Slides from my session for the marketing students at Windesheim College. About why performance matters to your end user, how to measure performance and what to look for when optimizing performance of your website...
13. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour/day
Performance complaints patterns per branche/day
Retail100 Travel30
Research from MeasureWork & Social and More. Twitter mentions collected for Twinkle100
webshops between July 1 2014 - July 1 2015
Average:
179 tweets p/hour
14. 21% of social complaints are about
user experience
Research from MeasureWork & Social and More. Twitter mentions collected for Twinkle100
webshops between July 1 2014 - July 1 2015
15. 30 33 36 39 42 45 48 51 2 5 8 11 14 17 20 23 26
Week/Year (2014-2015)
Performance complaints pattern per branche/day
Retail100 Travel30
Normal average:
2398 tweets p/day
Research from MeasureWork & Social and More. Twitter mentions collected for Twinkle100
webshops between July 1 2014 - July 1 2015
16. 30 33 36 39 42 45 48 51 2 5 8 11 14 17 20 23 26
Week/Year (2014-2015)
Performance complaints pattern per branche/day
Retail100 Travel30
Research from MeasureWork & Social and More. Twitter mentions collected for Twinkle100
webshops between July 1 2014 - July 1 2015
Normal average:
2398 tweets p/day
Holiday average:
2897 tweets p/day
17. 18% increase in
performance complaints
during holiday season
Research from MeasureWork & Social and More. Twitter mentions collected for Twinkle100
webshops between July 1 2014 - July 1 2015
18. 30 33 36 39 42 45 48 51 2 5 8 11 14 17 20 23 26
Week/Year (2014-2015)
Performance complaints pattern per branche/day
Retail100 Travel30
Research from MeasureWork & Social and More. Twitter mentions collected for Twinkle100
webshops between July 1 2014 - July 1 2015
Holiday average:
2897 tweets p/day
Complaint top 3:
1. Downtime (36%)
2. Mobile readiness (21%)
3. Slow (19%)
Complaint top 3:
1. Downtime (39%)
2. Slow (29%)
3. Mobile readiness (11%)
20. 0-0,5 0,5-1 1-1,5 1,5-2 2-2,5 2,5-3 3-3,5 3,5-4 4-5 5-6 6-7 7-8 8-9 9-10 >10
Conversionrate(%)
Category Title
Real User Monitoring: True Conversion Rate
Data collected by MeasureWorks at various e-commerce websites using real user monitoring, reference: http://bit.ly/MW-VEUrum
0%
10%
Competitive Custom B2B
21. Real User Monitoring: True Conversion Rate
Data collected by MeasureWorks at various e-commerce websites using real user monitoring, reference: http://bit.ly/MW-VEUrum
0%
10%
Optimal Conversion: 1,8s
0-0,5 0,5-1 1-1,5 1,5-2 2-2,5 2,5-3 3-3,5 3,5-4 4-5 5-6 6-7 7-8 8-9 9-10 >10
Conversionrate(%)
Category Title
Competitive Custom B2B
22. Real User Monitoring: True Conversion Rate
Data collected by MeasureWorks at various e-commerce websites using real user monitoring, reference: http://bit.ly/MW-VEUrum
0%
10%
Optimal Conversion: 1,8s
LD50: 4,3s
0-0,5 0,5-1 1-1,5 1,5-2 2-2,5 2,5-3 3-3,5 3,5-4 4-5 5-6 6-7 7-8 8-9 9-10 >10
Conversionrate(%)
Category Title
Competitive Custom B2B
23. Real User Monitoring: True Conversion Rate
Data collected by MeasureWorks at various e-commerce websites using real user monitoring, reference: http://bit.ly/MW-VEUrum
0%
10%
Optimal Conversion: 1,8s
LD50: 4,3s
Poverty Line: 7,6s
0-0,5 0,5-1 1-1,5 1,5-2 2-2,5 2,5-3 3-3,5 3,5-4 4-5 5-6 6-7 7-8 8-9 9-10 >10
Conversionrate(%)
Category Title
Competitive Custom B2B
24. On average a fast experience
converts up to 70% higher...
