Earlier this year, a previous post addressed using web analytics
to optimize a paid search campaign.  This drew some attention, as web
analytics (WA) are one of those things that everyone knows they need, but not
always sure exactly what actions are called for in a given set of data. I
suppose some of this can be blamed on the usability of the dashes as it’s pretty
easy for them to get unwieldy…which can lead to a full blown case of
“analysis paralysis.”

It’s time to share some direction on using WA to optimize
natural search campaigns. The following reports can be found in almost every
web analytics package and are fairly consistent, but depending on campaign
goals, the insights and actions taken may vary:

1. Top Referring keywords. Look at the long tail here; 25% of the queries
   performed are ones Google has never seen. The referring keywords to the site will show themes and patterns that
   are otherwise difficult to discern.  More than once we’ve changed
   directions on a campaign because we’re seeing volume around a type of query
   we’ve never seen.  Many times the impetus for a decision like that is born
   here.
2. Referring Domains. This metric is essentially telling you
   who your biggest traffic drivers are.  Search engines and sister sites
   tend to occupy the top of the list.  However, we see some interesting
   things happening in the middle to end of this referral list.  This is a
   great way to: A. Measure the effectiveness of a link building campaign (if
   we’re seeing visitors from sites we built linking relationships with that we
   haven’t before that’s a good thing right?) and B. Find site themes and
   verticals that you may be able to generate buzz with (e.g. if we’ve got a
   particular blogger reviewing a product or service, this can inform the type of
   content on the page which could lead to greater link bait).
3. Click paths. This metric is more or less telling you how
   people navigate through the site.  There are a lot of things to be
   determined here but a big one is the effectiveness of your site layout.
   If we’re seeing a lot of people having to go through a few clicks and all
   ending up on the same page, it would indicate that there’s an opportunity to
   engage people more effectively by improving that click path.
4. Paid vs. Natural. This is an excellent metric for identifying
   gaps.  With paid search, we can quickly target the high volume terms and
   use ROI/conversion rate data to inform our decisions on where we want to
   compete organically.  Likewise, the places where we’re seeing a lot of
   activity in organic terms where we don’t have paid coverage can help us expand
   a paid campaign.
5. Geographic referrals. The more targeted and niche the web becomes,
   the more important geography is (and no, the irony of this isn’t lost on
   me).  Nevertheless, we’ve had instances where a flurry of offline
   promotions leads to a surge in a particular geo-specific market.  Certainly
   the offline team will want to know that the radio blast in Philly led to an $X
   lift in revenue. We’ll use geo data to
   develop new content, launch targeted landing pages, and in some cases, even
   modify service offerings to better target geo revenue sources.
6. Visiting trends. Almost every analytics package puts this
   metric on the forefront of their dashboard so you can see how many visitors you
   have this month verses last month and so on.  Resolution Media uses this to evaluate
   seasonality and optimize accordingly. Correlations between seasonality and
   referring keywords are also helpful in determine where linking opportunities
   could be.
7. Top Landing Pages. Lots of useful action items come from
   here.  This metric essentially tells you where your buzz is.  Keep
   these pages fresh and make sure your users can access them easily.  Seeing
   where human visitors land is a good indicator for what spiders are crawling in
   on as well.  From there, this data can be used to optimize the structure
   and internal linking scheme of the site.   For example, if we note
   that Page A is a much more popular landing page than Page B, C or D, we should
   make sure B, C and D are linking to A with optimal anchor text (based on what
   themes and keywords are on page A).
8. Conversion Rates. This is the million dollar metric right
   here!  When visitors come to the site, are they doing what we want them to
   ultimately do?  How often?  More than they were? Conversions are what
   answer these questions.  From there, we may have a number of action items
   we need to take based on what the data is telling us.   Don’t take
   brash actions if conversions suddenly drop (or spike).  However, KNOWING
   when those spikes or drops occur, and looking at what other things happened
   around it (see almost any other metric listed here) as soon as possible is
   absolutely essential to taking the right actions.  It could lead to
   campaign spending changes, landing page optimization, re-targeting keywords,
   building new link bait and a host of other scenarios.
9. Bounce Rate. This is one of those metrics that I think
   varies quite a bit from project to project.  One bounce rate may be great
   for one kind of site and a total failure for another.  It’s essentially
   telling you how many people happened upon a single page on your site and didn’t
   bother to go elsewhere.  We generally chalk that up to them not finding
   the information they were looking for.  If we’ve got pages targeted
   specifically around one or two keywords, we may be looking for a lower bounce
   rate than a page that casts a wider net.  Measuring bounce rate according
   to page type is essential to evaluating the effectiveness of our content and
   the messaging.
10. Browser type. It’s weird how this was a metric that fell
    out of favor for awhile and is starting to make a comeback.  I’m talking
    about mobile here people!  If we’ve got a project that is a multi-media
    extravaganza with elements that aren’t visible to a spider or a mobile browser,
    and our browser type metrics are telling us a significant amount of traffic
    comes to us from this type of user, then this should absolutely impact how we
    present that information.

