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Transcript of LeveragingWebAnalytics_TechnologyLeaders
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technologyleaders
LeveragingWebAnalytics:
H o w to c la r ify yo ur g o a ls,
b uild w inning me tr ic s a nd
measure your way to success
B y A n d r e w E d w a r d s
featuring e5o:
The 5 Necessary
Steps to WebOptimization
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technologyleaders
Leveraging Web Analytics 1
Table of Contents
Executive Summary
A Quick Take on Web Analytics and its Promise. . . . . . . . . . . . . . . . . . . 2
Chapter 1:Knock Knock. Whos There?Understanding Our Prospects and Turning Them into Customers . . . . . . . . 4
Chapter 2:
Its not Web Analyticsits Web ROI
. . .and How That Changes Everything . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
Chapter 3:We Cant Have Any Pudding if We Havent Eaten Our Meat
The Five Necessary Steps to Web Optimization (e5o). . . . . . . . . . . . . . . . . 11
Chapter 4:Get em and Keep em
Reaching, Engaging, Converting and Retaining Customers. . . . . . . . . . . . 21
Chapter 5:
Conclusive EvidenceThe "How Do I make This Happen?" Part . . . . . . . . . . . . . . . . . . . . . . . . . 35
About Technology Leaders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
About the Author
Andrew Edwards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
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Leveraging Web Analytics 2
Executive Summary
A Quick Take on Web Analytics and its Promise
As the web marketplace has matured, the need to derive tangible business
benefits from the web has become an obvious challenge. In response to
this, many of us have recognized the importance of web analytics in mea-
suring and achieving ROIbut few of us are reaping enough benefit from
web analytics technology.
And just as the need to receive a measurable return from our web sites has
increased, so has the simple recognition that, for most of us, there is no
repeatable method by which to make this happen. For many of us, there-
fore, the web site is a cost center, when it is supposed to be just the oppo-
site: a profit center or a measurable productivity enhancer.
It is no longer enough to cite the traditional disconnects between mar-
keting and technology. The time has come to identify a straightforward
best-practice for acheiving web optimization and web ROI.
A number of very powerful and very configurable web analytics tools
and offerings are on the market today. Yet the tool often is configured
incorrectly, or allowed to run in default mode. Worse, there is often no spe-
cific plan of action to adequately measure the right things, and then to do
something about fixing the problems discovered through measurement.
Therefore, measurement doesnt really spring to life.
By performing two parallel actions, companies can begin to make headway
in this important area:
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Leveraging Web Analytics 3
First, to recognize that there is a necessary class of professionals that must
be dedicated to the cross-disciplinary (marketing/technology) task of
achieving web ROI with web analytics tools.
Second, that those professionals require a repeatable, practical methodby
which to operate. This method can briefly be described as a series of five
steps* including:
1- Define Drivers (figure out what the on-line goals are)
2- Build Metrics (decide what to measure, and with what tool)
3- Plan Actions (decide what to do after reviewing metrics)
4- Create Changes (execute the actions that were planned)
5- Measure Success (measure again; see if goals were achieved)
Only by implementing the five steps above, and by making it a part of
every key web-based project, can an organization reasonably assure itself
that it has performed measurable, repeatable web optimization.
Quick Takeaway:
Web analytics software can only be leveraged for success by dedicating
specialized talent and expertise to the task; and by utilizing that talent
within a repeatable web-optimization process.
The above represents a high-level review of the value of web analytics.
Well go much deeper into the process of putting web analytics to work in
the following chapters-please read on.
*eBusiness 5-step Optimization (e5o)
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Leveraging Web Analytics 4
Chapter 1
Knock Knock. Whos There?Understanding our Prospects and Turning Them into Customers
Name a business transaction of any kindin banking, in manufacturing,
even the simple organization of a meeting. Likely, therell be critical, mea-
surable information that will serve to coordinate efforts and to determine
the success of the effort itself.
Now consider something that would be truly shocking: what if our bank
had no way of telling us the value of our investments? Wed look at our
account statement and the only things it would tell us would be, Well, it
looks like you have some money in savings; also, you wrote more checks
last month than the month before. And apparently you made some
deposits. How quickly would we switch banks?
Now lets think about our web site.
Why do we have one?
Is it one overriding reason? Or several reasons of somewhat equal
importance?
Ultimately, everyone wants something out of their web site. Like more
money. Or, maybe the ability to save money.
That may sound very, very obvious. But the next part isnt. If the site is
important to us, we need to know how successful it is at doing what we
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Leveraging Web Analytics 5
want. And not just sort of generally, like the bad bank we just mentioned.
We need to know much more exactly. Because if we dont know exactly
whats going on with it, we cant know how to improve it.
What makes this even more intriguing is that, of all the business channelsat our disposal, there is only one that can unobtrusively yield constant,
accurate, living data about our customers or other users.
Heres news: its the web site.
If this is true, it then seems to makes little business sense not to measure
accurately and effectively. To accomplish
this, well need to leverage a certain set of
tools and disciplines commonly known as
web analytics. Well want to implement
some of the very capable tools on the
market in order to get an accurate mea-
sure of what is really going on with our
web sitejust the way we would want to
track any other investment we had made.
