10. €"
Media site
Enrolment
Targeted
€"
embedded add
Add Network
Visitor
€"
€"
Advertiser site
Departure(
Impact(on(site(
€" Negative €" Positive
11. Web Analytics
measures the
movement towards
these goals
12. A simple analytics model:
A$en'on" Engagement( Conversion(
NEW
VISITORS
GROWTH CONVERSION
SEARCHES RATE
PAGES TIME
TWEETS
MENTIONS
NUMBER
OF VISITS
PER
VISIT
ON
SITE
x"
ADS SEEN ORDER
LOSS VALUE
BOUNCE
RATE
13.
14.
15. Why did customers drop off?
‣Price
‣Functional errors?
‣Performance issues?
16. Why did customers drop off?
‣Price
‣Functional errors?
‣Performance issues?
What’s the business impact?
‣Lost customers?
‣Revenue risked?
‣In Euros?
20. Web Analytics Usability
(what did they do on (how did they
the site?) interact with it?)
Complete Web Monitoring
21. Web Analytics Usability Performance
(what did they do on (how did they (could they do what
the site?) interact with it?) they wanted to?)
Complete Web Monitoring
22. Web Analytics Usability Performance
(what did they do on (how did they (could they do what
the site?) interact with it?) they wanted to?)
Complete Web Monitoring
VoC
(what were their
motivations?)
23. Web Analytics Usability Performance
(what did they do on (how did they (could they do what
the site?) interact with it?) they wanted to?)
Complete Web Monitoring
VoC Social Media
(what were their (what were they
motivations?) saying?)
24. Web Analytics Usability Performance
(what did they do on (how did they (could they do what
the site?) interact with it?) they wanted to?)
Complete Web Monitoring
VoC Social Media Competition
(what were their (what were they (what are they up
motivations?) saying?) to?)
25. “Hard” data
Web Analytics Usability Performance
(what did they do on (how did they (could they do what
the site?) interact with it?) they wanted to?)
Complete Web Monitoring
VoC Social Media Competition
(what were their (what were they (what are they up
motivations?) saying?) to?)
“Soft” data
26. “Hard” data
Web Analytics Usability Performance
(what did they do on (how did they (could they do what
the site?) interact with it?) they wanted to?)
Complete Web Monitoring
VoC Social Media Competition
(what were their (what were they (what are they up
motivations?) saying?) to?)
Source: Complete Web Monitoring, Sean Power/Alistair Croll, 2009
“Soft” data
49. Which website would you recommend in terms of
performance?
Desktop only, fixed
Buy a summer holiday
100 users selection of shops
online
(Travel30)
50. Ranking Perceived Technology
1 Sunweb
2 Globe
3 Neckermann
4
D-reizen
5
Arke
Technology vs. Perceived Study performed by MeasureWorks for Emerce eTravel, 2013
51. Ranking Perceived Technology
1 Sunweb Sunweb
2 D-reizen Globe
3 Neckermann Neckermann
4
Arke D-reizen
5
Globe Arke
Technology vs. Perceived Study performed by MeasureWorks for Emerce eTravel, 2013
52. Ranking Perceived Technology
1 Sunweb Sunweb
2 D-reizen Globe
3 Neckermann Neckermann
4
Arke D-reizen
5
Globe Arke
Technology vs. Perceived Study performed by MeasureWorks for Emerce eTravel, 2013
57. 50
Many functional
37,5
issues reported
Round 1 with Zalando
25
42,1 45
12,5
20 24
15,4
7,7 3,9
0 4
Zalando HM V&D Tom Tailor
Design Speed Mobile Readiness Other
1. Buy a T-shirt 2. Review
40
30
Round 2
20
34 54
10
12 15,4 21 18
8 6
0
Zalando HM V&D Tom Tailor Design Speed Mobile Readiness Other
Mobile Only research:
- Task completion: Only use smartphone to buy a book
- N = 100, users range from 20-65
61. 100
75
50
44 46
25 24 26
16 16 16
12
0
Bol.com Selexyz Bruna Other Design Speed Mobile Readiness Other Design Speed Mobile Readiness Other
1. Buy a book 2. Review 3. Buy at a different store
Mobile Only research:
- Task completion: Only use smartphone to buy a book
- N = 100, users range from 20-65
80. Why it matters? 76% of mobile
consumers won’t retry more than twice
Source: Compuware, 2012, Engaging the tablet user; What to expect from web sites?