There are a host of additional web analytics reports that
lead to the optimization of a natural search campaign.  Reading back over
the list, much emphasis was put on site usability, which supports that driving
traffic to the website is half the battle, and having a website that drives the
traffic to take a desired action can be just as important.

22-May-08 2:00 PM
Continued here:
Using Web Analytics for SEO

Popularity: 31% [?]

Continuing our Things I Wish I Knew… series, Daniel Shields offers his Top 10:

1.  Not Everyone Knows What You are Saying

The ecommerce workplace is made up of very diverse areas of expertise. Where a few folks here and there might get what you are saying with little effort, most of the people whom you work with are not steeped in statistical understanding, much less its vernacular. For the good of the company, and the sanity of the analyst, it might be advisable to find an in-house reader who gets most of it, but can point out where language might be an issue.

2.  Customer Support Exists for a Reason

A major impulse to try to overcome is the same which keeps a person from asking for directions in Culpepper, Virginia. You might know you are lost, and you have a pretty good idea that people know how to help you, but for some reason, it means more if you turn the map around and fold it different ways a dozen times to see if it makes a difference. Taking this ego-shot and allowing it to remain an open window for progress is a key item to reaping greater rewards from vendor solutions and the myriad applications which complement them. Shave a couple hours off your time and simply ask for directions.

3.  Experts Have Expertise

Early about in my freshman year of analytics, I made assumptions about the vast cache of experts in the field of ‘web analytics’. Mistakenly, some of those were that each was a virtual encyclopedia of best practices and skill in every facet of the world of online measurement. Luckily, with the guidance of some gracious consultants and my boss, I was able to understand the landscape in terms of where each expert rooted their strengths. Knowing that made each a much more valuable source of information in terms of topics which applied to specific parts of my obligatory reporting.

4.  Management Needs Analytics

In order to make critical decisions in an online retailer, it is an absolute necessity to understand the ways in which numbers impact functions of the business. Managers make decisions on a daily basis which require output from measurement. This is as true for marketing as IT, Sales, Advertising, or Development. Making reports available to managers to align business goals is a major step in driving a web analytics process into a company. Getting that point across to management and administration will facilitate resource allocation as well as recurring discussion on points of impact.

5.  Analytics Needs Management

Much like respect, analytics is a two way street. It is clearly an input/output function. There needs to be ‘Follow-Up’ and ‘Feedback’. An analyst, or internal owner of data, needs to see the results in order to balance improvement across the goals and initiatives which are helping the business grow. Not getting the discussion to start around web analytics data internally is, in my estimation, probably the most detrimental to installation of useful analysis.

6.  Prepare to Stand Your Ground

The first lesson of quantitative analysis is that numbers are not emotional. Math exists outside of the human psyche. Therefore, it should not have representation or meaning attached to it outside of the definitions of the operations. This part of the memo is not extended to the rest of the people whom analytics affects. People, their work, the graphics which make up a site, and the world in general cannot extract emotion from their decisions. The lesson here is to know well in advance that if you live by the numbers, prepare to survive by the numbers.

7.  Who Knew Experimentation Could Be So Much Fun

I guess I get a little excited when it comes to building and executing complex experiments. For me, stepping into the world of multivariate testing and usability was almost a fulfillment of a vocation. When I was interviewed for my position, Mildred the GM at CableOrganizer.com, explained that the job consisted of tedious math and required certain stepping stones to maturity. Learning to perform on page A/B and multivariate experiments was a minimum. With some training provided by the WAA’s own Robbin Steif, I found myself neck deep in possibilities. It was a mix between graphic design, marketing, and science which appealed to every part of my thirst for fulfillment.