The Elements are in Place
Today, we find ourselves with a wide
choice in web analytics vendorpack-ages. Many of these packages are capable of delivering highly sophisticat-
ed information about user activity.
And, as we will demonstrate, we can also implement a real-world method-
ology for putting this class ofmeasurement tools to work.
It is possible today to combine these elements and achieve an important
goal: that of finely-tuning our web site so that it functions as a unique and
powerful business tool. In this light, notputting our site to work is like
having a titanium, thirty-speed bicycle sitting in the garagewhile were
squeaking around the neighborhood on a tricycle.
Notputting our site to
work is like having atitanium, thirty-
speed bicycle sitting
in the garagewhile
were squeaking
around the neighbor-
hood on a tricycle.
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Leveraging Web Analytics 6
The logic sounds fairly straightforward. We have a way to better under-
stand our customers behavior: the web, properly measured and observed.
We know too that if we understand how customers are interacting with our
site, we can make improvements directly to the site and come closer to
getting customers to do what we want on the web.
It all seems so obvious and so simple.
So, why isnt web analytics being leveraged successfully more often?
Let us take a look at some of the challenges.
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Chapter 2Its not Web Analyticsits Web ROI. . .and How That Changes Everything
There is no small amount of science in getting a web site to yield useful
business data. First, there are tremendous amounts of raw informationgenerated by web usage (such as log files and cookie data). Then, there are
dozens of kinds of sophisticated products that take this raw data
and turn it into "reports" of many different kinds. Finally, there are the
reports themselves, and they tend to look like lots of other technical
reportsbar charts, pie charts, charts and charts and more charts.
It tends to be very geeky sort of stuff.
It is the sort of stuff that the people who are responsible for running a
businessthe senior executives in the business lines as well as the salesand the marketing executivestend to gaze at for a few moments and then
place in a corner of their desk and wait for it to be covered up by some-
thing more important.
Let us propose that the reason for this is that, typically, a hundred or more
pages of charts and graphs do not help a busy executive make any deci-
sions. Believe it or not, theres actually stuffmissing from these reports.
Theres no news. Theres no story. Nothing to be proactive about.
So weve got this firehose of information coming out of the web site. And
people are kind of running away from it. They seem like they are uncom-
fortable with it. Its techy, its geeky, and anyway they dont know what to
do after theyve seen it.
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The Web Development Metaphor
Theres a useful analogy to be made here about technology and results.
Lets say we knew we needed to reach a certain audience, and we knew wecould reach them with a targeted site. All the market research is done,
all the merchandising is done, everything is in place. Except for the dev-
elopment". The technical part.
And lets say that a certain marketing executive decided that the site
wasnt going to go livebecause neither he/she nor anyone on his/her staff
knew how to use web developmenttoolkits.
Theres a reason why this will never happen. That reason is, because the
entire set of skills referred to as web development has been built
around leveraging complex and configurable software tools to produce
required results (eg. websites).
But something like this mighthappen if the following were true:
That there was no class of professionals who even knew how to skillfully
use the software, in order to create the proper digital files for launch. In
other words, no web developers.
This, unfortunately, is the dynamic that inhibits the use of web analytics.
Think of web analytics software/services as the equivalent ofweb development
toolkits. Think of the process of web optimization as web development.
Whats lacking in most companies is:
A cross-disciplinaryclass of professionals who are able to use
web analytics software in acarefully defined process to create
valuable results.
In the case of web analytics, the results are not beautifulweb sites. The result
is a web site that is optimized for maximum ROI.
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Leveraging Web Analytics 8
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Leveraging Web Analytics 9
The Goal is Web ROI
Now that weve discussed some of the barriers, it is relatively easy to see
why the tools arent really being used to maximum advantage.
And heres how we can begin to fix the problem.
The first part comes from fixing how we think about it.
Just as we dont think of catalog creation, print-
ing and distribution as a collection of technolo-
gies (even though it employs them) and exper-
tise (even though expertise is required), we
shouldnt make the same mistake with this thing
we are calling web analytics.
Simply put, let us therefore stop talking about
web analytics. Lets start talking about web
ROI. Because thats what this is all about.
The implications of this are profound.
It means that the whole endeavor is on a new footing. We are no longer
concerned with getting data and deploying software. We are interested inachieving results. Measurable, repeatable results. Like more customers
converted. Like more sales. Like more users directed to information more
quickly.Like more dollars dropping to the bottom line as a measurable
result of our efforts on the web.
If these sound like marketing goals or like business goals, its because they
are. If anyone tries to tell us there is some other goal to be served by web
analytics, we must tell them to go away. Quickly. They are wasting our time.
So weve identified that this is about marketing. And weve identified that
there are missing pieces.
Lets stop talking
about web
analytics.
Instead, letsstart talking
about web ROI.
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Leveraging Web Analytics 10
We talked about a class of professionals as one of the (mostly) missing
pieces. But we also talked about a carefully defined process. Lets take a
look at the parts of that processthe parts that will help us in achieving
better, measurable web ROI.
