The reason is simple: The ecosystem within which you function on the web contains mind blowing data you can use to become better.

Your traffic grew by 6% last year, what was your competitor's growth rate? 15%. Feel better? : ) When should you start doing paid search advertising for tours to Italy for 2011? In May 2010 (!). What is your "share of search" in the netbook segment compared to your biggest competitor? 9 points higher, now you deserve a bonus! How many visitors to your site go visit your competitor's site right after coming to yours? 39%, good god! Where to do display advertisements to ensure you get in front of men considering proposing to their girlfriends (or boyfriends)? Go beyond targeting men between the age of 28 and 34, use search behavior and be really smart.

I am just scratching the surface of what's possible.

It is simply magnificent what you can do with freely available data on the web about your direct competitors, your industry segment and indeed how people behave on search engines and other websites.

The secret to making optimal use of CI data lies in one single realization: You must ensure you understand how the data you are analyzing is collected.

Not all sources of CI data are created equal. It is key that before you use the data that comScore or Nielsen or Google or HitWise or Compete or your brother-in-law shove into your face that you understand where the data comes from.

Once you understand that you choose: 1. The best source possible that is 2. The right answer for the question you are asking (which implies you have to be flexible!).

Here are the sources of competitive intelligence data.

#1: Toolbar Data.

Toolbars are add-on's that provide additional functionality to web browsers, such as easier access to news, search features, and security protections. They are available from all the major search engines such as Google, MSN, Yahoo! as well as from thousands of other sources.

These toolbars also collect limited information about the browsing behavior of the customers who use them, including the pages visited, the search terms used, perhaps even time spent on each page, and so forth. Typically, data collected is anonymous and not personally identifiable information (PII).

After the toolbars collect the data, your CI tool then scrubs and massages the data before presenting it to you for analysis. For example, with Alexa, you can report on traffic statistics (such as rank and page views), upstream (where your traffic comes from) and downstream (where people go after visiting your site) statistics, and key-words driving traffic to a site.

Millions of people use widely deployed toolbars, mostly from the search engines, which makes these toolbars one of the largest sources of CI data available. That very large sample size makes toolbar data a very effective source of CI data, especially for macro website traffic analysis such as number of visits, average duration, and referrers.

Search engine toolbars are a ton more popular which is the key reason that other toolbars data sources, such as Alexa, are not useful any more (the data is simply not good enough).

Toolbar Data Bottom-line: Toolbar data is typically not available by itself. It is usually a key component in tools that use a mix of sources to provide insights.

#2: Panel Data.

Panel data is another well-established method of collecting data. to gather panel data, a company may recruit participants to be in a panel, and each panel member installs a piece of monitoring software. The software collects all the panel’s browsing behavior and reports it to the company running the panel. Additionally the person is also required to self report demographic, salary, household members, hobbies, education level and other such detailed information.

Varying degrees of data are collected from a panel. At one end of the spectrum, the data collected is simply the websites visited, and at the other end, the monitoring software records the credit cards, names, addresses, and any other personal information typed into the browser.

Panel data is also collected when people unknowingly opt into sending their
data. Common examples are a small utility you install on your computer to get the weather or an add-on for your browser to help you auto complete forms. in the unreadable terms of service you accept, you agree to allow your browsing behavior to be recorded and reported.

Panels can have a few thousand members or several hundred thousand.

You need to be cautious about three areas when you use data or analysis based on panel data:

The panel methodology is based on the traditional television data capture model. In a world that is massively fragmented, panels face a huge challenge in collecting accurate and complete (or even representative) data. A rule of thumb I have developed is if a site gets more than 5 million unique visitors a month, then there is a sufficient signal from panel-based data.

Panel Data Bottom-line: For companies such as comScore and Nielsen panel data has been a primary source for competitive reporting they provide their clients. But because of the methodology's inherent limitations, recently panel data is augmented by other sources of data before it is provided for analysis (including for a subset of data you'll get from comScore and Nielsen – please check & clarify before you use the data).

#3: ISP (Network) Data.

We all get our internet access from Internet Service Providers (ISP's), and as we surf the Web, our requests go through the servers of these ISP's to be stored in server log files.

The data collected by the ISP consists of elements that get passed around in URLs, such as sites, page names, keywords searched, and so on. The ISP servers can also capture information such as browser types and operating systems.

The size of these isps translates into a huge sample size.

For example, Hitwise which chiefly relies on isp data, has a sample size of 10 million people in the United states and 25 million worldwide. Such a large sample size reduces sample bias (surprise!). There are also geographically focused competitive intelligence solutions, like Netsuus in Spain, that provide analysis from excellent locally sourced data.

The other benefit of ISP data is that the sampling bias is also reduced; since you and I don’t have to agree to be monitored, our ISP simply collects this anonymous data and then sells it to third-party sources for analysis.

ISP's typically don’t publicize that they sell the data, and companies that purchase that data don’t share this information either. So, there is a chance of some bias. Ask for the sample size when you choose your ISP-based CI tool, and go for the biggest you can find.

ISP Data Bottom-line: The largest samples of CI data currently available comes from ISP data (in tools like Hitwise and Compete). Though both tools (and other smart ones like them) increasingly use a small sample of panel data and even some small amount of purchased toolbar data.

#4: Search Engine Data.

Our queries to search engines, such as Bing, Google, Yahoo!, and Baidu, are logged by those search engines, along with basic connectivity information such as IP address and browser version. In the past, analysts had to rely on external companies to provide search behavior data, but increasingly search engines are providing tools to directly mine their data.

You can use search engine data with a greater degree of confidence, because it comes directly from the search engine (doh!). Remember, though, that the data is specific to that search engine—and because each search engine has distinct user base, it is not wise to apply lessons from one to another.

With that mild warning here are some amazing tools. . . .

In Google AdWords, you can use Keyword Tool, the Search-based Keyword Tool and Insights for Search.

Similar tools are available from Microsoft: Entity Association, Keyword Group Detection, Keyword Forecast, and Search Funnels (all at Microsoft adCenter Labs).

Search Engine Data Bottom-line:Search engine data tends to be the primary, and typically the best source you can find, for search data analysis. If you are analyzing data for your SEO or PPC campaigns and you find the search engine providing the data then you should instantly embrace it and immediately propose marriage!

#5: Benchmarks from Web Analytics Vendors.

Web analytics vendors have lots of customers, which means they have lots of data. Many vendors now aggregate this real customer data and present it in the form of benchmarks that you can use to index your own performance.

Benchmarking data is currently available from Fireclick, Coremetrics, and Google Analytics. Often, as is the case with Google Analytics, customers have to explicitly opt in their data into this benchmarking service. But this is not always true for all vendors, please check with yours.

Both Fireclick and Coremetrics provide benchmarks related to conversion rates, cart abandonment, time on site, and so forth. Google Analytics provides benchmarks for visits, bounce rates, page views, time on site, and % new visits.

