AUthor & Download:
http://whitepapers.chiefmarketer.com/content41379
Inside:
Leveraging Data to Put Customer Need First
Case Study with QVC.com
Combining Personalization & Optimumization
Case Study Threadless.com
How to Mine Big Data for Insights
How is Real-Time Analytics Different from Traditional OLAP?
How to Identify Your Most Valuable Customers & Keep Them Coming Back
2. Table of Contents
2. Introduction
3. Understanding the mechanisms
that drive predictive analytics
4. Leverage data to put customers’ needs first
5. Case Sudy: QVC.com
6. Validating impactful customer segments
7. Connect customer insight with real-time marketing action
9. Automate post hoc segmentation for every experience
10. Applying the mechanisms to
personalization and optimization efforts
10. Customizable segment inclusion based on business needs
11. Challenges associated with mining for insights
12. Content evaluation by customer segments
across multiple success events
13. Case Study: Threadless.com
14. Focus on customer segments and their impact across experiences
15. Case Study: Clothing retailer uses predictive
analytics to extend testing practices
15. Conclusion
16. About the author
16. About Web Analytics Demystified
17. About Monetate
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3. Introduction
When the customer wins, the marketer wins. This statement reflects how
organizations should approach their marketing efforts to succeed in these
highly competitive times. Organizations that put the customer first and
focus on the relationship, rather than the transaction, see their customers
respond positively, driving loyalty, retention, and additional business.
But it’s often challenging for marketers to understand how to identify their
most valuable customers, let alone have the ability to interact with them
and influence their behaviors. Couple this with a challenge to communicate
the value that delivering personalized experiences through segmentation
discovery and targeting has on the bottom line of the business, it becomes
clear why many organizations have yet to adopt initiatives that allow them
to put the customer first and at the center of their marketing efforts.
Marketers can use data effectively to understand where they should focus
their attention and resources. There are many paths that marketers and
business teams can go down. In this paper, sponsored by Monetate, we
describe strategies for organizations to identify key customers and create
winning relationships.
“Discovering New Opportunities in Marketing” highlights organizations
that are discovering new opportunities in marketing based on confirmation
of their hypotheses, learning more about their customers, and taking
further action. By seeing the value in the time and effort mining for
insights and, subsequently, taking action on them, these organizations
are focusing on the customer relationship and putting their customers at
the center of their business.
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4. Understanding the mechanisms that drive predictive analytics
The mechanisms that drive predictive analytics can be quite complicated.
Marketers have many challenges identifying where to look for insights,
and the first is often just getting started.
The answers lie within customer segments. A segment of customers is
simply a subset of the visitor population that consumes an organization’s
digital content. These segments have shared attributes—both known
and unknown—that allow organizations to derive insights and provide
the experiences consumers want. The insights help indicate where
organizations should focus and spend their additional marketing efforts.
Depending on how a company is organized and what data is being used,
getting insights from customer segments can be a challenge. While the
website’s analytics tool can be of some help, it often does not include all
the data sets available to get a complete picture.
On the right is a report showing where key visitors segments have a
positive impact on a website’s conversion rate. The general population has
a mean conversion rate of 2.71%, while the key customer segments have
significantly higher conversion rates.
Reports like these allow organizations and marketers to narrow their
focus on where to begin. Organizations are speaking directly with their
customers through this data and are using this information to predict key
customer segments.
Monetate LivePredict’s reporting interface shows where key
customer segments have been identified as having a positive
impact on the conversion rate of the digital property.
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5. Leverage data to put customers’ needs first
The definition of big data is often debated and comes with many different
interpretations. Organizations often assume big data simply refers to
gargantuan amounts of information so massive and unwieldy that it
essentially stifles a marketer’s ability to use it effectively.
But there’s another way think about data—one that empowers marketers
to use it as an asset. In a recent Forbes article, big data is interpreted
as collection of information from traditional and digital sources inside
and outside your company that represents a source for ongoing
discovery and analysis.
