IBM Coremetrics 4th Annual Online Retail Holiday Readiness Report Industry Benchmark Analysis and Best Practice Guide to Maximize Holiday Returns

1. SPECIAL REPORT
IBM Coremetrics
4th Annual Online Retail
Holiday Readiness Report
Industry Benchmark Analysis and
Best Practice Guide to Maximize
Holiday Returns
J U N E 2 011
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2. IBM Coremetrics 4th Annual Online Retail Holiday Readiness Report
Table of Contents
Introduction 1
Trends in Online Shopping 2
Consumers Are Spending More on More Items 3
Mobile Device Usage and Social Media Are Growing 5
Consumer Attention Continues to Decline 7
Carting and Ordering Hit Record Highs 8
Single-Page ‘Bounce’ Visitors Remain High 10
Best Practices 11
Focus on the Customer Life Cycle 11
Capitalize on the Mobile Channel 15
Retarget Your Browsers and Abandoners 17
Use Personalized Product Recommendations 20
Cultivate the Social Media Channel 21
Make the Holiday Season Profitable 22
Copyright ©2011 Coremetrics, an IBM Company. All Rights Reserved.

3. IBM Coremetrics 4th Annual Online Retail Holiday Readiness Report
Introduction
The 2010 holiday season was huge for online retailers. Web merchants racked up double-digit increases
in total site sales and average order value as consumers shook off the effects of the recession. Those
increases have continued into 2011, IBM® Coremetrics® Benchmark data shows, suggesting that the
upcoming holidays could well be another record-setting season for online retail.
Yet pitfalls loom. Consumer attention has flatlined at its weakest levels ever, sinking to new lows in such
metrics as average time on site and page views per session, according to Coremetrics Benchmark data.
Discriminating visitors are spending a lot less time browsing retail sites than they did several years ago.
They’re shopping surgically—zeroing in quickly on the items they want—and are more likely than ever to
“bounce” after a glance at a single page.
Meanwhile, mobile browsing and shopping has surged impressively as consumers indulge in the
convenience and rich functionality of feature-laden tablets and smartphones. Mobile sales as a
percentage of overall site business nearly doubled in our reporting period, with mobile shopping poised
to break into double digits by the holidays. Social media visitors and sales have lifted modestly—yet these
shoppers are more than twice as likely to convert compared to overall site visitors.
In this fourth annual holiday guide from Coremetrics, an IBM Company, you’ll find in-depth analyses of
key trends in online shopping and usage based on anonymous data aggregated from more than 500
U.S. retailers participating in the Coremetrics Benchmark program. This report also offers best-practice
guidance on how you can adapt to fast-moving trends and make the most of your opportunities during
the critical holiday season, including a look at:
• Trends in key performance metrics over time
• Emerging opportunities and challenges in online retail
• Proven strategies to maximize success and deepen customer engagement
• Key technological capabilities for web analytics and online marketing
In preparing this guide, our goal is to help you, the online retailer, formulate powerful programs and tactics
to take this holiday season head-on.
Happy selling!
Copyright ©2011 Coremetrics, an IBM Company. All Rights Reserved. SPECIAL REPORT 1

4. IBM Coremetrics 4th Annual Online Retail Holiday Readiness Report
Trends in Online Shopping
The holiday season is the proving ground for the strategies, tactics, and technologies that your company
has in place to boost sales by attracting and retaining customers. The opportunity is huge with online retail
sales predicted to increase significantly over the next several years. In support of this, the independent
research firm Forrester has found:
• 83 percent of consumers prefer to shop online than in crowded stores during
Thanksgiving weekend1
• 21 percent of online shoppers expect to spend more over the web in 20112
Such trends are reflected in our analysis of Coremetrics Benchmark data. The following section of this
report examines trends in five key areas:
• Consumers are spending more on more items
• Mobile device usage and social media are growing
• Consumer attention continues to decline
• Carting and ordering hit record highs
• Single-page “bounce” visitors remain high
About Coremetrics Benchmark. Data in this report is based on Coremetrics Benchmark, which
captures online marketing results and commerce data from more than 500 contributing U.S. retailers.
The industry’s only peer-level benchmarking solution enables Coremetrics customers to measure
performance against the competition (in anonymized, aggregated form). Coremetrics Benchmark comes
standard with IBM® Coremetrics® Web Analytics at no additional cost.
1
Bizrate Insights and Forrester Research, “Online Retail Holiday Study,” December 2010.
2
Forrester Research, North American Technographics® Retail Online Survey, Q3 2010 (US), September 2010.
Copyright ©2011 Coremetrics, an IBM Company. All Rights Reserved. SPECIAL REPORT 2