28. “You’re more likely to miss stuff just
because it takes a long time to scroll
down the page”
~ User 56A on the MeetHue.com website
Presented by MeasureWorks & Philips at ShoppingToday 2013, reference: http://bit.ly/MW-ST2013
30. “Your getting blamed for
things that are not your fault”
Presented by MeasureWorks & Philips at ShoppingToday 2013, reference: http://bit.ly/MW-ST2013
43. 0
10
20
30
40
50
60
70
80
90
100
0 1 2 3 4 5 6 7 8 9 10
Bouncerate per pagetype/session
Bouncerate(%)
Page load time (sec.)
Median Campaign Product search
Data collected by MeasureWorks at various e-commerce websites using real user monitoring, reference: http://bit.ly/MW-VEUrum
44. 0
10
20
30
40
50
60
70
80
90
100
0 1 2 3 4 5 6 7 8 9 10
Bouncerate(%)
Page load time (sec.)
Median Campaign Product search
Bouncerate per pagetype/session
Data collected by MeasureWorks at various e-commerce websites using real user monitoring, reference: http://bit.ly/MW-VEUrum
57. 1: Configure test
2: Key Optimizations
3: Performance metrics
Use Akamai State of the Internet quarterly reports to select right bandwith per country: http://www.akamai.com/stateoftheinternet/
84. 1
Insert tag (.js file)
into (mobile) web
pages
Pages are requested
from browser/device
As pages execute,
tag collects
performance metrics
After onload tag
send detailed report
for further analysis
tag.js
tag.js
tag.js
tag.js
2 3 4
85.
86. Relies on navigation timing API, custom variables can be added
Turn on
“Site Speed”
in your GA
account!
http://bit.ly/1ivGWTt
90. Aunshul Rege of Rutgers University, USA in 2009
1000 emails
1-2 responses
1 fool and their money, parted.
Bad language (0.1% conversion)
Gullible (70% conversion)
1000 emails
100 responses
1 fool and their money, parted.
Good language (10% conversion)
Not-gullible (.07% conversion)
97. Complete Web Monitoring
Web Analytics
(what did they
do on the site?)
Usability
(how did they
interact with it?)
98. Complete Web Monitoring
Web Analytics
(what did they
do on the site?)
Performance
(could they do
what they wanted
to?)
Usability
(how did they
interact with it?)
99. Complete Web Monitoring
Web Analytics
(what did they
do on the site?)
Performance
(could they do
what they wanted
to?)
VoC
(what were their
motivations?)
Usability
(how did they
interact with it?)
100. Complete Web Monitoring
Web Analytics
(what did they
do on the site?)
Competition
(what are they up
to?)
Performance
(could they do
what they wanted
to?)
VoC
(what were their
motivations?)
Usability
(how did they
interact with it?)
101. Complete Web Monitoring
Web Analytics
(what did they
do on the site?)
Competition
(what are they up
to?)
Performance
(could they do
what they wanted
to?)
VoC
(what were their
motivations?)
Usability
(how did they
interact with it?)
Social Media
(what were they
saying?)
102. Complete Web Monitoring
Web Analytics
(what did they
do on the site?)
Competition
(what are they up
to?)
Performance
(could they do
what they wanted
to?)
VoC
(what were their
motivations?)
Usability
(how did they
interact with it?)
Social Media
(what were they
saying?)
“Soft” data
“Hard” data
104. X
A simple online business model:
Marketing Conversion Optimization Revenue
New
visitors
Bounce
rate
Conversion
rate
Order
value
Growth
Loss
Time on
site
Pages per
visit
Number of
visits
Search
Tweets
Mentions
ADs seen
126. ‣ A Facebook user reaching 7 friends within 10 days of signing up
(Chamath Palihapitiya)
‣ A Dropbox user who puts at least one file in one folder on one
device (ChenLi Wang)
‣ Twitter user following a certain number of people, and a certain
percentage of those people following the user back (Josh
Elman)
‣ A LinkedIn user getting to X connections in Y days (Elliot
Schmukler)
Some examples
(From the 2012 Growth Hacking conference. http://growthhackersconference.com/)
127.
