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The Real Cost of Slow Time vs Downtime

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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.

Published in: Technology

The Real Cost of Slow Time vs Downtime

  1. 1. The Real Cost of Slow Time vs Downtime Tammy Everts @tameverts CMG Performance and Capacity 2014
  2. 2. Slide 2
  3. 3. Who’s had an outage-related emergency? Slide 3
  4. 4. Who’s had a performance- related emergency? Slide 4
  5. 5. Slide 5
  6. 6. Slide 6
  7. 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 Slide 7 “ ”
  8. 8. Let’s look at some real-world examples.
  9. 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 Slide 9
  10. 10. Slide 10
  11. 11. Slide 11 Real User Monitoring at Walmart How to Measure Revenue in Milliseconds
  12. 12. Slide 12
  13. 13. Slide 13 Shopzilla’s Site Redo: You Get What You Measure
  14. 14. Slide 14 Case study: The impact of HTML delay on mobile business metrics
  15. 15. Slide 15 YSlow 2.0, Stoyan Stefanov
  16. 16. Slide 16 Firefox and Page Load Speed – Parts 1 & 2
  17. 17. Slide 17 20% more organic traffic 14% more page views Increased sales For Smartfurniture.com, faster pages =
  18. 18. Slide 18
  19. 19. Current state of the union for web performance
  20. 20. Slide 20
  21. 21. Slide 21 Radware: State of the Union for Ecommerce Web Performance [Fall 2014]
  22. 22. Slide 22 Time to interact (TTI) The moment primary content and call-to-action are rendered in the browser
  23. 23. Slide 23 Optimal load time 8-second delay Jakob Nielsen: Website Response Times
  24. 24. Slide 24 Radware: State of the Union for Ecommerce Web Performance [Fall 2014]
  25. 25. Downtime vs slow time
  26. 26. Average revenue loss per hour of downtime Average revenue loss due to one hour of performance slowdown (slower than 4.4s) Slide 26 TRAC Research/AlertSite: Online Performance Is Business Performance $21,000 $4,100 However…
  27. 27. …website slowdowns occur 10 times more frequently than outages. Slide 27 TRAC Research/AlertSite: Online Performance Is Business Performance
  28. 28. 2X the impact Slide 28
  29. 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. Slide 29 Radware 2013 Global Application and Network Security Report “ ”
  30. 30. Agenda Slide 30
  31. 31. Permanent abandonment rate Slide 31 Akamai: The Impact of Web Performance on E-Retail Success Outage Slow performance 9% 28%
  32. 32. Slide 32
  33. 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 Slide 33
  34. 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. 35. How to measure the short-term and long-term impact of slow time
  36. 36. Slide 36
  37. 37. Slide 37 Lenny Rachitsky: The Upside of Downtime
  38. 38. Minutes of downtime x Average revenue per minute = Downtime losses Slide 38
  39. 39. Slide 39
  40. 40. Average cost of downtime $5,600 per minute $300K+ per hour Slide 40 Gartner: The Cost of Downtime (July 2014)
  41. 41. Slide 41
  42. 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 Slide 42
  43. 43. Slide 43
  44. 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) Slide 44
  45. 45. Slide 45
  46. 46. Step 2: Measure TTI / AFT / Speed Index for pages in flows for typical use cases Slide 46
  47. 47. Slide 47 Step 3: Calculate difference between threshold and actual measurement 5.6 -4.4 2.2 seconds
  48. 48. Slide 48 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
  49. 49. Slide 49 Step 5: Calculate losses 3.5% decrease in conversion rate x 2.2s slowdown______________ 7.7% decrease in conversion rate
  50. 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… Slide 50
  51. 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 Slide 51
  52. 52. Slide 52
  53. 53. Takeaway
  54. 54. Slide 54
  55. 55. Slide 55
  56. 56. Tammy Everts @tameverts tammye@radware.com webperformancetoday.com Slide 56 Questions?

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