5. IBM Coremetrics 4th Annual Online Retail Holiday Readiness Report
Consumers Are Spending More on More Items
Average order value (AOV) surged to a new high in our reporting period, hitting a record $204.58 in April
2011—up a massive 70 percent from a low of $120 in June 2008. And consumers are buying more items
online, reaching a new high of 8.26 items per order in March 2011—nearly double the 4.8 items per order
in December 2008.
Between the 2009 and 2010 holiday seasons, retailers saw a double-digit gain in AOV. Order values were
also up substantially on Black Friday and Cyber Monday 2010 compared to 2009, as shown in Figure 1.
Holiday Season Average Order Value
2009 2010 % Gain
November $ 175 $ 195 11.3%
December $ 172 $ 190 10.7%
Black Friday $ 170 $ 191 12.1%
Cyber Monday $ 180 $ 195 8.3%
Figure 1. Online retailers posted double-digit AOV gains during the 2010 holiday season.
As the economic rebound continues, retailers have the opportunity to capitalize on consumers’ newfound
willingness to spend. Smart retailers will not rest on their successes and blindly assume that spending will
remain strong past the 2011 holidays, but will aggressively expand their emarketing, web analytics, mobile,
and social efforts to maximize returns while strengthening long-term customer loyalty.
Retargeting browsers and abandoners with personalized emails and targeted display ads is a proven way
to prompt return visits and conversions among would-be buyers. Product recommendations technology
can contribute 10 percent and more of total sales, Coremetrics Benchmark data has shown, boosting
both AOV and items per order. Strong mobile device support is essential to satisfying the fast-growing
population of mobile browsers and shoppers, while social media offers an emerging channel to deepen
consumer engagement and trigger site visits.
Copyright ©2011 Coremetrics, an IBM Company. All Rights Reserved. SPECIAL REPORT 3

6. IBM Coremetrics 4th Annual Online Retail Holiday Readiness Report
U.S. Retail: Average Order Value April 2008 - April 2011
$220.00
$200.00
$180.00
$160.00
$140.00
$120.00
$100.00
2008 Apr
May
Jun
Jul
Aug
Sep
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2009 Apr
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2010 Apr
May
Jun
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2011 Apr
U.S. Retail: April 2008 - April 2011
Average Number of Items Per Order
8.50
8.00
7.50
7.00
6.50
6.00
5.50
5.00
4.50
4.00
May
Jul
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2008 Apr
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May
Figure 2. Both average order value and average number of items per order hit record highs in early 2011,
signaling opportunities for a banner holiday 2011.
Conclusion: Increases in average order value and average number of items per order should prompt
savvy retailers to look for ways to smartly engage online shoppers and capitalize on consumer use of
social media and mobile devices.
Copyright ©2011 Coremetrics, an IBM Company. All Rights Reserved. SPECIAL REPORT 4

