Eventually, every website fails. If it's a household-name site like Amazon, then news of that failure gets around faster than a rocket full of monkeys. That's because downtime hurts. As a for-instance, in 2013 Amazon suffered a 40-minute outage that allegedly cost the company $5 million in lost sales. That's a big number, and everybody loves big numbers.
But when it comes to performance-related losses, is it the biggest number?
In this presentation from the CMG Performance and Capacity 2014 conference, Radware Web Performance Expert Tammy Everts reviews real-world examples that compare the cost of site slowdowns versus outages. We also talk about how to overcome the challenges of creating as much urgency around the topic of slow time as there is around the topic of downtime.
7. Downtime is better for a B2C web service than slowness. Slowness makes you hate using the service, downtime you just try again later.
Lenny Rachitsky
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9. Performance affects many business KPIs every day
Revenue
Conversions/downloads
User satisfaction
User retention
Time on site
Page views
Bounce rate
Organic search traffic
Brand perception
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26. Average revenue loss per hour of downtime
Average revenue loss due to one hour of performance slowdown (slower than 4.4s)
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TRAC Research/AlertSite: Online Performance Is Business Performance
$21,000
$4,100
However…
27. …website slowdowns occur 10 times more frequently than outages.
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TRAC Research/AlertSite: Online Performance Is Business Performance
29. Whether it’s a public website or an internal web-based application, most of us believe that a successful DoS/DDoS attack results in a service outage.
However, our Security Industry Survey (conducted with 198 respondents within a wide variety of global companies, most of which were not Radware customers) uncovered that the biggest impact of DoS/DDoS attacks in 2013 was service level degradation, which in most cases is felt as service slowness.
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Radware 2013 Global Application and Network Security Report
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33. Customer lifetime value (CLV)
Total dollars flowing from a customer over the entire relationship with that customer
CLV is one of the biggest predictors of retail success
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34. Slide 34
New visitors
Return visitors
Time on site (minutes)
2:31
5:31
Page views/visit
3.88
5.55
Purchase intent
Return visitor is 9X more likely to make a purchase than a first-time visitor.
35. How to measure the short-term and long-term impact of slow time
42. Challenges of measuring impact of slow performance
Need actionable performance data
Need visibility into performance of third-party scripts
Need visibility into quality of experience (QoE) for users (availability PLUS speed)
Need to be able to measure the business impact of performance issues
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44. How to calculate short-term losses due to sub-optimal performance
Step 1: Identify your cut-off performance threshold
4.4 seconds = average delay in response time when business performance starts to decline (TRAC)
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46. Step 2: Measure TTI / AFT / Speed Index for pages in flows for typical use cases
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Step 3: Calculate difference between threshold and actual measurement
5.6
-4.4
2.2 seconds
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Step 4: Pick a KPI
1-second delay =
2.1% decrease in cart size
3.5 - 7% decrease in conversions
9 - 11% decrease in page views
8% increase in bounce rate
16% decrease in customer satisfaction
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Step 5: Calculate losses
3.5% decrease in conversion rate
x 2.2s slowdown______________
7.7% decrease in conversion rate
50. How to calculate long-term losses due to slow performance
1.Identify percentage of converting traffic that experiences speeds slower than 8-second poverty line threshold.
2.Identify current CLV for those customers’ (individual or aggregated).
3.Using the stat that 28% of those customers will permanently abandon pages that are unacceptably slow, identify the lost CLV.
For example…
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51. CLV loss sample scenario
If median total value of customers over the past 3 years is $1000, then predicted future value for the next three years is $1000.
(CLV is $2000.)
Current converting user base of 10,000.
10% of those customers (1000) experience TTI of 8+ seconds.
28% of those customers (280) will not return.
CLV loss = $280,000
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