speed of ecommerce report 1-20-2014 -...

www.yottaa.com Speed of the E-‐Commerce Web: A Performance Study of the IR500 Q4-‐2013

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P E R F O R M A N C E R E P O R T

Speed of the E-‐Commerce Web: A Performance Study of the IR500 Q4-‐2013



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Table of Contents

Executive Summary ........................................................................................................... 3

Methodology .................................................................................................................... 4

Anatomy of a Page Load Sequence .................................................................................... 6

IR 500 vs. “All Web” .......................................................................................................... 7 Site Performance and Content Complexity Metrics .............................................................................................. 7 “Back End” Metrics: IR 500 vs. All Web ................................................................................................................. 8 “Front End” (User Engagement) Metrics: IR 500 vs. All Web ................................................................................ 9

Performance Factors Within IR 500 ................................................................................. 10 Performance by eCommerce Platform ................................................................................................................ 10 Performance vs. Hosting Provider ....................................................................................................................... 11 Performance vs. Content Delivery Network ........................................................................................................ 11 Performance vs. Industry Sector ......................................................................................................................... 12 Performance vs. Merchant Type ......................................................................................................................... 14 Performance vs. Revenue .................................................................................................................................... 14

On-‐page Content vs. Overall Performance ....................................................................... 16 Page size and Number of Requests vs. Time to Interact ..................................................................................... 17 Content Type vs. Time to Interact ....................................................................................................................... 19 Image count vs. Time to Interact ......................................................................................................................... 20

Appendix ......................................................................................................................... 21 Fastest 20 Sites .................................................................................................................................................... 21 Slowest 20 Sites ................................................................................................................................................... 23 About Yottaa ........................................................................................................................................................ 25


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Executive Summary The web today offers online retailers unprecedented opportunities to engage users and grow their business. But these opportunities also present an increasingly complex set of challenges driven by the explosion of mobile devices, platforms, networks, browsers, rich media, social integration and third party tags – factors that put site performance and user engagement at risk. In order to quantify key user engagement metrics of the E-Commerce web, Yottaa measured the performance of the Internet Retailer 500 (IR 500) sites. In this report we’ve examined:

● How performance of the IR 500 sites compares to the rest of the web;

● How segments within the IR 500 compare to one another;

● Factors correlated with performance among the IR 500.

Some of the key conclusions include: ● The IR 500 sites do not provide a substantially better user experience than average sites, despite

having a significantly better-‐performing backend;

● Infrastructure choices such as hosting provider, E-‐Commerce platform, and content delivery networks (CDNs) exhibit surprisingly little impact, on average varying by less than 2 seconds;

● Site revenue is (weakly) correlated with performance;

● The strongest-‐correlating factors in site performance are related to the size and complexity of a web page’s content (e.g., quantity of 3rd party tags, requests per page, bytes per page).

These results are revealing of changes that have occurred on the web since the early 2000’s. In the past ten years the average web page has grown in complexity on an exponential scale. This has effectively relocated the performance “bottleneck.” Now the front-end work (meaning the processing that occurs in the user’s browser to parse and render content) has become the main challenge in delivering a fast page. Performance experts estimate that 80-90% of the average page's load time occurs in the visitors browser, with only 10-20% of the time consumed by backend processes and bit delivery across the Internet. This “relocation” of the bottleneck has effectively leveled the playing field for web performance in eCommerce. The largest companies – those with the ability to spend massive sums of money on sophisticated technology and infrastructure – now have little to show in terms of net performance gains over smaller online retailers. This is true when comparing the top of the IR 500 list to the bottom of the list, as well as comparing the IR 500 to wider Internet. The data shows that among successful eCommerce companies, backend metrics that are driven by hosting provider and eCommerce platform do not correlate with better user engagement metrics (e.g., Time to Interact). Likewise, sites reporting using a content delivery network are not substantially faster. eCommerce sites looking to improve performance may choose instead to focus on on-page content: the amount of content on the page shows strong correlations to user engagement metrics.


