In a recent alert on Jakob Nielsen’s site, the “guru of usability” helps us understand the really important website analytics and how to interpret them better. He then helps us understand the ways in which to improve our analytics, particularly the dreaded Bounce Rate.

The bounce rate of a site is measured by calculating those who enter through any page and leave from the same page versus those who enter through any page and click-through to another page.

Recent research has shown that an increasing number of people are entering sites not though the home page, but through some deeper, interior page. This can be due to the increase of social bookmark sites like Digg and Del.icio.us, which points the web user to particular content. As a result, the bounce rate of most sites is going up.

To better understand one’s own bounce rate and how to reduce it, Nielsen recommends understanding the bounce rates of particular visitors. Alas, not all bounce rates are equal, just as not all visitors are equal.

There are basically 4 categories of visitors:

1. Those entering from the likes of Digg. These are the least important to you because they are a fickle bunch and will have unusually high bounce rates.

2. Those who enter from direct links from other websites. These visitors are in essence receiving a recommendation from some other site. People who follow these recommendations may not have been looking for your site or product directly. They have some degree of interest, but if the usability of the site is poor or does not match their expectation, the bounce rate will be high.

3. Those entering from search engine traffic (whether it be SEO or paid links) will have a specific interest in your brand and your product. They are actively searching and wanting to engage with your company. Nielsen state, “If they leave immediately, there is something wrong with your landing pages.” Check your usability, your copywriting, and don’t forget to modify keywords.

4. Loyal users are those that return repeatedly to your site. This is your core consumer audience. If they return repeatedly, they may only be checking for new content on the site. Upon finding it, they will engage longer with your site than many other visitors. As long as they keep coming back, it’s okay if this user has a low page count.

All in all, Nielsen recommends shifting your attention from the “unique visitor” as the gold standard for a site’s success. Because the majority of unique visitors will be of the #1 and #2 variety above. Instead, count loyal customers and convert them with new content, new products, new special offers just for them. And try your best to convert the unique visitor into a repeat visitor.

Make sure the site doesn’t have confusing navaigation and is light on the copywriting. Insure that there is a clear path for the visitor to follow and provide them with next steps. Don’t force them to guess where the special product or offer is, expose it.

According to a recent Wall Street Journal article about the US economy and spending habits, consumers at every rung of the socio-economic ladder are changing their purchasing behaviors. To better deal with rising food and energy costs, consumers are increasingly turning to the web for ways to save both online and offline. To make matters complex, online retailers are accustomed to seeing high visitor falloff or abandonment. In fact, according to Marketing Sherpa shopping cart abandonment rates are normally pegged at almost 60%. This challenge presents the need to better connect the online and offline world.

In one of my recent blog entries, I discussed the online-offline gap and the methodology used to test new techniques to shorten this gap in order to understand consumer behavior. In this blog entry, I present three techniques that can potentially shorten the gap.

Solution #1: Coupons (Online coupons and mobile coupons)

The recent spike in food and energy cost has driven US shoppers to use coupons more frequently. While coupon usage rates vary, the up tick is expect to continue beyond the short term (see article). To better understand consumers, some retailers have offered coupons in exchange for personal information, including an email address. The benefit of this technique is that once a retailer has the email address, they can use their analytics packages to track visitors from an offer in an HTML email to a website. This allows to retailers to identify and track anonymous users on the website.

The new challenge is that retailers are now focusing on introducing coupons in the mobile space. McDonald’s has recently initiated a mobile coupon campaign in Salt Lake City. The campaign provides McDonald’s with aggregate data for respondents, including their phone number, age, gender and zip code). While these may seem to be valueless, a consumer’s mobile number can actually serve as a unique identifier as consumer demand continues to grow (mobile subscriptions have reached a level that’s equivalent to half of the world population).

Solution #2: Click it and Pickup

Some retailers have implemented a purchasing program that allows consumers to place an order online yet pick it up at a nearby store. This feature entices consumers who normally abandon a site due to high shipping costs to complete the purchase (this is one of the top reasons shopping carts are abandoned). The neat thing about this solution is that visitors who are anonymously browsing the website will log in to complete the purchase and retailers can then track their identity.

To implement this feature, retailers need to tie their inventory management system to the web so that employees in the store can prepare the online order for pickup. To accomplish this, retailers need to establish a solid order management process which is actually harder to do than it sounds. Retailers such as Wal-Mart (specifically Sam’s Club) and Best Buy have rolled out these programs only to get spanked due to reports of incomplete orders or items being improperly packaged/prepared for pickup. Other retailers, such as Circuit City, have perfect the process by also attaching a guarantee. The additional benefit of an in-store pick up program is that it further grows sales.