In all three cases, you can compare your performance to specific vertical markets (for example, retail, apparel, software, and so on), which is much more meaningful.

The cool benefit of this method is that websites directly report very accurate data, even if the web analytics vendor makes that data anonymous. The downside is that your competitors might not all use the same tool as you; therefore, you are comparing your actual performance against the actual performance of a subset of your competitors.

With data from vendors, you must be careful about sample size, that is, how
many customers the web analytics vendor has. If your web analytics vendor has just 1,000 customers and it is producing benchmarks in 15 industry categories, it might be a hit or a miss in terms of how valuable / representative the benchmarks are.

WA Vendor Data Bottom-line: Data from web analytics vendors comes from their clients, so it is real data. The client data is anonymous, so you can’t do a direct comparison between you and your arch enemy; rather, you’ll compare yourself to your industry segment (which is perfectly ok).

#6: Self-reported Data.

It is common knowledge that some methods of data collection, such as panel-
based, do not collect data with the necessary degree of accuracy. A site’s own analytics tool may report 10 million visits, and the panel data may report 6 million. To overcome this issue, some vendors, such as Quantcast and Google’s Ad Planner, allow websites to report their own data through their tools.

For sites that rely on advertising, the data used by advertisers must be as
accurate as possible; hence, the sites have an incentive to share data directly. If your competitors publish their own data through vendors such as Google’s Ad planner or Quantcast, then that is probably the cleanest and best source of data for you.

One thing to be cautious about when you work with self-reported data. Check the definitions of various metrics. For example, if you see a metric called Cookies, find out exactly what that metric means before you use the data.

Self-Reported Data Bottom-line: Because of its inherent nature, self-reported data tends to augment other sources of data provided by tools such as Ad Planner or Quantcast. It also tends to be the cleanest source of data available.

#7: Hybrid Data (/All Your Base Are Belong To Us).

Competitive intelligence vendors are observing you from the outside. Any single source, toolbar or panels or isp or tags or spyware etc, will have its own bias / limitation.

Some, smart, vendors now use multiple sources of data to augment the data set they started their life with.

The first method is to append the data. This is what's happening in the case of Quantcast and Google Ad Planner, in both cases they have their own source of data to which your self reported data is added. The resulting reports are "awesomely good".

The second method is to put many different sources (say toolbar, panel, isp) into a blender, churn at high speed, throw in a pinch of math and a dash or correction algorithms, and – boom! – you have one "awesomely good" number. A good example of this is Compete or the DoubleClick Ad Planner.

Google's Trends for Websites is another example of a tool that uses hybrid data for its reporting (see answer #2 here).

The benefit of using hybrid methodology is that the vendor can plug in any gaps
that might exist between different sources.

The challenge is that it is much harder to peel back the onion and understand some of the nuances and biases in the data (sometimes mildly frustrating to analysis ninja's such as myself!).

Hence, the best-practice recommendation is to forget about the absolute numbers and focus on comparing trends; the longer the time period, the better.

Hybrid Data Bottom-line: As the name implies, hybrid data contains data from many different sources and is increasingly the most commonly used methodology. It will probably be the category that will grow the most because frankly in context others look rather sub optimal.

[Update:] #8: External Voice of Customer Data.

This is one often overlooked source of competitive intelligence (/benchmarking) data. There are several ways to use Voice of Customer data.

For starters various companies such as iPerceptions (like CoreMetrics, Google Analytics, Fireclick above for clickstream) publish Customer Satisfaction & Task Completion Rate (my most beloved metric!) numbers for various industries.

If I am in the internet retail game I can use these benchmarks to compare my performance:

Or I can dig deeper and compare my performance by the Primary Purpose segments:

Both of the above are from the iPerceptions Q4 2009 Ecommerce Benchmark report. You'll find other reports in the Resource Center.

With other sources like the ACSI (American Customer Satisfaction Index) you can get a big deeper. Just choose an industry from their site, I choose Internet Travel, and bam!

If I am Travelocity I am wondering what in the name of Jebus did the other guys do last year to have all those gains in Satisfaction where I got a zero.

And really what are those guys at Priceline eating! 5.6 points improvement just last year, 15 points over the last 9! Sure they started with a smaller number but still.

What can I, sad Travelocity, learn from them? From others?

In both cases above the intelligence came from a third party doing the research and giving you data for free.

But you can also commission studies, from the two companies above or one of thousands like them on the web.

Or you can do it yourself.

I just met a Top Web Company the other day and I spent $300 on 20 remote usability participants to go to the website of Top Web Company and their main competitor. I gave the usability participants the exact same tasks to do on both sites.

The scores were most illuminating (and embarrassing for Top Web Company). It allowed me to (without working at either company) collect competitive intelligence about how each were delivering against: 1. Task Completion Rate and 2. Customer Satisfaction.

You could collect your own competitive intel using UserTesting.Com, User Zoom, Loop11, or one of many other tools.

Or for even "cheaper" (and a bit less impactful) insights you can use something delightful like www.fivesecondtest.com. Upload how your pages, upload those of your competitors (or complete strangers not in your industry) and learn from real users which designs they prefer and what works best.

Hybrid Data Bottom-line: I love customers, I love Task Completion Rate as a powerful metric, I love VOC. Above are three simple ways in which you can collect competitive intelligence using Voice of Customer data and drive action perhaps even faster than the first seven methods!

[PS: Nothing, absolutely nothing, works better to win against HiPPOs than using competitors and customers!]

The Optimal Competitive Analysis Process.

A lot of data is available about your industry or your competitors that you can
use to your benefit.

Here is the process I recommend for CI data analysis:

Don’t skip the steps, and glory will surely be yours.

See the additional posts linked to below for types of analysis you can do once you choose the right tool [OR you can also start on page 221 of my new book Web Analytics 2.0!].

Ok now your turn.

Do you use a source of competitive intelligence data not covered in this blog post? Which of the above 7 is your favorite? Was there something surprising you learned in this post? What is one thing you would add to the critical analysis above?

Please share your tips, best practices, critique in comments.

Thanks.

PS:
Couple other related posts you might find interesting:

• Competitive Intelligence Analysis: Metrics, Tips & Best Practices
• Paris Hilton, Kim Kardashian & Telling Stories With Data
• Competitive Intelligence Analysis: Google / DoubleClick Ad Planner
• Competitive Intelligence Analysis: Google Insights for Search
• Competitive Intelligence Analysis: Google Trends for Websites
• Google’s Search Based Keyword Tool

The Definitive Guide To (8) Competitive Intelligence Data Sources! is a post from: Occam's Razor by Avinash Kaushik

I recently did a webinar for the Search Engine Strategies conference (I am doing the opening conference keynote at SES London and SES New York) and my Market Motive co-faculty member Greg Jarboe sent me this KPI via email:

"Your webcast was a big success. Your KPI questions per attendee was off the chart!"

