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How to Start a Tagging Project November 20, 2012

Posted by Joe Kamenar in web analytics.
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Tagging a website can be a very challenging process. If not done properly, you will end up with a lot of data being collected, but without any information. Also, the data you collect may be inaccurate and segmentation non-existent. It is very important to have a process or methodology to implementing web analytics tagging Some of what I have learned from working with various clients will be presented in this post.

Understand the Purpose of Your Website

When building out a new site or implementing web analytic tagging on an existing site for the first time, there is a process you need to follow. The typical way a new project gets done is that someone just decides to use Google Analytics, opens an account, gets their tracking code, sticks it on each page and then just waits for the data to flow through and reports to be populated. But the problem with that approach is that there is no clear value to the data you are getting, other than just knowing visits, page views, traffic sources, top pages and time on the site. Your goal as a web analyst is to be able to do the following:

  • Answer the business questions about the site
  • Provide measurement as to the effectiveness of marketing campaigns
  • Identify user bottlenecks in the site
  • Provide insight on how to increase the site’s conversion rate
  • Know who your users are
  • Know which content areas users are most interested in
  • Know if you are reaching the right types of users with your marketing
  • Determine how the company can save money by moving offline actions to online
  • And many more!

Business Questions

Before you can start defining KPIs and supporting metrics, you first need to know what business questions need to be answered. The most fundamental question is – “Why does your website exist?” Other general questions include:

  • What role does the site play in providing revenue or business leads?
  • Will the site be used to provide various audience segments with the tools needed to conduct the company’s business?
  • Will it be used to provide corporate branding information and build interest in your company’s product or service?
  • Will it be used to provide employees with information?
  • Will it be used to promote a social cause?
  • Will it be used to provide the first level of customer support, in an effort to reduce incoming calls to your call center?
  • Will it be used to keep customers loyal to your product or service?

Other more specific examples of business questions are:

  • How many unique visitors does our site get?
  • What percent of  unique visitors use the various tools on our site?
  • What percentage of visitors register on our site?
  • What are the user roles of our registered visitors?
  • What parts of the country does our traffic come from?
  • Are visitors reading important content on our site?
  • What is the login frequency of our registered visitors?
  • Is our site-search helping visitors find what they are looking for?
  • What are the best-selling products on our site?
  • How many users are using the self-service tools on the site?
  • How effective is our QR codes in attracting prospects?
  • What content is being consumed by mobile visitors?
  • What pages are not being viewed?
  • What is the subscriber email address saturation rate for each marketing channel?
  • What is our conversion rate by product vertical or country/region?
  • Which products respond better to email marketing campaigns?
  • Where on the site do potential customers decide to use the phone to complete a transaction?
  • How well is our cross-sell marketing working to put new products or services in front of existing customers?

These are just a few of the literally hundreds of different types of questions you may be asked about your company’s website. The best way to gather all of these questions is to simply interview the “stakeholders”. A stakeholder is someone who has an interest in how the site is working or how the site is being used. Stakeholders can be in departments such as HR, IT, Sales, Marketing, Customer Service, and others.

Align Data Collection to Support KPIs

Some organizations go a bit crazy when collecting web data. For example, I’ve seen a client set up a traffic variable that collects which checkboxes a customer would select as his shortcuts for a portal. Yet no report was being used with this information (nor would one have been useful). Enabling all the parameters you have available can increase the overhead on your analytics tool, and can sometimes cause you to hit limits on the amount of data that can be processed. If any data that you are collecting (other than out-of-the-box) data does not serve a purpose in relating to your KPIs (business goals), then stop collecting it. You can phrase this another way – If you can’t derive actionable insights off of any collected data, then don’t collect it.

Develop Your KPI Framework

Once you know the business questions and how to use your analytics package, you can then determine the site KPIs, as I had discussed earlier. For each business question, you need to define a metric that can provide a benchmark for that particular question. Another approach is to look at the key business objectives, then determine what goals and initiatives are needed to achieve these objectives, and then finally look at the KPIs. This is known as a KPI Framework.

Here is a sample KPI framework for a pharma company that uses its websites to promote their brands to health care practitioners (HCP’s), and to educate HCP’s on how specific diseases respond to treatments using their products. The end goal is to get these HCP’s to prescribe that drug or therapy to patients who have that particular disease or condition.

Key Business Objective Goals / Initiatives Sample KPIs
Motivate Physicians to Prescribe the Brands
  • Connect with more HCP’s
  • Increase participation in webinars
  • Increased engagement with brand content
  • Increase the number of motivated HCPs
  • Increase the number of HCP’s who request samples
  • Channel visits (Connect), response rate
  • Newsletter registration rate (Motivate)
  • Webinar registrations, registration rate
  • Percent of Motivated visitors
  • Request for samples (Motivate)
Increase engagement with the website over multiple platforms
  • Deliver content that can be consumed over mobile and tablet platforms
  • Increase  utilization of mobile apps
  • Keep content fresh to encourage return visits
  • Visit rate from mobile and tablet users
  • App downloads
  • Percentage of Limited, Light, Deep and Extensive engagements (Educate)
  • Return visit rate
Increase Reach and Marketing ROI
  • Reach more HCPs
  • Increase email response rate
  • Increase paid search clicks
  • Increase banner CTR
  • Increase use of social media
  • Decrease cost per engagement
  • Email link click-through (Connect)
  • Change in visits month-over-month from paid channels (Connect)
  • Change in visits from social media channels (Connect)
  • Change in cost per campaign visits

As you can see here, for this pharma company, their key metrics are – Reach, Connect, Educate and Motivate. A report would show the total number of visitors and percentage of visitors who fall into each of these categories, along with a visit report that shows what percentage of visits included a particular key metric. Let’s look at what these KPIs mean.

Reach – Sample KPI

In the global sense of your website and online marketing, there is the concept of “Reach”. Every time a person receives an email from your campaigns, or sees a banner at (including rich media ads), sees a branded paid search ad, reads a sponsored post in a Facebook news feed, gets a tweet where a brand/product or company name is mentioned, and so on, this is known as a Reach. Essentially, you have reached someone with your message. From a web analytics standpoint, this can be difficult to measure, as in most cases, web analytics measurements start when the visitor reaches your website. So, in order to measure Reach, you need to have access to offline data. This can include the number of banner and paid search impressions from your marketing agency reports, along with any stats from social media partners. One key item that I ignored is organic search page results. If your SEO is good, then whenever your company name and message appear to a prospect in an organic search results page, you have also reached this person with your message. You can get this data from tools by Google, Bing and Yahoo. Each of these three companies has their own suite of “webmaster tools”. Look into these tools to get a better picture of your overall Reach.