8.  Analytics Needs Regular, Consistent, and Objective Validation

Take nothing for granted. At every turn, little pieces of HTML code and applications being worked on or edited by some party have potential impacts on the data which we hold so dear for decisions. These should be perceived as threats and guarded against accordingly. There were three occasions where our major analytics vendor code was completely eliminated from important pieces of our site template in 2007. Each resulted in loss of data. In other instances, data was artificially inflated in terms of traffic due to scripts and crawls which were being run for one purpose or another; again, data rendered problematic until the good stats were boiled out. While every failure was not attributed to analytics, its ultimately the confidence of the data which suffered. The lesson: keep up with your data and know when things look funny…then, explain away the happenings.

9.  Live and Die By Measurement

As an analyst, eventually there is an epiphany that a world of measurement is easy to manage as a vertex of both tasks and value over time. By taking on certain actions or initiatives based on analysis, you champion causes for improvement. When the figures from the work come back in a statistically relevant state, some ought to clearly be wearing your signature. Be they good or bad, they are results associated with changes based on your suggestions. So, over time, your suggestions gain merit based on your experience, and the returns, in earnest, should be appropriately attributed and the rewards shared. A good employer will recognize your contribution and construct a system whereby your achievements will be based on your skill, ambition, experience and initiative in helping the company achieve its goals. When those goals converge is the sweet spot for income, bonuses, and benefits.

10.  Follow Your Data: Analysis is Not the End of Analytics

Being able to produce reports and materials to place monitors on is wonderful, but making sure the data is being used for the right purposes is a job beyond the analysis. When work in analytics began for me, I had scheduled deadlines on which to deliver my take on the previous week’s performance versus some comparable information. Over time, I started to realize things were slow to change based on the insights which I extracted and outlined in my papers. After a couple weeks I started basically shouting out about certain points trying to drive them home, until I began to feel like it was becoming useless to produce reports. By the end of the 3rd quarter, I was approached by Paul, the VP and COO from CableOrganizer, who noticed my cries, to move my actions from only reporting into managing major facets of resources to get the jobs done based on the analysis I was providing. With that, the growth started to produce value which was much more desired than mounting paper columns.

Daniel Shields is a talented young web analyst working for CableOrganizer.com, Inc. and focusing his efforts on conducting highest-quality research on web visitor behavior.

Daniel and the team at CableOrganizer.com are also developing Wicked Business Sciences, which has created patent-pending ecommerce technologies geared toward business improvement through measurement and personalization.

7-Apr-08 1:00 PM
Here is the original post:
Top 10 Things I Wish I Knew When I Started in Web Analytics #3

Popularity: 10% [?]

We’ve all heard the classic conundrum of businesses today – “Half of our Marketing efforts are working, we just don’t know which half”. Site Analytics strives to answer that statement by gathering data to allow business to align their message, media, offer and channel with their desired audience to optimize the results and return for the company.

However, in online business today, the conundrum has gotten much more complicated. Where does the analytics of the website end and analysis of the customer begin? While we construct our KPIs and dashboards to capture the successes of our campaigns, ad placement, engagement and conversions to measure the success of our company objectives, in the end isn’t the end goal really about the customer and the measurement their experiences and successes (or lack of them)?

Spending Growth on Customer Experience

In a recently published report ‘Customer Experience Spending Intensifies in 2008, by Megan Burns’, Forrester Research identified areas where North American business leaders are looking to focus their attention for 2008. In comparison to the previous year Forrester found some significant spending and planning increases, notably:

• 84% total increase in efforts to improve online usability
• 78% total increase to improve cross-channel interactions
• 80% total increase to make online interactions more enjoyable

While the research points to the continued growth of the analytics industry and covers increasing size of the customer experience budgets, another trend identified by Forrester drives the end focus of all the measurement back to the customer and their interpretation of success.

“We expect these trends to lead to more customer-centric cultures and processes by enabling firms to be more disciplined in their approach to customer experience…”

Why focus measurement on the Customer’s Experience?

The Internet channel is becoming a (if not the) primary channel for most businesses today and Ecommerce continues to grow with online growth rates significantly outpacing the offline growth rates in most industries. So
why is Customer Experience a top spending focus for 2008 and why did almost all
(91%) of executives surveyed in the Forrester research report say customer experience will be either very important or critical to their 2008 efforts?

Simple really… your customers are trying to complete their transactions, your site is letting them down, and they are switching to a competitor. And by the way, the results are getting worse instead of better.