I don't know why I had not thought of this wonderful KPI. So much better than # of attendees.

As always though context is king.

It could be a good thing ("you were great, engaged the audience") or a not such a good thing ("no one understood a thing you were saying, hence so many questions"). Only upon reading the actual questions could I figure out which case it was (mercifully case #1 for me!).

End of a minor web analytics lesson on going beyond obvious metrics and never, ever, never forgetting context.

Back to our story. . . an hour is too short a time to answer all the questions (even in a webinar just focused on attendee questions). So here is a small selection from the 80 questions I could not answer in the wide ranging webinar.

We will cover measuring success of SEO efforts on one web page, how to do search engine optimization for b2b websites, how to rank for highly saturated industries / categories / keywords, and which competitive intelligence tools do I use for search program optimization (and targeting display ads using search data!).

I hope you all find the answers to be of value.

#1. How do you measure SEO performance on a page level? I'd like to know how well my seo efforts for a particular pages have performed.

Every measurement question should start by taking one step back and thinking of goals.

In this case here are some obvious ones:

Now it is not hard to figure out how to measure performance! [Before you do any kind of measurement please consider going through the above exercise. It is simple, effective and works like a charm - not to mention allows to get going faster.]

Before you analyze do one small thing. Log into the Advanced Segmentation tool in your web analytics tool. Create a segment for Organic Search traffic. Sources -> Contain -> Google, Bing, Yahoo! etc. Save. Another way to cheat at this is to simply use Medium Matches Exactly Organic.

If your web analytics tool requires you to call the vendor to set up advanced segments or re-tag your site to get segments then switch. There are too many choices in the market.

Now log into whatever web analytics tool you use and drill down to the specific page you are interested in ("Top Pages Report" / "Content Title Report" etc). Apply the Organic Search segment to that report (in Google Analytics segments are on the top right, in other tools please refer to user manual).

More traffic, not that hard. Stretch the time period to six months (or some large date range – remember SEO takes time). What do you see? Nice and gradual up and to the right trends. Do your happy dance! Something's working. Now look down at the table under the graph that shows traffic sources. If you did your segment correctly you'll see just the search engines and how much each is contributing to your overall traffic. Does the distribution match your goals?

Ready for the next step? Click on Referring Keywords and now you are looking just at the keywords bringing traffic to this page. Do the keywords match the intent of the page? Do they contain keywords you were specifically targeting? No? Why not? On the other hand what are the surprises? Is the customer intent contained in the keywords telling you how to change / improve the page? Do it!

Indexing. . . I am a big fan of Google's Webmaster Tools because of the wealth of data available, if you are not using this free resource (no matter if you are a SEO or not). Bing's Webmaster Tools have also evolved a ton, please claim your account right away and dive in. [I have not had much fun with Yahoo!'s web master resources.] In either tool you are looking for how well your site is indexed (report: Your site on the web -> Top search queries -> Impressions), how well your pages are indexed and, my absolute favorite, which keywords your search results are showing up. You are checking to see if:

1. the pages you are targeting are being indexed frequently and

2. if your site is showing up for the keywords you were targeting.

You want validation that you are showing up for the set of keywords you are optimizing for (above) and that your pages are being recorded as being optimized for the right keywords (above the above :).

Success. . . I humbly believe that the biggest mistake most of us doing SEO make is that we are far too obsessed with ranking and meta this and that and how to work back algorithms etc etc. We should focus more on what was the business impact of our SEO efforts.

So in this context go back to your page report (from step 1 where you applied the organic segment) and look at the $Index [which is: (goal value + e-commerce revenue) / unique views of the page you are analyzing]. That is a crude measure how how efficient your page is being at converting. Of course look at our favorite metric bounce rate by keyword (that tells you if you can get people to give you one solitary click, the most primitive measure of SEO success).

If you truly want to kick it up a notch as a SEO please please please go to the Goal and Ecommerce / Conversions reports and apply your organic segment, stretch the time period, and report (aggressively) how well your SEO efforts are delivering value to the business.

Do it at a overall level, do it by country, do it by search engine, do it by specific keywords you were targeting. . . . and take two minutes to straighten your clothes because a new level of love and praise are about to be dumped on you by your company / client!

[Does the above seem like a lot of work even if it is straight forward? It is. I know we look for short cuts. There is no such thing in real life. But if you are willing to put in a little bit of sweat equity then you'll stand miles apart from your SEO competitors. Not a bad trade off, right?]

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#2. Is there a fundamental difference in SEO strategies for business-to-business sites vs consumer focused ones?

[It is worth pointing out I am not a hard core SEO, that would be Todd Malicoat, I just play one one TV! Think of below as my personal lessons from the front-line of doing this work to the extent my humble skills allow.]

The basic techniques you use to do search engine optimization between b2b and b2c do not change all that much.

Ok All that is the same, no matter if you are a b2b, b2c, b2a (business to aliens, yes they do exist!). Do all that first to make sure you are not coming to play the super bowl naked.

Here are a few things that are different with b2b. . . . .

* Some very effective SEO strategies like allowing users to add reviews and comments and extend the scope of the page do not work as well with b2b as it is a differ net type of engagement and experience with your customers. Well don't give up. You have many many white papers, though leadership papers, webinars, Big B2B Association publications where you contributed and more locked up in pdf or, much worse, behind a forced "give me your login" / "create a account" page. I am going to give you a false email, why not just give me the content, AND let the search engine index it efficiently after all you want people to consume the content.

Did I say already content is king?

* One of the most common issues with b2b websites is that they often have a very specific understanding of their space when it comes to how their potential customers search for information. This results in not speaking the same language (say keywords) as their customers. When I work with b2b websites I spend a lot of time in the AdWords Keywords Tool, Insights for Search, Compete etc analyzing keywords and search behavior in my category. This knowledge goes back into re-doing content, urls etc.

This is of course a good method for b2c as well, but it is significantly more important for b2b.

* Start a conversation. There will likely be a lot fewer individuals talking about you / your industry, a lot fewer tweeting and expressing their love (or hate). I get it. But conversation on your site and away from your site is key (obvious fact). Why not host a user forum on your website for current and future customers to come together and share their thoughts / ideas / complaints / rave about your competitors (scared?)? Why not seek out the few people who do talk about the industry on twitter and engage with them? Why not start a YouTube channel with a series of how-to videos? Why not, : ), start a blog? Not just to highlight your own pomposity and press releases but to really share and lift your industry (not just your company)? Why not become the destination for industry professional?

So few people in the b2b space bother to start conversations, why not use that to your advantage? Even if you can hook 100 people is that not more than worth it?

Three small things that I would prioritize higher when I work with b2b sites.

What do you do differently when it comes to your b2b clients?

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#3. When trying to help your rank in search engines. . . when you are in a saturated industry like health or travel insurance – how does the approach change or differ?

Two words: Long Tail!