Connect – Sample KPI

Once a visitor responds to your company’s message via Reach by clicking through to your website, you have a “Connect”. A Connect is visit to your site that is not from where a visitor either types in the URL or bookmarks the site.  It is a visit that comes directly from a marketing campaign.

Educate – Sample KPI

If you want to measure the percentage of you visitors that you Educate, you would look for visits where particular success metrics (or goals) have been met. An Educate visit can be defined as one where two or more pages were viewed, or if an information PDF was downloaded, or a video watched. In the pharma world, videos can include topics like “mechanism of action”, clinical trial studies, or presentations from subject matter experts. If a visitor watches any of these videos, you better believe that this person has been educated on the drug and how it is used. You as an analyst can segment this metric based on new visitors or repeat visitors. It is the new visitors that you may be more interested in educating, as these visitors may be more likely to use your product or service than a visitor who does not take the time to get educated on your brand.

Motivate – Sample KPI

In the pharma world, an HCP does not purchase drugs right from the website. Unless, of course, the drugs are vaccines, which can be purchased by validated users. Some pharma companies allow validated users to request samples of a drug online, so this would be one example of a motivated HCP. Other actions that would count toward a Motivate KPI include registering to receive more information (get on the email list), subscribe to a newsletter, register for a conference or webinar, or any other action where the visitor provides personal information to the company. Thus, your “Motivate” KPI would be the percentage of visits where a Motivate action was taken. As a practical way to do this, you would create a visit segment where a Motivate event occurred.

Engagement Rate – Sample KPI

Another type of metric that can be used to determine how successful a website is in engaging the visitor is to look at an engagement rate. Here are some standard definitions that a pharma company uses when measuring how engaged their site visitors are:

  • Limited – Those who bounced (viewed just one page)
  • Light – Non-bounced visits that are of a duration of a minute or less in time on site
  • Deep – Visits that are between 1 minute and 5 minutes, or who engaged in a survey, poll, or who downloaded key content, or who shared an article via social media
  • Extensive – Visits that are greater than 5 minutes, or where they watched key videos or webcasts.

To determine the engagement rate for each engagement type, simply divide the number of visits for each type of engagement by the total number of visits. Depending on your analytics tool, you may be able to create visit segments for each type of visit, then track the number of visits in each defined segment, divided by the total number of visits.

Getting Ready to Tag

Once you have an understanding of the key business questions of the site and have created a KPI framework, you are ready to start developing the tags that will collect that data. However, before you can start tagging your website, you need to come up with an overall tagging process. Here are some of the considerations you will need to make:

  • Account Profiles
  • Metrics vs. Dimensions
  • Scope of Tagging
  • Report Design
  • Page Naming
  • Success Events & Variables
  • Tagging Persistence
    • Page-Level Tagging
    • Visit-Level Tagging
    • Visitor-Level Tagging
  • Standard Variables
  • Custom Variables
  • Variable Map
  • Creating a Tagging Strategy Guide
  • Creating a Deployment Guide
  • Debugging & Testing
  • Creating Test Cases

Account Profiles

An account profile (or report suite, as it may be called), is key to how your data will be captured and reported. When you create reports, you will be reporting on all data that is captured in that profile. Typically, a profile or report suite would contain data from one specific site, or country-specific site. You can also have data report into a second report suite, called a global, or roll-up, report suite, which looks at all of your site metrics in aggregate. Some reporting packages let you then look at pathing across the various sites, and de-duping of visits to each site, so you can get a total look at unique visitors to all of your sites.

Even within a single site, separate profiles can be used to segment what visitors do and who your universe of visitors is for different portions of your site. The best example is for a portal, where you have an area for non-registered visitors to use, along with a section that is only for those who are logged in. If you have each part of the site reporting to a separate account profile, then you will have an easier time separating the activities of these two types of visitors without the need for segmentation. Some of the key metrics you can then do on the authenticated side of the site is to look at what percentage of visitors or unique visitors use key features in the portal, along with knowing what the top pages or sections are, and perform other visit-based ratios, where you only want visits from authenticated users. Another good use of separate profiles is where your site has several versions (fixed web, vs. tablet vs mobile web), and you want to report on key activities on each platform.

Scope of Tagging

Depending on the complexity of your site and how your business team and UX (user experience) teams want to use the data, you need to come up with a list of high level activities or items to be tracked. In the case of the auto dealer finance portal, here is an example of the scope of tagging:

  1. Content Consumption
  • Top content groups
  • Top content sub-groups
  • Top used features on the site
  • Least used features on the site
  • Percent of dealers who use shortcuts
  • Percent of visits where site search is used
  • Percent of site searches that turn up no search results
  • Top 20 site search terms
  • Percent of visits where the FAQ is accessed
  • Dealer ID
  • OEM (Chrysler, Ford, GM, Toyota, Honda)
  • User role (management, accounting, finance, sales, service)
  • User Profile
  • Password Resets
  • User ID Management
  • Challenge questions
  • Top tools used
  • Retail sales & service guides
  • Management & reporting
  • Leased vehicle return guides
  • Messages & bulletins
  • By OEM
  • By region
  • Vehicle service contracts submitted
  • Vehicle credit applications submitted
  1. Site Navigation
  1. Login Frequency, segmented by
  1. Self Service Capabilities
  1. Access of Core Dealer Resources
  1. Audience Segmentation
  1. E-Commerce Activities

During your stakeholder interviews, you would typically learn this information. Another way to get this is to look at the business requirements document or site design document and determine how to measure each item listed. Then, filter this down to a key set of high-level tagging, like I did here.

Coming up later will be more information on tagging a website, including how to design reports and create a tagging deployment guide.

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Useful Web Analytics Definitions November 14, 2012

Posted by Joe Kamenar in web analytics.
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Here are some key terms and concepts that you will encounter as a web analyst. Depending on the type of industry you are in, you may find some of these useful in your analysis.

Metrics vs. Dimensions

In web analytics, you will often hear the terms “metrics” and “dimensions”, and it is important that you understand the difference between them. A metric is either a count or a ratio. A count can include visits, visitors, instances, time on site, page views, downloads, single-page visits, number of site searches,  orders, and other items that stand on their own. A ratio is a combination of two counts, such as pages per visit, conversions divided by starts (conversion rate), average order per visit, bounce rate and other combinations of two metrics.

Dimensions are items that you are measuring, such as browser type, location, pages, content groups, search terms, downloads, videos, and such. For each dimension, you apply one or more metrics. When you hear the term “drill down”, or “correlation”, you are essentially taking one dimension, and then looking at how a second dimension breaks down on the first dimension. For example, suppose you have two dimensions of interest – content groups and visitor types. You can do a one dimension report where you look at visits and page views to each content group, or you can do a two-dimension drill-down or correlation report where for each content group, you look at what user types engaged with that content group, based on the visit and page view metrics.