Solution #3: Customer Satisfaction Surveys

According to a 2007 consumer behaviors survey by Accenture, the quality of service was the leading reason that customers abandoned a provider (this reason actually outweighed price by 20%). In fact, retailers such as Borders are relying on these surveys to better understand how consumer behavior is driving more sales. These surveys are commonly rolled out on sales receipts; retailers encourage customers to complete these surveys by offering a monetary prize (ranging from $500 to $1,000). While these survey engage the user after the purchase is complete (unlike the two solutions above), consumers can be identified when they provide their personal information to win the prize. By combining the consumer’s purchase history with their attitude (aka satisfaction survey) and their online behavior (website analytics), retailers get a more robust profile of consumers that they want to attract and retain.

More Than Three Solutions

The solutions above are only the tip of the iceberg as far ways that retailers can bridge the gap between the online and offline worlds. In addition to the above solutions, retailers that want to bridge the gap should consider investing in a customer relationship management (CRM) solution. A CRM allows the retailer to store the necessary data on consumers (transactions, attitude, personal info), analyze the information and build customer profiles for targeting.

Well it’s official. Two of my greatest loves (data visualization and real estate information) were married recently in this video. And what a beautiful couple they make – a powerful example of how even the most complex data sets can be communicated in a language that anyone can understand.

Speculativebubble, you fascinate me.

Man I love how Ajax, video, and Flash based Rich Internet Applications (RIA) are getting incorporated into the next generation of websites. I could talk for hours about the greatest and latest buzz around cool flash/Ajax websites, online games, rich modular experiences, integrated video, etc.; but instead I’m going to talk about web analytics programs we have in our tool box today and how you can use them to analyze all those cool technologies like you would any regular HTML site.

I recently heard someone complain about a Flash based tool they had that looked and worked great (well at least they thought so); however they couldn’t measure the effectiveness of the tool without investing in building custom analytics and reports. They’d invested most of their budget to ensure the tool had all the bells and whistles; however they couldn’t effectively realize the ROI on their investment.

I asked them why they didn’t use their web analytics program to analyze the effectiveness of the tool and generate reports much like any other website. They said the only stats they got were basic page view data like how many times the page that contained the Flash tool was accessed, how long people spent on the page, where they came from, etc. All the regular stats you’d expect from a page view analysis, however that didn’t tell them how users were interacting with the tool, which part of the tool they were using, if they were converted in the tool, the path/flow the user took, which section of the tool they were abandoning, etc. They thought they had to build a custom application that could provide the data their web analytics product couldn’t. They were surprised when I told them this wasn’t the case. A good web analytics product can provide all the data needed and more, you just need to know how to configure it correctly.

First let me explain why most people don’t think a web analytics product can track within a Flash tool. Most analytics products are initially configured to only report when a page is loaded. They show the Flash file only being loaded once each time the page is loaded and have no way to measure what the user did when using the tool. This is true for most embedded media (Flash video, Flash applications, applets) or pages that only load once that contain Ajax, show/hide DIV CSS Layers, etc.

Normally this is fine for HTML sites, however you can configure web analytics products that rely on JavaScript calls (like WebSideStory’s HBX) to track any element on a page even after the page has been loaded because you can call the JavaScript again using Flash ActionScript, Server Side Scripts (using AJax), or other event based JavaScript functions.

Most popular ASP based analytics products like WebSideStory HBX, Coremetrics, Omniture, etc., rely on JavaScript to provide the actual data rather than analyzing log files. Typically you place a piece of code on every page. When the page loads the code triggers some JavaScript that provides the page name, category/section, funnel/path, conversion data, etc., to the web analytics product.

Well what if you could trigger the JavaScript call from within a Flash tool, and provide whatever data you wanted to the web analytics product stating a different page name, category/section, path, etc. An actual page view is only recorded as such because the JavaScript passes the data to the web analytics product saying it’s a page view. In theory I can browse the homepage of a site, and a Flash movie on the page might call the JavaScript 50 times telling the web analytics product I’m on 50 different pages, however the reality is that I only loaded the homepage once. Once you think of a page view as any call to the JavaScript you can start wrapping your head around how you’d configure the Flash tool to provide all the data needed through the web analytics product without having to build a custom application.