Harris Interactive conducted the third annual survey of online consumer behavior, sponsored by Tealeaf®, and the findings were alarming:

• 9 out of 10 consumers experienced an issue that caused them to abandon a transaction
• 53% of users who experience website issues contact the company’s call/contact center to resolve but 49% of users who contact a company after experiencing a web-related issue were still unable to have that issue resolved.

The result of this poor customer experience translated into two immediate waves of online abandonment:

• 42% of users say they abandon or switch to a competitor when they experience even one online site issue
• 52% say they stop doing business with the company entirely, and 76% either stopped doing business entirely, decrease the amount of business they do, or lodged a complaint with the Better Business Bureau.

The third wave is even more risky. This is the threat to your brand loyalty and long-term customer value as a result of the poor customer experience and inability to complete an online transaction. With continued growth in blogging, social networks and viral content, your site failures are broadcast to an increasingly receptive audience actively seeking unmitigated third party reviews.

Indicators of a poor customer experiences are not limited the obvious but still prevalent today: site errors messages, performance issues and broken links – but include functional and business process challenges, and issues centered on usability and site-design. Collectively, however, they all have one commonality—
they all forced the consumer to abandon the transaction.

For the third year running, nearly 90% of users responded that they had experienced an issue that caused them to abandon a transaction. This rate of “failure” is extremely high and is not improving—in fact, it’s actually getting worse. Considering there are significantly more users and transactions every year, with a consistent rate of failure, the number of individuals and transactions adversely affected by issues each year is actually increasing.

The first threat (the “first wave” of abandonment) is very real, with 42% of users saying they abandon or switch when they experience even one issue. These users have little tolerance for failure today and that tolerance will only continue to decrease until leading ebusinesses focus their attention and budgets on improving the customer experience on the website and in the online support centers. Consumers expect the online channel to work as well as offline channels such as storefronts, branches, catalogs and agents with 82% saying they expected the online experience to be the same as the offline.

The second threat (the “second wave” of abandonment) is significant and is newly identified by the 2007 Harris Survey. The heightened rate of churn for online customers – with 52% saying they stop doing business with the company entirely and a full 76% who either stopped doing business entirely, decreased the amount of business they do with the company, or lodged a complaint with the Better Business Bureau is a serious threat to online businesses that demands that call/contact centers be equipped to handle the needs of online consumers, or risk losing them to competition permanently, since the tolerance for poor customer service after web-related issues is extremely low.

The third threat is just as challenging, and perhaps even more risky. This is the threat to your brand loyalty. One interesting example the survey identified is that the single most important factor to consumers in doing business online was website security. However, the survey also found site issues to seriously undermine consumer confidence, specifically relative to online security and privacy concerns.

While businesses today tighten belts and budgets for tough times ahead, Forrester expects metrics and executive attention to the customer’s experience to rise to top of mind, and budget. Forrester addressed these identified gaps in the true understanding of the customer.

“Most firms today struggle to measure the quality of their customer experience. To establish a framework for measuring customer experience quality, firms should identify key customers, the most important moments of truth in the customer experience continuum, the criteria customers use to evaluate those critical interactions, and metrics — both subjective and objective — that capture how well the organization met customer expectations in each area.”

Effective understanding of the customer does not stop with well designed and built site analytics dashboards and Key Performance Indicator reports; that is just the beginning of visibility into the complete online experience and your customer’s behavior and experiences.

It would be incredulous to believe an online business today could operate without detailed website analytics to gather the bits and bytes to measure the website’s effectiveness, In light of that:

• Why is there a gap in extenuating site analysis into the success of the customer?
• Why are customers continuing to experience issues completing online transactions?
• Why are online conversion rates stagnant across so many industries?

Web Analytics alone can’t provide all necessary measurement and optimization data to improve the customer’s experience.

Eric Peterson, from WebAnalytics Demystifed Inc. discussed these thoughts in a recent paper ‘Customer Experience Management and Web Analytics, From KPIs to Customer Transactions’ covering the foundational needs to combine multiple measurement disciplines for e-businesses today to understand true user behavior and allow companies to improve their customer’ experience.

“In today’s e-business environment, both Web Analytics and Customer Experience Management systems together should be considered foundational to website measurement and optimization. These similar-yet-distinct systems each contribute to a site owner’s ability to recognize, react, and respond to the ongoing challenges they face. Used together, these two technologies are collectively able to resolve the “What, Where, When, and “Why” of visitor interactions on the Internet.