 

Logins vs. Visits

I see a lot of confusion in this area. Many business users assume that there is no difference between a login and a visit on a site like a portal, where a user must log in. They don’t understand why the two values can differ so greatly. Let me explain the reason for this confusion. A visit, in analytics-speak, is based on hits to tagged content on the website where no more than 30 minutes have elapsed between hits. If I am logged in to a portal, visit some pages or conduct some business, but then walk away from the site for 35 minutes, then come back and go to another page on the portal, I will be counted as a new visit. However, if the login security did not time me out from being logged in, I will not register a new login. Hence, we have one login, but two visits.

Conversely, I can come to a site, login, spend a few minutes doing my thing on the site, then log out. 10 minutes later, either me or someone else at my company logs in from the same computer. Now, I have two logins, but only one visit, as far as the analytics tool sees it. Keep in mind that there is no correlation between logins and visits, as each metric is tracked differently! It is rare that a company will build out their login sessions to match a web analytic session.

Key Performance Indicators (KPIs)

A KPI is essentially a key metric. Depending on your business, some key metrics can be “bounce rate”, “average order size”, “conversion rate”, cost per customer, “loyalty rate”, “banner click rate”, “self-service” rate, and others that give you an idea of how your site is meeting its objectives. For a pharma company I did some work for, their key KPIs focused on what percent of their visitors were “engaged”, “educated”, and “motivated”.  KPIs should reflect the key business goals of the site, and not things like visits, page views, pages per visit, visitors, and other basic metrics. KPIs need to be tied directly to site objectives, and be accepted by the organization.

 

Unique Visitors

A unique visitor is counted only once during a measurement period. This means that if I visit a site three times during a month, I will register as three separate visits, but only as one unique visitor. A lot of organizations obsess with the number of unique visitors. There is one big problem with the unique visitor metric – it is not accurate. A unique visitor is measured not always by sticking a cookie in a browser, but also by looking at the user-agent string. This is a combination that includes the browser type and visitor IP. Many business internet users (and some home internet users) do not have a “static” IP. They have what is known as a “dynamic” IP address, which means it can change during the week or month, as the internet provider assigns a new IP address from their pool. So, to your web analytics package, any single visitor can look like a different visitor each time they access the site. Thus, they are considered as “unique”, even if they are one and the same person, sitting at the same PC or laptop.

 

New vs. Return Visitors

This is typically a key visitor segment that you see in web analytic reports. It shows the breakout of new visitors vs. return visitors. A new visitor is a unique individual who made his first visit to your site during a reporting period. A return visitor is a unique individual who made a visit to the site during the current reporting and during a prior reporting period. Basically, a new visitor is someone who has never been to your site before, while a return visitor is someone who has been to the site over at least two reporting periods.

 

Bounce Rate

When a visitor comes to your website and leaves after viewing just that one page, this is known as a “bounce”. A key metric, known as the bounce rate, measures the percentage of time that a visitor bounces from any given page A high bounce rate is of concern when the page being visited comes from any sort of paid marketing, as the visitor clearly is not interested in going deeper into your site. As a web analyst, you need to identify your site’s landing pages and track the bounce rate over time for each page. It is critical to keep the bounce rate low for landing pages for paid media sources, as everyone who bounces is a wasted marketing spend, especially if the cost is based on a pay-per click model.

 

Time on Site

Many companies like to see “time on site”, or “TOS” as a key metric. I am not sold on this one. A visitor who comes to your site, looks at a page, then takes a call or responds to a text, while still on your site is not really spending that time reading content on your site or downloading key materials. What is important instead of the actual time on site metric is how this metric trends over time. If your average TOS starts to decrease, it can mean different things based on the purpose of your site. If in the past, a visitor had to spend a lot of time trying to find what they were looking for, but now, due to an improved FAQ or site search they find it quickly, the TOS may actually decline. Is that bad? Not necessarily. If your success metrics are showing an increase, then the decline in the TOS shows that your visitors are not wasting time looking for things.

 

Click-Throughs

When a visitor sees an ad or banner for your site, that is known as an “impression”.  When the person clicks on the link to get to the site, that is known as a click-through. The click-through rate (CTR) is a key metric for advertisers, as this is the percent of impressions that get clicked on.

 

Page Engagement Rate

A page engagement rate shows you how many times the page is viewed per visit. For example, if you have a page that had 1,000 visitors and that was viewed 1,500 times, then the page engagement rate is 1.5. Typically, topical stories or news articles may have an engagement rate close to 1.0, while pages such as your FAQ and other core pages may have an engagement rate that is higher.

 

Banner Fatigue

Banner fatigue is not a specific metric. Rather, it is a trend number that you need to monitor. If your site caters to mostly a fixed number of users, such as a business portal or physicians who are involved in a particular specialty, you will find that over time, users will stop clicking on banners on the site. These banners are typically internal banners that are used to cross-sell or promote other portions of your site. Essentially, you are measuring the click-thru rate of the banner, where you track the number of times the banner is displayed and divide that by the number of times the banner is clicked on. This rate is then monitored to watch to see when it just drops off. When you see this, you can recommend to your design team that this screen real estate be uses for a new promotion.

 

Page Views / Visit

One of the “out of the box” metrics that you see in a lot of web analytic tools is the average page views per visit. Many companies like to see this metric in their reports. It is the total number of pages viewed by your site visitors, divided by the number of visits to the site.

 

PPC

PPC simple means “pay per click”, which means that you get charged each time a person clicks on the link or ad to get to your website. Paid search is an example of PPC, as is sponsored links. Another term that is used along with PPC is “CPC”, which is the cost per click. This is how much the search engine charges for paid search results or sponsored links.

 

Referring Domain

If a person comes to your site, linked from another website, that site is known as the referring domain. When I look at referring domains, I like to look for things like coupon sites, deal sites, and other sites that I know nothing about that are bringing traffic to my site. Since you are not in control of these links, you can’t create campaign codes for these visits.

 

Natural Search

Natural search is also known as “organic” search. This is where your site gets listed in the search results on the main page, where you are not paying for placement.  The process of trying to optimize your website to rank high in natural search for various keywords is known as “SEO”, or search engine optimization. While most web analytic packages will show you visits from organic search, along with the keywords, you can’t tag an organic search visit with a campaign parameter, since the search engine is simply returning existing URLs of your site.