When you say saturated most people mean that for the "top" keywords they are interested in there is too much competition. For example: "hotels in las vegas", "cheap health insurance" etc.

When there are a lot of players in the field it can be difficult to show up for the "head terms", especially if there are some strong players in the field. In these cases I have had a very positive experience focusing not on the head terms (terms for which there is a lot of traffic) but rather focusing on the long tail (usually key phrases that individually have little traffic but collectively these key phrases can deliver a ton of traffic).

So, if relevant for your business, try to rank for "california health insurance plans" or "california individual health plans" etc. Key phrases (not just words) that each have much less competition (and will likely deliver more relevant audiences).

You can use various keyword tools out there to identify these key phrases and then adapt your SEO strategy (pages, content, urls, etc) to focus on them. One way I use is to just type in competitor urls into AdWords Keyword Tool and then research what is working for them and adapt my strategy.

Targeting the long tail with SEO can be a bunch of work, hence I have recommended in the past that one effective and cheap way is to use paid search to monetize the long tail. But I can tell you from experience that it works. For example for this blog the top 10 (head) keywords bring in something like 5k visits and the long tail (around 25k keywords) bring close to 34k visits. All organic (I am not rich enough to afford paid search!).

One more bonus tip: Leverage "universal search".

Videos, pictures, downloads, offers, buttons, maps, uploaded menus, coupons, and on and on and on.

When you search for many terms relevant to me you'll see videos pop up, my book (uploaded into Google book search) show up with preview thumbnails, some of my flickr images and my twitter account and so on and so forth. For many of these searches I don't rank #1. But man do those listings (when triggered by the search engine's algorithms) stand out and grab the Searcher's attention. Often for competitor or big paid web analytics tool queries where I have a snowball's chance in a hot place of standing out.

It is ironic that most big companies (with so many assets to leverage) are pretty bad at this. So you win! :)

Also Google (I work there) Local Business Center is really good: http://www.google.com/local/add If you are a small business then this is one more important arrow to have in your quiver!

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#4. Can you look at your competitors sites in the analysis tools you have discussed?

Yes.

But first. . . . it is important to realize that you need to have two skills before you look at competitive intelligence tools:

If you meet the above two requirements. . . . .

I love using competitive intelligence tools because they give me a perspective and context that is simply missing from Omniture or WebTrends or CoreMetrics or the clickstream tools.

In the search context here are some of my favorite tools and what I use them for.

Insights for Search:

I adore I4S because it is perhaps the most comprehensive "database of intentions" thanks to providing us all with access to worldwide Google organic search data.

Use it to understand the latest trends in your category. For example: "How is interest in the computer security category (All Categories -> Computers & Electronics -> Computer Security) and what are the top 100 search terms and the fastest rising brand names / products / searches in that category?"

Use it to identify opportunities. "What states do people search for credit cards the most? What states do people search for Visa credit cards?" Oh look the states with really high credit card searches don't have really high visa card searches, maybe we should do some offline advertising!

Use it to time your campaigns. "When should I have started SEO and PPC campaigns for Italy Tours 2010?" In April 2009!! That's when people first started looking for them. Now go plan for 2011.

Helpful article: How to use Google Insights for Search.

Ad Planner:

This wonderful tool is really built to help you do better display advertising. You log in and you have the delightful ability to do demographic (male, female, age, education, income etc) and psychographic (baby boomers, extreme sports fan, household decision makers, luxury goods consumers, moms etc) segmentation. You can hone in precisely which websites most likely contain your desired audiences. Show them relevant ads and get clicks!

But in the search context there are two things that you use this tool for.

Type in any website you want, expedia.com in my case, and checkout the site and search affinity data:

[If you don't see the image above, turn off your ad blocker.]

"The affinity score estimates how many times more likely you are to reach an audience who visits a specific site or searches for specific keywords versus an audience on the internet overall." Source.

Sweet 'eh?

Second, click on the tab that says Search by Audience and then the Keywords Searched button and now you have an ability to use search behavior to identify audience pools.

To use the examples of my beloved Indianapolis Colts (go Colts!!!). . . . I have an ability to type in a bunch of related keywords (the tool suggests most used ones) and find out which websites are most likely to be visited by people who search for these keywords:

[If you don't see the image above, turn off your ad blocker.]

At the top are keywords I typed. On the bottom are most commonly searched keywords, I can choose these if I want.

I hit ok and then sort by Comp Index, to ensure I sort the data by the highest audience concentration (audience that searches for all things Colts in this case).

I can use this search and web data to identify where audience I am most interested in exists. I can use it to find out the keyword data for those sites. I can use this to identify sizes (visitors, page views etc) of those websites.

Nice right? Actionable too!

Helpful article: How to use Google Ad Planner.

Compete.Com:

Compete is a paid tool (and it only contains US data). I really love using it because of the wealth of search data it can provide, at an affordable prices.

[I have had a complimentary Pro account for the longest time thanks to the nice people from Compete, that might bias my opinion. Other than that I have no other affiliation with Compete.]

In context of Search I use the data for. . .

1. Identifying what are the top referring keywords for any site that I am interested in:

Above data for www.clickequations.com (the paid search analytics company I am on the advisory board of). Of course when you log in with a paid account you would see rest of the data like paid and natural search split for each keyword and time and what not.

Craig will not be happy that he ranks only #12 on the keyword list! :)

I can either use this data to go after keywords that are not currently referring traffic to ClickEquations (more for me!!) or I now know what keywords I need to target to take ClickEquations down in my quest for world domination! Ha!

See how focused you can be with data?

2. Identifying share of search for a keyword:

In this case I would like to own the pear fruit market, though at the moment I only own two trees. So I go into Compete to find who my current competition is (above exact match data for query "pears"). I can get lots of details about volume, paid and organic share, what percent of traffic comes to a site from that keyword, etc etc.

Now that I have a benchmark I can go about my super awesome kick butt SEO efforts and one way I know I am winning is to check this report in a month or two (or three weeks after whenever I think I am done). If I show up here I know I am having a impact.

These are just three of the many tools I use. There are a whole lot out there that sometimes give you similar data to the above three, or often give you a lot more. Just remember that there is a lot you can learn from what is going on in your ecosystem and at your competitors.

Ok now your turn.

Got a couple tips you want to share with us about how best to do SEO for B2B sites? How would you measure success of SEO efforts spent on a page on your website? Would you use any of the four ideas I have suggested? Care to comment on how to do SEO for crowded industries or for keyword categories where one or two players seem to dominate? What is your favorite search competitive intelligence tool?

Please share your tips / best practices / comments / critique.

Thank you.

Dear Avinash: Search / SEO Metrics & Analytics Questions + Answers is a post from: Occam's Razor by Avinash Kaushik

As we spring to action full of passion I wanted to share with you all a short list of things that will expand your little world of online marketing & web analytics.

