with chat for support or chat
for sales?
• Where should we put the chat button?
Known Best Practices
By working directly with customers over the years, our
professional services team has developed a playbook of
implementation standards that seem to work time after
time. This project afforded us the opportunity to statistically verify or refute the observed efficacy of many of these
practices.
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5. Data Interrogation
Many people inside our organization, because of the
nature of their jobs, have an intimate knowledge of our
data structure. The insight brought to bear on this project
by our database administrators, developers, professional
services personnel, quality assurance team members,
and many others proved an invaluable resource. Their
understanding of the interdependence between seemingly disjunctive data points coupled with a dogged
curiosity for discovery often led us in new and important
directions.
Live Chat Benchmark Statistics
This section of the report, divided into sub-sections, shows
and explains the findings from this research effort.
Live Chat & Conversions
In this section’s analysis, we examined tens of thousands of
individual purchase conversions. It yielded some of the
original report’s most intriguing findings. The same holds
true today.
• Chatters are 7.5x more likely to convert than visitors
who don’t chat. Up from 4.1x in 2009.
Statistics Methodology
• Chatters buy, on average, 24% of the time.
This section includes a discussion of the statistical
decisions made during this project.
• Chatters spend about 55% more per purchase than
non-chatters.
• Chatters who engage via proactive invitation are 8x
more likely to convert than visitors who don’t chat.
Up from 6.3x in 2009.
Median vs. Mean
Many of the benchmark statistics presented in this analysis utilize the median rather than the mean. The median,
distinct from the arithmetic mean, is the middle value of
the data. Half of the data set is less than or equal to the
median and half is greater than or equal to the median.
The median is still a type of average, however, so it is
appropriate for a given benchmark to say that, “the
average BoldChat customer…”
Knowing that higher traffic impacts benchmarks, here are
some of the above statistics recalculated against our
higher-traffic customer base.
We decided to use the median because it corrects for
outlying data while an arithmetic mean does not.
• Chatters with higher traffic websites buy, on average,
17% of the time.
Confidence Interval
Where appropriate, we also provide statistical ranges
within a 95% confidence interval. Ranges allow people to
see the upper and lower boundaries that can be expected.
Intervals also allow us to make the following types of
statements: “We can be 95% confident that the average
BoldChat customer will experience between X and Y…”
• Chatters are 5.5x more likely to convert than visitors
who don’t chat.
• Chatters who engage via proactive invitation are 9.8x
more likely to convert than visitors who don’t chat.
And while both result sets are impressive, here is a calculation for the “elite conversion segment” set of customers.
These businesses have turned chat conversion into an
artform worthy of study, and accolades.
• Chatters with the elite buy, on average, 55% of the time.
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6. Chat Engagement
These data points are focused on actual live chats occurring between a website agent and a visitor.
• The average percentage of website visitors who
engage in chats is 1.7%. This is essentially
unchanged from 2009.
• Within a 95% confidence interval, the engagement
rate ranges between <1% and 15%.
• For our higher traffic websites, less than 1%
of visitors engaged in chats.
Readers are advised to remember that this statistic represents the middle of the data set; half the sample experiences engagement percentages equal to or above this
figure and half experience engagement percentages
equal to or below this number.
If a site aims to maximize engagement, we know it’s
possible. We know by looking at the range associated
with the “elite engagement segment” of our customers.
This group chats with 9-22% of their site visitors.
Proactive Chat
Proactive chat is the issuance of a form, image, or other
component that generally appears on top of a website
and invites the visitor into a chat interaction.
• The average percentage of website visitors who
accept proactive invitations to chat is 8.5%. Up
from 6% in 2009.
• The acceptance rate for proactive invitations
continues to vary widely. Within a 95% confidence
interval, the acceptance rate is between 1% and
29%. Previously, this range had acceptance rates
between 1% and 22%.
• The ‘Chat Form’ type of invitation is still more widely
accepted. It’s nearly 37% more likely to be accepted
over other types. However, in 2009, it was 50% more
likely to be accepted.
Proactive appears to be critical for higher traffic websites.
Among these sites, proactive had an average acceptance
rate of 9.7%.
Proactive chat is an area where many customers attempt
to optimize. Looking at the “elite proactive segment” of
our customer base, proactive acceptance ranges from 13%
to 46%, but the Chat Form type of invitation is no more or
less likely to be accepted.