 

Direct / Bookmark

When a person comes to your site without the benefit of a referring domain or ad campaign, this is known as a direct visit. Since it is not possible to know if a person either typed in the URL or had it bookmarked in their browser, there is no distinction between the two. The percentage of these visits that are said to come from direct/bookmark is often under-reported, as many web users use the search bar to enter a website name, such as facebook.com. The first result is either a sponsored result or a natural search result for the site, and when the visitor clicks on the link, the analytics package treats this as a visit from paid search or organic search, and not a direct visit.

 

Cost per Click

This term is used in online marketing. Cost per click is also known as “CPC”. It is how much you pay, on average, each time someone clicks through from a link or ad to your website.

 

Cart Abandonment Rate

In e-commerce, products are often placed in an online shopping cart. If the prospect adds items to a cart, but never completes the sale, this is known as a cart abandonment. One of the jobs of a web analyst is to figure out why carts are being abandoned, and to make suggestions to reduce this rate. Some organizations also want to know the dollar value of abandoned carts to get an idea of how much money they are leaving on the table, theoretically.

 

Frequency of Purchase

Customers are often segmented by how often they make a purchase. This is known as “frequency of purchase”.

 

Average Order Size

The average order size (AOS) is the total revenue from online sales divided by the number of sales. Plenty of experimentation and testing is done on how to increase the AOS. Amazon does this by showing recommended additional products, or what customers tend to purchase together.

 

Self-Service Transactions

A self-service transaction is one where the user completes some action using the web instead of calling the help desk or using direct mail to complete the transaction. A few of my clients wanted to be able to measure call volume reductions as more of the customer needs are satisfied online. Self service transactions can include things like password resets, accessing reports that would typically be mailed, resolving problems using information from FAQs instead of picking up the phone and calling, obtaining a return authorization, or anything else where you want to encourage your site’s to use the site to conduct business instead of calling a person.

 

Media Site Metrics

You may hear your marketing team talk about media sites. These are typically news sites or portals where ads can be placed. Examples of media sites include CNN, Fox News, ESPN, Web MD, Yahoo, AOL, Huffington Post, and similar sites. Media sites typically make their money from ads on the site. Banner revenue is often based on the number of impressions the banner gets. Sponsored Links on pages earn revenue to the media site when a link is clicked. If you are the analyst for a media site, your managers may be interested in the number of page views, key content areas and what the key pages are where people visit.

 

Cross-Sell Opportunities

If you are in the financial services business (insurance, investments, banking, mortgages, etc…), one of the purposes of the site is to sell new products to existing clients. This is known as “cross sell”. One measure of success will be to know how often your site manages a cross sell. To do this, when a customer logs in, the backend logic of the site coding needs to be able to know what type of customer this is and what types of products the customer does not have. For example, if your company provides auto loan financing and mortgages, if a customer logs in to pay her bill, and this customer does not have a mortgage with the company, a banner can be displayed on the main page that promotes a refinance program or getting a quote for a home mortgage. When this page is loaded, a “cross sell opportunity” event would be set. If the visitor clicks through and takes a step toward getting a loan, such as filling out a mini-loan app or requesting information, then this would be considered as a cross-sell success.

 

Lead Generation

Many companies don’t transact business entirely on the web. For example, people typically don’t buy cars online, or things like sunrooms, health insurance, auto insurance, and other large-ticket products. Another example of this includes consulting agencies, accounting firms, law firms, financial planners, and so on. The website is typically used to generate a lead that then gets followed up on by a sales rep. So, measuring the number of leads generated is a key success metric, along with the campaigns that generated these leads. Ideally, you would either use campaign stacking capabilities in your web analytics tool to associate leads with the campaign string that brought the visitor to this point, and perhaps some sort of Lead ID that can be stored with your data, and assigned to the prospect. This way, if you have the right talent at your company, your company will then be able to measure the value that each of the campaign touches had in terms of revenue, and tie in the online behavior with offline revenue.

 

Registration Rate

This metric is often used to measure how well your site is doing in getting visitors to register for something. It can be a newsletter, email list  (for discount offers or special promotions), or anything else that gets the visitor one step close to being a prospect. Registration Rate is often used in B2B sites, where the purpose of the site is not necessarily to sell something to the visitor from the site.

 

Login Frequency

Another B2B related metric is the login frequency. It can be broken down to a series of frequency buckets, such as once or twice a month, three to ten times a month, 11 to 20 times, and so on. You would show what percentage of registered users login at each frequency. This will let you see how important your site is to your user base, with the goal of trying to move users from the lower-frequency buckets to the higher frequency buckets.

 

Download of Whitepapers

Many B2B sites offer something called “whitepapers” for download. A whitepaper is basically an in-depth report on some topic related to the business. For example, I have seen tag management system companies offer a whitepaper on how to measure the ROI of a TMS. A digital consulting company provided a whitepaper on how to use data appliances to simplify the “big data” problem facing many companies. The goal of putting out whitepapers is twofold. They can be given out without registration to anyone who wants it, with the goal of making a name for the company, or they can be offered only upon registration, with the goal of acquiring the prospect’s contact information for their marketing team. One mistake I often see is when a company requires registration in order to get the whitepaper, but simply provides the download link after registration, instead of sending it to their email address or making them verify the email by clicking on a link in the email to get to the download page. There have been many times where I have registered to get a whitepaper under the name of Mickey Mouse, with some bogus email address. If I can get the info without providing a valid email address, why should I? In any case, the downloading of a whitepaper should be considered as a success event and tracked accordingly.

 

Conversion Funnel

A conversion funnel is a key element of any lead generation or ecommerce site. It can either be page-based or event-based, and it shows the number of prospects who get to each stage of the conversion process. I am not going to go into detail on this one, as if you don’t know what a conversion funnel is, and you are a web analyst, you have bigger things to worry about! One key item to monitor in a conversion funnel is the dropout rate at each stage. If you can identify the problems that a prospect may be having at each step and make the necessary changes to improve the user experience, you can reduce the dropout rates and increase the overall conversion rate.

 

How to Measure ROI

As a web analyst, you win points (and perhaps a bonus and raise) by showing your company how to increase the ROI on your site, and how to measure that ROI. But, in order to do this, you need to understand what this all means. If you don’t already know, ROI stands for “Return on Investment”. It is the money that the company makes on money invested. Basically, it is the gain from an investment minus the cost of the investment, divided by the cost of the investment. Suppose for example, you have a baseline of an average of 10,000 orders per month from 434,000 visitors. That is a conversion rate of 2.30%. If your average revenue per sale is $50, your total revenue would be $500,000 from these visitors. If, through your analysis, you figure out how to increase the conversion rate to 3.1%, your resulting number of orders would be 13,454, for a revenue total of $672,700, or a difference of $172,700. If it cost your company $50,000 to make these improvements, your ROI would be ($172,000 – $50,000) / $50,000, or 245%. Note that this ROI was based only on the gross revenue, and does not factor in the cost of goods or services sold. In a true ROI model, you need to look at the net revenue after the cost of goods sold before being able to measure ROI. In the above example, suppose that on a $50 sale, your company makes $20. At a 2.3% conversion rate, the revenue on the 10,000 customers would be $200,000, instead of $500,000. At a 3.1% conversion rate, the 13,454 customers would provide a total of $269,080 in net revenue, for an ROI of 138%.