81. Why it matters? 89% of (mobile)
consumers will leave to the competition
Source: Oracle, 2012, Customer Experience Survey
83. (CLOUD) DATA CENTER INTERNAL USERS INTERNET CUSTOMERS
Third-party/
Cloud Services
Storage DB Servers Web Servers Major Local
This is what you control... Network What you’re blamed for..
ISP
Content
ISP
Delivery Mobile
Load Networks Carriers
Middleware App Balancers
Mainframe Servers Servers
97. Real User
Real User Benchmark
Monitoring
Performance Measurement toolkit
98. Navigation timing
2 ways of measuring...
Browser RUM
Disclaimer: There’s also third category Datacenter RUM, this will not be
covered in this out of the presentation. Contact me if your want details
99. h"p://www.w3.org/TR/naviga2on32ming/5
Some background info:
Navigation timing
http://66.7percentangel.com/2011/12/breaking-down-onload-event-performance-bookmarklet/
http://www.html5rocks.com/en/tutorials/webperformance/basics/
http://www.w3.org/TR/2011/CR-navigation-timing-20110315/#nt-dom-content-event-start
101. 1 2 3 4
As pages execute, After onload tag send
Insert tag (.js file) into Pages are requested
tag collects detailed report for
(mobile) web pages from browser/device
performance metrics further analysis
tag.js
tag.js
tag.js
tag.js
Browser RUM
128. Synthethic monitoring Real User Monitoring Real User benchmarking Performance surveys
Performance Measurement toolkit
129. Synthethic monitoring Real User Monitoring Real User benchmarking Performance surveys
Benefits Benefits Benefits Benefits
Heartbeat, runs without traffic Real usage information from Testing of user scenario’s Soft data feedback
Test specific customer journeys all users!! with real devices/bandwith Abandonment optimization
Object level detail Trending/Optimization Optimization details Test before go live
Collect detailed alerts, including Business impact Competitive scan
root cause analysis
Desktop/Mobile Site Desktop/Mobile Site Desktop/Mobile Site Real User
Desktop/Mobile Site
Websitepulse LogNormal Webpagetest Wufoo
Watchmouse Torbit Browserstack Usabilla
Alertsite New Relic Loop11
Google Analytics Crazyegg
Mobile Apps Mobile Apps Mobile Apps Mobile Apps
Gomez Gomez Perfecto Mobile Loop11
Keynote New Relic Device Anywhere
Localytics
Google Analytics
Performance Measurement toolkit
133. First thing is to establishing a baseline:
A pre-defined set of metrics
134. First thing is to establishing a baseline:
A pre-defined set of metrics
that describes normal behavior
135. First thing is to establishing a baseline:
A pre-defined set of metrics
that describes normal behavior
in order to detect variancies
136. First thing is to establishing a baseline:
A pre-defined set of metrics
that describes normal behavior
in order to detect variancies
and to be comparable within historic context
138. Purchasing a book, Customer journey
must be completed (speed), Metric: Speed
where every page loads under 4 sec., Target: Sec
using IE8 and higher, User scenario
from any location in the Netherlands, User locations
for 95% of all users, Percentile
every day between 6am and 12pm, Window
measured with Real User Monitoring. Collection type
Source: Metrics 101, Velocityconf 2010
166. Low hanging fruit
‣ Reduce page size
‣ Enable Gzip
‣ Reduce the number of
roundtrips
‣ Structure the page to improve
rendering & download
‣ Enable caching
‣ Clean up & remove duplicates
‣ Minify javascript
167. Low hanging fruit Advanced optimization
‣ Reduce page size ‣ Non-blocking scripts
‣ Enable Gzip ‣ Optimizing images
‣ Splitting payloads
‣ Reduce the number of ‣ Asynchronous loading
roundtrips
‣ Structure the page to improve ‣ Pre-loading
rendering & download ‣ Etc.
‣ Enable caching
‣ Clean up & remove duplicates
‣ Minify javascript
168.
169. Page size:
1660 Kb
# requests:
89
Time to render:
1,29 sec.
Document complete:
3,68 sec.
Not Optimized
170. Page size: Page size:
1660 Kb 498 Kb
# requests: # requests:
89 48
Time to render: Time to render:
1,29 sec. 1,10 sec.
Document complete: Document complete:
3,68 sec. 1,54 sec.
Not Optimized Optimized
171. Page size: Page size:
1660 Kb 498 Kb
# requests: # requests:
89 48
Time to render: Time to render:
1,29 sec. Timeto first visual: 1,10 sec.
1,10 sec. vs 1,90 sec.
Document complete: Document complete:
3,68 sec. 1,54 sec.
Not Optimized Optimized