October 12, 2007

A conversation with Avinash Kaushik, Web Analytics Guru

Avinash Kaushik is a leading expert in the new field of Web Analytics. His blog, Occam's Razor, is one of the most popular blogs on this subject. He has lots of other exciting things happening: he's the Analytics Evangelist for Google, author of the book Web Analytics: An Hour A Day published by Wiley, and most recently, is a co-founder of a startup, Market Motive, focused on spreading knowledge for Internet Marketing. He was kind enough to agree to an email interview, given below.

If you are interested or involved in Web Analytics, I guarantee that his answers will give you much to think about.


Q
- How did you get into Web Analytics? What is it about this field that attracted your interest?

AK - I ended up in Web Analytics by pure chance.

My former roles were in decision support systems, both on the business and technical side of the fence. The Intuit job, my foray into web analytics, was attractive more because of the people and the company.

But I had always been fascinated by the web and the job allowed me to put my experience in decision support with the fantastic piece of art that the web is.

At some level it was lucky to get into web analytics with no baggage or hang ups or having read any books, it allowed me to bring a fresh and completely different perspective to it.

Q - In your study of web site user behavior, what are some of the most surprising results you've found?

AK - I am surprised that even in 2007 given how pervasive the web is and how it is used that we continue to obsess on conversion rates, essentially solving for a minority of site traffic as if people came to our sites for just one purpose. That is so 1997.

I am frequently humbled by the lessons customers have taught me when we listen to them using surveys or multivariate tests or site visits. Cool and sexy is not always enough. Simplicity is the key. Solving for customers and bottom-line is possible. Having clear calls to action on all pages (especially on those where there is no "add to cart button") and the importance of solving for your customer personas (just look at www.newegg.com, no one will call it the prettiest site in the world and yet it consistently outranks www.apple.com and www.amazon.com when it comes to customer satisfaction!) cannot be emphasized enough.

Q - With the benefit of your deep background in this field, what do you think of the Google Analytics product: What are its strengths? Which types of companies is it most useful for? Which areas do you think need to be improved?

AK - I have just published a comprehensive review of all web analytics vendors - link: http://www.kaushik.net/avinash/2007/08/web-analytics-vendor-tools-comparison-and-one-challenge.html . Your readers might find that video helpful in understanding the industry, its challenges and what unique strength each web analytics vendor brings to the table.

In the video I mention two key strengths of Google Analytics:

1) Data Democracy: Google Analytics is a drop dead easy tool to use and presents a lot of complex web analytics data in a very easy to understand manner. Because of this it flips the traditional web analytics model were a few people in the company had access to the data and shared it with others. With GA you can give everyone access to the tool and they can help themselves.

2) Best of breed search analytics: The reports and segmentation options you'll find in Google Analytics to analyze your site's search data is really good. Perhaps it should not be surprising that a web analytics tool from a search engine is good at that. You don't have to tag your campaigns because of auto tagging which saves hassle and improves data quality. Your data is also imported and integrated and presented with some unique reports.

In terms of who GA is right for...... Google Analytics is right for any company that will benefit from the above two features. The nice thing is that unlike the past were you can rule tools in and out on paper, now you don't have to take a random person's, or a "guru's" opinion, on benefits of the tool. GA is free. Throw it on your site and try it for yourself and using your own data from your own site you can determine if it is right for you.

In terms of what needs improvement.... Currently GA provides 27 pre-built segments that you can apply to any of the 80 odd reports to get 27 times 80 sets of segmented data. But I am selfish. I would love to have even more flexibility when it comes to creating visitor segments that are most relevant to each business.

Q - Your blog, Occam's Razor is one of the most successful blogs in this field. What has blogging meant to you? Are there things you would do differently with the blog if you had to start over?

AK - My wife's opinion is that the blog is our third child. :)

When I started writing the blog a little over a year ago my hope was to have around a thousand visitors a month because that is how many people I thought were my core target audience. Yesterday the number of RSS feed subscribers were at 4,600 and there were 30,000 visitors last month. That in many ways simply astounds me.

These numbers also mean that I feel a deep sense of obligation to the people who read the blog. There is always a pressure to deliver the highest possible quality in the posts that my humble skills will allow.

The blog means the world to me because of the conversation that I can have with people from around the world (around 30% of the site traffic is international). All these wonderful people write comments and their own perspectives which I learn from and all these comments add to the conversation (on my blog visitors have written approximately as much content as I have written, word for word).