Summary

I hope this overview of some basic definitions will help you better understand what type of metrics to collect on your website and how to use these metrics to improve your site in meeting your organizations’ goals.

What is Web Analytics? November 14, 2012

Posted by Joe Kamenar in web analytics.
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Web analytics is the collection, measurement, reporting and analysis of data from your website, covering both site activity and user types. The purpose of web analytics is to better understand the following:

  • How visitors got to your website
  • How your website is used
  • How your site visitors behave
  • Who is visiting your website
  • How to measure the success of your site
  • How to increase your site’s conversions through a process called “optimization”.

Web analytics is also used to measure the effectiveness of advertising campaigns, by being able to associate “success events” to various campaigns. By integrating campaign cost data with success metrics, a web analyst can provide insight into how much it cost to achieve a success event. Some examples of success events include a purchase, user registration, newsletter registration, webinar registration, social media share, or other desired activity from your site.

Web analytics can also tell you how effective your conversion process is, and where you are losing potential customers or registered visitors. By setting up a “conversion funnel”, you can measure the percentage of visitors who fall out of the conversion process at every important stage in the conversion process. Based on this information, you and your web team can then look to see why you are losing visitors at these stages, and then hopefully better optimize the site to reduce this fallout.

Another key area of web analytics is A/B and multivariate testing. These are processes where you change one or more items on a web page or a campaign and compare the resulting metrics to a “control” group that receives the un-modified, or baseline, version. These types of testing are used to determine things like:

  • What types of templates work best
  • What types of copy or colors work best
  • What types of offers have a higher conversion rate

While there are specialized tools that are used for performing A/B and MV testing (Test & Target, Site Spec, Website Optimizer, Monetate, for example), you can do basic testing and analysis with many web analytic packages.

One of the biggest complaints I hear from clients is that they don’t trust the data they get from their analytics packages. A lot of this can be traced to poor tag strategy, poor tagging, and poor implementation. While in theory, getting analytics data can be as simple as slapping some Google Analytics code at the bottom of all the pages on your website, in reality, if you want to get meaningful data on which to make data-driven decisions, you need to do a lot more than that. You will need to identify major goals, minor goals, key events, visitor and visit segments, conversion funnels. and much more. One of the goals of this blog is to provide you with a broad overview into the many aspects of web analytics.

Stay tuned for more posts about how to become a better web analyst, for your company.

How to Track Email Open Rates March 4, 2010

Posted by Joe Kamenar in web analytics.
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The email open rate is a metric that is not always accurate, but seems to be one of the main metrics that those who manage email campaigns want to know. The accuracy can be off because in order to measure if an email is opened, a tracking pixel is embedded in the body content of the email message.  Some email reader clients turn off images by default, so unless images are enabled, the tracking pixel won’t register, and thus the email won’t count as being opened, even if the visitor clicks on any links in the email that go back to the website. Other issues, such as preview panes, also affect the accuracy of the open rate, but overall, analyzing the email open rate to look for trends or spikes can give you some insight to how well you are either segmenting or personalizing your messages or using enticing headlines to get people to open them.

Depending on your budget, you may or may not have an email service that gives you open rate statistics. If you think that a standard web analytics package will give you this, think again. Since most analytic packages only measure what happens on your website, they are not privy to knowing if a recipient simply opens your email, but does not click through to any links to get to your site. So, how do you measure the email open rate? If you have the ability to create a simple PHP, JSP or ASP page with a MySQL database, you can create a tracking system that can be as simple or as complex as you would like. You also need to know how to create the email subject and body content, and be able to send it using the “mail” function of your server. The body content will contain your email message, along with a line of tracking code.

To track email open rates, you need to embed the tracking code in your email body content.  Here is a sample that I used for a project I am developing:

<img border=’0′ src=’http://yoursite.com/track.php?MID=1111&SID=2222&#8242; width=’1′ height=’1′>

What this does is to call a PHP script titled “track.php” and it passes a couple parameters that are unique to the email. One is the Merchant ID (MID), and the other is the Subscriber ID (SID). For my project, I want to track the open rates for all my participating merchants when they send out emails to their subscribers. You can use any tracking parameters that you want, based on your needs. If you simply want to know who opened your emails, you can append this – ?email=email_address to the end of your php page name. Of course, you do need the ability to seed each email message with the proper email address. Or, you can simply use – ?campaign=campaign_name and can hard code this into the tracking tag in the email body. To do this, you may need to be using a “mail” client on your PHP, JSP or ASP server. I am not sure what you would do if you simply type up some content send out an email blast using your AOL or Gmail account. You would need to embed some HTML into the message to get your tracking to work.

Now, you need to be able to track these emails when  they are opened. To do that, you will create a simple script that writes your data to a simple database table. If you have never created a database table, you need to first learn how to do that, and that is beyond the scope of this post. Simply create a table that has an auto-increment ID field, plus a field for each tracking variable you wish to track. Then, create a simple script, such as this PHP script that I wrote that would be saved as “track.php”:

<?php
// This code is called by the tracking image call in the email.

// Initialize the database, using the protocol given by your web host:
$username = “dbo2666651512”;
$db_password = “98Qst38Z”;
$database = “db8765431512”;

// Set a variable that gets the current date and time (optional):
$now = time();
$date_added = date(“n/j/y”,time());

//Get the parameters from your email tracking code. These are my parameters:
$MID = $_GET[‘MID’];
$SID = $_GET[‘SID’];

// Database code. The table I created is named ’email_table’
mysql_connect(“db660.perfora.net”,$username,$db_password);
@mysql_select_db($database) or die( “Unable to select database”);

$query = “INSERT INTO email_table VALUES (”,’$date_added’,’$MID’,’$SID’)”;
mysql_query($query) or die( mysql_error() );
mysql_close();
exit;
?>

What will happen is this – when someone opens my email, the value for the Merchant ID ( MID) and Subscriber ID  (SID) are entered into the table named “email_table”. Ideally, you would want to first check to see if that MID and SID combination had already been entered, so you don’t duplicate the count if someone opens the email a second time. I also store the date added, so I can do an analysis of opens over time. Every times someone opens an email sent by my merchant clients, that combination along with the date the email was opened will be entered as a new entry to the table. With this information, if I also track the number of emails that were sent by each merchant, I can calculate the open rate (number of opens / number of emails sent). I could also append a campaign ID to the tracking code, so I can then determine which campaigns had better open rates for the merchant.