Looking at big data from this perspective allows marketers to envision
themselves using it to put their customers first. There are many data
sources that fall under this interpretation, including:
• Website analytics
• Email campaign results
• Data collected from test participation
• Mobile data
• Third-party data
• Display ad data
• CRM data
In these data sets, customers show where and when their needs are being
met and where they are not. Conversion rates, bounce rates, time on site,
interaction with content rates, revenue data, and page consumption are all
signals of what visitors want when they visit a website.
Smart marketers evaluate these data sets to get a better understanding of
what their visitors want. When they take action based on this data, they
put the customer first—and when the customer wins, the marketer wins.
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6. QVC.COM:
Extracting customer insight with data
At QVC.com, Steve Loving, senior project manager, works with the
consumer insights and business intelligence teams where he focuses on
quantitative insights. His responsibilities include managing and running all
of the experiments that take place on QVC.com.
Loving leverages marketing solutions, including Monetate LivePredict,
primarily to extract insights—both broad and deep—on digital consumers.
QVC.com uses basic analytics and then adds more than a dozen additional
data sets for advanced segmentation, running analysis at the member
level for insights into specific actions customers take as a result of highly
targeted tests.
“This effort allows QVC to make a much more efficient use of optimization,”
says Loving. “There has been a lot of quantitative data showing that
weekends are different from weekdays, and the same can be said for time
of day. We have been able to exploit these differences and speak better
to our customers.
“Segmentation is the most powerful tool that one can have in an optimization
toolset. Segmentation by way of data collection has allowed QVC to
be more strategic in our testing initiatives as we move to explore known
segments better and focus attention and resources on broader segments
as directed by the data. For example, strategies have been developed where
we present different creative for customers versus prospects.”
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7. Validating impactful customer segments
Key customer segments can be identified based on data collected from
their performance on conversions and other important success events.
Once the data is collected and organized, specific processes need to
be established to validate the impact that these customers are making,
including developing iterative campaigns directed at these customers.
For example, if visitors from a certain geographic location convert at
a higher rate than those at another location, processes should include
examining the visitor experience and then coming up with hypotheses as
to why these visitors convert at a higher rate. These hypotheses should be
turned into ideas of what other content—or what other experiences—can
be presented to these visitors.
The result of such processes has the potential to further validate the
findings and could lead to even higher conversion rates. These processes
also should include hypotheses as to why other geographic regions are
underperforming, also leading to the creation of alternative experiences
that could increase the conversion rates of underperforming segments.
5 Processes to Help Validate Impact
1. Identify trends of customer segments from any and all data
sets available.
2. Validate these trends across data sets (i.e., if Mac users convert
higher on a website than PC users, correlate how Mac users respond
to email or display campaigns).
3. Outline several hypotheses as to why key segments respond
positively or negatively to digital experiences.
4. Turn those hypotheses into ideas, identifying the potential for
alternative experiences or content to change the behavior. The latest
technologies streamline this process by automatically correlating the
performance of a segment with the campaigns or experiences seen.
5. Speak directly to these segments and focus on the relationship
rather than the transaction.
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8. Connect customer insight with
real-time marketing action
As visitors identify themselves based on their impact on key performance
indicators (KPIs), marketers can use this information to create hypotheses
and ideas about why these visitors react one way to a digital experience
while another group of visitors reacts differently.
This report highlights a common scenario: Different customer segments—
for instance, geographic regions—respond quite differently than the mean
when it comes to many KPIs. For instance, visitors in the South might
spend, on average, more than visitors in the mid-west. By looking at this
data, you can derive many opportunities to take action on, including:
• Language used in marketing material/content
• Proximity to physical stores (including
those of competitors) where goods might
be more or less readily available
• Localized popularity
• Urban versus rural
• Weather in those areas
There might be an opportunity to present or target what could be
more appropriate messaging to different regions of the country. This is
reminiscent of the whole “soda vs. pop” nomenclature debate, or even
different words that have similar meanings, i.e., sales tax or VAT, which
can cause customers to not make a purchase because they don’t think the
website wants, or is able, to do business with them.
Another way for marketers to understand geographic differences would
be to examine exactly what consumers in certain regions purchase. For
instance, customers in warmer climates will purchase different products
than those people battling cold weather and snowstorms at the same time.