7. IBM Coremetrics 4th Annual Online Retail Holiday Readiness Report
Mobile Device Usage and Social Media Are Growing
Coremetrics Benchmark data reveals strong and steady increases in mobile device usage in both site
visits and sales. Though our snapshot is somewhat limited, from October 2010 to April 2011 as mobile
data was first launched in Coremetrics Benchmark at the end of 2010, mobile usage is clearly rising and is
a critical channel that no online retailer can afford to shortchange or ignore. For instance, in our six-month
reporting period, the mobile channel as a percent of total site sales nearly doubled, from 3.4 percent to
6.5 percent.
We expect that mobile site traffic will grow well beyond the 7.6 percent recorded in April 2011 and be in
the double digits by holiday 2011. Sales via mobile devices—at 6.5 percent of all site sales as of
April 2011—is impressively high and illustrates that consumers are using iPhones, iPads, BlackBerries,
and Android devices for more than just finding directions to a store.
U.S. Retail: Mobile Site Traffic November 2010 - April 2011
8.00%
7.00%
6.00%
5.00%
4.00%
3.00%
Nov Dec Jan Feb Mar Apr
U.S. Retail: Mobile Sales Percent November 2010 - April 2011
7.00%
6.00%
5.00%
4.00%
3.00%
Nov Dec Jan Feb Mar Apr
Figure 3. The mobile channel shows strong growth in percent of both site visits and sales.
Site visits and sales by social media visitors were less than 2 percent in our limited reporting window of
October 2010 to April 2011, rising incrementally over those six months. Interestingly, as seen in Figure 4,
the percentage of social-driven site sales is higher than social-driven site visits (1.6 percent versus
1.2 percent respectively in April 2011). This indicates that social visitors (often Facebook fans or Twitter
followers) are uniquely predisposed to purchasing and are responding to offers exclusively on social
media. Though the population is relatively small, it’s a promising segment that retailers are smart
to cultivate.
Copyright ©2011 Coremetrics, an IBM Company. All Rights Reserved. SPECIAL REPORT 5

8. IBM Coremetrics 4th Annual Online Retail Holiday Readiness Report
U.S. Retail: Social Site Traffic November 2010 - April 2011
1.25%
1.00%
0.75%
0.50%
0.25%
0
Nov Dec Jan Feb Mar Apr
U.S. Retail: Social Sales Percent November 2010 - April 2011
1.75%
1.50%
1.25%
1.00%
0.75%
0.50%
0.25%
0
Nov Dec Jan Feb Mar Apr
Figure 4. Social-driven sales exceed social-driven site traffic, indicating social visitors
are highly inclined to convert.
A comparison of key metrics across overall, mobile, and social visitor populations reveals some interesting
insights:
• Social visitors. They’re more than twice as likely as the overall population to convert, at a rate
of 10.7 percent versus 5.2 percent. Many of these social visitors are likely responding to offers,
as their bounce rate (62.8 percent) is high and their time on site (3:26 minutes) is low.
• Mobile visitors. They’re less engaged than the overall population, with fewer page views, less
time on site, lower conversion, and higher bounce rates. Though this is not unsurprising, it does
underscore the need for retailers to monitor and optimize the mobile user experience.
All Means Mobile Social
Page views per session 7.5 4.8 5.2
Average time on site 7:20 3:42 3:26
Conversion rate 5.2% 3.9% 10.7%
Bounce rate 35.1% 44.8% 62.8%
Figure 5. A comparison of key metrics across the overall, mobile, & social segments of retail site visitors.
Conclusion: Mobile and social visitors are rapidly becoming a force to be reckoned with. Retailers
need to move fast to ensure they meet the expectations of fickle mobile visitors, and should continue
cultivating the important segment of social media users.
Copyright ©2011 Coremetrics, an IBM Company. All Rights Reserved. SPECIAL REPORT 6

9. IBM Coremetrics 4th Annual Online Retail Holiday Readiness Report
Consumer Attention Continues to Decline
Despite encouraging gains in AOV, consumer attention hit record lows in the past year. The average time
spent on site fell to its lowest point of the past three years in October 2010, down to 7:04 minutes from
10:04 in April 2008—a 30 percent decline. Average page views per session also found a new bottom in
December 2010—7.44, down 45 percent from a high of 13.5 in April 2008.
As shown in Figure 6, the new lows are small dips in lines that are relatively flat over the past 1½ years
after dropping precipitously from levels of 2008. Discriminating consumers are clearly engaging in surgical
shopping, while the growth of social media and mobile usage and general information overload has cut
into the time that they used to spend on retail sites.
To counter these trends and shrunken windows of engagement, retailers should redouble efforts to make
sites personalized and compelling. Use of relevant product recommendations, product review sections,
and social media are proven techniques to lengthen site visits. Retailers should also revisit fundamental
web analytics and A/B testing to optimize site navigation and the overall experience.
U.S. Retail: Time on Site April 2008 - April 2011
10:33
10:04
9:36
9:07
8:38
8:09
7:40
7:12
6:43
2008 Apr
May
Jun
Jul
Aug
Sep
Oct
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2011 Apr
U.S. Retail: Page Views Per Session April 2008 - April 2011
14.00
13.00
12.00
11.00
10.00
9.00
8.00
7.00
Sep
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Figure 6. Average time on site and page views per session hit new lows in late 2010.
Conclusion: A leveling off of consumer attention spans illustrates a new reality of discriminating
customers and surgical shopping. Retailers need to diligently test and implement techniques, such as
relevant product recommendations and site optimization, to improve these important metrics.
Copyright ©2011 Coremetrics, an IBM Company. All Rights Reserved. SPECIAL REPORT 7