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Methodology Yottaa conducted a performance test of all companies appearing in the 2012 edition of the Internet Retailer 500 (IR 500). The IR 500 is a comprehensive list of the top US eCommerce companies ranked by annual sales. Many companies in the list feature multiple sites, so the total pool includes over 1,000 URLs. The tests were run using real browsers across 16 locations on five continents, capturing the entire page loading sequence of each site using Yottaa Website Test. (With 16 locations and five samples per location, 80 samples total were collected per site.) Here’s a sample result: http://www.websitetest.com/ui/tests/52741092b15c415efe00003f


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Each sample captures key user engagement and performance metrics: …the entire page loading sequence:

…and a waterfall chart of the page loading process, providing insight into the contribution of every asset to site performance:


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Anatomy of a Page Load Sequence Figure 1 illustrates the chronology of stages in a web page load process. The user engagement metrics discussed in this report are largely derived from the demarcations of these stages.

FIGURE 1. ● DNS Time – the elapsed time from the request to when the Domain Name Server has responded with the

correct IP address;

● Time to Connect – the elapsed time from the request to when the TCP/IP handshake is complete and a connection to the origin server is established;

● Time to First Byte – the elapsed time from the request to when the first byte of the HTML file arrives at the client (the user’s browser) from the server;

● Time to Last Byte – the elapsed time from the request to when the last byte of the page’s HTML file has arrived at the browser;

● Time to Title – the time elapsed from the request to when the page’s title appears in the browser tab;

● Time to Start Render – the time elapsed from the request to when the first pixels paint on the otherwise blank page;

● Time to Display – the time elapsed from the request to when the visible elements of the page are finished displaying;


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● Time to Interact – the time elapsed from the request to when all active elements on the page have finished parsing and the user can scroll and utilize any interactive elements on the page.

IR 500 vs. “All Web” Summarized in the table below are the key site performance and content complexity metrics for the IR 500 sites against those of a broader “All Web” data set. (The data for “All Web” includes performance data from 14,000 sites representing a broad spectrum of industries and traffic profiles, measured in a similar manner to the IR 500 sites.) The subsequent two pages explore the back end and front end metrics further.

Site Performance and Content Complexity Metrics

Metric Unit All Web E-‐Commerce

Back End

DNS msec 117 28

Connect Time msec 170 125

Time to First Byte msec 950 332

Time to Last Byte msec 1,171 355

Front End

Time to Title msec 1,844 1,391

Time to Start Render msec 3,095 2,493

Time to Display msec 6,388 6,019

Time to Interact msec 7,894 7,519

Content

Complexity

Domains # 10 22

Asset Count # 59 108

Asset Weight Bytes 1,145,094 1,294,110

JS Count # 11 22

JS Size Bytes 173,446 283,304

CSS Count # 5 6

CSS Size Bytes 34,489 50,807


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Image Count # 33 60

Image Size Bytes 670,578 813,470

“Back End” Metrics: IR 500 vs. All Web Below, Figure 2 displays metrics indicating the backend response times. The term “backend” describes various stages in a web page’s delivery process that occur outside of the visitor’s browser. The backend stages we measured include:

● DNS Time – the elapsed time from the request to when the Domain Name Server has responded with the correct IP address

● Time to Connect – the elapsed time from the request to when the TCP/IP handshake is complete and a connection to the origin server is established

● Time to First Byte – the elapsed time from the request to when the first byte of the HTML file arrives at the client (the user’s browser) from the server

● Time to Last Byte – the elapsed time from the request to when the last byte of the page’s HTML file has arrived at the browser.

FIGURE 2.

Comparing the IR 500 data to the wider Internet reveals a wide margin in backend metrics. On average, a site in the IR 500 is able to deliver the main HTML file in 0.35 seconds, while the rest of the Internet averages over 1 second. Excellent backend performance is typically achieved through investment in high-end infrastructure and services, including IP Anycast DNS service and managed or private hosting environments. These results reflect a strong focus on datacenter performance by IR 500 firms.