As long as you have the appropriate programming background, you can do any types of analysis that you wish on the data your store. The main point of this post was simply how to track the email open rates.

If you have been struggling with how to monitor email open rates, I hope this post will give you some ideas on how to do it and what you can actually track.

Understanding Multichannel Analytics January 29, 2010

Posted by Joe Kamenar in web analytics.
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While web analytics can give you a pretty accurate picture of how well online buyers respond to online marketing activities, it fails to tell you anything about how your online marketing affects offline purchase behavior and how offline marketing affects online behavior. If you website has a 3% conversion rate, what about the remaining 97% of your visitors? If you send out 50,000 coupons and get a 2% direct response rate, what about the other 98% of those who got the coupons? Is there a way to measure what they do? Enter multichannel analytics.  Multichannel analytics is a process where all marketing channels are analyzed to develop a more complete view of visitor behavior.

The Four Marketing / Purchase Quadrants

While there are four quadrants of multichannel analytics as outlined in the figure on the right, this post will discuss the two online/offline combinations shown in red. I will briefly explain some of the issues regarding multichannel analytics, some methods of tagging offline marketing and offline purchases, and show you some of the benefits.

The biggest problem with tying in offline efforts or offline conversions is lack of a common point between the two. You have two different databases, one of online data and one of offline data. Unless you have the equivalent of a primary key, you cannot join the two data sets together. Imagine a customer walking into your store or calling your order link and giving you their unique visitor cookie. That would make it fairly easy to tie in their online behavior to their offline purchase. You would be able to track what brought them to your website and what they did before coming to your store.  Unfortunately, in the real world we cannot tie these efforts together, so we need to develop solutions. Solutions for both of the red quadrants will be discussed as they relate to the multichannel analytics integration process, as shown in the following figure:

Tracking Offline Marketing to Online Purchases

There are two solutions to tracking your offline marketing efforts. The first solution is to use vanity URLs in your offline marketing efforts. For example, if you go to DellRadio.com, you will be redirected to a dell.com URL that has some tracking code. In the URL string, you will see a parameter titled “cid”, which is used by SiteCatalyst as a campaign ID. Thus, any purchases from visits to DellRadio.com will be credited to their radio campaign.

You can do the same thing with all of your offline efforts. Put vanity URLs on your newspaper or magazine ads, in your mailers and coupons, on billboards and other forms of display advertisements. Use specific vanity URLs in your radio and TV ads, and simply have your IT department do a “301 redirect” that converts these vanity URLs into coded mainstream URLs that your analytic tool can process.

The second solution to the offline marketing effort is to promote the use of tracking codes in your offline media such as infomercials. Someone watching the infomercial can either call the phone number or order online. If they enter the promo code on the website, you will know that the order was the result of the TV ad. However, what this will not tell you is the percentage of those who came to the site from the infomercial but did NOT buy. If you simply want to allocate revenue to an offline marketing effort, a promotion code will work well with any offline media that drives traffic to your main URL. Within your analytic package, you would tag the code entry as an event, and then look at the revenue that is associated with each event (specific code for each offline activity).

Tracking Online Marketing to Offline Purchases

Now that you have a way to track how your offline efforts work to get visitors to your website, how do you measure what they do when they don’t order online?

Capture Visitor Intent

If your business is both online and retail (physical store), you can measure intent to come to the store by tracking results of your store locator and directions links. By setting these as goals, you can then see what searches were done by visitors who have expressed intent to come to your store. To help capture the buyer while he or she is in the buying mood, some stores like Barnes and Nobles offer the ability to enter a zip code to see if a book of interest is available at a local store. If so, the customer can reserve it online and go pick it up right away. If you can offer this type of service, you need to tag this event so it can capture what brought the customer to the website, and be able to tie in the physical purchase (offline) to the online marketing that resulted in the purchase.

Generate Campaign-Based Coupons for Offline Purchases

It is also possible to have your website generate a unique coupon ID that can be for the particular product that was searched.  By creating an ID that represents marketing segmentation (campaign type, campaign source, media placement, keywords, and so on), you can store this information in both your analytics package and your store database. If you use a campaign translation file for your analytics platform, you will want to include the same campaign ID as a prefix to your coupon. The same coupon concept also applies to service businesses such as insurance, reservations, home and professional service businesses, etc…, where you give the prospective customer a coupon ID that they can use to get a discount. If your business takes orders or inquiries over the phone, you could have your site coded to include the coupon code next to the phone number on all pages. By tracking the redemption of these coupons, you can compute a click-to-store conversion rate, and factor in offline revenue that was attributed to specific online marketing campaigns. This will give you a higher ROI and perhaps provide justification for more web-related investment.

Implement Phone Number- Based Tracking

Unique tracking phone numbers can also be used to measure the impact of your online marketing efforts to offline purchases. A service like Voicestar provides these tools. You can place trackable phone numbers on your site, or use services like “Click to Call” and “Form to Phone” options. Their system has an API that lets you get data right out to your analytics tool and dashboard. Tracking phone calls is very important, as it is human nature to still want to talk to someone on the phone before making a purchase decision. When using a phone tracking service, or even if you have a block of your own phone numbers to use, it is important to not have the phone numbers as a part of the static content. The phone numbers need to be integrated with an algorithm that can associate the phone number with a particular campaign.  To further tie in the visitor to the phone number, a cookie should also be set that relates to the tracking source. Thus, if the visitor leaves the site, and comes back at a later time, the initial campaign that brought him or her to the site will still receive credit for the sale.

The biggest drawback to this type of campaign tracking is that depending on what level of detail you want for your marketing segmentation, you can end up needing dozens or hundreds of phone numbers. This can possibly become expensive and difficult to manage. Instead, you can create a 3 or 4 digit “extension” that is tied to a web-related order number, and when someone calls the number, the phone operator asks for the extension. This has no incremental cost to implement.

Another phone tracking service is offered by Mongoose Metrics. Their service integrates with most web analytics tools to create an automated URL postback after each call is made.  You can perform the same type of analysis, ecommerce conversion and segmentation that you would from any other page to be analyzed. You can see instantly how well your online marketing activities are generating online revenue.

There are many ways to implement phone-based tracking, and they all require integrating your site code with your analytics platform and your backend system. Edgewater Technology can provide you with the needed expertise to implement such a program.