In terms of different..... I wrote a post at the end of the first month I think, I would not have written that in hindsight. But other than that I would not do anything different, the blog has managed to stay hyper focused on what my initial vision was and I think it works well.

Q - Even now, Web Analytics is seen as an afterthought in some web companies, rather than being an integral part of the business process. How do you convince these companies of its importance?

AK - I agree with you, it still exits in silos (both from organization and data perspectives).

At some level it really requires the business realizing the importance from the inside that matters. No amount of outsiders coming and pontificating can drive fundamental change.

If you are inside the company then you have an inside track to helping your company realize the value of web analytics. My advice would be to focus on two simple things in a very hard core way: 1) value the web can deliver to the bottom line and 2) value the web can deliver to your customers. The interesting thing is that the web can do both of those in an efficient and scalable manner, unlike any other channel.

And if you want to help your company do #1 and #2 you need web analytics. Start showing it in small ways (rather than trying to create a overnight revolution, those rarely succeed) and I assure you that your company will "get it". Few people can argue with profit and fewer still can argue making customers happy.

Q - You've just launched a new company, Market Motive. Can you tell us more about it? Who are your target customers? Will you be offering any free content, or is it all behind the "paid" curtain?

AK - Market Motive's mission is to focus on helping Online Professionals be massively successful through access to the latest best practices and insights from the best people in each discipline. We hope to deliver that by providing fresh and unique content that will only be available at www.marketmotive.com.

The initial areas of attention will be: SEO, PPC/SEM, Web Analytics, Conversion, Email Marketing, Online PR, and Marketing Processes. We will provide videos, podcasts that provide a unique way to learn, these will be complemented with live phone-in sessions were subscribers will be able to ask their questions and get them answered by the dream team.

The target audience is Professionals whose job it is to deliver for their companies in any / all of the above mentioned seven areas.

The content created at Market Motive will be available on an unlimited consumption basis to only the subscribers. All the faculty have blogs on which they are very active.

Q - What advice would you give to a small company that's just starting to get deeper into Web Analytics (beyond basic Page Views and Referrer URLs)?

AK - Use your web analytics tool to answer questions and not simply measure "KPI's".

Here are the three questions to answer:

1) Where are people coming from? (Referring URL's, Search Engines, Key Words, etc) This helps you infer intent and identify valuable sources of qualified traffic (by simply measuring bounce rate).

2) What do they do when they are on my site? (Content Consumption, Top Entry Pages, Top Visited Pages, Site Overlay etc) This helps you understand what people might be looking for and is it easy to find and is it what you want them to see.

3) What were the outcomes, both for you and the visitors?  (Revenue, Conversion Rate, Task Completion Rates, # of leads, Likelihood to Recommend, Customer Satisfaction etc) Your site should make a difference to their existence. Is it?

Q - What is the biggest mistake in the use of WA? What should people watch out for?

AK - Usually the weakest link is that website owners rarely sit down and define why their site exists and if that's the case then any metric will look like success. You should be able to answer in fifteen words of less "why does my site exist" and then be able to identify two metrics that help you measure if your website is delivering.

The other big mistake is that Marketers and Website Owners think that they represent their customers. This is mostly false. We, company employees, are too close to our companies to ever be able to think like our customers. If you want to know what your customers think of your website experience, ask them.

Q - What radical changes do you think we will see in Web Analytics in the next 3-5 years? Do you expect to see a big impact from the proliferation of Social Networks (like Facebook)? What about SEO and the increasing importance of search engine traffic?

AK - The web reinvents itself and that is what makes it fun. I think with all the web 2.0 buzz we are in the middle of one such transformative experience. Each such transformation like that requires the measurement methodologies to evolve as well. We are now trying to figure out how to measure ajax and flash and videos and podcasts and so on.

In the next couple of years I think web analytics will change radically. In the near term we will evolve to measure the aforementioned fluid experiences much more effectively. In the slightly longer term I am anticipating (and hoping) that web analytics will transform into business analytics. A way of life, a normal way of existence, just like other pieces of analytics that tend to have nothing special about them, and not an afterthought.

I have recently written about Web Analytics 2.0 (http://www.kaushik.net/avinash/2007/09/rethink-web-analytics-introducing-web-analytics-20.html) and how we already need to think differently to be more optimally competitive.