Scenarios like these occur frequently in the physical retail space. Visitors
likely will not be purchasing outdoor furniture or similar items in the
dead of winter in the Northeast. If what is happening helps reframe your
hypothesis, the action to take is a no-brainer. Marketers would then target
or promote appropriate items based on what data—and a little bit of
common sense—tells them.
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9. Monetate LivePredict reveals where key segments
of the general population and their impact on Average Order Value.
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10. Automate post hoc segmentation
for every experience
For organizations that are new to predictive analytics or even website
optimization, it’s imperative that processes be established to include key
segments for analysis in all experiences, including tests. These processes
will add time and a potential need for additional resources if your goal is to
drive revenue and move the business forward.
Organizations can start off simply down this path, and in little time see
the fruits of their labor. Opportunities will quickly present themselves as
customer segments reveal themselves through data, including segments
that can provide virtually limitless opportunities to iterate:
• Traffic sources. Identify the top website referrers, including paid
or organic search, affiliate traffic, display, and email traffic.
• Visit stage. First-time and repeat visitors often tell different stories.
• Date and time. Visitors behave differently throughout the day, for
instance at work compared to relaxing at home. Weekends and
weekdays can also tell interesting stories.
• Technographics. Consider different operating systems, browsers, and
devices. Without a doubt, there are nuggets to consider based on
the massive adoption of smartphones and tablets to access the web.
Browsers can also speak through the data, especially if quality assurance
issues arise.
• Geography. Visitors from different regions and countries behave
differently. Look at analytics and identify top-performing and under-performing
locations.
This process also helps to benchmark key segments and their behavior
with the end result being that organizations think of the customer first,
rather than the transaction. This process allows for further discovery
and iteration on key segments. For example, the segment of ‘first-time
visitor’ soon evolves into ‘first-time visitor from paid search’ and then
‘first-time visitor from paid search who visited on the weekend.’ The path
to personalization and optimization is by way of segmenting and iterating
on these segments.
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11. Applying the mechanisms to personalization and optimization efforts
Customizable segment inclusion
based on business needs
There are many customer segments that are applicable across all
organizations regardless of industry. These are often standard segments
included with most analytics or optimization tools. Segments can include
device, visit stage, traffic source, time of day or geography, and could extend
to on-site behaviors such as categories/products viewed or purchased.
Although these segments might seem basic, they are tremendously
valuable. When organizations take a hard look at these standard segments
and how they differ in terms of performance, they are often surprised.
Retailers, for example, often see major differences between weekends and
weekdays. Media organizations are likely see major differences between
different sources of traffic, while financial organizations could see stark
differences in behavior between repeat and new visitors.
Organizations serious about their personalization and optimization efforts
have to take segmentation to a higher level if they truly want to get the
most from their programs. If a robust analytics program is in place, it
will likely be a great source for customer segments that you will want to
standardize for analysis.
There are many places to look internally for these additional segments,
which can vary based on specific industry.
• Financial Organizations: Customer account types (visitors with checking
accounts/visitors with savings accounts, etc.), account balances, time
since last visit, source of traffic (helpful for targeting prospect content
versus branded content).
• Media/Publishing Companies: Content affinities (i.e. repeat sports
section visits on a newspaper website), subscribers who consume more
than a certain number of pages per visit, subscription series.
• B2B: Firmographics, content affinities, source of traffic, demand
generation/funnel status.
• Retail: Content affinities, source of traffic, previous purchase history,
cart abandoners, amount purchased (above or below the mean average
order value), third-party data sets.
Each business is different and has its own unique set of customer segments.
Although not immediately crucial to get more customized segments in
place at the onset, it becomes more important as your organization gets
more strategic and advanced.
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12. Challenges associated with mining for insights
Now it’s time to put the words “when the customer wins, the marketer
wins” into action. In this section, we walk through the challenges
experienced by organizations that do segmentation analysis and then put
forward strategies to make it more effective, laying the groundwork for
putting the customer first and at the center of their business.
Although many organizations test first, smart marketers will create
website experiments only after they obtain at least some insight into their
customers. But testing is not easy, and analyzing the results of tests can
be even tougher.
Testing involves robust processes around execution and analysis. Many
organizations find themselves spending countless time, energy, and money
on tests that only seem to result in flat performance with no significance.
