DataLeaks 2010 Online Event Performance...

DataLeaks 2010Online Event Performance

Revealed

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@davepitta

HOST

David PittaDemand Generation Manager & Evangelist

SPECIAL GUEST

Brian StarkVP, Corporate Development

Online Events Academy#OEAevent

PROGRAM

BrightTALK™

ONLINE EVENTS ACADEMY@brighttalk

http://www.brighttalk.com/r/zmf

This presentation will use BrightTALK™data to answer two questions:

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1. What results can I expect from online events?

2. What are best practices to optimize performance?

4

DataLeaks 2010Online events performance benchmarks

BrightTALK hosted large online events in 2010

210

11276 66

2600

1700

1100

600

0

500

1000

1500

2000

2500

3000

0

50

100

150

200

250

Human resources Technology Financial services Professional services

Larg

est o

nlin

e ev

ent i

n th

e co

mm

unity

Aver

age

even

t atte

ndan

ce

Average and maximum attendance data for 2010 online events on BrightTALK (sorted by top communities)

Average number of attendees (in 2010) Largest event size (in 2010)

Source: BrightTALK™ data

Online events build communities


0

500

1000

1500

2000

2500

0 1 2 3 4 5 6 7 8 9 10 11 12

Aver

age

num

ber o

f sub

scrib

ers

in c

hann

el

Months since channel launch

BrightTALK™ Channel growth by community in 2010Human resources Technology Professional services Financial services (b2b)

Company size influences community growth based on reach

7Source: BrightTALK™ data

0

200

400

600

800

1000

1200

1400

1600

1800

0 1 2 3 4 5 6 7 8 9 10 11 12

Aver

age

num

ber o

f sub

scrib

ers

in a

cha

nnel

Months since channel launch

Channel growth by company size in 2010Small business channels Large business channels

Successful programs generate repeat viewings

1 webcast, 57%2 webcasts, 18%

3 webcasts, 8%

4 webcasts, 5% 5+ webcasts, 12%

Number of webcasts viewed per channel subscriber in 2010

8Source: BrightTALK™ data

Frequency of repeat viewings varies by community

9

1 webcast, 44%

2 webcasts, 18%

3 webcasts, 9%

4 webcasts, 7%

5+ webcasts,

21%

Number of webcasts viewed per channel subscriber in

financial services

1 webcast, 67%

2 webcasts, 18%

3 webcasts, 7%

4 webcasts, 3%

5+ webcasts,

5%

Number of webcasts viewed per channel subscriber in

technology


Your online event community is ~10 times more likely to interact with your communications

0%

5%

10%

15%

20%

25%

30%

35%

40%

BrightTALK™ Channel subscribers Unaffiliated email addresses

Per

cent

age

of e

mai

ls

2010 email performance by subscriber type Open rate Click rate


11

DataLeaks 2010Online events performance cost per lead

$13$8 $14

$25$3

$50

$75

$75

$2

$0

$20

$40

$60

$80

$100

$120

Online Events Academy CPC Whitepaper Distribution Trade Shows

Cos

t per

lead

Average cost per lead (CPL) for BrightTALK using different mechanisms

Technology

External marketing

Personnel

BrightTALK spends ~$18 to generate a lead in the Online Events Academy

leads of NumberMarketingHeadcountTechnologyCPL Internal ++

=

$13$8 $14

$25$3

$60

$75

$75

$2

$0

$20

$40

$60

$80

$100

$120


Cos

t per

lead


Technology

External marketing

Personnel

Which is less investment(for us) than paid search

CPC for our common keywords:Webcasting: $5Online events: $3

Conversion rates: 5%

leads of Numbercosts Personnel rate Conversion click per CostCPL search Paid +×=

$13$8 $14

$25$3

$60

$75

$75

$2

$0

$20

$40

$60

$80

$100

$120


Cos

t per

lead


Technology

External marketing

Personnel

And considerably less investment than content syndication

Typical cost for content syndication:$70-$80 per lead

leads of Numbercosts Personnel CPL Vendor CPL nSyndicatio +=

Physical mediums are the least cost effective lead generation tool

$13$8 $14

$25$3

$60

$75

$75

$2

$0

$20

$40

$60

$80

$100

$120


Cos

t per

lead


Technology

External marketing

Personnel

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DataLeaks 2010Online events best practices

Activity is the single biggest indicator of success

0

1000

2000

3000

4000

5000

6000

7000

1 - 10 11 - 20 21 - 30 31 - 40 41 - 50 51 - 60 61 - 70 71+

Aver

age

num

ber o

f sub

scrib

ers

in a

cha

nnel

Number of webcasts produced

Average number of subscribers in BrightTALK™ Channels by webcast activity


Attracting a large live audience increases engagement

18

On demand

60%

Live40%

Number of views in 2010 by type for BrightTALK webcasts

14.5

31.3

0

5

10

15

20

25

30

35

On demandLive

Aver

age

view

ing

time

(min

)

Average viewing time in 2010 for all webcasts on BrightTALK

by viewing type


Viewing preference varies by community

19

On demand

59%

Live41%

Number of views in 2010 by type for financial services webcasts

On demand

70%

Live30%

Number of views in 2010 by type for technology webcasts


17%

34%

49%

0

25

50

75

100

-30 -28 -26 -24 -22 -20 -18 -16 -14 -12 -10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

Nor

mal

ized

aud

ienc

e si

ze

Days

Normalized audience development for 2010 IT webcasts featured in BrightTALK™ Summits

Registration only Live viewers On demand viewers

Prior to live event After live event


How does the audience develop pre, during and post for

a 100 person event?