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Leveraging Web Analytics 11
Chapter 3
We Cant Have Any Pudding if We Havent Eaten our Meat:
Five Necessary Steps to Web Optimization (e5o)
In the previous chapter, we began by saying there was no small amount ofscience in web analytics. However, in obtaining results with web analytics
software, there is probably more art than there is science.
Once weve understood that our goal is driven by marketing concerns, we
immediately begin to apprehend one fairly obvious fact: that there is no
software for our on-line marketing that allows us to press the make-it-bet-
ter button and then see wonderful results come tumbling out.
Except for a very small number of cases, obtaining results will require two
irreducible elements: a process of best practices; and skilled web analyt-
ics people in order to make the process yield results.
Many companies fail to optimize their web marketing efforts because they
lack one, or very often both, of these two critical components.
This is neither to say that there arent very capable people in the marketing
department; nor that there arent capable people in the IT world as well.
There are, and they know exactly what they are doing.
The problem is that measuring and optimizing web sites is a new thing for
almost everyone. And the set of skills it calls upon bridge different depart-
ments within an organization.
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Leveraging Web Analytics 12
The class of professionals that specialize in this is only just now beginning
to emerge: web optimization professionals. These folks may already be
found within the organization. Or they may be represented by a new breed
of service companies that are hybrids of marketing, technology and profes-
sional servicesand that work to bridge the gaps between marketing and ITand the software itself.
This type of professional will focus on using web analytics tools as the
most likely way of achieving measurable e-business ROI.
To do this, they, or organizations that want to do this themselves, will have
to engage in some very particular behavior.
They will have to work themselves through five separate and very impor-
tant steps. Each step is so important that we feel comfortable in calling the
process "e5o" (eBusiness 5-step Optimization) and making the following
statement:
If a company has notfollowed each of the e5o steps, they have demon-
strably not performed web optimization.
e5o: Five Steps That Must Be Followed
Here are the steps. Well go into detail a little further along.
1- Define Drivers (figure out what the on-line goals are)
2- Build Metrics (decide what to measure, and with what tool)
3- Plan Actions (decide what to do after reviewing metrics)
4- Create Changes (execute the actions that were planned)
5- Measure Success (measure again; see if goals were achieved)
Lets talk about how each of these steps can work in a real world situation.
1-Define Drivers
This part of the process is essentially a strategy and a discovery exercise. It
will call upon people who have both very high-level requirements as well
as more targeted, specific requirements of the site.
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Leveraging Web Analytics 13
Let us imagine a company that is holding a high-level web strategy meet-
ing, and that one of the attendees is a senior executive in the company.
This business-line executive might say I need to get more leads out of the
site.
After all the marketing discussions are over, and the muffins and jam have
been cleared from the executive meet-
ing room, one thing emerges: lead gen-
eration is probably the main reason the
site exists.
That company has just begun defining
its drivers.
Of course, there are tactics that derive
from this. Well want, for instance, to develop a rich, nuanced understand-
ing of the sites drivers in order to develop the best way to reach prospects;
the best way to convert prospects to customers; and the best way to retain the
customer after sale. Well get to those in a chapter to follow. But lets keep
going down the list.
2-Build Metrics
Heres where were able to really take advantage of the built-in tracking
abilities of the web, as an advantage over traditional, off-line marketingintelligence techniques. Its in this phase where we employ some very par-
ticular tools that do a great deal of sophisticated parsing and reporting on
the activity that takes place on the site.
There are a number of capable tools on the market. They come from com-
panies like Omniture, WebTrends ,Google, and CoreMetrics and
are commonly known as web analytics tools". Many of us are already
familiar with one or more of these toolkits.
The level of complexity found in web analytics tools can vary greatly.
However, all are designed to deliver reports based on site activity record-
ed by our web servers.
After all the marketing
meetings are over, one
thing emerges:
that getting leads is
probably the main
reason the site exists.
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Leveraging Web Analytics 14
The most common mistake in using web analytics is in thinking that sim-
ply having a canned (standard) report is tantamount to having done
web analytics. Worse, many may believe that web analytics toolkits will
deliver useful results after it is implemented and allowed to run in default
mode.
The fact is, allowing web analytics tools to run out of the box (e.g.
without making it answer any business questions), is a profound mistake.
It renders the software as near useless as it can get.
Important point: there is nothing wrong with the tool. There is only a
problem in how it is being used.
To demonstrate how common this problem is, consider the following question:
How often have reports arrived on peoples desks andas we indicated
abovethey just sort of sit there?
Our guess is, pretty often. And it isnt because people are too dumb to
understand the report. Its because the report isnt reporting anything worth
reporting. Page views? Hits? Total visitors? How does knowing that make
money for us?
Even for a well-versed web analytics expert, the basics mentioned abovehave little insight to offer these days.
These days, we are concerned with much finer views into customer
behavior.
For instance:
What activities define a valuable prospect?
Lets look at (e.g. use web analytics tools to measure) the people who
came to our site and accomplished what we wanted them to accomplish.
People who we converted from prospects to customers. What did they
commonly do before they got to the successful conversion?
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Leveraging Web Analytics 15
If we knew that, we would be able to predict, via observable behavior, a
valuable prospect: someone who was acting like they were about to do
something valuable (buy something, contact us, download our demo).
We might then have a couple of options.