The most forward-thinking companies have already recognized the value of investing in solutions beyond Web Analytics in order to measure and optimize their web channel. By understanding the true strengths and weaknesses of Web Analytics products and how Customer Experience Management systems can best be leveraged, web site owners will be able to extend their web measurement and optimization processes to achieve far greater levels of success – ultimately by improving the site, serving customers better, and increasing site revenue.”

Measure the Customer not the Website

The strongest companies today are taking action to align internal processes and measurement with cross-channel experiences like the website and call-center teams to improve measurement beyond the browser and making their customer experience their top-priority. Not surprisingly this translates to firms that put customer experience on the radar screen at the executive level are best positioned to improve the success of their customer’s experience across the entire enterprise.

While it’s debated today in site forums, user groups and blogs whether “Web Analytics is Hard” or “Web Analytics is Easy”, the recognized need to improving the customer’s experience is universally accepted by analysts, practitioners, experts, pundits and of course by the real end-focus of all these efforts, the customers themselves.

Learn more about how you can leverage Site Analytics using Customer Experience Management
Download all referenced reports from this article along with a Tealeaf customer case study

References

Forrester Research, an Independent Research firm in February 2008, “Customer Experience Spending Intensifies In 2008” by Megan Burns with Harley Manning, Olga Melnikova, and Steven Geller.

The Two Waves of Online Abandonment: The 2007 Harris Interactive Survey of Online Customer Behavior, Sponsored by Tealeaf®

Forrester recently surveyed 287 customer experience decision-makers from large US firms about their 2008 plans. Almost all — 91% — said customer experience will be either very important or critical to their 2008 efforts. See the February 7, 2008, “Obstacles To Customer Experience Success, 2008” report.

The Two Waves of Online Abandonment: The 2007 Harris Interactive Survey of Online Customer Behavior, Sponsored by Tealeaf®

Eric Peterson, WebAnalytics Demystifed Inc, 2007 ‘CUSTOMER EXPERIENCE MANAGEMENT AND WEB ANALYTICS, From KPIs to Customer Transactions’

7-Apr-08 10:45 AM
Read the original: 
The Pursuit of Measurement: The Customer’s Experience

Popularity: 16% [?]

When analyzing online advertising begin by looking at impressions. Delivered impressions tell you how many people were exposed to your ad. Impressions are passive. When an online ad is served up and someone views it, it is counted as an impression.

The purpose of someone seeing your ad is to entice them to visit your website. In order to visit your website, a customer interaction such as a click is needed. The click sends a customer to a company website. Once a customer arrives at the designated website - that is considered delivered traffic. Delivered traffic can be defined as user clicks and website visits after exposure to an ad.

How is your ad performing? Is the ad getting customers to visit your site? A quick metric to use is delivered traffic rate (DTR). DTR is total delivered traffic divided by impressions served. If your DTR is 2% or more you have efficiently accomplished your goal of getting people to your website. A two percent DTR indicates the robustness of your ad, and is a general rule of thumb. I don’t think there are case studies on DTR yet.

Once customers reach your site what are they doing? Good metrics to measure that are actions and leads. An action is a way a customer can express interest in a product or service on your website. A lead is usually a customer whose interest in a product or service is expressed by electronically submitting personal contact information.

The unofficial relationship between actions and leads is 6:1. In other words every six actions should net you one lead.

Action rate and lead rate determine how well customers are interacting with a website. Action rate is defined as total actions divided by total delivered traffic rate (DTR). The action rate speaks to the robustness of a site. The higher your action rate, the more people interact with your site.

The lead rate can be defined as leads divided by delivered traffic rate (DTR). The lead rate allows you to see the relationship between leads and delivered traffic. It is a funnel effect. A customer can not submit a lead unless they are at a website. A customer arrives at a website as delivered traffic.

The final metrics to look at are cost per action, and cost per lead. Cost per action is total cost divided by total actions. Cost per lead is total cost divided by total leads. These metrics let you know how much each action and lead cost. CPA and CPL vary depending on industry.

By analyzing metrics such as impressions, delivered traffic rate, action rate, and lead rate you can determine how well your advertising had done.

8-Mar-08 9:00 AM
Original post: 
Analyzing Online Advertising using Dart

Popularity: 14% [?]