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“Front End” (User Engagement) Metrics: IR 500 vs. All Web Figure 3 shows metrics indicating website performance on the front-end. The front-end describes stages in the page load process that occur in the visitor’s browser. These metrics indicate the user’s experience – that is, how long content on the page takes to load from the perspective of the user. These metrics offer the clearest picture of page performance overall. The front-end stages we measured include:

● Time to Title – the time elapsed from the request to when the page’s title appears in the browser tab

● Time to Start Render – the time elapsed from the request to when the first pixels paint on the otherwise blank page

● Time to Display – the time elapsed from the request to when the visible elements of the page are finished displaying

● Time to Interact – the time elapsed from the request to when all active elements on the page have finished parsing and the user can scroll and utilize any interactive elements on the page.

FIGURE 3. On the front end, the IR 500 averages are indeed faster than the Internet average. It is worth noting, however, that the margin between performance of the IR 500 and the rest of the web has diminished when compared to results for backend performance (Figure 2). On the front end, the IR 500 beats the rest of the Internet by 4% for the Time to Interact metric, whereas a comparable margin on backend metrics is 240% for the Time to Last Byte metric. Because front-end metrics directly impact the experience of a visitor – and thus the degree of visitor engagement with the site – these results reveal that there is no significant difference in a visitor’s experience on IR 500 sites compared with the rest of the web. The difference between the averages for Time to Interact of the two groups is less than 0.30 seconds.


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Performance Factors Within IR 500 The IR 500 list includes information on the web technologies used by each of the firms for the sites they run. To explore possible factors correlating with performance within the IR 500, we examined performance of sites per groupings of technologies used. The following charts show the results for average performance of sites per eCommerce platform, hosting provider, content delivery network, and retail sector.

Performance by eCommerce Platform “eCommerce platform” refers to a collection of software and hardware services powering eCommerce sites. A platform may include shopping cart software, a content management system, and a billing system, among others. To explore whether sites on certain eCommerce platforms performed differently than others, we compared average performance metrics for sites using the ten most popular platforms in the IR 500. Figure 4 compares average results in a common user-experience metric (Time to Interact) and two common backend metrics (Time to First/Last Byte) for these 10 platforms.

FIGURE 4. Among the 10 most popular platforms, sites on Yahoo have the slowest average user experience performance. Sites on Yahoo’s platform took an average of over 9.5 seconds to load. Sites on RedPrairie were fastest, averaging 6.0 seconds. With the exception of Yahoo, differentiation across the other platforms ranges from 6.0 seconds to 8.0 seconds. An eCommerce platform typically influences the performance of the backend processes, indicated by metrics like Time to First/Last byte. Notably, in this study the average backend metrics per platform show no correlation with the average user experience metrics (overall load time). For instance, the platform with the fastest user experience on its sites, RedPrairie, happens to have the slowest average backend metrics. Conversely Yahoo, with the slowest sites, has among the fastest average backend metrics.


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Given that that there appears to be no relationship between backend metrics and user experience, this comparison indicates little impact of an eCommerce platform on the average user experience of sites on that platform.

Performance vs. Hosting Provider Another technology choice worth exploring is that of a hosting provider. Figure 5 shows average performance of sites on the eight most popular hosting providers in the IR 500. There is some overlap with providers from the eCommerce Platform comparison (figure 4), because many platforms now include hosting in their service offering. Performance of a given hosting provider affects metrics such as Time to First/Last byte, which indicate fast resolution of backend processes.

FIGURE 5. Sites on Yahoo’s hosting solution are slowest. With Yahoo excluded, variation among the remaining hosters is less than 2 seconds. Sites on Fry’s hosting solution are fastest, at about 7.0 seconds overall load time. In a finding that is similar to that of the eCommerce platform comparison, there’s no clear correlation between Time to First/Last Byte and the overall user experience results. While sites on Yahoo's hosting have the slowest average backend as well as the slowest overall load time, the rest of the entries do not exhibit that pattern. Indeed, this is likely because a hosting choice primarily impacts backend metrics, rather than metrics strongly influenced by the rest of the application delivery chain.

Performance vs. Content Delivery Network A CDN is a network of servers located in a number of geographic regions where the static content of a web page can be cached. The goal of using a CDN is to achieve parity in performance for site visitors in any geographic location by overcoming “middle mile” latency involved in sending data across long distances. Well over half of the IR 500 sites report using a CDN. Among IR 500 sites that report using a CDN, Figure 6 shows performance of sites on the 6 most popular CDN solutions.