We could tailor their experience based on their perceived valuea
special offer?
Or, what if lots of them got nearly through the process we wanted them to
followand then left consistently on a certain page? We might be able to
review that loser page and fix it.
In order to gain this insight, we have to configure our web analytics
to measure it.
In the above example, we will want to carefully construct campaign defini-
tions based upon the combination of an entry page and its referrer; gather
related pages into content groups; focus path analysis on critical pages
within the site; and create custom reports aligned with our business objec-
tives. Depending upon the site and our goals, pre- or post-processing may
be required to deliver the needed information.
Also, we will want to have established a persistent cookie protocol (which
helps identify a return visitor) in order to separate particular groups of
users from the general run of traffic. Of course, we will also want to have
used some of the filters available within the software to keep from measur-
ing such things as intra-company traffic, web-spiders and the like.
There are many other ways to leverage the tools. In our review, weve
only included one example.
Weve now completed two of the five steps in the process: we figured out
what we wanted people to do. And weve measured how close theyre get-
ting to doing it.
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Leveraging Web Analytics 16
The next part takes us out of the realm oftoolkits and into the what do
we do now? part of the process.
3-Plan Actions
Weve already configured the toolkit and have gotten reports back. Nowwell dig deeper into the statistics to analyze the data, perform some mean-
ingful calculations and make recom-
mendations.
This is the part where toolkit alone cant
take us. Only a certain level of knowl-
edge about both marketing goals and
technology will get us through this
part.
Its the part where, even when theres
a richly detailed report lying around,
nothing else happens.
One of the barriers here is that, often enough, companies have a communi-
cations problem between the issuers of the report and the recipients of the
report. Typically, the issuers are in the IT departmentbecause they knew
something about how to configure the tool to deliver the report. But the
recipients are oftenor should bein the marketing department or thebusiness-lines.
Simply put, the frame of reference used by a capable IT person is different
(not to say nearly unrecognizable) to a capable marketing or line-of-busi-
ness person. Both are critical to the organization. But if the report arrives
on the desk of the marketing person, but it is designed to address the rather
technical frame of reference of an IT professional, the report is virtually
useless.
Unfortunately, the reports are not going to somehow turn into a form of
advice. Someone inside or outside the organization has to do this.
The frame of reference
used by IT professionals
is different from that
used by marketers.
Therefore, marketershave to learn the lan-
guage of web analytics.
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Leveraging Web Analytics 17
Marketers and other business professionals, specifically, have to learn the
language of web analytics reports to drive their own action plans.
It might take time; it might be annoying. But there is almost no way
around it.
Of course, there is one way around it. There are companies that specialize
in taking an organization through some or all five of these steps and as part
of that, are prepared to turn the report into useful action plans.
Whichever way is right for the organization, the same activity has to take
place:
Look at the data. Interpret the data. Target problem areas with
decisive action.
We may notice, for instance, that a goodly percentage of our best
prospectsthe ones that, way back in define drivers, we wanted to con-
tact usare getting pretty far through the process of actually contacting
us.
But they are stopping short.
Where? Well, we might observe that theres a page on which we ask usersa list of questions. And lots of folks are not getting past it. Too many ques-
tions? Maybe. The wrong questions? Perhaps.
Another example: we notice lots of users dropping off on a key conver-
sion page. And well take a look at that page and see theres an offer
being made, and a contact us button. But the offer is perhaps not that
clear. And the button is not that visible. The physical space between the
offer and the contact button iswell, lets just say you cant see them both
at the same time.
Clearly, we should invest some time and effort into identifying some new
ways of presenting that page and its contents.
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Leveraging Web Analytics 18
Were now creating actions plans.
At this point, weve clearly stated what we really wanted users to do. And
we configured our analytics tool to know where to look for trouble. We
think weve found the problem. And weve made some plans to fix it.
Of course, we wont really know ifweve fixed it until later, when we
measure again. But well get to that.
The next thing that happens is, someone has to actually make the changes.
4-Create Changes
This part, of all the steps in the process, is the most obvious and easy to
understandbut is also the one that can cause the most headaches.
There are many ways to get changes done. Most organizations know who
will be making the changes before they begin the process at all.
But the nature of the changes is rather important, and it dictates some
guidelines in choosing who should be making the changes and how they
should be managed.
The changes might be on the content side (for instance, a different offer),
the design side (a page thats easier to understand), a technology side (thepage needs to load quicker), or an information architecture side (the
important page needs to be easier to find). Most organizations will know
where to find the capable folks to do this kind of work.
It is important, however, to be economical in the types of changes that
need to be made. The effective changes might be very simple. They might
take an hour. Of course, they might take much longer. But they might just
take an hour.
The implication is:
Be careful that the group involved in recommending changes has noth-
ing to gain by making lots of them.
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Leveraging Web Analytics 19
Now weve defined our drivers, configured our toolkit to measure rele-
vant activity, identified and planned to fix a problem, and executed the
action plan. How do we know it was worth the effort? Soon, well know.
Well know because we will measure whether it was worth the effort.
Now we have to go back to our web analyticsplatform and put it to work
once again.