The build-up of registration and viewing over time

~60% of the audience registers before the event

17%

34%

49%

0

25

50

75

100

-30 -28 -26 -24 -22 -20 -18 -16 -14 -12 -10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

Nor

mal

ized

aud

ienc

e si

ze

Days



Prior to live event

After live event


58%

On the event day, 34% of the total audience is captured live; 15% comes in on demand

17%

34%

49%

0

25

50

75

100

-30 -28 -26 -24 -22 -20 -18 -16 -14 -12 -10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

Nor

mal

ized

aud

ienc

e si

ze

Days



After live event

15%

34%


22%

Live day

Over the following 72 hours, 20% of the total audience watches on demand

17%

34%

49%

0

25

50

75

100

-30 -28 -26 -24 -22 -20 -18 -16 -14 -12 -10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

Nor

mal

ized

aud

ienc

e si

ze

Days



20%

34%

After live event


21%

The final 30% of the audience arrives 3-30 days after the event

0

25

50

75

100

-30 -28 -26 -24 -22 -20 -18 -16 -14 -12 -10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

Nor

mal

ized

aud

ienc

e si

ze

Days



After live event


34%

17%

49%

Providing instant on demand is critical for broad reach

17%

34%

49%

0

25

50

75

100

-30 -28 -26 -24 -22 -20 -18 -16 -14 -12 -10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

Nor

mal

ized

aud

ienc

e si

ze

Days




~40% of the total on demand audience views the content within 3 days after the live

event.

Nearly 80% of that viewing happens in the first 24 hours


Whereas other approaches limit viewing growth


22%

43%

35%

0

25

50

75

100

-30 -28 -26 -24 -22 -20 -18 -16 -14 -12 -10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

Nor

mal

ized

aud

ienc

e si

ze

Days

Audience development for platforms that don't support instant on demand



The best time of day to broadcastis community dependent

2727

0500

100015002000250030003500400045005000

Num

ber o

f vie

ws

Hour of day (viewer's local time)

Viewings by hour of day for financial services

Live On Demand

0

5000

10000

15000

20000

25000

30000

Num

ber o

f vie

ws

Hour of day (viewer's local time)

Viewings by hour of day for technology

Live On DemandLive On demand


Live On demand

Mondays are underutilized for webcasting

0

500

1,000

1,500

2,000

2,500

3,000

3,500

Sun Mon Tue Wed Thu Fri Sat

Num

ber o

f vie

win

gs

Viewings by day of the week for 2010 financial services webcasts

On demand Live

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,000

20,000


Num

ber o

f vie

win

gs

Viewings by day of the week for 2010 technology webcasts

On demand Live


On demand audiences prefer off-peak times, live prefers mid-week

0

5

10

15

20

25

30

35

40


Aver

age

view

ing

time

(min

utes

)

Average viewing time by day of week in technology

Live On demand


0

5

10

15

20

25

30


Aver

age

View

ing

Tim

e (M

inut

es)

Average viewing time by day of week in financial services

Live On demand

Longer webcasts tend to attract bigger audiences…

0102030405060708090

Aver

age

num

ber o

f vie

wer

s

Webcast length

Average number of event attendees by webcast length in

financial servicesLive On demand

020406080

100120140160180

Aver

age

num

ber o

f vie

wer

s

Webcast length

Average number of event attendees by webcast length in

technologyLive On demand


…but are less likely to retain them

0%

10%

20%

30%

40%

50%

60%

Perc

enta

ge o

f vie

wer

s w

atch

ing

mor

e th

an 9

0%

of th

e w

ebca

st

Webcast length

Percentage of technology viewers watching more than 90% of the webcast by event

lengthLive On demand

0%

10%

20%

30%

40%

50%

60%

Perc

enta

ge o

f vie

wer

s w

atch

ing

mor

e th

an 9

0%

of th

e w

ebca

st

Webcast length

Percentage of financial services viewers watching

more than 90% of the webcast by event length

Live On demand


Cloud was the hottest topic in 2010

0

5000

10000

15000

20000

25000

30000

Num

ber o

f vie

ws

Number of views on BrightTALK in 2010 by tag

Social media topics are drawing the C-suite

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

twitterfacebook

searchSEOgifts

smallProspectingCold Calling

Outboundbusiness

marketingmobile

SocietyProbate

emailstrategy

customerSocial Media

Online EventsROI

Percentage of Viewers

Top 20 most popular tags by level of the viewerC-Suite VP Director Manager Other

Embedding may convert 1-2% of your website traffic to registrations

Source: BrightTALK™ data, Compete.com, BrightTALK Analysis

1.9%

1.1%1.0%

0.8%

0.0%

0.2%

0.4%

0.6%

0.8%

1.0%

1.2%

1.4%

1.6%

1.8%

2.0%

Financial advisor portal Professional services content library

HR webinar repository Technology resource library

Perc

enta

ge o

f tot

al u

niqu

e vi

sito

rs

regi

ster

ing

for w

ebca

sts

Estimated conversion rates from webcast content embedded in different locations on the web

Number of survey questions asked is not a strong driver of attendance on BrightTALK

0

20

40

60

80

100

120

BrightTAK Minimum (8)

1 additional 2 additional 3 additional 4 additional 5+ additional questions

Aver

age

num

ber o

f pre

-eve

nt re

gist

rant

s

Number of registration questions

Average number of pre-event registrations by number of questions asked

(2010 data)

Conclusions

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Online events can develop large, engaged audienceConstant activity helps accelerate community developmentFocusing on live attendance will improve program performance

Webcasting platforms can aid community developmentInstant on demand can increase viewings by ~20% during the 72 hours following the eventEmbedding may, on average, capture 1-2% of your total website traffic

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DataLeaks 2010 Online Event Performance...

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