10. IBM Coremetrics 4th Annual Online Retail Holiday Readiness Report
Carting and Ordering Hit Record Highs
In another positive development, both shopping cart and ordering sessions reached new highs during our
reporting period. Shopping cart sessions (when a shopper has carted an item) reached 10.9 percent in
February 2011, up from a low of 8.3 percent in September 2008. Ordering sessions peaked at 5.3 percent
in February 2011 as well, more than double the 2.6 percent of September 2008.
But product page views per session fell to a new low of 1.7 in November 2010, trending steadily
downwards in the 12 months preceding, and less than half the 3.7 product page views per session
of April 2008. Combined, these three data points corroborate observations on the surgical shopping
phenomenon—shoppers are visiting fewer product pages, but they’re carting and purchasing more items.
U.S. Retail: April 2008 - April 2011
Shopping Cart Session Percent
12.00%
11.00%
10.00%
9.00%
8.00%
7.00%
May
Jul
Sep
Oct
Dec
Jan
Feb
Mar
Jun
Jul
Aug
Sep
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2011 Apr
2008 Apr
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2010 Apr
May
U.S. Retail: Order Session Percent April 2008 - April 2011
6.00%
5.00%
4.00%
3.00%
2.00%
1.00%
0
May
Feb
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U.S. Retail: April 2008 - April 2011
Product Page Views Per Session
4.00
3.50
3.00
2.50
2.00
1.50
1.00
May
Jul
Sep
Oct
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Jan
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2010 Apr
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Nov
Figure 7. Consumers are carting and ordering more items, but they’re viewing fewer product pages.
Copyright ©2011 Coremetrics, an IBM Company. All Rights Reserved. SPECIAL REPORT 8

11. IBM Coremetrics 4th Annual Online Retail Holiday Readiness Report
Conclusion: Savvy retailers will strive to improve product page views per session, using relevant
product recommendations and social media techniques, to capitalize on consumer inclinations to cart,
order, and spend.
New visitor and shopping cart conversion. Retailers are increasingly successful at converting new
visitors, with new visitor conversions hitting a high of 4.9 percent in December 2010, more than double
the roughly 2 percent typical during 2008. This metric has trended gradually upwards for more than a year
and reflects growing consumer trust of web sites they haven’t dealt with before, and in online retail
in general.
Shopping cart conversion, however, has been erratic over the past two years, with less than one-third of
carting sessions ending in conversion. With no sustained gains in this critical metric, retailers can benefit
by applying web analytics for a fresh re-examination of their ordering funnel, and retargeting abandoners
with personalized emails and display ads.
U.S. Retail: April 2008 - April 2011
New Visitor Conversion Percent
6.00%
5.00%
4.00%
3.00%
2.00%
1.00%
0
Feb
Jun
Nov
Jan
Feb
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2008 Apr
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2009 Apr
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U.S. Retail: April 2008 - April 2011
Shopping Cart Conversion Percent
40.00%
38.00%
36.00%
34.00%
32.00%
30.00%
May
Jul
Sep
Oct
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Mar
2010 Apr
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2008 Apr
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Aug
Figure 8. New visitor conversions are rising gradually, but retailers haven’t been able to make
sustained improvement in shopping cart conversions.
Conclusion: Erratic and unsustained movement in shopping cart conversion trends suggest the
need for retailers to re-examine their carting and ordering processes, using web analytics to identify
key drop-off points. Testing and optimization towards improving this key metric can pay off with sizable
increases in top-line revenue.
Copyright ©2011 Coremetrics, an IBM Company. All Rights Reserved. SPECIAL REPORT 9