We all have a tendency of getting caught in a rut, using the same tool to do the same things and spew forth the same data. Change is hard, even if we know that we should be executing a multiplicity strategy to win in the web analytics 2.0 world.

Before all the excitement of the new year wears out, here are five simple things I would love for you to try so that your company will have a glorious truly data driven 2010!

#1: Don't suck.

Seems obvious. And yet in our quest for ever more hard problems to solve we forget that the number one goal of every website is not to suck. Especially at the really simple and basic things.

At a recent conference there were three keynotes.

One was extolling the wonderfulness of their multi channel campaign tracking. When I went to their website it was a 100% flash website with a constrained small size where it took too much looking to click on anything and then too much scrolling to read anything and unclear calls to actions (if any). That's sucking. No amount of great multi channel tracking will save this company, they suck at the basics.

The second was about predictive analytics and how using massive integrations between online and offline databases they had accomplished some really cool reporting of data (and make no doubt the IT work done over 18 months to accomplish this was cool). Their home page is a mess. 24% of the content covers what any visitor might want, rest is the company shouting at you (in many annoying ways). That's sucking.

The third was about how to create data driven cultures and how this person had created a impressively big cross functional team across multiple countries and standardized on Omniture after a lot of work over two and half years. I did a search on some of their products and they did not have page one search listings (on Google or Bing) for what should be their head terms. (That's sucking.) They did have PPC ads, which I click on the ad for specific product they land me on generic nonsense pages. That's sucking.

I share these stories to illustrate vividly how we in the web analytics world get lost in our data and Omniture and Google Analytics and reporting and lose sight of the the basics and the customer experience.

It is important to realize that if you suck nothing else matters. Not your api driven integrated massively multi channel attribution analyzed campaign lifetime databases. That is not going to save you or your company.

Before you attempt the hard make sure that you do all the standard stuff to ensure your company has a fighting chance to win.

Here are some tips to inspire you:

• I LOVE looking at the bounce rates for the top 20 landing / entry pages to the site. Find the losers, fix 'em. These guys are so bad they could not even get one click from the visitors.

• Sit down with the owner of the top ten pages to the site and look at them. I mean really look at them and ask this question: "What the heck are we trying to do with each page?" Make sure there is a clear answer (and a match between Customer Intent and Webpage Purpose).

• Check the load time of your important pages. Use something simple like: www.WebSiteOptimization.com Or whatever complicated tool you have.

• Sign up for your websites campaigns using your personal email address. See how the emails look. Relevant? Personal? Click on the links, what to you see on the landing pages? Fix!

• Create a funnel for your cart / checkout / lead submission process. Find the biggest abandonment page. Fix it.

• Ask your Finance department where most money is being spent on the web. PPC? Affiliate? Display? What? Take a week to segment that data and find out how to save 10% of the cost.

• Count the number of links on your main pages. I mean count them. There are 98 links on a travel site I am looking at right now, on the page for a hotel in Chicago. 98! This is a top site.

  What are the analytics people doing if they are not helping the product page owner figure out how to kill atleast 50% of those links on a product specific page. There should be one link: Search for Hotel or Make Reservation! Do this for your site.

• Fix the 25 things Dr. Pete lists in this delightful checklist: 25-point Website Usability Checklist.

There are so many ideas. I hope that before you go for massive web analytics glory that your use your wonderful powers first to make sure your site and customer acquisition strategy does not suck.

PS: Bonus tip: Make sure you visit your website once a week, atleast.

#2 Learn basic statistics.

The days of tools and reports simply puking data out are rapidly reducing. No longer can tools or "analysts" just puke 15 metrics on a report and hope to survive.

Web Analytics tools are starting to become smart (see: Analytics Becomes Intelligent). Data is starting to truly get numerous.

For all of the above reasons it is becoming ever more important that you are know atleast Statistics 101. You don't have to be armed with the knowledge of how to create various models or be able to jump into SAS and get naked with it. But you are going to have to know what a mean and a median and r squared and standard deviations and Z scores and confidence intervals and all that lovely stuff is.

If you have not been exposed to statistics perhaps you can take a class at a local community college or university. Many employers will pay for ongoing job relevant education.

Alternatively get one of the simpler books on the topic and immerse yourself in self education. Regardless of if you are a novice or an expert I think one of the best books to start with is The Cartoon Guide To Statistics ($13). A cartoon book? Yes. It is quite good.

Once you know statistics 101 you'll find that you'll think of data analysis differently and you'll get better at finding that proverbial needle of insight in the haystack of data. Knowledge of statistics is a key arrow to add to your analytical skills quiver.

Hello statistical significance!

#3 Try one (or two) new usability / VOC tool/'s.

My passion for the customer is, as they say, legendary!

Part of it is the humility I have developed at the powerlessness of clickstream data to answer all the needed questions. Part of it is that there are just so many darn good options out there to listen to our customers.

So this year why not try one of the newer more powerful and yet cheap usability analysis tools?

Here are some tools that are pretty cool and unique:

• Five Second Test. I absolutely love the idea of collecting "first impressions" from current customers, employees or just randomly selected people. Within thirty seconds you can take a screenshot of your lovely home page or landing page, upload it and for free get feedback from real people.

• 4Q / Kampyle / UserVoice. Each of these tools does something completely different, and yet each allows people to type things that you can read and be wow'ed or saddened by. Why not try one of these tools this year and truly get in touch with your customers and a real and meaningful way?

• UserTesting.com. You are not a small enough company, or a big enough one for that matter, to do usability testing. This is usability testing for ultra cheap, $29 per person. Set out the tasks, identify your audience, test happens, you watch the video and read comments, you cry, you fix things, you become rich.

  Also checkout Feedback Army.

• WebSort / OptimalSort. The information architecture on most website is terrible and the reason is that company employees create it for themselves. A great option to hear from the customers was to do card sorting studies. Problem? Expense! Not any more baby. Both these tools are quite affordable, all online and in a fraction of the time it would take to do a offline card sorting study you can get the key data you need. Sweet.

You don't have to do all of the above. But you do have to listen to your customers.

In 2010 Consider trying just two tools listed above that you have not used so far. I promise you that you'll want to give me a big hug the next time you see me.

#4 Try one new competitive intelligence tool.

I practically have a illicit love affair with competitive intelligence. And I am not embarrassed!

If I ever come to see your company, or you see me presenting publicly, then you have seen me present data about your company / industry and then proceed to say nice / not nice things. There is just so much gold out there to be discovered.

Here are some tools for you to try, ideas for analysis you could do:

• Compete.com / Trends for Websites. I love the depth of data now available in both tools for free (even if you use just the free part of Compete). Index your overall performance against your competitors.

  Where do people go after they leave your site? What are the top five referrers for your competitor? What are the top sites that get traffic for the word love? All free from Compete.

  People who visit my site, what other sites do they visit? What are the things they search for? What's the difference between US traffic and India? All free from Trends for Websites.