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FIGURE 6. There’s variation among the averages per CDN from approximately 7 seconds to nearly 11 seconds. Akamai, the recognized leader in the field, is near the top, though in this study, sites on GSI Commerce are faster on average. Additionally, IR 500 sites reporting a CDN average a Time to Interact of 7.49 seconds. The average of those not reporting a CDN is 7.71: a difference of only 0.20 seconds. It is also interesting to note that less than half a second differentiates the average user experience for sites using the four best performers: in-house solutions, Amazon CloudFront, Akamai, and GSI. For IR 500 sites, CDN does not make a noticeable difference in performance. Performance vs. Industry Sector The IR 500 list categorizes each firm by the type products sold. For instance, Amazon is categorized as a “Mass Merchant,” and Best Buy is listed in “Computers/Electronics”. Figure 7 shows the average performance of sites in each of the categories used in the IR 500.


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FIGURE 7.

Performance of each sector averages range from just less than 7 seconds to about 9.5 seconds. Only 4 of the sectors averaged a faster time than the overall average for the IR 500 (7.5 seconds).


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Performance vs. Merchant Type Another category in the IR 500 describes the type of merchant. This means distinguishing bricks-and-mortar merchants (e.g. Wal-Mart) from “web only” firms (Amazon); as well as manufacturers selling their own products (Dell) and catalog operations (L.L. Bean). We thought it feasible to think that web-only businesses may have better performance than companies for which eCommerce is only a portion of revenue. Figure 8 shows averages of sites in each category for a user experience metric (Time to Interact).

FIGURE 8. Among the four merchant types, average performance varied by only 0.2 seconds – 7.4 seconds to 7.6 seconds – amounting to functionally equivalent averages. Interestingly, web-only businesses do not perform better than other merchant types.

Performance vs. Revenue Big revenue is the sole criterion that gets a firm into the IR 500. Despite that apparent commonality among the IR 500 sites, there remains a wide range of revenue within the list. At #1 on the list, Amazon had $48 billion in sales for 2011; a figure 3,229 times greater than Summit Sports’ $15 million at #500. Figure 9 shows the performance sites across this wide spectrum of revenue. A data point representing the average performance of each site is plotted against the revenue of that firm.


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FIGURE 9. First, site performance correlates slightly with revenue. That is, if a site pulls in more revenue, it's more likely to be fast. This is most clearly evident when looking at performance outliers: sites with averages over about 14 seconds in load time stop appearing after revenue hits $1b. This is likely attributable to richer companies investing more dollars directly into performance. For instance Wal-Mart, the #4 firm for revenue, employs a team of engineers focused mainly making the company's sites faster.1 Investment on that scale comes at a cost that's out of reach for many other companies on the list. Despite the correlation, however, the top revenue-grossing firms do not produce websites that are dramatically better than average. The top 3 sites, for instance, cover a range of 6.0 to 8.0 seconds. This proves that performance is not something that has to be bought at a high price: firms at the bottom of the IR 500 list do create sites that perform on par with the richest firms. One second separates the averages for the top 10 eCommerce sites from the bottom 250. (See figure 10)


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FIGURE 10. This histogram shows average revenue and average Time to Interact for four site categories. Sites in the bottom half of the IR 500 (#'s 251-‐500) are on average over 1 second slower than the top 10 sites. Sites with more revenue perform slightly better on average. However, the difference separating the richest firms with much smaller players is nearly insignificant, in particular given the vastly different IT budgets and resources.

On-‐page Content vs. Overall Performance In comparing the IR 500 to the rest of the web and segments within the IR 500, we found few correlating factors. Where we did see correlation, it was not strong. We found that:

● Performance of user experience metrics among the IR 500 was only slightly better (a margin of 4%) than the rest of the web

● eCommerce platform and hosting provider didn’t show a clear winner for performance – averages were within 2 seconds

● Among the 4 most popular CDN providers, less than .5 seconds separates the averages for each

● Segments of retail sector and merchant type showed even less variation

● Higher revenue correlates with better performance, but the difference between the top and the bottom is only about 1 second in average page load time.

In this section we’ll examine how the amount and complexity of on-page content matches with overall load time.