5-Measure Success
Using the same criteria that we used to discover a potential problem area,
we now run fresh reports. That means: the same criteria, over the same
elapsed period of time. We may need to re-instrument the pages now that
they have changed. But the measurement criteria must stay the same, or
the measurement will be rendered statistically meaningless.
If things have worked out well, well see a jump in the percentage of
prospects that were converted to customers. In our hypothetical case, that
means: more of the people we wanted to contact us, are contacting us.
If weve placed a value on each of those contacts, each percentage point
gain can mean significant dollar gains for the organization. Often a gain of
just a few points can mean the difference between the site being a contrib-
utor to the bottom line, and an expense.
Lets assume that were reasonably happy with the result of our exercise.
Weve been able to define what we want from the site. Maybe weve even
given a dollar value to each contact made through the site, enabling us to
understand exactly how much each percentage point gain might mean to
us. Then, weve followed all the steps and ended up with a 3% improve-
ment in contacts made.
Can we do better?
Probably, we can. In that case, we can go ahead and try to plan additional
actions to drive even betterresults.
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Leveraging Web Analytics 20
Repeated rounds of measurement and change will lead to
enhanced results.
Now weve completed a full cycle of web optimization. Weve defined our
objectives; measured activity; planned and executed actions; and proventhe result by measuring our success.
Taking Ownership of Web Optimization
Now that weve improved the site, it might
be comforting to think that weve reached
the finish line and can now end our web
optimization project.
Wrong.
Rather, as contribution to the bottom line becomes necessary; and as the
ability to report accurately about contribution becomes absolutely essen-
tial, leveraged web analytics becomes a way of doing business.
To lead the way in web optimization, we want to go through the above
process early and often. We should always be looking out for ways to
improve the site. Constantly trying to get a better sense of our customer.
Continually aligning our site to respond to the evolving needs of our
clientsand the always-changing competitive environment.
Not as an I did that already exercise. But as a way of continually breath-
ing new life into both the site and the organization.
Simply, by treating the web as the critical marketing tool that it is.
There are more dimensions of web analytics for us to explore. Within
each step there are a number of critical factors that will drive real-world
decisions about the site. The next chapter begins to discuss these in
more detail.
As contribution to
the bottom line
becomes necessary,
web analytics
becomes a way of
doing business.
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Leveraging Web Analytics 21
Chapter 4
Get em and Keep em:Understanding How to Reach, Engage, Convertand Retain Customers
Imagine for a moment the five steps we talked about as a stack of building
blocks, and were looking at them head on. Below, youll see they look like
boxes with their names lined up next to them (figure 1). This shows us a top-
to-bottom progression of things to do in order to achieve optimization.
We are now going to add an
extra dimension to our stack of
building blocks by talking
about how each of the four
items in the title: Reach,Engage, Convert and Retain,
fits within each of the five
steps.
These four items: Reach,
Engage, Convert and Retain,
form a customer-centric con-
version cycle, and proper
understanding of how each
one works will enable us to
maximize our ability to sell to
and retain clients (figure 2).
Define Drivers
Build Metrics
Plan Actions
Create Changes
Measure Success
Figure 1:The Five Necessary Steps
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In other words, we have to perform each of the five optimization steps so
that we can better Reach our prospects, Engage them in interactive rela-
tionships, Convert them to clients, and Retain them for valuable repeat
business.
To visualize this, add four stacks of blocks, each five blocks tall.
Go ahead and cross-reference this for a minute. For instance, we are going
to be looking at the intersections of two concepts like Define Drivers
and Engage. Meaning, we will talk about what we want to engage our
users to do.
Or, we might talk about Plan Actions and Retain. Here well want to
understand what we can plan to do on the site to retain users better than
they are currently being retained.
Definitions
First, lets agree on what the terms mean. A number of these concepts
already have pretty wide currency in off-line marketing. Were here to
Define Drivers
Build Metrics
Plan Actions
Create Changes
Measure Success
Reach Engage Convert Retain
Steps
Customer Cycle
Figure 2: with Customer Cycle
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define what they mean on the web.
Reach
This is how we get them to arrive at our web site. It might be by putting a
big billboard on the highway with our URL. It might be by purchasing alink on Google. It might be a button on another web site that is owned by
our organization. Doesnt matter. Reach is how we get them to show up in
the first place.
Engage
Our visitors are of little or no use to us if they arent engaged. Are we
happy if they get to our home page, see our companys name, and leave?
Of course not. Thats almost worse than if they hadnt come at all.
If theyve done that, they have definitely not been engaged. But, what
about if they clicked on one more pageand then left?
Still not so good.
Okay, how about if they went to four pages; then came back the next
week and went to five pages; and then clicked on an about our prod-
uct page. Twice.
Thats an engaged prospect. We want to treat them differently than the fel-low who moused over a couple of jpegs on the home page and then went
to another companys site(see Plan Actions, above).
Convert
While the definition of engaged can be a little gray, the definition of
converted ought not be vague at all.
Convert links right back to the original, strategic driver that may have
been defined at our hypothetical meetingthe one where it was decided
that the site needed to refer contacts to the sales force.
A prospect is only converted once they have performed the desired action.
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In our hypothetical case, that would be when they have in some way con-
tacted (or asked to be contacted by) the company.