• Google's Search-based Keyword Tool. If you have never explored the long tail for your website (if you are a medium to large site) using SbKT you might be committing a crime. If you have never taken a list of keywords AND the landing pages recommended by SbKT where you have zero impression share and given it to your SEO team then you should feel bad. There is so much here.

  [Learn how to use SbKT here: Monetize The Long Tail of Search.]

• Google Ad Planner. Some display / banner ads stink because they are just terribly produced and blink and annoy you with sound and do insane things when you move your mouse over them inadvertently. Most display ads stink because they are not relevant / well targeted. Make sure that is not your ads. Use the Ad Planner to hone into the exact sites where you can find your audiences.

  What sites are visited by: Men who are in the market for engagement rings. Women who are interested in the NFL. Young adults who are looking to buy net books. Affluent 100k+ folks or comic book buffs or brides to be.

  Now go buy advertising on those sites (from any ad network) and earn a higher ROI on your campaigns.

  [Learn more about Ad Planner: Competitive Intelligence Analysis: Google Ad Planner]

These four tools should keep you busy for a long time. Don't go at it all at once. Ask your boss's boss what his next 90 day priorities are, find the tool above that might have the insights, go on a honeymoon with it.

#5 Identify two new micro-conversions and goal values for each.

The road to web analytics glory (and a promotion for you) runs through the Micro Conversions path.

I am absolutely convinced that we don't get the love that we deserve from our company leaders because (even if we get beyond data puking) we rarely quantify the impact of all of work that the website is doing.

During Q1 make it your personal quest to identify two new micro conversions for your website (many ideas in the preceding blog post).

Now make sure, and this is absolutely key, you take one more step and quantify the economic value of each micro conversion (instructions and ideas: pages 159 to 162 in my new book Web Analytics 2.0).

That economic value will help you arrive at the number on the right, $83,848. That number will finally help you understand the complete value your website is adding to your business (only $21,454 is from the Macro Conversion). That number will allow you to measure your campaigns with a level of accountability that will be supremely awesome.

If you do nothing else on this list (I hope it does not come to that), please make sure you do this item. It is that important (especially if you are a non-ecommerce b2b government peaceful protest photo sharing website).

For the true Analysis Ninjas let me share one bonus item, one thing that will put even them above the top. . . .

Bonus: #6 Measure one thing that is "intangible".

The hardest thing to do in online analytics is to measure the intangible. How did people feel about the website experience? What was the positive brand lift? Did the unaided brand recall improve 60 days after the campaign (online or offline)? And more such questions.

Each is really hard to answer, one must think differently.

Here is a post with seven different strategies: Brand Measurement: Analytics & Metrics for Branding Campaigns.

As an Analysis Ninja go all out on three of them this year and take your business to the next level of measurement and insights.

Good luck ya'll!

Ok now your turn.

Care to share examples of sucking that you have killed on your websites? Got a creative use of statistics in your web metrics practice? Which is your favorite online customer listening strategy? Have you had success with quantifying goal values for your micro conversions?

What is your company's online, or online analytics, new year resolution?

Please share your thoughts via comments, thanks much!

Five Sweet Web Analytics Resolutions To Kick It Up A Notch is a post from: Occam's Razor by Avinash Kaushik

Even with a broken right hand I can't help but write this post!

The waterfall of positive feeling stems from the fact that this book was very hard to write.

I only had one job, at Intuit, when I wrote my first web analytics book. I now have several full time jobs, plus this blog, plus speaking around the world, plus a family, plus… so much more.

It took weekends of writing and nights of editing and days of research combined with practicing the preaching by doing oodles of analysis and, more importantly, the support of the most understanding wife in the world.

At the end of it all it is rather gratifying to see one's book at a bookstore, helps grasp the magnitude of the process. And there's absolutely nothing quite like hearing your five year old yell in a busy Borders bookstore: "I FOUND DADDY'S BOOK!"

This blog post is in three parts: The pitch. Request for help. A lovely contest [Contest closed now, thanks for the entries!].

You don't have to read the whole thing & skip ahead, but that would hurt my feelings. :)

Here we go. . .

The Pitch:

I invite you to consider buying my second web analytics book. It is not only the most current book on everything important and bleeding edge in Web Analytics, it is a labor of love that will help you transform your personal thinking and assist in revolutionizing your organization (big or small).

It is not a technical book, though it will make you technically dangerous. It is not just a business book, though every dna strand in this book is more about online marketing than online analytics. It is not a hard book to read, though it is brain food.

Here's why I think you'll love it:

Chapter 1 The Bold New World of Web Analytics 2.0

No dragging of the feet, the book starts with a bang by laying out the framework that will be the center of every company that will leverage data (qualitative, quantitative, competitive) on the web. It ends with a challenge to embrace Multiplicity – without this it's goodbye greatness.

Chapter 2 The Optimal Strategy for Choosing Your Web Analytics Soul Mate

It will be hard for you to find a more compelling four step process to choose the right web analytics tool for your company. Soul searching, questions to torture vendors with, comparing vendors, running a pilot and negotiating a contract, it's all in there. You be off to the races right.

Chapter 3 The Awesome World of Clickstream Analysis: Metrics

The thing I enjoyed about this chapter (I know I wrote it, but still. . .) was that the first half works really hard to evolve your critical thinking skills. I love that because we take too much for granted, now you'll be skeptical. A good thing. The second half shows exactly how to pick the best metrics for your org and, my absolute favorite (Page 64), how to diagnose the root cause of a metrics performance.

Chapter 4 The Awesome World of Clickstream Analysis: Practical Solutions

When people think of web analytics everything they think about is chapter 4, and yet you'll find so many yummy treats here. The best WA report, segmentation, site search, SEO & PPC analysis, email, rich media, cookies, data sampling. . . . I am out of breath!

Chapter 5 The Key to Glory: Measuring Success

If I have one jihad it is to massively convert every person who touches the web to focus on measuring Outcomes! It is the one reason we can't achieve the greatness we so richly deserve. No more! Glory will be yours!! B2B. B2C. Small Biz. Large Biz. Non-Ecommerce. We make love to 'em all! One thing you'll read here that you'll read no where else? Computing Economic Value, a concept that will liberate you.

Chapter 6 Solving the “Why” Puzzle: Leveraging Qualitative Data

Oh, oh, oh qualitative analysis!! I am a Mechanical Engineer with a MBA, a late covert to the power of understanding the super sexy "why" by leveraging lab usability studies, surveys, card sorts, online remote testing and more. You get a jump start. The thing you'll adore: Pages 190 – 192.

Chapter 7 Failing Faster: Unleashing the Power of Testing and Experimentation

Sure you've heard of A/B and multivariate testing. But do you know how to truly win the game? There is no technical mumbo-jumbo here, just the real deal and how to get testing right. The thing you might not know / realize the power of: Controlled Experiments. I am convinced this is God's gift to online humanity, you'll agree with me by the time you reach Page 208.