Successful insights and optimizations from Web Analytics (WA) data hinges on analyzing timely, consistent, and accurate/clean data; all online advertising should be tagged with WA URL tracking parameters to provide a complete and centralized view of site activity and conversions. Now that disclaimer is out of the way, here are 10 quick and simple ways to use WA data to optimize Paid Search (PPC) Campaigns:

1. Traffic Volume & Conversion Rate Comparisons – Comparing performance between Paid and Natural traffic, paid engine to paid engine, and Paid keyword to Natural keyword offers a great opportunity to set goals and find new and missed opportunities. If keyword ABC has an 11% conversion rate from Google Natural, but 2% on Google Adwords (paid), a PPC optimizer should be making comparisons between landing pages, copy, etc. to make drastic changes versus minimal ‘tweaking’. Without the WA/Natural performance data to benchmark against, an optimizer would have been content (and quite happy) with doubling the conversion rate to 4%.
2. New Keyword Opportunities – Looking at keyword level performance data from both the natural search engine reports and the internal search box queries is important to do monthly to find new paid search keyword opportunities. Look for new misspellings, high volume converters, or run a vlookup to identify missing paid search keywords. Add new keywords, increase appropriate paid ranks/bids where gaps exist, and focus budget on top converters to find instant gains.
3. New Traffic Source Opportunities – Domain referral reports show where visitors are coming from the associated volume and conversion rates. Look deeper than the big search engines, what do the converting sites have in common? Is there a way to increase exposure to this audience with Display ads or Contextual Ads? Do you notice a lot of mobile traffic converting? Do you see an increased average order size from non-US visitors? Is it time to think about getting budget for PPC mobile ads or international search engines?
4. Budget Forecasting – Flat month-to-month PPC budgets seem to be the standard, yet I have never seen a single business where conversion rates or volume doesn’t change month-to-month. Seasonality is evident in WA data and monthly ad budgets should reflect those ebbs and flows, down to the engine and campaign levels. Just because certain search engines get more press doesn’t mean they should get more budget, unless conversion rates dictate it.
5. Segmenting User Behavior – Using click path tools, do you notice similarities in Ask.com paid traffic that is different from Yahoo? What about people who search on brand keywords? Visitors who
   have been to the site previously? You bet – there is no average user, why give them a single website experience? Personalize user experience based on what you already know…or are seeing unfold that visit.
6. Identifying “Influencer Keywords” – A
   2005 DoubleClick study showed consumers search anywhere from 2.5 to 6 times before making a purchase and refine those searches from generic keywords to brand or product names prior to conversion. When judging the success of your generic keywords like “mortgage”, “computer”, “car rental”, etc., it’s important to use WA data to find out if they do indeed bring converting users, even if it’s for that initial introduction to the site.
7. Identifying Conversion Latency – As previously mentioned, not everyone converts immediately. What is your same-session conversion rate? How many days pass before a visitor returns to convert? How many sessions does it take before conversion? Page views? Time on site? Don’t judge PPC success until the latency period has passed. Know your audience’s sales cycle and build that into campaign expectations and testing windows.
8. Finding Day-Part Opportunities – Sundays and Mondays will vary in conversion volume and rates, as will 9am and 9pm or MSN to Google. Turn your PPC spend dials up and down to maximize ad exposure; keep in mind “AdScores” penalize excessive bid/budget changes. We’ll save predictive modeling for a future post.
9. Hot Products, Top Converters – With a limited budget and possibly thousands of Product URLs, which product pages get the attention (detailed keyword lists, customized copy, page-level optimizations, budget share)? WA tools typically have a product analysis/comparison report to view quantity of orders, product page visits, revenue/order size, profit margin, conversion rates and more, by product. For most e-commerce companies, the 80/20 rule holds true; see what moves the needle (or doesn’t) with WA data
   and focus your limited resources where appropriate.
10. Landing Page Analysis/Bounce Rates – There are typically multiple landing page choices for your PPC destination URLs – home pages, category, sub-category, product pages, geo, seasonal promo pages, and more. Bounce rates and entry to conversion stats are immediate indicators of what is or isn’t working. Use A/B or multivariate tests to improve both page ‘stickyness’ and conversion
    rates.

Having WA access is major advantage for Paid Search optimizers – use it if you got it and keep in mind that these 10 tips are only the tip of the iceberg. The real challenge to using WA data to optimize our campaigns is gaining access. I’ll save that diatribe for another article, but a quick quote from Andy Beal sums it up well: “Too many clients guard their web data as if it’s the secret recipe to KFC. For us search marketers, it’s like navigating a plane through a thunderstorm without instruments.”

28-Feb-08 9:00 AM
Continued here: 
Using Web Analytics to Optimize PPC Campaigns

Popularity: 2% [?]