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Page size and Number of Requests vs. Time to Interact When examining the content of a web page, the key metrics are:

● Total page size (also referred to as page weight) -‐-‐ the total number of bytes of all content on the page

● Number of requests – the number of times a browser has to make a round trip to a server to fetch content

These two metrics are similar in that they generally reflect how much “stuff” is on a page, as well as how taxing the page will be to render. More bytes and more requests both mean more work for visitor’s browser to do to render the page. Below, Figures 11 and 12 show strong correlation to performance as numbers of bytes and complexity rise. Furthermore, there’s wide separation between the top and bottom: even excluding the top buckets in the histograms (which are open-ended, therefore containing outliers) a difference of about 7.0 seconds separates the top and bottom in average Time to Interact. Impact of Page Size

FIGURE 11.


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FIGURE 12. For eCommerce sites in the IR 500, this may be the beginning of an answer to questions raised in sections 1 and 2: Why are sites in the IR 500 so much faster than the rest of the web on the backend, but for user experience metrics the gap closes to nearly nil? Why is there no correlation between hosting provider performance and end-user experience? The on-page content correlates strongly to Time to Interact, pointing to that as an answer. It appears that among the IR 500, larger, more complex pages lead to longer average page load time, and poorer user experience.


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Content Type vs. Time to Interact Two single categories of content actually have stronger correlations than page size: Number of JavaScript files on the page, and the number of domains content is pulled from. Figures 13 and 14 show the rise in Time to Interact as numbers of JavaScript files and number of domains rise. Impact of JavaScripts

FIGURE 13. Impact of Domains

FIGURE 14.


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A likely explanations for JavaScript’s strong correlation are that scripts are more taxing for the browser than other types of content. Where JavaScripts appear, there can be dozens of assets in tow, including HTML, images, and CSS. And as figure 12 shows, assets are bad for performance. Domains are also negative for performance, since they introduce inconsistency. A domain appearing on a page means there is content coming from a third party, and there’s inherently less control over those assets. There could be network or server problems with the site supplying the content, and those problems spill onto the page.

Image count vs. Time to Interact In studies of the wider Internet, Image Count has been observed to be one of the highest-correlating factors in overall performance. This is due to the fact that a large proportion (typically about 70%) of the bytes on a given web page are from images. As Chart 15 shows, in the IR 500 Image Count actually doesn’t correlate so strongly with Time to Interact. This may be because IR 500 sites do more to optimize their images through compression, sprites and other techniques than average websites do.

FIGURE 15. Conclusion: The frequency of individual types of content are also strongly linked to Time to Interact among the IR 500.


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Appendix

Fastest 20 Sites Figure 16 below illustrates the site performance and content complexity metrics for the fastest 20 sites among the IR500. Not surprisingly, we see that these fast sites – loading in just one or two seconds around the world – are quite light content-wise: typically just a couple hundred KB of content, relatively few page assets, and a minimal number of domains that the content is pulled from. It should be noted that although these sites are efficient from a content perspective, that may also be an indicator that they use fewer third party widgets (e.g., social, content, analytics) which may result in a less rich, engaging online experience.


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1 National Trade Supply NTSupply.com, Prothermostats.com, EnergyMonitors.com, DehumidifierExperts.com, IAQSource.com

1,530 2,474 4 17 103,877

2 Discount Ramps.com LLC Discount-Wheelchair-Ramps.com, Discount-Trailers.com, TrekPet.com, MotorcycleRamps.com, ATVRamps.com