Utilize Site Surveys to Understand Buying Behavior

Another way to gauge consumer intent is to use online site exit surveys. Companies like iPerceptions, ForSee and others can provide you with surveys that your site visitors can take regarding their online experience. You can ask about the likelihood of them making a purchase offline, and how much their online experience would influence their buying decision. On your online order forms and lead forms, you can also ask the question, “How did you hear about us?” in the form of a drop-down select or radio buttons. Include your offline marketing methods as choices. If the online traffic source is “direct entry”, then you can assign credit for the sale to the way the customer said they heard about your site.

Assign Values to Online Leads

If your business model is to let visitors fill out a form to be contacted by an agent or representative, there are a couple of different ways to tie success (revenue) to a campaign. Some analytic packages let you assign a dollar value to goal conversion pages, such as filling out a request for information form, a pre-application, or other form of customer contact. This dollar value is based on two factors – the average close rate of online leads, and the average dollar value of each deal. For example, if your company closes 15% of all of its leads, and the average deal is worth $500, then the value of each lead is $75 (15% of $500). Thus, your web analytics package can compare that value to the cost associated with generating the lead, and the nature of actions that lead up to it (pages visited, items downloaded, actions taken, and so on). If your analytics tool is set up to give credit to the first campaign touch point (PPC campaign, banner ad, referral site, etc…), you can still assign credit for the lead to the original campaign, even if the visitor does not convert until a later date.

The drawback with this method is that you are dealing with averages as far as the value of a lead. With average lead values, you cannot measure if a particular campaign brings in a higher-value customer than does another campaign. You can, however, get an average picture of how effective your online campaigns are right within your web analytics tool, without having to import any external data. For many organizations, this will provide much more insight than they are already getting about their offline purchases. It does require fine tuning the value you are using as the average lead value, based on your close rates and average dollar value of a new customer.

Track Campaign IDs with Lead Form Submissions

An alternative to this is to create an offline method of tracking online campaigns when a form is submitted. Your campaign code that you use in your web analytics package can be stored in a cookie and submitted as a part of your lead form. If all these leads are entered into a database, the campaign code can also be entered, and later receive credit for an eventual sale. The exact dollar value of the deal can then also be assigned to the campaign, just like for an eCommerce site. The integration of the online and offline data would then need to be done. Edgewater has expertise in merging online and offline data and can help you develop a comprehensive measurement system.

Reaping the Benefits of Multichannel Integration

So far, I have touched on some of the ways to “tag” offline marketing activities so they can be read by your web analytics program, and how to tag offline behavior that is due to your online marketing efforts. However, to put it all together requires access to all the data, both online and offline, plus an integration plan that combines strategy, technology, business logic, web analytics data, BI data, implementation, analytics and other disciplines to provide the desired results. Since this process cannot be explained in a blog post, your choices are to use vendor-specific tools or the expertise of Edgewater to work with your business to develop a true multi-channel analytics capability. As a result of such a capability, you will be able to obtain actionable insights, such as these (some are industry-specific):

  • Enhanced ROI – Once you are able to assign additional offline revenue to your online marketing efforts and online revenue to your offline marketing efforts, you will see a higher ROI, enabling you to justify additional spending on both your online marketing and other web efforts, such as site testing and optimization.
  • Retail Merchandising Decisions – If your business is retail, your online data can be mined to see what items tend to be purchased together, enabling your retail operation to group these same items together for in-store customers.
  • Upsell Opportunities – If your offline customers tend to respond to particular upsell opportunities when they call in or get called back, you can use this information to target similar online customers or visitors, based on data that can be stored in tracking cookies.
  • Re-marketing Intelligence – If you know what online customers come back to your site to buy later, you can use this knowledge to market similar products or services to your in-house mailing or phone list.
  • Additional Retail Outlets – If you see a significant request for retail outlets in areas that you are not currently serving, you can have the data you need to consider expanding your physical presence.
  • New Promotional Activities – If you know that your online visitors express an interest in finding a store based on looking at particular products that they want right away or that tend to be expensive to ship,  you can create geo-targeted online campaigns that are designed to get more buyers to your store. This can also work well for seasonal or event-driven items (snowstorm, hurricanes, extended deep freeze, etc…), where the need for a product is now, not 7 to 10 days from now. By tracking these click-to-store visitors, you will be able to measure the success of these campaigns.

Hopefully, this post will give you some insight into how multichannel analytics works, some of its challenges, how it can benefit your organization, and how a company like Edgewater Technology can help you put it all together.

10 Actionable Web Metrics You Can Use – Part 2 January 13, 2010

Posted by Joe Kamenar in web analytics.
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In Part 1 of this post, I discussed 5 percentage-based metrics that can provide actionable insight. In Part 2, I will go over 5 index-based metrics that can also provide insight to problems that may need to be addressed in order to maximize the value of your website.

1. Campaign Quality Index (CQI)

This index measures how well targeted your campaigns are at driving qualified traffic to your site. Suppose 40% of your traffic comes from a particular campaign, but the traffic only provides 20% of your overall conversions. The CQI for this campaign would be the percent of conversions from the campaign (20%), divided by the percent of visits from the campaign (40%). A value of one means that a visitor from this campaign is as likely to convert (purchase, sign up, request information, etc…) as from any other campaign. A value less than 1.0 means they are less likely to convert, while a value greater than one means they are more likely to convert. If the value is less than 1.0, then you need look at the reasons. You can break this down to individual search engines, or even keyword groups for each search engine, and for each individual banner campaign or other paid campaign you use, including referral partners. Perhaps the targeting is not sufficiently narrow, or the message is not being carried through the site (high bounce rate). You will want to work with your SEM team and landing page design team to make the needed changes. When you make improvements, you can track their effectiveness by watching the index change. Ideally, your analytics dashboard should be created so that you can see the changes over periods of time.

2. New Customer Index (NCI)

This index is focused on transactions (not revenue) from new customers. It is defined as the percent of transactions from new visitors divided by the site percentage of new visitors. For example, if 40% of your transactions are from new visitors, and 60% of your traffic is from new visitors, your New Customer Index is 0.67. A value of 1.0 means that a purchase is equally likely to come from a new or returning customer. A value less than one (as in this example), means that a new visitor is less likely to become a customer. A value greater than one means that a new visitor is more likely to become a customer than a returning visitor. Your goal is to strive for a value of one or better. If the value is less than one, you will need to look at factors that contribute to a low value. To do this properly, you would want to create a New Customer Index for each type of campaign you run, and compare that to those who come to your site from direct entry. A low performing index for paid search or banner campaigns can mean that you are not targeting the correct market, or that your search terms are not correlated to those looking to purchase your product or service. If the campaign is a banner campaign, either the message is not on target, or the media partner you are using is not attracting the correct demographic.