Chapter 8 Competitive Intelligence Analysis

The most magnificent advantage the web possesses: everyone's data is available for everyone else to use. If Hilton Hotels has the data for Choice Hotels why not use it to "crush" them (sorry Sarah!). This chapter shows you how. I think the thing you'll be surprised by is at the start of the chapter (Data Sources, Types and Secrets).

Chapter 9 Emerging Analytics: Social, Mobile, and Video

The chapter I had the second most fun writing. Mobile, twitter, blogs, videos etc are just so darned hard to measure and so much changes every few hours that I had to really really work hard to find the essence of each and then make specific practical measurement recommendations that will stand the test of time. It was hard.

Chapter 10 Optimal Solutions for Hidden Web Analytics Traps

This is a collection of major reasons I think people fail at web analytics, and of course I boldly try to share how to avoid that fate. Behavior targeting, dashboards, accuracy, data mining, predictive analytics, and, the thing you'll appreciate the most IMHO, five steps for intelligent analytics evolution!

Chapter 11 Guiding Principles for Becoming an Analysis Ninja

All my life learnings laid bare. . . this is where you, yes you, start to evolve from a Reporting Squirrel to an Analysis Ninja! No metrics, data pukes, guidance on creating every more reports. No, none of that. Rather… analytical techniques, tips and tricks to apply to your job, how to evolve your thinking to a higher level.

Chapter 12 Advanced Principles for Becoming an Analysis Ninja

The chapter I had most fun writing (and rewrote the most number of times). It deals with two of the hardest practical challenges we face in the field of measurement: multi-touch campaign attribution analysis and multi channel analytics. Both are very hard to get right, both have a ton of fud out there, it was fun to share my recommendations.

Chapter 13 The Web Analytics Career

The chapter I should have had in the first book. How to plan a career in web analytics (paths, salary, longevity), and how to then cultivate the right set of skills. If you are a leader then how to spot great talent, how to interview them and make the right choice.

Chapter 14 HiPPOs, Ninjas, and the Masses: Creating a Data-Driven Culture

Some might argue, rightly so, that the most elusive thing to accomplish is to truly bring data democracy to your organization. This chapter bravely hopes to help you do exactly that: excite people about data, remove organizational barriers, use data to change behavior, dealing with data quality, and creating data driven HiPPO's.

Convinced?

Nothing, absolutely nothing, in life is easy. But if you have the will and access to knowledge then that just might help you choose an optimal path, a path where your hard work will yield above normal results. That's my hope, and promise, with Web Analytics 2.0.

Jennie and I have decided to donate 100% of our proceeds from this book, just like for the first one, to two charities. This book benefits The Smile Train and Ekal Vidyalaya. We are very excited about that.

Request For Help:

As you all know my philosophy for this blog is eat like a bird, poop like an elephant. But if you are up for it I would love to ask you for a bit of help.

Recommend the book.
If you know someone who needs to turbocharge their online existence, please recommend Web Analytics 2.0 to them. Even in our hyper connected world, nothing works like a personal recommendation.

If you use a link please consider using: http://bit.ly/akwa20 That link has an affiliate code, all proceeds of which go to the above mentioned charities.

Review the book.
If you have a blog, website, twitter account, any kind of platform, it would be great if you could write a review of the book and help spread the word.

If you purchased the book online then please, pretty please, review the book on the store's website. Amazon. Borders. Target. Powells. Whatever you used.

Connect me.
I am very very bad at pimping. So if you know someone who is someone (or knows someone who knows someone) then please consider connecting us. Especially people outside our analytics / search circle. Authors. CEO's. Journalists. Influencers. TV anchors (or weather man/woman). Oprah (I can dream, can't I?).

Our world is separated by six degrees of separation, I am sure you know someone who just might consider helping me with my cause.

Share a picture.
I love getting to know my audience, and while your emails and tweets are pretty fun there is nothing like a picture.

I had a "Web Analytics: An Hour A Day Fan Mail" flickr group that has some incredible pictures from around the world, bringing my audience closer to me.

I would love to do the same again for my "Web Analytics 2.0: Fan Mail". Be as creative as you want to be. Babies. Cats. Posters. Cars. Places. Or the best, you. All would be welcome.

I will only post the pictures with your permission. Please send them to blog at kaushik dot net. Thanks!

A Lovely Contest:

[The contest is closed now. Winning entry details.]

Steve Cunningham invited me to be a part of a little "contest" he is running. The prize is a delight, you get to win a pack of seven books on online marketing & social media: Six Pixels of Separation, The New Community Rules, The Whuffie Factor, Trust Agents, Crush It!, Duct Tape Marketing, and Web Analytics 2.0.

How to win you ask? Two ways.

1. Answer this question in comments below: If you were to measure the success of a company's social media efforts how would you do it?

Pick any social media channel, or all. Only a short answer is required. The most innovative / interesting answer wins. No answer is too small or too simple.

[If you have my book already then my answers in the book to this question will win you major brownie points, but perhaps not the contest! :)]

2. You can get four more chances to win, if you want. Simply visit these blogs and answer a different question on each: Steve Cunningham, Beth Kanter, Tara Hunt, and John Jantsch.

Good luck!

A Word of Thanks:

This is from my book's acknowledgment page…

I would like to express my deep appreciation to the readers of my blog, Occam’s Razor. In approximately three and a half years I have written 411,725 words in my 204 blog posts, and the readers of my blog have written 615,192 words in comments! Their engagement means the world to me and motivates me to make each blog post better than the last. It is impossible to thank each person, so on their behalf let me thank three: Ned Kumar, Rick Curtis, and Joe Teixeira.

A very solid case can be made for the fact that neither one of my books would exist without you and your engagement and encouragement.

Gracias. Arigato. Ngiyabonga. Xie xie. Obrigado. Shukriya.

Web Analytics 2.0 Book: In Stores Now!! is a post from: Occam's Razor by Avinash Kaushik

"You know what… web analytics tools like Site Catalyst, Yahoo! Web Analytics, WebTrends, and yes even Google Analytics, are mostly glorified data pukers. Each tries to outdo the other in trying to collect ever more data and regurgitating it. For all the math they do, it is astonishing how little intelligence they have, how little actual smarts are applied."

Silence for a a few mins.

Awkward glances.

Then this: "What do you mean, and what can we do?"

Me: "I wish the tools would use an algorithmic approach to highlight the things an Analyst needs to know, give 'em some starting points. Why make people dig for hours?"

You have to hand it to the team at Google, you "provoke" them and they respond. Google Engineers truly rock!!

Today Last week the Google Analytics team announced a raft of sweet features that take the current functionality in GA, wrap a liquid hydrogen fuel tank on it and shot it into a higher value orbit. Take some time to learn more about how you put more power behind your analysis punch: Google Analytics Now More Powerful, Flexible And Intelligent.