That is, the results at the end of the tests show no detrimental or positive
impact on visitor behavior.
Generally speaking, there are two contributing factors to flat test results.
The first is because the test and control experiences are not different
enough to cause changes in visitor behavior. The other cause relates to
what was described earlier, when different segments respond to different
experiences. When the results are flat—and there’s no positive or negative
impact in the test results—it’s very likely that there are different customer
segments whose performance cancelled each other out.
Tests that show no significant lift occur so often that organizations
need to drill deeper to discover sub-segments for which significant lift
did occur. Don’t just look at the test overall, but focus on how different
sub-segments performed within the experiment. Some solutions make
these sub-segments available for manual analysis, while other products
automate the discovery of these sub-segments and make them available
for experiments within the same solution.
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13. Content evaluation by customer segments
across multiple success events
As mentioned earlier, not all visitors react the same to one message. Time
and again, different segments react differently to website experiences,
potentially impacting success events across all of an organization’s digital
properties, including email (opt-outs) and social media (sharing negative
experiences with others).
If you consider all that is possible on the website, it becomes clear that the
area of focus for an organization should not always be a primary conversion
event such as making a purchase. Organizations have to shift their focus
away from just looking at primary success events if they are going to learn
from their customers and how they consume their messages and content.
Organizations that apply this layered approach to their analyses see this
occur all the time. For example, on a lead generation website, paid search
traffic could have higher conversion rates for filling out a web form, while
first-time visitors or organic traffic result in a lower rate of form completes,
and visitors on smartphones have a lower average page view rate. All of
this analysis is incredibly important as marketers develop hypotheses to
what the ideal experience is for each segment of traffic.
Reports that help organizations understand how the many segments of
traffic could impact the multiple success events on the website provide
ideas on how to change the segments experience for the better. These
reports are some of the best idea-makers available.
Monetate LivePredict shows how a marketer can manipulate the
different digital success events and get visibility as to how key
customer segments responded to those success events.
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14. Threadless.com: Using segmentation
strategies to drive content decisions
Threadless is a community-based company that prints graphic designs
created and chosen by a very passionate and talented group of artists.
Visitors to Threadless.com vote on thousands of monthly submissions.
Winners receive cash rewards and Threadless gift cards, and have their
work printed on clothing and other products sold on the website and in
physical retail stores.
Todd Lido, head of marketing at Threadless, has his hands full encouraging
participation, creating opportunity for artists, and selling products.
Threadless.com’s segmentation strategy helps the company gain insight
into where to focus its marketing efforts. For example, the company was
able to confirm that people who viewed kids’ products converted at a
much higher rate than visitors who did not view those products.
Threadless also rolled out new functionality called “Threadpics” where
users can supply their own pictures with Twitter hashtags. Threadless was
able to derive that visitors who engaged with this content on the website
had a 4x higher conversion rate than other visitors.
Based on findings like these, Lido and his Threadless team know where to
focus their efforts not only online, but for off-site marketing efforts such
as display advertising. They are being “informed as to what the customer
wants, and it is influencing what they do next,” he says.
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15. Focus on customer segments and
their impact across experiences
The quickest way for an organization to shift from generalized testing
of all audiences to targeted testing of valuable customer segments is to
establish sound segmentation strategies. That said, there is an inherent
challenge here. Although segmentation reports within a particular test
are valuable, the insights are limited to that particular experiment. For
organizations to better learn about their segments of traffic, they need to
understand how these segments respond to all experiences delivered on
the website, regardless of whether they are tests or not.
There are many ways to approach this challenge, which can include highly
detailed record keeping and consolidation of segments after each test
or campaign. But no matter the approach, it’s certainly worth the time
and effort. Organizations are able to get a better understanding of their
customers, allowing them to fine tune their hypotheses around segments,
which enables better idea creation around what alternative experiences
might lead to differences in behavior.
Additionally, this mechanism of analyzing customer segments around
all tests or campaigns enables organizations to iterate on their customer
segments. For example, the image to the right shows the segment ‘South
Central’ and its impact on recent tests and campaigns. This report also
breaks down that segment into sub-segments. Note that the city of
‘Findlay’ is an outlier within the greater segment of ‘West South Central.’
