Sometimes more web traffic hurts. What happens when more visitors cause poor Web performance? As a marketer, ecommerce manager or IT professional, your responsibility is to maximize online revenue, protect your brand, and ensure customer loyalty by providing consistent quality Web experiences at all times. But did you know that a lack of readiness resulting in poor web performance during peak traffic times significantly impacts your business results? A new survey of retail, travel and financial services online consumers found that customers spend a significant percentage of their budgets during peak traffic times, and 67% expect websites to work well regardless of the number of visitors. Moreover, 72% stated that their expectations were not met during 2009 peak traffic periods, and this is what they did about it: •78% went to a competitor’s site due to poor performance at peak traffic times •88% were less likely to return to a website •47% left with a negative perception of the company •42% discussed it either with friends or online Want to know more about how to protect revenue, brand and customer loyalty during peak traffic periods?

2. Contents
Executive Summary Pg 4‐5
Customers Spend Big During Peak Traffic Times,
Pg 7‐11
and Won’t Tolerate Poor Web Performance
User Expectations Were Not Met in 2009 During
Pg 13‐16
Peak Traffic Periods
Poor Experiences During Peak Traffic Times
Directly Impact Business Results Pg 18‐23
Best Practices for Managing Peak Traffic Times Pg 25‐26
Appendix I – Methodology Pg 28
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3. Introduction
 Peak Online Traffic Periods are critical since more Web visitors
mean more revenue opportunities. Yet what are consumers'
expectations during peak traffic times, and how do they behave
when they experience poor web performance?
 To find out, Gomez commissioned Equation Research to conduct
a study of consumer Internet usage experiences during peak
traffic times
 1,538 respondent interviews were carried out between Dec16 – 22, 2009
 Study was conducted across 3 verticals: Retail, Travel and Financial
 Examples of Peak Traffic Periods:
 Holiday Shopping Season, Valentine’s Day, Mother’s day, 4th of July,
Summer, Tax Season, Financial Market Meltdowns, Back to School
Shopping. Thanksgiving, Xmas to end of the year...
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4. Executive Summary
Key Finding 1
 Customers spend big during peak traffic times, and won’t tolerate poor web
performance
 51% spend a significant percentage of their retail budget during peak times
 67% expect websites to work well regardless of how many visitors the site
gets during peak traffic times
Key Finding 2
 User expectations were not met during 2009 peak traffic periods
 72% experienced slower web sites more frequently during peak traffic times
than at other times
Key Finding 3
 Poor experiences during peak traffic times directly impact business results
 78% went to a competitor’s site due to poor performance at peak times
 After a poor experience…
 88% are less likely to return to a website
 47% left with a negative perception of the company
4  42% discussed it either with friends or online

5. Executive Summary Across Industry Verticals
Vertical Key Findings
• 51% spend a significant percentage of their budget during peak
times
Retail • 41% would abandon a retailer’s Website at peak times and shop
somewhere else after only one or two bad experiences
• 33% had a bad experience on a retail Website this 2009 Holiday
Shopping Season
• 35% make a significant percentage of their travel bookings during
peak times
• 53% would abandon a travel Website at peak traffic times and book
Travel
somewhere else after only one or two bad experiences
• 24% had a negative experience on a travel Website during 2009
peak travel season
• 51% of financial service users & 65% of online stock traders had
poor Web experiences during peak usage times in 2009
Financial Services
• 42% of financial service users & 57% of online stock traders would
switch to a competitor if dissatisfied with their financial provider’s
Website
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6. Key Finding 1
Customers Spend Big During Peak Traffic
Times and Won’t Tolerate Poor Web
Performance
6

