Impact of web latency on conversion rates

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    Notes on slide 1

    Once upon a time, performance was a dark art. We struggled to deliver “good enough” without really knowing why.

    We managed by anecdote. We were sure faster was better, but we couldn’t tie it to specific business outcomes.

    The notion that speed is good for users isn’t new. The concept of “Flow” – a state of heightened engagement that we experience when we’re truly focused on something – was first proposed by mihalycsikszentmihalyi

    It turns out that attention and engagement drop off predictably. At ten milliseconds, we actually believe something is physically accessible – think clicking a button and seeing it change color. At 100 milliseconds, we can have a conversation with someone without noticing the delay (remember old transatlantic calls?) At a second, we’re still engaged, but aware of the delay. At ten seconds, we get bored and tune out, because other things come into our minds.

    How much was fast enough? It was anybody’s guess.

    And guess they did.This is Zona’s formula for patience, the basis for the “eight second rule.” Unfortunately, things like tenacity, importance, and natural patience aren’t concrete enough for the no-nonsense folks that run web applications.

    IT operators and marketers are completely different people. What convinces an IT person to fix performance doesn’t convince a marketer. They want to know how it will impact the business fundamentals.

    By now, we know that everything matters. Usability, page latency, visitor mindset, and even sentiment on social media platforms all contribute to the business results you get from a site.

    Fortunately, we’re getting better at linking performance to business outcomes.

    One example of this is performance experimentation that Google’s done. Google’s a perfect lab. Not only do they have a lot of traffic, they also have computing resources to do back-end analysis of large data sets. Plus, they’re not afraid of experimentation – in fact, they insist on it. So they tried different levels of performance and watched what happened to visitors.

    The results, which they presented at Velocity in May, were fascinating. There was a direct impact between delay and the number of searches a user did each day – and to make matters worse, the numbers often didn’t improve even when the delay was removed. You may think 0.7% drop isn’t significant, but for Google this represents a tremendous amount of revenue.

    Microsoft’s Bing site is a good lab, too. They looked at key metrics, or KPIs, of their search site.

    They showed that as performance got worse, all key metrics did, too. Not just the number of searches, but also the revenue (earned when someone clicks) and refinement of searches.

    Shopzilla overhauled their entire site, dramatically reducing page load time, hardware requirements, and downtime.

    They saw a significant increase in revenues

    The site improvement increased the number of Google clicks that turned into actual visits

    It also affected search engine scores. By improving load time, search engines (in this case Google UK) “learned” that this was a good destination. That’s right – Google actually penalizes sites that are slow by giving them a lower page ranking.

    While this shows us metrics for large sites focused on sales and ad clicks, it doesn’t tell us about fundamentals.There are four fundamental site models, each of which has different business goals. An e-commerce site focused on transactions wants to convert visitors to buyers. A SaaS site wants to make subscribers renew. A media site wants to serve relevant ads and maximize searches or views. And so on.

    If we want to convince marketing, we need to measure business metrics.

    By tying performance and availability to Key Performance Indicators – KPIs – business and operations can finally have a conversation.

    Whether those KPIs are shopping cart abandonment

    Or visitor “bounce rate” (the number of visitors that leave immediately)

    Or just traffic.

    So what KPIs would we like to learn about? This is what web analytics folks work by, whether they’re running a media site, a SaaS platform, a transactional application, or a collaborative social network. It’s what the business cares about.

    Strangeloop agreed to set up an experiment using their technology which would help measure this.

    First, traffic. Despite splitting visitors to be optimized and unoptimized evenly, we had many more optimized sessions captured by the analytics. This may be a result of slower-loading pages failing to execute the analytics script, or abandoning the visit before the page had time to load.

    Unoptimized visitors are roughly 1% more likely to leave the site immediately, without proceeding to other pages.

    Strangely, the unoptimized visitors consisted of more new visitors than the optimized ones did. This seems counter-intuitive and warrants further study.

    Optimized visitors spent more time on the site

    And looked at more pages during their visit – if you’re a media property, this means more impressions for your advertisers.