1,619 2,622 3 27 185,574

3 Walgreen Co. Salubeauty.com, Walgreens.com 1,738 2,636 1 14 90,159

4 Nordstrom Inc. Nordstrom.com 1,933 5,800 31 89 628,904

5 Replacements Ltd. Replacements.com 2,013 3,632 17 46 327,240

6 Wolverine World Wide Inc. BatesFootwear.com, Harley-DavdisonFootwear.com

2,059 3,172 4 10 98,067

7 Systemax Inc. Systemax.com 2,070 3,155 2 55 171,585

8 1800Mattress.com Mattress.com 2,149 3,279 8 59 255,205

9 Shoebuy.com Inc. BagsBuy.com 2,393 3,307 10 35 417,181

10 W.W. Grainger Inc. Grainger.com, LSS.com 2,404 4,263 19 76 479,959

11 Altrec.com Inc. GreatOutdoors.com 2,412 4,468 23 60 536,983

12 OpticsPlanet Inc. RangeFinders.com 2,432 3,304 7 55 347,692

13 Benchmark Brands Inc. FootSmart.com 2,549 3,366 10 42 510,580

14 Apple Inc. Store.Apple.com 2,582 3,293 3 65 1,073,384

15 Guess? Inc. shopMarciano.ca 2,605 5,955 15 63 1,078,071

16 BikeBandit.com BikeBandit.com 2,606 4,380 6 58 850,366

17 Gaiam Inc. RealGoods.com 2,611 3,259 3 38 737,732

18 DSW Inc. DSW.com 2,654 3,528 11 38 740,350

19 Best Buy Co. BestBuy.com 2,659 4,095 20 61 585,433

20 The Neiman Marcus Group Inc. BergdorfGoodman.com 2,666 6,245 58 169 907,246

FIGURE 16.


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Slowest 20 Sites Figure 17 below illustrates the site performance and content complexity metrics for the slowest 20 sites among the IR500, with home pages that take well over 10 seconds to load around the world. These sites exhibit high content complexity – with lots of images and other page assets, all pulled from dozens of domains, likely featuring extensive use of third party widgets (e.g., social, content, analytics). So while the good news is that these sites are likely at the forefront of the modern, social web, the resulting performance is likely hurting user engagement and holding back important business metrics (bounce rate, time on site, conversions, purchases). Finally, it should be noted that a site need not be forced to choose between a modern, sophisticated site – or a fast one (see next section!).


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1 Gaiam Inc. FirmDirect.com, RediSetGo.com

44,400 44,784 13 44 1,031,325

2 Dover Saddlery Inc. DoverSaddlery.com, SmithBrothers.com

27,592 27,916 24 81 929,140

3 Biblio Inc. For.TheLoveofBooks.com 24,529 25,666 30 109 818,015

4 BabyAge.com Inc. BabyNameRegistry.info, BabyStore.info

24,271 24,609 18 67 1,348,070

5 Cooking.com Inc. PillsburyStore.com 22,478 22,823 14 59 521,174

6 Marc Ecko Enterprises ShopEcko.com 19,369 19,829 20 110 2,810,918

7 Envelopes.com ActionEnvelope.com 18,512 18,819 8 384 1,094,197

8 Nutrisystem Inc. Nutrisystem.com 17,299 19,593 65 220 1,770,145

9 hhgregg Appliances Inc. hhgregg.com 16,434 18,745 51 310 2,458,801

10 Deluxe Corp. LogoMojo.com 15,710 17,901 24 83 824,688

11 Lancome-USA.com Lancome-USA.com 15,470 18,347 54 233 2,228,648

12 Net Direct Merchants MantelsDirect.com 15,437 15,749 30 137 1,545,480

13 Artbeads.com Artbeads.com 14,367 16,077 31 161 2,069,173

14 Mattress USA Inc. PartySuppliesDelivered.com 13,813 18,417 66 193 2,159,196

15 Shoplet Shoplet.com 13,638 14,944 48 210 1,961,759

16 FreshDirect LLC FreshDirect.com 13,600 16,880 38 197 1,203,644

17 Williams-Sonoma Inc. WSHome.com 13,461 14,477 32 165 2,298,642

18 Zale Corp. Zales.com 13,432 16,033 32 129 4,499,560

19 Urban Outfitters Inc. FreePeople.com 13,431 14,549 31 197 14,019,488

20 Gander Direct Marketing Services LLC GanderMountain.com 13,035 14,374 23 118 1,268,331

FIGURE 17.