This deeper analysis allows organizations to get a better understanding of
the visitors that make up these segments.
As seen in Monetate LivePredict, marketers are presented with
an analysis of a segment, in this case ‘West South Central,’ and its
impact across all experiments. In this example, ‘West South Central’
performed well in three campaigns and positively in three other
campaigns, including ‘Referring Traffic from mysavings.com.’
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16. Clothing retailer uses predictive
analytics to extend testing practices
A well-known niche clothing retailer incorporates predictive analytics into
its optimization initiatives to extend the capabilities of its testing solution.
This effort also validated some key overarching themes that the retailer
thought existed, but didn’t have the supporting data. For example, the
company always suspected that when a particular clothing style was
selected or purchased by males that females had similar preferences. The
retailer now uses this knowledge to direct important marketing initiatives
that would have otherwise not been a priority.
Another key learning that the retailer has seen since adopting a data-driven
segmentation program is discovering that its best-performing segment
is married working couples. Although it long believed that this was true,
confirmation through data had a powerful impact on how they managed
their personalization and optimization programs.
And not only did this organization find and confirm key segments, but it
also identified those segments that were underperforming such as mobile
traffic and visitors from specific states.
Conclusion
Organizations that spend time and resources putting the customer
first, and deriving what’s important to them based on all data available,
are discovering new opportunities to use predictive analytics that drive
personalization and optimization. They learn what their visitors want—
and what they don’t want—and then take action, speaking directly
to their customers.
This is not an easy process by any means, but success is possible given the
tools available on the market today. Once in place, processes need to be
flexible, allowing for iteration and constant learning about visitors as the
digital landscape changes incredibly fast.
Organizations can get started today with relative ease using their current
optimization solutions. Begin simply with a few general segments to
include such as traffic source, operating system, or geography. Don’t
overload yourself, which could lead to analysis paralysis. Be assured
that you soon will be able to find new nuggets of gold that will enhance
your personalization and optimization strategy, adding further value to
your organization by automatically identifying the attributes of over- and
under-performing segments, and helping you prioritize the opportunity
each one represents.
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17. About the Author
Brian Hawkins, partner at Web Analytics
Demystified, has worked in the optimization
space since 2006 when he started at
Offermatica, which is now Adobe Target. He
worked in a variety of roles over the years in
the testing and optimization space in both a
technical and strategic consultative capacity, and has helped scores of
companies get value out of their testing platforms by laying the groundwork
for the incorporation of strategic best practices and by providing roadmaps
that allow organizations to adopt a culture of optimization.
About Web Analytics Demystified
Web Analytics Demystified, founded in 2007 by internationally known
author and former Jupiter Research analyst, Eric T. Peterson, provides
objective strategic guidance to companies striving to realize the full
potential of their investment in web analytics and optimization. By bridging
the gap between measurement/optimization technology and business
strategy, Web Analytics Demystified has provided guidance to hundreds
of companies around the world, including many of the best known retailers,
financial services institutions and media properties on the Internet.
For more information on Brian Hawkins and Web Analytics Demystified,
please visit www.webanalyticsdemystified.com, email brian.hawkins@
webanalyticsdemystified.com, or call (415) 735-4295.
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18. About Monetate
Monetate generates billions of dollars of new revenue for businesses,
helping them grow 33% faster than the industry average. Brands such as
Best Buy, National Geographic, and Celebrity Cruises rely on Monetate to
put the customer first, creating winning customer experiences that drive a
sustained, competitive advantage.
The Monetate Acceleration Cloud connects two crucial elements that have
always been treated separately within organizations: knowledge about the
customer and marketing actions to deliver a better experience. Delight
your customers with winning customer experiences that build authentic
relationships and drive new revenue across any channel, all within one
seamless solution.
• Interact with your customers through winning website experiences that
take place in the moment and across every page.
• Engage your customers with relevant emails that are personalized at the
time recipients actually open them.
• Reach and attract the customers you love, and convert lost visitors, with
intelligent display and retargeting campaigns.
Start your journey to a winning customer experience. Request a demo
today at http://monetate.com/demo or contact us at 877-MONETATE
(US and Americas) and +44 207 099 2101 (EMEA).
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