    On a second e-commerce site running roughly the same experiment, conversions were 16 percent higher and orders were 5.5% higher.

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    Impact of web latency on conversion rates - Presentation Transcript

    1. Performance Impact
      How Web speed affects online business KPIs
    2. Today’s Hosts
      Hooman Beheshti,
      VP Product, Strangeloop
      Alistair Croll,
      Analyst, Bitcurrent
      Author of O’Reilly’s Complete Web Monitoring
    3. 10 s
      1 s
      100 ms
      10 ms
      Zzz
      !
    4. http://www.flickr.com/photos/spunter/393793587
      http://www.flickr.com/photos/laurenclose/2217307446
    5. Everything is interwoven.
    6. We’re getting better
    7. Impact of page load time on average daily searches per user
    8. Impact of additional delay on business metrics
    9. 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
    10. 5-12% increase in revenue
    11. Transactional
      SaaS
      Buy something
      (Amazon)
      Use an app
      (Salesforce)
      Media
      Collaborative
      Click an ad
      (Google News)
      Create content
      (Wikipedia)
    12. Tying web latency to business outcomes
    13. KPIs
      http://www.flickr.com/photos/spunter/393793587
      http://www.flickr.com/photos/laurenclose/2217307446
    14. http://www.flickr.com/photos/mrmoorey/160654236
    15. ATTENTION
      ENGAGEMENT
      CONVERSION
      NEWVISITORS
      SEARCHES
      TWEETS
      MENTIONS
      ADS SEEN
      CONVERSIONRATE
      GROWTH
      TIMEONSITE
      PAGESPERVISIT
      NUMBEROF VISITS
      x
      ORDERVALUE
      LOSS
      BOUNCERATE
    16. It’s time for an experiment
    17. Strangeloop
      Visitor
      Webserver
      Decide whetherto optimize
      Normalcontent
      Accelerated
      Receivepage
      Optimize?
      Insert
      segment
      marker
      Processscripts
      Sendanalytics
      Unaccelerated
      Googleanalytics
    18. What we learned
    19. Traffic levels
    20. Bounce rate
    21. % New visitors
    22. Average time on site
    23. Pages per visit
    24. Conversion rate & order value
    25. Justifying an investment in performance
      (
      )
      Currentdaily orders
      Increased
      conversions
      Increasedorder value
      *
      +
      ROI(days)
      =
      Cost of performanceenhancement
    26. Justifying an investment in performance
      (
      )
      *
      +
      0.1607
      0.0551
      $10,000
      $2,158
      23.17days
      =
      =
      $50,000
      $50,000
      • Caveats
      • Your mileage will vary
      • This is just how to think about it
    27. Conclusions
      • Links between performance and business KPIs are undeniable
      • By talking the same language, IT and marketing can finally agree on what to do about it
      • Changing from “X times faster” to “$Y more money” makes the business care
      • More research is needed
    28. What we need next
      # ofvisits
      Optimized
      0
      10,000
      Visitorlatency
      Different visitors experienced different performance levels.
    29. What we need next
      # ofvisits
      21.58%better
      0
      10,000
      Visitorlatency
      Right now we have a single experiment, and a single resulting business impact.
    30. What we need next
      Best 5%
      Worst 5%
      # ofvisits
      Optimized
      0
      10,000
      Visitorlatency
      Visitors who were optimized fall into a range – the 5th to 95th percentile
    31. What we need next
      24%
      18%
      14%
      Gajillions
      12%
      9.5%
      $ perday
      0
      0
      10,000
      Visitorlatency
      If we have several experiments, we can understand the relationship better.
    32. What we need next
      Gajillions
      $ perday
      0
      0
      10,000
      Visitorlatency
      Every web business has a curve like this hidden inside it.
    33. Questions? (Submit your questions using the GoToWebinar question tool)
    34. More information
      Visit: www.watchingwebsites.com
      Visit: www.bitcurrent.com
      Twitter: @acroll
    SlideShare Zeitgeist 2009

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