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About Yottaa Maximize Mobile and Web Success With Yottaa Engagement Cloud The rise of mobile computing has raised the bar for online businesses. Browsing increasingly occurs on the go, which requires websites to immediately engage users and then focus their attention with an engaging experience that responds to their device, browsing context and on-page interactions. The Yottaa Engagement Cloud ensures a personalized, responsive solution that adapts to visitor context and user actions to improve engagement and increase mobile and web conversions. If your website is integral to your business, Yottaa helps you deliver a more engaging site that improves your business, for any business. User Engagement Challenges The web today offers unprecedented opportunities to engage users and grow your online business. But these opportunities also present an increasingly complex set of challenges driven by the explosion of devices, platforms, networks, browsers, rich media, social integration and 3rd party tags. The time and effort required to optimize user engagement via traditional approaches, such as site re-coding and DIY optimizations, has increased by orders of magnitude. There has not been a holistic solution to maximizing engagement to drive conversions, until now. The Solution: Yottaa Engagement Cloud Yottaa Engagement Cloud is a comprehensive solution enabling mobile and web businesses to improve user engagement. Yottaa customers enjoy higher conversions, lower abandonment rate and deeper insights into optimizing key engagement metrics across the wired and wireless web. Built on Yottaa’s patented Context Intelligence™ platform, the Yottaa Engagement Cloud delivers 3 key elements that deliver maximum engagement:

• Exceptional Mobile and Web Performance: The mobile revolution has created a significant challenge for legacy approaches to website optimization. In the US alone, 25% of users rely on mobile devices as their sole means of connectivity. 48% of time spent shopping online is on mobile devices, and when given the choice 35% of users will choose to browse your full site on a mobile device. A responsive site encourages users to interact and improves their perceptions of usability and quality. Users context switch every second, and in just one second a visitor’s likelihood to bounce increases by 65%. Yottaa enables you to achieve exceptional performance for every visitor context: desktop, mobile and search engine, applied automatically without manual code changes.

• Just in Time Content: Yottaa Engagement Cloud engages users by applying sequencing, prioritization and responsiveness as visitors flow through your site. Our proprietary Context Intelligence technology senses a user’s location, browser, device, Internet connectivity, and in-page interaction to sequence content delivery and rendering, prioritizing page elements for optimal timing and order. This makes transactions more personalized, compelling and engaging, and results in increased pageviews and time on site, while lowering bounce rate and decreasing abandonment across your mobile and desktop sites.


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• Minimize Site Disruptions: A recent Aberdeen Group report suggests downtime costs around $225,000 per hour, and the average Fortune 500 company web site experiences 80 hours of downtime a year. Site disruptions don’t just cost you money in the form of lost productivity and emergency maintenance costs; they also reduce your ability to generate revenue by over 22% annually. Yottaa maximizes uptime, ensures elastic scalability and minimizes site errors so your site generates revenue 24x7.

Guarantee Mobile and Web Success with Yottaa Yottaa Engagement Cloud is an industrial-strength platform powered by a global network of over 30 data center locations distributed around the globe. It is trusted by mission-critical websites across eCommerce, financial services, media, software-as-a-service, consumer goods, business services, electronics, and enterprise software. Among our customers are G20 government sites, Fortune 500 companies, and the fastest growing startups approaching IPO, including popular online brands such as PC Mall, Bayer, H&R Block, Fossil, and HubSpot. With Yottaa, you can optimize key E-Commerce engagement metrics:

1) Time to Start Render: Initiate user engagement immediately to engages visitors, evoking curiosity and interest in your offering.

2) Time to Display: Improve perceived usability and grabbing the visitor’s full attention by sequencing content processing and implementing responsive image to maximize sensory appeal.

3) Time to Interact: Keep users moving and accelerate interactions to maintain visitor focus, and ensure ongoing interactions as users are absorbed by your website experience.

4) Bounce Rate: Engage users by improving their perception of the time and effort required to accomplish tasks; after all, every second your visitors spend waiting for your site increases your bounce rate by 65%.

5) Pages per Visit: Increase site interaction with quick transitions and responsive page elements that engage users as they navigate and click.

6) Time on Site: Increasing visitor session times raises conversion potential and ensures your users engage with your valuable content.

7) Abandonment Rate Eliminating frustrations caused by site disruptions, sluggish performance or content that cannot be rendered on a user’s device improves goal attainment.

8) Conversion Rate: Avoid distractions and maintain focus to create engaged, loyal users and maximize revenue.

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