Expected Chat Volume
The possible range of the chats to visit ratio is substantially
affected by the size of the website and the use of proactive
invitations. The chart below gives averages on what one
can expect for chat volume based on the visit volume a site
receives each month. It appears that for larger sites, it is
more difficult in general to get the same proportion of
visitors to engage in a chat compared to smaller sites.
Adding proactive invitations, however, can substantially
increase one’s range of influence over chat. The expected
chat volume for any sized site should increase as proactive
chat becomes a larger part of the mix. By charting the
median values of engagement, one can see the importance of proactive chat. On average, it will more than triple
a site’s engagement rate.
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7. 5.00%
4.50%
4.00%
3.50%
3.43%
w/Proactive
3.00%
2.50%
1.93%
2.00%
1.81%
w/o Proactive
1.50%
1.00%
1.10%
0.91%
1.06%
0.32%%
0.50%
0.00%
0.34%
1-10K
10-25K
25-100K
100K +
Figure 1: Expected Chat Volume
Unavailable, Unanswered, and Abandoned Chats
These data points revolve around missed chat opportunities.
Pre-Chat Survey
Before a chat begins, many customers collect some information from the visitor. They do this because it either helps
them provide better service or to filter out unwanted
engagements.
It is clear that showing certain fields and/or making fields
required affects the average abandonment percentage.
Requiring a phone number appears to make a significant
difference worthy of note.
Median 47%
Status
Optional
Required
Phone
• The average percentage of website visitors who
abandon chats when a pre-chat form is presented is
47%. That’s up from 39%, which hints that visitors are
becoming less willing to complete a form prior to
receiving assistance.
Not Shown
45%
50%
56%
Email
44%
48%
50%
Name
45%
50%
48%
Figure 2: Pre-Chat Form Fields
• For higher volume sites, the abandon rate was 44%.
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8. Unanswered Chats
We regularly tell customers as a best practice to answer chats within 10 seconds. Initially, the data from this project challenged
that advice.
• The average wait time before visitors give up on a chat is 20 seconds when a pre-chat form is not in use which is up
from 15 seconds but,
• The average wait time before visitors give up on a chat is 54 seconds when a pre-chat form is in use. This is down
significantly from 113 seconds in 2009.
So, while visitors over time seem to be becoming less likely to fill out a pre-chat form, they are becoming more patient when
one isn’t in use, but less patient when one is. If they bother to fill out the form the chat needs to be answered today, faster than
in 2009. Overall, with each passing second, more and more visitors give up:
100%
90%
80%
70%
w/Prechat
60%
50%
w/o Prechat
40%
30%
20%
10%
0%
0
30
60
90
120
150
180
210
240
270
300
Figure 3: Unanswered Chat Survival
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9. Unavailable Email Form
When website operators are not available to chat, an email form can capture lead information for later follow up.
• The average percentage of website visitors who will submit an email form if one is presented to them is 17%.
This is down from 23%.
• Within a 95% confidence interval, the average percentage of website visitors who will submit an
email form if one is presented to them is between 0% and 57%.
Chat Satisfaction
Aggregated customer data confirms that live chat engagements are highly satisfactory for website visitors.
• The average percentage of chatters who will fill out a post-chat satisfaction survey when presented to them is 25%.
• Using the ‘window close prompt’ offered by BoldChat increases survey response by 39%. It’s even more effective
than the previous benchmark of 31%.
• The average satisfaction score given on a 1 to 5 scale across all survey questions is 4.4 which is identical to
the 2009 findings.
• On average, 10% of the people who submit a post-chat survey also include comments, down from 29%.
• The average satisfaction scores for all categories are between 2.75 and 3.5 for chats lasting less than 10 seconds.
• The satisfaction average goes up gradually from 3.5 up to 4.0 for chats that increase from 10 seconds up
through 30 seconds.
Satisfaction scores based on chat duration in seconds
5.00
4.50
4.00
3.50
2.50
Satisfaction
2.00
1.50
1.00
0.50
0.00
1
26
51
76
101
126
151
176
Figure 4: Chat Satisfaction and Chat Duration
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10. • The average satisfaction level increases up to 4.3 at
80 seconds and up to 4.5 at 180 seconds.
• Between 180 seconds and 1000 seconds for chat
length, the average satisfaction fluctuates slightly
between 4.3 and 4.5.
Chats that are too short score low from a satisfaction
standpoint but, interestingly, the inverse appears not to
be true. Even chats lasting nearly 20 minutes are still
scored highly.
Chat Satisfaction & Conversions
We were interested in the relationship between conversions and satisfaction. As such, we looked only at the
group of customers who both use conversion tracking for
purchases and offer a post-chat satisfaction survey. What
we found is telling:
• The sites in the top 20% for conversion percent
averaged 4.50 on their overall satisfaction scores.