128. A wealth of information creates a
poverty of attention...
(Computers, Communications and the Public Interest, pages 40-41,
Martin Greenberger, ed., The Johns Hopkins Press, 1971.)Herbert
Simon
129. Focus on the desired behavior, not
just the information.
http://www.psychologytoday.com/blog/yes/200808/changing-minds-and-changing-towels
26% increase in towel re-use with an appeal to social
norms; 33% increase when tied to the specific room.
133. Blink Relevance Availability Scalability Sum
5-second rule
Gut feeling
Instinct score
Don’t overthink it
Do we have the
available
resources?
Do we have the
skills?
Do we have the
tools?
Is it expensive?
134. Blink Relevance Availability Scalability Sum
5-second rule
Gut feeling
Instinct score
Don’t overthink it
Is this Channel
relevant to your
product/service?
Does your
audience hang out
on this channel?
Can you target
them effectively?
Do we have the
available
resources?
Do we have the
skills?
Do we have the
tools?
Is it expensive?
135. Blink Relevance Availability Scalability Sum
5-second rule
Gut feeling
Instinct score
Don’t overthink it
Is this Channel
relevant to your
product/service?
Does your
audience hang out
on this channel?
Can you target
them effectively?
Do we have the
available
resources?
Do we have the
skills?
Do we have the
tools?
Is it expensive?
How scalable is
this channel?
Can we easily
increase it?
Law of diminishing
returns
136. Blink Relevance Availability Scalability Sum
5-second rule
Gut feeling
Instinct score
Don’t overthink it
Is this Channel
relevant to your
product/service?
Does your
audience hang out
on this channel?
Can you target
them effectively?
Do we have the
available
resources?
Do we have the
skills?
Do we have the
tools?
Is it expensive?
How scalable is
this channel?
Can we easily
increase it?
Law of diminishing
returns
1-5 1-5 1-5 1-5 BRASS score
141. “Hit them with a beat! The decision to continue
listening to a song is often determined in the first 10
seconds” - Dr. Dre, Source Magazine
The Skip: http://musicmachinery.com/2014/05/02/the-skip/
172. The kayak effect: http://bit.ly/UgTneD
People prefer to wait for up
to a minute to get what they
want from an app rather
than get it instantly – if, and
it’s an important if, they
believe the app is working
for them
178. Setting a performance budget:
A pre-defined set of metrics
that describe normal behavior
in order to detect variances
and to be comparable in historical context
182. Service Window
Purchasing a bed,
must be completed (speed),
where every page loads under 3 sec.,
from any location in the Netherlands,
for 95% of all users,
every 5 minutes between 6am and 12pm,
using IE9 and higher,
Customer journey
Metric: Speed
Target: Sec
User scenario
User locations
Percentile
measured with Synthetic Monitoring. Monitoring type
Business
Performance
207. 0
250
500
750
1000
January-14 April-14 July-14 October-14 January-15 April-15 July-15 October-15
#Pageviews(x1000)
Forecast pageviews Actual pageviews
Traffic realized
Traffic forecast
Max infra capacity (90%)
Safety infra capacity (80%)
# pageviews at peak
hour of peak day per
week/month
Build your spreadsheet...
218. It’s a process. Integrate the
performance budget in your
continuous delivery cycle
219. Analyze the performance as your
users experience it and
compare against your budget to
identify what areas need
improvement
Build faster websites
and optimize the
rendering of your
application and the
perception of speed
Automate & Update
performance testing and
integrate into your delivery
processes
Repeat
Measure Build Run
221. Developer
Makes it real,
builds &
deploys code.
Marketer
BizDev,
validates
customers
demand and
continuously
generates new
ideas
Designer
Designs
compelling
customer
experience
with
performance
in mind
Analyst
Tracks
performance
budget, drives
conversion
experiments
and keeps
you honest.