In this post I'll want to share rest of the story, what came of the above provocation.

The first thing you'll notice in Google Analytics is a new cool ability to better identify the "known unknowns", i.e. we know what we want to know, but we don't know if and when it is happening.

The feature is, rather cutely, known as Custom Alerts.

Here's an example. Everyone tells me that Twitter is nothing but hype. But

[sidebar]
i started to write this post in preparation of the GA new features launch, unfortunately the next day i broke my right hand. that meant going to emetrics to do the announcement in a temporary cast, and of course no blog post. i had surgery this past thu. metal plate and some screws in, things will be normal in a few weeks.

i unfortunately still can't type the thoughtful teachable post i had in mind, rather here are two videos that tell you about two features i am really proud of. hope you'll love 'em as well.
[/sidebar]

custom alerts: identifying the known unknowns

video: 8 mins:

intelligence: identifying the unknown unknowns!

video: 16 mins:

love it?

i hope you had fun learning a bit more about these two cool features. promise me you are going to set up two segmented custom alerts today!

let me answer one question that might be top of mind: the features are rolling out to all accounts starting last thu, it'll get to yours any day.

it would be great to hear from you, please share your feedback, suggestions and critique via comments. thanks.

Analytics Becomes Intelligent. Hello Insights! is a post from: Occam's Razor by Avinash Kaushik

It is with immense excitement that I am sharing the news that I have just finished writing my second book!

Web Analytics 2.0:
The Art of Online Accountability & The Science of Customer Centricity

It is a long title ain't it? The good news is we are going to refer to it simply as Web Analytics 2.0.

In this post I wanted to share thoughts about the book, the process of writing it (and doing three rounds of edits!) and outcomes.

The Background

Since mid-2008 Willem Knibbe, my wonderful Acquisition Editor at Wiley, was very kindly encouraging me to update my (best selling!) first book, Web Analytics: An Hour a Day.

The "problem" was the book continued to sell at a nice rate and I was not sure what to update because 90% of the content was still current and relevant.

Still there was a lot of new stuff I had written, new models I had developed, new and more advanced techniques, new problems we were dealing with in the world and so on and so forth.

That lead to my proposal to Willem to write a new book that would use Web Analytics: An Hour a Day as a starting point. The second book would be an advanced book that would allow the first book's readers to truly become Super Analysis Ninjas, and for those that had not read the first book to have the finest possible immersion in web analytics.

And that's just what Web Analytics 2.0 is.

The 2.0 Book

The book's core philosophy is based on the framework you have seen me talk about on this blog. . . the quest to answer four key questions: the What, How Much, Why, and What Else. . .

The awesome thing about writing a advanced book is that I can start with a bang! No history and what not. It starts with: Here is how your world should look like and this is why its important, now let's get down to business.

That's by page 9. : )

And then it just keeps kicking it up a notch. Bam! Bam! Bam!

Like the first book this is not a book about Omniture or Xiti or Google Analytics. It is not a "press this button in the tool and then press that one" book.

It hopes to be brain food.

Here is how you should think. Here are the traps to avoid when picking key performance indicators. Here are the core analytical techniques you should apply. Here are a bunch of reality checks. Here is how to embrace outcomes, regardless of the size of business you have. Here is how to achieve higher highs with testing and by listening to customers (literally). Here is how you leverage your competitor's data. Here is how you becoming a true Analysis Ninja (step, by step, by step).

And none of that is even close to the coolest part of the book (see why I am so darn excited?).

There are so many topics I deal with each day that I have not had time to write about on the blog, all the things I practice all day long in the five jobs I hold.

The book gave me the impetus to write all that down.

So there are complete sections in the book that teach:

Why tracking the social web is such a massive problem.

How to measure success of blogs.

Meaningful non-crappy twitter analytics.

Mobile analytics! This was so much fun to write about.

Measuring rich applications whose primary usage happens with no internet connection.

And more such things.

But you might end up buying the book simply for Chapter 12, it covers two things that I think will rock your world:

1. Multi-touch campaign attribution analysis (dissected and presented in a way like you have not seen it any where, I think)

2. Multi-channel non-line analytics (practical tips, best practices, unique stories to inspire you)

Even after all that I was not completely satisfied. : ) There are two more new things to end the book. A complete chapter on how to start, nurture and advance a career in web analytics. The last chapter of the book is on how to overcome the hardest challenge of it all: creating a data driven organization!

The Writing Experience

This was a very hard book to write, in many ways harder than Web Analytics: An Hour a Day.

That's partly because this time around I had my full time job, my work with my start-up Market Motive, my advisory roles in three companies, my world travel to support my professional speaking career, my blogging (the only thing that suffered), and of course my family.

It is difficult to find time and energy to write a book with all that (and impossible without a magnificent wife who takes on three times a normal human's load to support you!). Especially to pull the writing and three rounds of edits in four months!

It was also hard because this is a much more advanced book with so many topics on the bleeding edge. It is hard to make sense of it all and understand it enough to apply a reality filter and then write something that people can apply today, and use for a very long time.

And yet it was a lot of fun to write this book.

I think that's primarily because with the first book I had no real sense for what the book would become, who it would impact, how far it would go.

This time around I have a much better sense for all that.

So many of you have written to me about all the ways the book has touched your lives. As I wrote this book that was constantly at the back of my mind. It pushed me to work harder and do better because I realized all the places it would go, all the people who will crack it open, all the expectations it had to meet.

I had this visual of all the people who might buy this book and how in some way something I wrote could have an impact on them. That was pressure, but it was also fun.

The Second Little Book That Could

Some of you know that my wife Jennie and I had decided that we would donate all the proceeds from the first book to charity. We had chosen The Smile Train and Doctor's Without Borders and split 50% of the proceeds between each.

My hope was that Web Analytics: An Hour a Day would sell enough for us to donate the $10,000 advanced we had received.

We have thus far received, and donated, 18 months worth of royalties from the book, approximately $70,000 (!!).

Not in my wildest dreams had I imagined that! And there is no way that we could have afforded to donate that much money.

In a very small way this blog and the book have helped other people in our lovely world. It has been an extremely gratifying experience for us.

With Web Analytics 2.0 we have decided to do the same again.

100% of my author proceeds from the book (and all the amazon affiliate sales) will be donated to The Smile Train and Ekal Vidyalaya.

Ekal Vidyalaya runs schools in remote locations that reach the poorest of the poor children in India. Without Ekal these children would have a very limited set of opportunities in life, if any.

When the going got really tough with this book the thing that kept me going was to produce a book that would have a big impact on people who buy it and a small impact on the charities Jennie and I choose.

The 411

The book can be pre ordered on amazon now, if you are so inclined.

It will be released mid-October 2009.

Wish me luck.

Web Analytics Books! is a post from: Occam's Razor by Avinash Kaushik