At this point, the web site has done its most important job. Not its only
job. But its most important. It got someone to do what we wanted him orher to do: to buy, to call, to stick around, to get information quickly. Any
of these would qualify as true conversion, depending on the type of site
we have.
Retain
The cost of keeping a customer is much, much less than going out and
acquiring new ones. So well want to pay special attention to folks who
already bought from us, or who have already contacted us. In other words,
well want to retain customers who have been converted from prospects.
The site needs to be constructed in such a way as to accommodate
these customers. Discounts, targeted offers, customized, cookie-driven
content all play their roles. Usually, well know weve retained a cus-
tomer when weve succeeded in getting them to repeat or upgrade their
prior conversion.
But along the way, well want to be able to tell if their usership is falling
off, or if they have once again gotten into a buying pattern and then
abandoned it. Well want to examine that and see what can be changed tofix thatand to keep those folks engaged until their next purchase.
The Four Types of Sites
Now weve got a series of actions that we can take; and we have spoken
about the way we want to pull potential customers through the conversion
and retention process.
But before we can begin any of the careful planning that gets web opti-
mization accomplished, we will want to understand and agree upon what
type of site we have. Because the goals of our site will be determined by
which type of site it is.
We will propose that for our purposes, there are really only four types of
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siteswhile recognizing that some sites combine certain of these elements.
In our list, we have named the type of site, and in bold, the result we
expect from that type of site.
The Four Types of Sites
Commerce: sales
Lead-generation: contacts
Content (and sometimes Branding): long, trackable visits
Self-Service: quick, valuable visits
Once weve agreed on one of these types of sitesand we contend there
are few if any sites that are notone of thesewe can begin the process of
optimization. We begin by deciding what we want out of our siteand the
customer-centric approaches we need to take in order to drive results.
Lets visualize this as it relates to the table that weve created. Weve got
five sequential steps to perform in order to improve our ability to Reach,
Engage, Convert and Retain customers. But depending on the type of site
we have, our considerations and our deliverables will be different. For
instance, if we are planning our actions for improving the engagement
process for a content site, that is going to be a different task than if we
were doing the same for a self-service site.
Now well take the table and make it three-dimensional by adding the
types of sites. This gives us a 3D cube that happens to illustrate for us how
we can structure our thinking through the entire process, no matter what
type of site we have.
Lets take a look(figure 3):
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Site Type Customer Cycle
Five
Optimization
Steps
Define Drivers
Build Metrics
Plan Actions
Create Changes
Measure Success
Content
E-Commerce
Lead Generation
Self-Service
Retain
Convert
Engage
Reach
Web Optimization Cube
leveraging web analytics
Technology Leaders, LLC (www.technologyleaders.com) 230 Park Avenue, New York, NY 10169
(212) 808-3058 [email protected]
Figure 3: Web Optimization Cube (Copyright 2008 Technology Leaders)
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We now have a structure where we can collect and retain ways we want to
approach each part of the web optimization process.
And, we can ask important questions by looking at different instances ofthe cube, for instance:
How do we Define the ways in which we want to Engage users in a Lead
Generation site?
Or:
How do we Build Metrics to measure how we Retain people in an E-
Commerce site?
Rather than try to fit all our words into cubes, lets allow the illustration to
be a theoretical guide; and give ourselves some space to lay out the plans.
In order to facilitate moving ourselves through this process, lets take a
look at a sort of working guide that gives us a way to track the tasks
necessary in each part of the job.
Turn to the next page to find the detailed working guide.
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Working the Process
For each of the five steps to web optimization. . .
Define Drivers
Build Metrics
Plan Actions
Create Changes
Measure Success
. . .we have included detailed tasks that comprise each step. These tasks
are associated with the four customer-centric, relationship-building disci-
plines that are necessary to drive web success:
Reaching Prospects
Engaging Prospects
Converting Prospects to Customers
Retaining Customers
We also know that our tasks will be different depending on what kind of
site we are:
Content E-commerce
Lead Generation
Self-Service
The Five Necessary e5o Steps: Detail
1. Define Drivers
This strategic part of the process really asks only one question: what do I
want visitors to do? So while other parts of the customer-cycle are impor-
tant, this part focuses rather tightly on the Convert part of the cube.
Weve included a number of questions, below, that will help inform the
strategic discussion. Please use them as guidelines to keep the project
headed in the right direction.
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Generally, as a part of defining drivers, we will want to have:
Identified stakeholders within the organization
Discovered the specific needs they have from the site Socialized the concept of Web Optimization and Web
Analytics by discussing its importance and presenting industry
examples
The goal here is to obtain sufficient buy-in so that the team will stay
with you as you lead them through the rest of this process.
Lets begin to define what we want to achieve (e.g. define drivers) inside
each part of our customer cycle.
Reach
Here we are asking Who do we want to reach, and how do we want to
reach them? Well want to:
Identify techniques already in place to reach prospects and get
them to the site
Define the characteristics, categories, and sizes of target audi-
ences
Identify the offers we are currently making to attractprospects to the site
Engage
Now were asking What defines engagement for us? In order to clarify
this, pursue the following exercises:
Identify visitors likely goals upon arriving at the site (map to
offers, above)
Identify the first steps we want visitors to take in order to lead
them to conversion
Build a visual map of this critical path.
