Performance ImpactHow Web speed affects online business KPIs
Today’s Hosts
Hooman Beheshti, VP Product, Strangeloop
Alistair Croll,Analyst, BitcurrentAuthor of O’Reilly’s Complete Web Monitoring
10 s
1 s
100 ms
10 ms! Zzz
http://www.flickr.com/photos/spunter/393793587 http://www.flickr.com/photos/laurenclose/2217307446
Everything is interwoven.
We’re getting better
Impact of page load time on average daily searches per user
50ms p
re-h
eader
100ms p
re-h
eader
200ms p
ost-header
200ms p
ost-ads
400ms p
ost-header
-0.70%
-0.60%
-0.50%
-0.40%
-0.30%
-0.20%
-0.10%
0.00%
Impact of additional delay on business metrics
50 200 500 1000 2000-5.00%-4.50%-4.00%-3.50%-3.00%-2.50%-2.00%-1.50%-1.00%-0.50%0.00%
Queries per visitor Query refinement Revenue per visitorAny clicks Satisfaction
Added delay
Per
cen
t ch
ange
Shopzilla had another angle
Big, high-traffic site◦100M impressions a day◦8,000 searches a second◦20-29M unique visitors a
month◦100M products
16 month re-engineering◦Page load from 6 seconds
to 1.2◦Uptime from 99.65% to
99.97% ◦10% of previous hardware
needs
http://en.oreilly.com/velocity2009/public/schedule/detail/7709
5-12% increase in revenue
Tying web latency to business outcomes
http://www.flickr.com/photos/spunter/393793587 http://www.flickr.com/photos/laurenclose/2217307446
KPIs
http
://w
ww
.flic
kr.c
om/p
hoto
s/m
rmoo
rey/
1606
5423
6
NEWVISITORS
GROWTH
BOUNCERATE
LOSS
CONVERSION
RATE
ORDERVALUE
xTIMEON
SITE
PAGES
PERVISIT
NUMBEROF
VISITS
SEARCHES
TWEETS
MENTIONS
ADS SEEN
ATTENTION ENGAGEMENT CONVERSION
It’s time for an experiment
Strangeloop
Googleanalytic
s
Visitor Webserve
r
Optimize?
Decide whether
to optimize
Insertsegmentmarker
Normalcontent
Accelerated
Unaccelerated
Receivepage
Processscripts
Sendanalytics
What we learned
Traffic levels
Optimized Unoptimized0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000 8,505
4,740
Tot
al n
um
ber
of v
isit
s
Bounce rate
Optimized Unoptimized12.80%
13.00%
13.20%
13.40%
13.60%
13.80%
14.00%
14.20%
14.40%
14.60%
13.38%
14.35%
Bo
unce
rat
e
% New visitors
Optimized Unoptimized0.00%
2.00%
4.00%
6.00%
8.00%
10.00%
12.00%
14.00%
16.00%
10.85%
13.61%
Per
cent
new
vis
its
Average time on site
Optimized Unoptimized0:00:00
0:07:12
0:14:24
0:21:36
0:28:48
0:36:00
0:30:10
0:23:50
Tim
e (s
econ
ds)
Pages per visit
Optimized Unoptimized0
2
4
6
8
10
12
14
16
18
15.64
11.04
Pag
es
Conversion rate & order value
Conversion rate Order value
-20.00%
-15.00%
-10.00%
-5.00%
0.00%
5.00%
10.00%
15.00%
20.00%16.07%
5.51%
Chan
ge in
sh
oppi
ng c
art m
etri
c
Justifying an investment in performance
Currentdaily orders
Increasedconversions
Increasedorder value
Cost of performanceenhancement
* +=
ROI(days)
( )
Justifying an investment in performance
Caveats◦Your mileage will vary◦This is just how to think about it
$10,000 0.1607 0.0551
$50,000
* +( ) $2,158
$50,000=
23.17days=
Conclusions
Links between performance and business KPIs are undeniable
By talking the same language, IT and marketing can finally agree on what to do about itChanging from “X times faster” to “$Y more
money” makes the business careMore research is needed
What we need next
Optimized
Different visitors experienced different performance levels.
0 10,000Visitorlatency
# ofvisits
What we need next
21.58%better
Right now we have a single experiment, and a single resulting business impact.
0 10,000Visitorlatency
# ofvisits
What we need next
Optimized
Visitors who were optimized fall into a range – the 5th to 95th percentile
Best 5% Worst 5%
0 10,000Visitorlatency
# ofvisits
What we need next
If we have several experiments, we can understand the relationship better.
24%
18%14%
12%
9.5%
0 10,000Visitorlatency
$ perday
0
Gajillions
What we need next
0 10,000Visitorlatency
$ perday
Every web business has a curve like this hidden inside it.
0
Gajillions
Questions? (Submit your questions using the GoToWebinar question tool)
More informationVisit: www.watchingwebsites.comVisit: www.bitcurrent.comTwitter: @acroll
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