7. 51% Spend a Significant Percentage of Their Retail Budget During
Peak Traffic Times
Retail Findings
Most 14%
51%
A significant 37%
percentage
A little
40%
None
9%
Figure 2: Percentage of retail online spending that occurs during
peak traffic times
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8. 35% Make a Significant Percentage of Their Travel Bookings
During Peak Traffic Times
Travel Findings
7%
Most
28% 35%
A significant
percentage
A little 48%
None
17%
Figure 3: Percentage of online travel bookings done during
peak traffic times
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9. 67% of Online Consumers Expect Websites to Work Well Regardless of How
Many Visitors the Site Gets During Peak Traffic Times
Customers are just as demanding during peak
Cross‐Vertical Findings traffic times
I expect web sites to work no matter 67%
how many visitors they have
I understand that more visitors will slow
26%
web sites down
No specific expectations 4%
Figure 4: Online consumers' expectations during peak traffic times
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10. 41% Would Abandon a Retailer’s Website at Peak Traffic Times &
Shop Somewhere Else After Only One or Two Bad Experiences
10% would go to a competitive site after only one bad experience
Retail Findings
None, I'd leave after the first bad
experience
10%
41%
2 31%
3 33%
4 11%
5 or more 6%
Poor experiences will not impact
the websites I use to shop
10%
Figure 5: Number of poor web experiences tolerated during peak traffic
times before shopping somewhere else
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11. 53% Would Abandon a Travel Website at Peak Traffic Times &
Book Somewhere Else After Only One or Two Bad Experiences
• Online consumers are less tolerant with travel sites than retail sites
Travel Findings
• 17% would go to a competitive site right away
None, I'd leave after the first bad
experience
17%
53%
2 36%
3 26%
4 7%
5 or more 4%
Poor experiences will not impact
the websites I use for travel
10%
Figure 6: Number of poor web experiences tolerated at peak traffic times before
booking travel somewhere else
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12. Key Finding 2
User Expectations Were Not Met in 2009
During Peak Traffic Periods
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13. 72% of Online Consumers Experienced Poor Performance More
Frequently During Peak Traffic Periods than at Other Times
Slower Web Sites was the problem most commonly
Cross‐Vertical Findings
encountered
Slower Web Sites 72%
Errors on Web Pages 58%
Problems Completing Transactions 51%
Figure 1: Type of issues encountered more frequently during 2009 peak traffic periods
13

14. 33% Had a Bad Experience on a Retail Website this 2009 Holiday
Shopping Season
15% found problems encountered during the 2009 Holiday
Retail Findings
Shopping Season to be ‘unacceptable’
Had a bad experience? 15% 33%
Yes ‐ and it is
unacceptable
Yes ‐ but it doesn't 18%
bother me
No ‐ I haven't had
67%
a bad experience
Figure 8: Poor web experiences encountered on a retail Website this 2009 Holiday
Shopping Season
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15. 24% Had a Negative Experience on a Travel Website During 2009
Peak Travel Season
Slow load time was the most frequently cited issue at 18%
Travel Findings
Had a bad experience?
Slow load time 18%
Yes 24%
Problems completing
11%
transactions
No
Errors on web pages 10%
76%
Other (specify) 1%
Figure 9: Poor Experiences Encountered on Travel Websites During 2009 Peak Traffic
Times (Summer and Thanksgiving/December seasons)
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16. 51% of Financial Service Users & 65% of Online Stock Traders
Had Poor Web Experiences During Peak Usage Times in 2009
Slow load time was the problem most commonly encountered
Financial Findings
51% financial service users 65% online traders
reported these problems reported these problems
Slow load time 43% Slow load time 58%
Problems completing Problems completing
23% 28%
transactions transactions
Errors on web pages 20% Errors on web pages 31%
Other (specify) 2% Other (specify) 1%
Figure 10: Poor Experiences Encountered on a Financial Website During 2009 Peak Usage Times
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17. Key Finding 3
Poor Experiences During Peak Traffic
Times Directly Impact Business
Results
17

18. Poor Web Experiences During Peak Traffic Times Directly Impact
Business Results
Cross‐Vertical Findings
• 78% have gone to a competitor’s site due
to poor performance at peak times
Poor web experiences impacts After a poor experience..
revenue, brand & loyalty
• 88% are less likely to return to a site
Brand • 47% left with a less positive
perception of the company
Customer
• 42% have discussed it with family,
friends, peers or online
Loyalty
18