12. IBM Coremetrics 4th Annual Online Retail Holiday Readiness Report
Single-Page ‘Bounce’ Visitors Remain High
The bounce rate (the percentage of single-page sessions) has remained fairly steady over the past 1½
year, rising slightly over that period and hitting a record high of more than 35 percent in December 2010.
Despite remaining flat, the bounce rate is up sizably from 22 percent in April 2008. Multi-page sessions
are down in concert, hitting a record low of 65.5 percent in March 2011.
Corresponding with the surgical shopping trend, the elevated bounce rate makes clear that discriminating
visitors are likely to click away if they don’t find content that’s personalized and relevant. It underscores the
need for online retailers to ensure that landing pages reached from a display ad, email promotion, or paid
search listing are spot-on with what was advertised.
Retailers can also combat high bounce rates with personalized recommendations, product review
sections, videos, and social media, encouraging visitors to click on. In addition, complementing on-site
search results with product recommendations helps ensure relevant search page content and can trigger
additional conversions.
U.S. Retail: April 2008 - April 2011
Bounce Rate (Single Page Sessions)
40.00%
35.00%
30.00%
25.00%
20.00%
15.00%
’08 Apr
May
Jun
Jul
Aug
Sep
Oct
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Dec
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’09 Apr
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’10 Apr
May
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’11 Apr
U.S. Retail: April 2008 - April 2011
Multi-page Session Percent
82.00%
77.00%
72.00%
67.00%
62.00%
’08 Apr
May
Jun
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Aug
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’09 Apr
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’10 Apr
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’11 Apr
Figure 9. The bounce rate hit a record high in Dec. 2010—conversely, multi-page sessions fell
to an all-time low.
Conclusion: To improve bounce rate performance, retailers need to ensure that landing page content
corresponds with what was highlighted in an email promotion and display or paid search ads. They
should also test and optimize page content to entice visitors into clicking through to multiple pages.
Copyright ©2011 Coremetrics, an IBM Company. All Rights Reserved. SPECIAL REPORT 10

13. IBM Coremetrics 4th Annual Online Retail Holiday Readiness Report
Best Practices
Going into the holiday season, how can you take advantage of increases in online sales and AOV, while
combating the decline in consumer attention? Online retailers that excel will relentlessly pursue these
objectives:
• Learn from a customer’s browsing path over an extended period of repeat visits
• Use historical behavior data to optimize all online marketing efforts
• Deliver highly personalized and relevant customer experiences across all channels
• Invest in processes of continuous improvement to create and execute marketing programs
that get better and better
Those best practice principles apply to five areas of strategic focus for the holidays and beyond,
which we examine in the next section of this report:
• Focus on the customer life cycle
• Capitalize on the mobile channel
• Retarget your browsers and abandoners
• Use personalized product recommendations
• Cultivate the social media channel
Focus on the Customer Life Cycle
Customer-centric marketing has been a theme that has resonated for years in traditional channels: print,
media, advertising, etc. In the digital landscape, it has more recently come into the spotlight as customers
are becoming more discriminating in their online behaviors and are being exposed to more information.
According to data gathered in IBM® Coremetrics® Lifecycle, on average it takes a consumer 6.8 digital
interactions before converting.
Whether it’s through display advertising, email, search, customer reviews, mobile or social campaigns,
consumers are exposed to numerous digital channels influencing their online purchases and decision
making. As a marketer, it’s important not only to be measuring each of these digital channels, but also
capturing these individual consumer behaviors over time. While a consumer may have clicked through on
a paid search campaign and made a purchase, there were likely a number of other activities that ultimately
led to the conversion.
He or she may have clicked through from natural search to gather information, then been exposed to
a display ad, then saw customer reviews, then read about a sales promotion on Facebook—all before
clicking on that one paid search campaign. By understanding this full customer life cycle, marketers can
more clearly define what campaigns, content, and products influence customer life cycle progression and
adjust marketing spend appropriately.
Copyright ©2011 Coremetrics, an IBM Company. All Rights Reserved. SPECIAL REPORT 11