Establish relative importance of pages and what criteria would
determine a successful visit to a particular page (time spent,
clickthrough, etc.)
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Convert
Here, as we define what conversion means for us, we are deciding on the
whole reason we have built this magnificent information engine known asa web site. Its all about funneling prospects to perform this (or this series
of) action(s). We will want to:
Narrowly define what activities constitute conversion
o Recognizing that in some cases conversion may occur
off-line
Establish a monetary value for each conversion
Decide if there are different levels of conversion, and what the
relative importance of each one is (e.g. a phone call to a sales
person is better than an email to an info@).
Make sure we are focused on one true conversion goal, as
opposed to numerous soft goals.
Retain
Here we are determining how important repeat visitors are to us; how
important upsell and cross-sell is; and how we will determine what consti-
tutes having retained a customer. We will:
Decide upon whom we want to retain as a customer Accept the cost at which we will attempt to retain them
Specify behavior that will satisfy our criteria for retention
Understand how much that behavior is worth. It should be a
number derived from:
Profit on items sold
Cost savings related to infrastructure (for example) web-
usage v. phone center usage
Amount saved on new-customer acquisition
Cost of retention efforts
When we have finished the key task of defining what we want in each of
these phases, we can begin to build the measurement program.
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Build Metrics
Here, we need to select, design and configure a metrics program that maps
to the four stages of our customer-centric lifecycle. Weve provided some
broad examples below.
Reach
An example of the types of things well want to do to establish measure-
ment programs include:
Identify how well track ad campaigns and e-mail campaigns
Identify how well measure the success of affiliate marketing
Set up measurement for such things as key referring pages
Build a method to track search-engine effectiveness
Identify the number of people reached by each technique
employed; and what percentage of the target audience has been
reached
Engage
Identify new as well as returning visitors
Measure number of engaged visitors by reach technique
Review freshness factor (e.g. ratio of content freshness to visits)
Identify and measure behaviors of browsers v. shoppers Review ratio of engaged visitors to total visitors
Measure profile of typical buyer-paths; identify percentage
of fall-off of visitors at different pages along the way to
conversion
Convert
Measure number of conversions for each reach technique
Measure conversions of various types of visitors
Measure scenario completion rates (e.g. how many overall visi-
tors finally converted to customers?)
Measure ratio of conversions as a percentage of engaged visi-
tors; finalize locations where visitors are dropping off
Identify visitor paths most associated with conversion
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Determine the average number of visits necessary to convert
Measure how many average visits were required to achieve
conversion
Retain Measure duration of visit
Determine frequency of return visits for converted customers
Review how recent are the typical conversions of return visitors
Review the rate at which converted customers do not return
Review the rate at which customers who nearly got converted,
do not return
Plan Actions
As part of this process, we will analyze the collected metrics, perform new
measurements based on emerging data (sometimes with multiple vari-
ables); and we will try to integrate measurements into a unified visitor
behavior model. We will also plan actions that help us optimize the effec-
tiveness of our customer-centric cycle.
It is important to note that at this point in the process, our tasks will have
become very specific and we should be able to enumerate a high number
of specific tasks within the Create Changes and Measure Success parts
of the worksheet.
These phases will naturally have fewer theoretical tasks, thereby short-
ening them in comparison to some of the earlier sections in this chapter.
Reach
Adjust marketing efforts, affiliate programs and offers to
reflect findings in measurement phase
Optimize search engine techniques
Maximize inbound-link campaigns
Review and adjust digital ad and email campaigns
Engage
Adjust landing pages
Adjust critical path pages
Adjust content focus
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Review creative; may result in redesign or re-think of creative
approach (with metrics built-in to new creative)
Refine personalization process
Convert Shorten the path to conversion page
Optimize conversion page based on user behavior measure-
ments
Adjust "offer" to reduce amount of visits it may take to success-
fully convert
Retain
Develop strategies to entice return visits
Follow-up campaigns
Value-based offers
Seek user opinion
Locate efficiency engines within the site; attract users to return
to them
Create Changes
This part of the process is focused on getting concrete changes made.
Consequently, the actions here are entirely dependent on the previous three
steps and will differ in each application. Now it is simply a matter of exe-
cuting the plans. Naturally, each stage. . .
Reach
Engage
Convert
Retain
. . .of the customer-centric cycle will have specific production deliverables.
The overall objective, apart from the specific changes required, is to make
certain that metrics are built into the site from this point forward. The site
will generate more useful information this way, rather than retro-fitting
an existing site.
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Measure Success
Using the same drivers that we defined at the beginning, and the same
measurements, we will measure again to determine the effectiveness of the
changes we made for each of the four customer-centric stages of. . .
Reach
Engage
Convert
Retain
. . .while recognizing that improvement is a constant goal, not a final goal.
In that light, the Plan-Create-Measure phases of the process should be
considered iterative.
Since web optimization is not a do it once and walk away operation, its
important to understand that we will want to work again and again to con-
tinue to improve upon what was already improved.