• The sites in the top 50% for conversion percent
averaged 4.48 on their overall satisfaction scores.
• The sites in the bottom 50% for conversion percent
averaged 4.25 on their overall satisfaction scores.
• The sites in the bottom 20% for conversion percent
averaged 4.24 on their overall satisfaction scores.
Another way to look at these results:
• Sites in the top 20% for satisfaction scores had a
266% greater chance to convert a chatter than
an average site.
• Sites in the top 50% for satisfaction scores had a
63% greater chance to convert a chatter than
an average site.
• Sites in the bottom 50% for satisfaction scores had
a 29% less chance to convert a chatter than an
average site.
• Sites in the bottom 20% for satisfaction scores had
a 35% less chance to convert a chatter than
an average site.
Conclusions
The data presented herein quantitatively supports the
following conclusions:
Live Chat Is an Increasingly Effective Sales Channel
For the average website, adding live chat will increase
conversions and average order size. A chatter is 7.5 times
more likely to convert than a regular website visitor and
this is up since the last time we reported this benchmark.
That, coupled with the fact that on average a buyer
through chat will spend 55% more, indicates that live chat
– and those employing it – is improving for sales throughput and value.
Proactive Chat Invites are Critical for Highly
Trafficked Sites
Chatters who engage via proactive are, for the average
site, 8 times more likely to buy. That should encourage all
sites to explore the technology with a serious intent for
implementation. But, for highly trafficked sites it appears
even more important. Chatters engaging on those sites
through proactive are 9.8 times more likely to buy. Additionally, proactive chat appears to be a website’s best tool
to impact overall chat engagement. Highly trafficked sites,
on average, have 9.7% of their proactive invites accepted.
Missed Opportunities Are Controllable, But Methods May
Change Over Time
Website owners are not helpless. Through the implementation of pre-chat forms (or not), optimization of answer
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11. speed, and inclusion of unavailable lead capture mechanisms, Internet businesses can significantly change the
number of engagements and follow-up opportunities
created by live chat. Business should keep an eye on these
statistics because over time, chatter behavior has changed.
Visitors are increasingly less likely to fill out a form before
chatting, but if they do, they want the chat answered more
immediately than in 2009.
Chat Satisfies and is Related to Conversions
Not only do chatters participate in post-chat surveys but
the average score they give across the variables of professionalism, responsiveness, knowledge, and other criteria
shows that these interactions are overwhelmingly positive.
Additionally, there appears to be a direct relationship
between high satisfaction scores and the likelihood a site
has to convert a chatter. Those in the top 20% for satisfaction scores had a 266% greater chance to convert a chatter.
7 Key Benchmarks
Based on the findings presented in this document, live chat
users should diligently manage, or seek the expertise of
professionals in order to ensure that their implementations
achieve, at least the following:
2. The implementation of proactive chat on top of reactive
chat should increase a site’s engagement rate by ~388%.
3. Chatters ought to convert at ~7.5 times the rate of a
regular website visitor.
4. Chatters via proactive chat ought to convert at ~8.5
times the rate of a regular website visitor. Customers with
more traffic can expect higher proactive acceptance rates.
5. The use of a pre-chat form ought to cause ~47% of those
who are presented with it to abandon, but should increase
the survivability of the chat request.
6. Sites that use an unavailable email form on average
capture contact data from 17% of those who are presented
with it.
7. Speed of answer is more import than in our previous
study. The 2009 benchmark indicated that answering a
chat within 10 seconds would yield interactions with
greater than 80% of visitors who initiated a chat. To
achieve that same engagement today, you’d need to
answer the chat in less than 5 seconds.
1. Depending on a website’s traffic volume the live chat
engagement percentage should be between ~1% and ~15%.
BOLDCHAT
BoldChat is a market-leading live chat solution enabling
businesses to quickly and effectively engage visitors on
their websites. BoldChat is offered in different editions
and includes other integrated communications
technologies like click-to-call, email management, SMS
management, and co-browsing. Organizations of all
sizes – from small proprietorships to large ecommerce
enterprises – can drive more conversions and higher
customer satisfaction by using BoldChat.
For more information:
Phone: (866)753-9933
Email: info@boldchat.com
Chat with us, start a trial or download more resources like
this one at: www.BoldChat.com
BoldChat is owned by LogMeIn, Inc. For more information,
please visit www.LogMeIn.com
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