14. IBM Coremetrics 4th Annual Online Retail Holiday Readiness Report
Natural
Display Search
Direct Ad
Load
Paid Email
Search
Searched Came directly to Responded to Returned via a Came to the
for HDTV the site, bought Newsletter TV Display Ad click. site via Natural
on Google. a Blu-Ray player. Clearance link. Picked a Product Search, entered
Recommen- discount code
dation on site. and purchased.
Figure 10. Marketers must understand the journey—the complete conversion cycle and all
of the key points of influence—in order to appropriately allocate marketing spend.
Furthermore, marketers must be aware of where customers are in their customer journey outside of
understanding all of those points of influence. First time visitors to a web site may be responding to
different campaigns through different channels. A first time buyer may respond differently and perhaps
have an affinity for certain products or content on the site compared to a repeat buyer. Each of these
‘milestones’ are an important point to help map the customer journey for your web site. Each retailer may
have different characteristics as to what should define a milestone: visits, purchases, product reviews,
or perhaps social media.
Figure 11. In this Coremetrics Lifecycle report example, milestones are mapped based on shopper
frequency. Of the 399,311 visitors over the last 400 days, 239,132 were unique visitors while
8,855 were 3x buyers. Furthermore, 9,995 visitors migrated from 1x buyers to 2x buyers.
Copyright ©2011 Coremetrics, an IBM Company. All Rights Reserved. SPECIAL REPORT 12

15. IBM Coremetrics 4th Annual Online Retail Holiday Readiness Report
Even though online shopping may differ over the holiday season as gift shopping is more common
than personal shopping, these life cycle analytics provide new opportunities for marketers to retarget
customers and build loyalty.
The IBM® Coremetrics® Explore and new Coremetrics Lifecycle solutions offer the tools marketers need to
prepare for the holiday 2011 season and beyond. Some techniques include:
• Track customer behavior over time. Versus a campaign-centric or page-view centric
analysis, beginning to understand individual customer behavior over time will help to develop
the broader context and story for how customers engage with your brand. IBM® Coremetrics®
LIVE (Lifetime Individual Visitor Experience) Profile™ tracks customers and prospects as they
interact with your business online, across multiple ad networks or via email, video, affiliate sites,
social media and more, providing a single comprehensive view of each visitor’s behavior over
time and across channels.
• Define your customer journey. With the customer behavior information in hand, look at
what segments or milestones define your customer journey or what your goal is for how you
want customers to interact and engage with your brand. With the right solution, you may even
be able to look at segments from last year’s online holiday shopping season to see if certain
behaviors, patterns or segments stand out that should be tracked this year.
Figure 12. Within Coremetrics Lifecycle, standard out-of-the box reports provide pre-made
milestones or you can create your own customized milestones. In this figure,
milestones have been mapped based on a more high-level customer journey starting
from customer awareness evolving to customer advocacy.
Copyright ©2011 Coremetrics, an IBM Company. All Rights Reserved. SPECIAL REPORT 13

16. IBM Coremetrics 4th Annual Online Retail Holiday Readiness Report
• Adjust your marketing efforts based on your customer life cycle. Begin to nurture
your customers based on where they are in the customer life cycle. As the holiday season
approaches, start looking more closely at the content, campaigns and products that are
most heavily influencing their behaviors.
Figure 13. In this example, Coremetrics Lifecycle shows that the marketing channel that most
heavily influenced the 2x buyer segment was an email campaign. Marketers should pay
attention to these analyses to adjust investment appropriately—not only for marketing
campaigns, but for web site content and product recommendations as well.
As the holiday season approaches, begin tracking these types of reports more closely
to make real-time decisions and execute campaigns in response to how customers
are progressing through the milestones.
Copyright ©2011 Coremetrics, an IBM Company. All Rights Reserved. SPECIAL REPORT 14