As regards to social networks and SEO etc I think that these types of wonderful things will never leave us (hopefully not). From a web analytics perspective we need to come up with more efficient ways to collect data, not matter which way life on the web evolves. I am optimistic that in the next few years we'll have that figured out.

 

Previous related articles:

      Top 8 Reasons to Implement Tracking and Measurement for your Web Site

      Web Design and the Scientific Method

       A conversation with Guy Kawasaki



July 26, 2007

Top 8 Reasons to Implement Tracking and Measurement for your Web Site

With the easy availability of full-featured, free online services like Google Analytics, an increasing number of companies are implementing Web Analytics tools for their web sites. Many of these implementations still focus on older metrics like page views and click-throughs. Although conversions and overall traffic levels continue to be important, today's Web Analytics tools - which have come a long way from the "Log Analyzers" of ten years ago - can provide a rich set of Business Intelligence metrics that allow web site managers to drill down to much greater depth in understanding user behavior.

In this article, we identify the core Business Objectives for a Web Analytics implementation.

Web Analytics Objectives

1. Traffic Measurement and Analysis
One of the primary goals of web analytics is to measure traffic quality, volume and engagement (e.g. time spent on site ).
Traffic can be segmented by source, into three categories:

  • Referrals from other web sites and from marketing campaigns
  • Free (organic) traffic from Search Engines, which depends on the quality of content and on SEO tactics
  • Paid (AdWords) traffic from Search Engines

2. Measure and Optimize the Effectiveness of Conversion Paths
This is the usual definition of web analytics; it includes an audit of key navigation paths, calls-to-action, pricing, discounts and the power of the overall sales pitch. You can also measure the effectiveness of individual web pages.

3. Test and Optimize Conversion Enhancement programs
Closely related to the previous item, this goal is all about enhancing revenues from a current buyer, by optimizing upsell and cross-sell strategies. It answers the questions: "How well do you encourage users to buy more? How often do you get repeat buyers?"

4. Measure "Bounce Rates"
This is one of the simplest and most important metrics, yet it is often neglected. This metric focuses on discovering which pages on the site cause users to drop off. This is a critical point of analysis - it can highlight deficiencies in the web site, navigation or content.

5. Gauge the Effectiveness of External Marketing Campaigns
Web site traffic analysis can provide valuable feedback about external Marketing campaigns: by source, medium (email, web page, print, blog feed) and campaign. It can be used to test various forms of advertising.

6. User Segmentation
A site audience is rarely completely homogeneous; it is usually made up of several distinct constituencies. A highly effective way to enhance the user experience is to segment users into groups by behavior and re-orient the site for each group, with special navigation and emphasis.

7. Day-parting
This is segmentation based on external factors not related to the user herself; e.g. time of day, geography, referring source, organic vs paid, and so on.

8. Drive Design and Usability Decisions
Many companies make site design decisions "blindly", without measurement or testing. However, instead of trying to guess what users will like, we can directly measure the effectiveness of various web design and usability decisions, individually and together, using multi-variate analysis and A/B testing. This means that we can improve a web site in a systematic, measurable way, while minimizing any adverse impacts.

Conclusion

As we've seen above, Web Analytics provides powerful capabilities to improve online sales and analyze user behavior. Which of the objectives in this list do you use? Do you see any that are missing from this list?



July 11, 2007

Dispatches from Searchnomics: Google's Avinash Kaushik on Advanced Web Analytics

[Things have been busy lately; I'm finally catching up on some older posts I've been meaning to get to ...]

I've written before (see: Google Analytics - take two , Bounce Rate ) about Avinash Kaushik - Author, Blogger and Google Evangelist. He's a recognized authority in the relatively new field of Web Analytics; his blog, Occam's Razor, is one of the highest-rated blogs on this topic. In his trademark style, Kaushik gave a highly entertaining and very informative presentation on Advanced Web Analytics at the recent Searchnomics Conference.

In his talk, he focused on Seven Tips that you can use Now! to implement and improve web analytics for your web site.

1. Join PALM! (People Against Lonely Metrics)
Kaushik began with the key point that one should never look at the data or chart for a single metric in isolation; when studying analytics data, one should always look at multiple metrics together [otherwise the metric gets lonely!]. For example, when looking at how many users viewed a single page or how many bounced - you want to look at those together, along with the site average, delta changes and indexed performance. Indexing metrics, especially, highlights the items that are working particularly well or badly. In this way, you can turn the metrics into actionable information.