19. 78% Have Gone to a Competitive Site Because of Poor Performance
During Peak Traffic Times
30% have gone to a competitive site right away due to poor
performance during peak traffic periods
Cross‐Vertical Findings
Yes ‐ I have little patience for 30%
poor website performance
78%
Yes ‐ but only after several bad
experiences 48%
No impact
22%
Figure 11: Percentage of consumers that switched to a competitive Website after a poor
Web experience during peak traffic times
19

20. 88% Are Less Likely to Return After a Poor Web Experience
28% have very little tolerance for poor performance and are
less likely to give the website another chance
Cross‐Vertical Findings
I'm less likely to return ‐ I have little 28%
patience for poor website
performance
88%
I'm less likely to return ‐ but only
after several bad experiences 60%
No impact
13%
Figure 12: Percentage of consumers less likely to return after a poor Web experience
20

21. After a Poor Web Experience, 47% Left with a Negative Perception
42% Discussed poor experiences either with friends
or online
Cross‐Vertical Findings
Left with a less positive perception 47%
of the company
Told friends, family or colleagues
34%
about the experience
42%
Wrote about the experience on
Facebook, Twitter, a blog or a 8%
forum
Figure 12: Impact on brand & actions taken after a poor Web experience
21

22. 52% of Financial Service Users and 68% of Online Stock Traders
Took Some Negative Action as a Result of a Bad Web Experience
Financial Findings
52% financial service users 68% online stock traders
took these actions after a took these actions after a
poor Web experience poor Web experience
Less likely to purchase
Less likely to purchase 29% 40%
additional services from
additional services from them
them
Tell my friends/family/peers Tell my friends/family/peers
or write about it on the 17% or write about it on the 29%
Internet Internet
Use another financial Use another financial
13% 27%
provider's site provider's site
Close my account 7% Close my account 14%
Figure 13: Actions taken as a result of poor financial website experiences
22

23. 42% of Financial Service Users & 57% of Online Stock Traders Would Switch to a
Competitor if Dissatisfied With Their Financial Provider’s Website
Financial Findings
Financial Service Users Online Stock Traders
42%
Yes 43%
58% No
57%
Figure 14: Would Switch to a competitor as a result of a bad experience on a financial
provider’s Website
23

24. Best Practices for Managing Peak
Traffic Times
24

25. Best Practices for Managing Peak Traffic Times
Load Testing is the only way to know how an application
will perform under peak traffic conditions:
• End‐User Experience: Will we provide quality user experiences when we have
more Website visitors, or will customers encounter more Web errors or
problems completing transactions?
• Web Performance: Will the website respond fast enough?
• Scalability: Will the application handle the expected user load and beyond?
– before it gets “slow”?
– before it stops working?
– will it sustain?
• Stability: Is the application stable under expected and unexpected user loads?
What if….
– there are more users than we expect?
– all the users do the same thing?
– we get too many orders?
25 25

26. Best Practices for Managing Peak Traffic Times
(Cont’d)
1. Get ready ‐ plan to load test whenever there is a change
 Launching marketing and sales campaigns
 Rolling out new Websites, applications and features
 Planning for seasonal and holiday spikes in web traffic
 Upgrading or virtualizing infrastructures
2. Adopt an “outside‐in” customer point of view
 Test & monitor your web performance from the Internet,
where your customers are
 Focus on key geographies (new markets, most visitors, top
revenue‐generating regions,…)
3. Ensure that your business goals are supported by IT
 Discuss upcoming plans & events with your IT counterparts
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27. Appendix
27

28. Design and Methodology
Overview
• Gomez Inc. engaged Equation Research to conduct an online study to
understand consumer Internet usage experience during peak traffic times
• Interviews conducted from December 16‐22, 2009
Methodology
• Respondents recruited from Equation’s nationally representative panel
• Survey results may have a margin of error of plus or minus three percent at a
95 percent level of confidence
Sample: 1,538 total respondents
• N=500 respondents who have bought a product or service online in the past 9 months
• N=506 respondents who have booked travel in the past 9 months
• N=532 respondents who have performed a financial transaction in the past 9 months
(including n=183 respondents who bought/sold stock online)
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