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Chapter 5:
Conclusive Evidence:The "How Do I Make This Happen?" Part
The organization that wants to achieve successful web optimization needs
to take a few critical steps that will pave the way for success. Weve
already discussed the five-step process, the four site types and the cus-
tomer life-cycle.
But what about the ways in which an organization prepares itself to per-
form web optimization? Here are some considerations:
Organizational Steps
RecognizeThe first thing to do is to recognizeas an organizationthat leveraging
web analytics is the key to success. There really is no substitute for deci-
sions made using quantitative knowledge.
In many companies, theres likely to be a considerable amount of selling
through of the concept before it is fully embraced. It is natural that some
folks may be sensitive about being judged on the performance of the
site. Or, therell be people who are likely to say dont measure yetwait
until I fix it.
These are understandable responses. But for the organization, they may not
be the best course of action. The best option is to get the facts about whats
going on with the site and plan actions around improving performance.
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Therefore, for those who contemplate putting off the decision to
measure:
The best way to avoid being judged byweb analytics is to embrace it nowand
achieve web optimization!
Align
Too often, theres a schism in organizations
between the IT folks who run the web archi-
tecture (and usually the web analytics tool) and the business-line folks.
Web analytics is often seen as an activity lying wholly within the domain
of the IT department. True enough, the robust technologies that support
web disciplines are properly placed inside IT.
But the value of web analytics is relevant only partly to IT (e.g. errors,
speed, etc.). The major portion of the value is relevant to the business side:
to Marketing, to Sales, to Customer Service.
When the IT group gets together with customer-oriented groups within the
company and they coordinate their efforts, good things start to happen.
They are able to achieve results with web analytics that are much superiorto those that result when one group or the other tries to proceed alone.
The best way to structure this type of cooperation is:
Marketing folks need to understand the discipline well enough to ask
the right questions; and the IT department needs to configure the web
analytics tools to provide answers to those questions.
Embrace
The Five Step Process is indispensable to web optimization. Simply put,
an incomplete process will not gain the desired result. Remember, the
object here is to show a measurable improvement on specific goals. It can
only be achieved by following the program from beginning to end.
There really is no
substitute for making
decisions based on
quantitative data.
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Design the web analytics program and stick with it.
Deciding halfway through the optimization project (for instance) that what
we really wanted was to take a gamble on providing on-line billing state-ments, negates the effort.
Do the measurementand then listen to what it says. It may turn out to be
that the above-mentioned on-line billing is not worth the effortbut mea-
surement may indicate that moving the buy page three places forward in
the architecture of the site will generate a measurable return.
Report
If a web site is improved in the forest, nobody can hear the cheering.
Or something like that.
Just as most marketing efforts are tracked and reported with some thor-
oughness, web analytics needs to be treated with the same rigor and
importance.
Therefore, report the improvements, and how we got them. But dont for-
get to report progress along the way. That way, well build a constituency
of support for web analytics.
To build this constituency, formulate web analytics data into targeted
reportsa different report for each important group within the company.
Make sure the reports are action-oriented, with data provided as supporting
documentation. Keep the focus on news and to-dosand away from pre-
sentation of statistics by themselves.
Paired with web analytics software, the web site is a torrent of information
about our customers. Irrigate the company with this unique and critical
intelligenceand the crops will grow greener.
The web represents a conundrum of sorts: it is the only business tool that
automatically generates its own effectiveness data (via web analytics soft-
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ware). But it is also the only business tool that has almost no other way to
evaluate it except for this data.
Leveraging web analytics is therefore both very valuable and quite unavoid-
able for those who want to maximize the effectiveness of their sites.
Wraps
Weve identified a process to optimize any type of site. Weve identified
the drivers we should expect in each of four possible site types. Weve also
identified the customer life-cycle on the web.
We hope that these concepts will help your organization deliver on the
promise and the power of web analytics.
If you have any questions about this guide or about web analytics, please
feel free to contact Technology Leaders at the locations provided on the
following pages.
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About Technology Leaders:
Technology Leaders is the world's most experienced web analytics consulting
company.
Founded in 2002, the firm is expert in the deployment and customization of all major vendor
offerings in the current web analytics space. It uses web analytics tools to mea-
sure user activity in a way that is meaningful to the organization.
TL's consultants then draw upon market expertise to make sense of what was
measured. Finally, TL helps customers take action by improving, optimizing,
and measuring again to prove effectiveness.
Organizations can now rely on one company to deliver a complete package
ofimplementation, analysis and the ability to measure improvement for web sites.
Technology Leaders Contact Information:
Technology Leaders, LLC230 Park Avenue
New York, NY 10169
(212) 808-3058
www.technologyleaders.com
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About the Author:
Andrew Edwards,the founder and Managing Partnerat Technology Leaders, is a
recognized e-business expert and pioneer with significant credits in on-line
marketing, web architecture, project development, and web analytics. In the 90s
he founded an award-winning interactive design agency servicing Fortune 50
customers and launched several brands on line. Expert in identifying and capitalizing
on market opportunities, he is also an accomplished interactive designer
and technology professional. He co-founded the Web Analytics Association
in 2004, and is thechiefarchitect ofthe web analytics approach developed by
Technology Leaders.
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