2. Give your data Context
Associated with the first point, Kaushik suggested that you should look at all your data in context. You can compare any given metric or set of metrics to either the average values for your site as a whole, or to the same metrics during a prior time period. He used Google Trends as an example, showing how you can compare two companies at different points in time.

3. Segmentation Rocks!
He pointed out that a web site audience is rarely completely homogeneous; instead, it is composed of many users who can be broken down into different segments. It is important to partition the data into segments according to the type of user. For example, segments can help you compare adword results vs organic results; if the bounce rate for adwords for a given segment is high, you are effectively losing money!

Most important: web site improvement actions are always implemented for specific segments, never for aggregates.

4. Enter the Matrix: It's a Multi-Dimensional World
Since real-world marketing proceeds along multiple dimensions - not just web site traffic, but also Emails, Ad words and Campaigns - it's important to analyze the data using multiple metrics along all these dimensions, in order to optimize your spending and conversion rates.

5. Think Looong Tail. Everything.
Kaushik explained that all of these Analytics graphs - Clicks, Visitors and Budget Spend - have something in common: a large head and a long tail. Similarly, when looking at Keywords: the expensive, branded keywords are all in the large head, while keywords characterized as generic/category/"early bird" are all in the long tail.

Typically, according to Kaushik, a lot of the AdWords spend goes into the head; but if you have good SEO implemented, you should be highly-ranked in the organic results anyway, so there should be no need to bid on it. On the other hand, long tail keywords, which are usually a lot less expensive, are used by end users very early in their buying process; if you want to focus on new customer acquisition, these are precisely the users you would want to target.

A critical insight: Web Analytics should not just provide reports, it should provide solutions to business problems.

6. Web Analytics 2.0 is Qualitative
The key questions Web Analytics should be trying to answer, for each user segment, are: What is the user here to do? How easy or hard was it for her to do it? And, finally, was the user's problem solved?

The bottom line is to consider the Customer Intent, by looking at a variety of metrics. Looking at Conversion Rate alone will not be sufficient to do that.

7. Web Analytics is Testing! 
Experimentation and Testing is an integral part of Web Analytics; otherwise, decision-making degenerates to using HIPPO - the "Highest-Paid Person's Opinion". E & T is your one powerful weapon against HIPPOs: you take the best ideas everyone has, and run them through tests. Let the data show you which ones are the most effective and which ones are not.

Kaushik pointed out that Google has a Multi-Variate Testing tool called the Google Website Optimizer, which allows you to test multiple ideas at the same time without the need for any IT changes.

----

Related Reading
Search meets Web Analytics at Searchnomics Conference  by Jeremiah Owyang, where Jeremiah does an excellent job of covering an equally useful Web Analytics presentation by Eric Peterson of Web Analytics Demystified.



July 05, 2007

Bounce Rate: Rich Web Analytics from a Simple Metric

Avinash Kaushik is at it again. The Web Analytics guru, blogger and now, Google Evangelist, recently wrote a fascinating article over on the Marketing Profs Daily Fix blog. In the article, entitled Bounce Rate: Sexiest Web Metric Ever? , Kaushik examines a fairly simple and uncomplicated measure: Bounce Rate, and shows us how it can be useful in a variety of ways to analyze web site traffic and to improve the conversion rate.

He defines bounce rate and highlights its importance, as follows:

In a nutshell bounce rate measures the percentage of people who come to your website and leave "instantly".
...
Bounce rate measures the quality of traffic you are acquiring, and if it is the right traffic then it helps you hone in on where/how your website is failing your website visitors.

For the time- and attention-challenged, here is a very quick summary of his main points for measuring bounce rate:

  • Find the definition of Bounce Rate for your Web Analytics tool and measure it for your web site as a whole (as a baseline).
  • Measure the bounce rate for your traffic sources.
  • Measure the bounce rate of your PPC campaigns.
  • Measure the bounce rate of your top-trafficked pages.

Interestingly, in one of the comments for the post, he highlights specifically how Google Analytics can be used to track this data.

Overall, Kaushik's article is a comprehensive look at the uses of this type of data. This is especially useful because Bounce Rate is a fairly simple metric that is offered by most WA tools, including Google Analytics (which is free!). If you are interested in Web Analytics, then I recommend checking out the original article at Marketing Profs and the abundant comments on the post.

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