3. Return Visitor Index (RVI)

This index is simply defined as the percent of return visitors divided by the percent of new visitors. A value of 1.0 means that your site has an equal distribution of new vs. return visitors. A value greater than 1.0 means that your site is more likely to attract return visitors, while a value less than 1.0 means your site is more likely to attract new visitors. Depending on your type of site and your effort on attracting new visitors or keeping existing visitors, you can see how effective your efforts are and can then focus on how to improve this index. If your goal is to encourage repeat visits, then you need to be concerned with how fresh or relevant your content is, or how effective any email campaigns are in getting registered visitors to come back to your site. Any anomalies need to be investigated. As an example, I once saw a huge jump in new traffic in a client’s site that was the result of an email campaign, according to the analytics report. However, the email campaigns were only to registered visitors, so in order to have received the email, you would have first had to have visited the site. Thus, the email campaign visits should show up as return visitors. What happened is that the email contained an offer for a free exercise DVD, and the link URL was hijacked and placed on a few deal sites. When visitors clicked on the link, they were attributed to the email campaign, as the link contained the email campaign code! By looking at the RVI, I was able to see that there was an issue that needed to be addressed.

4. Branded Search Index (BSI)

Organic search can consist of generic terms that relate to content on your site plus searches that include your company name or your brand name.  Each can be of interest to your search manager. If more visitors come to your site from generic keywords or terms, it means that your site is well optimized for content. If more of your search visits come from branded terms, it means that more people are finding your site by your brand name instead of from non-branded terms.  You can track this by creating a BSI metric. This is defined as the percent of visits to your site from branded terms divided by visits from non-branded terms. Values greater than 1.0 mean that you are getting more of your traffic from branded terms, while a value less than 1.0 indicate that generic terms are winning the organic search battle. Depending on your search strategy and goals, you can use this information to help adjust your optimization or brand promotional efforts.

5. Site Search Impact (SSI)

Site search is very important for many types of sites. Visitors who come to your site may use site search to help them quickly find what they are looking for. If they find what they want, they may be more likely to continue to reach a goal, such as a purchase or lead submission. If they don’t find what they are looking for, they may just leave the site. The SSI index can tell you the impact your site search has on your revenue. To calculate it, take the per visit revenue from those who use site search, and divide it by the per visit revenue of those who do not use site search. “Per visit” revenue is defined as the total revenue or lead value for the month, divided by the number of visits. If your SSI index is greater than 1.0, this means that your site search is making you money, compared to those who do not use search. If the index is less than 1.0, it means that your site search is costing you money, meaning those who use site search are less likely to either make a purchase or become a lead. This can be the result of not getting desired results from the search, or result pages that don’t satisfy your visitors’ needs. To solve this problem, you would then need to dive deeper into your site search report to identify and correct the issues.

Hopefully this two-part post on 10 actionable web metrics you can use has given you some insight into how to make your web analytics program more actionable. While some of these metrics are fairly easy to construct, others may require filtering, segmentation, calculated metrics and integration with offline data. Depending on your analytics tool, you may want to use a presentation package like Xcelcius to create and display your gauges and create a dashboard. Edgewater Technology can help you develop an actionable analytics program based on the goals of your company, and can create the appropriate tagging and reporting strategy that will let you see your actionable metrics at a glance. Contact Edgewater today to learn more about how we can help you get more out of your web analytics program.

10 Actionable Web Metrics You Can Use – Part 1 January 13, 2010

Posted by Joe Kamenar in web analytics.
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The end goal of a web analytics report should be to provide some guidance on how to take an action to improve how your website is meeting its goals. However, many analysts simply generate canned reports using their analytics tool and send it to their management for review. In this two-part post, I will share with you 10 different web metrics that can “at a glance” tell your management how well a particular campaign or goal is performing, plus provide some relevant actions that can be taken to improve the underlying performance of the metric.

In Part 1, I will look at five metrics that are expressed in percentages. In Part 2, I will look at five metrics that are expressed as an index. Ideally, these metrics would be designed to be seen as gauges on a dashboard, and some can have the ranges color-coded (green/yellow/red) to quickly show the impact of that metric. Here are the first five actionable metrics.

1. Campaign Margin.

If you are running any paid campaigns for an ecommerce site or lead generating site, you need to know your margin. In simple terms, your campaign margin is defined as your revenue from a campaign less its cost, divided by the revenue. Your goal is to stay as close to 100% as possible. You can create a report that shows the campaign margin for any campaign that involves external spend (banners, paid search, sponsorships, etc…), or an internal spend on employees’ time (social media marketing, forum and article posts, etc…). The smaller your margin, the less money you are making. With this metric, “0%” is breakeven. If you have a negative margin, you are losing money on that campaign. If you have a positive margin, you are making money. This type of margin can be shown as a gauge and placed on your analytics dashboard. If your margin is negative or near zero, you need to take action to look at why the campaign is costing so much or how you can increase the campaign’s effectiveness.

2. Percent Revenue from New Visitors.

This metric tells you how likely visitors are to order from you on their first visit, compared to ordering on successive visits.  In order to create this metric, you need to be able to segment your traffic by new vs. repeat visitors. To calculate the metric, take the revenue generated from new visitors and divide it by the total revenue.  If the percentage is more than 50%, you get more of your sales from first time visitors, If it is less than 50%, you get more orders from repeat visitors. If you see this percentage is low and you have limited repeat buyers, then perhaps you would want to do a better job to get a visitor to purchase on their initial visit. If you have a low percentage of revenue from new visitors, and you have a more expansive product line, then this metric is telling you that you get more of your sales from repeat visitors or customers, and you may want to focus on keeping your content fresh and maintaining campaigns such as email or social networking to keep your visitors coming back.

3. Engaged Visitor Percentage (EVP)

This metric is defined as the number of visits that contain an action or event that indicates engagement divided by the total number of visits. To use this metric, you must first determine what defines an engagement. This can be any of the following – visit a specific number of pages, visit particular pages of interest, subscribe or register to something on your site, post a comment, rate something, click on an ad, use a tool, navigate a map, download something, play a video, forward to a friend, or do anything else you wish to show engagement. By monitoring this metric over time, you can determine if your site is doing a better or worse job of engaging your visitors, if this is one of the goals of your site.

4. Utilization Factor (UF)

Some types of organizations have developed their website to encourage its users to conduct business through it instead of calling or submitting paperwork. For example, an insurance company may want claims to be processed via the web. A financial agency may want its brokers to process transactions via the web instead of sending in forms. If one of your goals is to encourage the use of your site to accomplish tasks, one way to measure this is to track the percentage of activities that are conducted on the web divided by the total number of activities conducted online and offline. This metric is a bit more complicated, as to do it entirely online you need to import the offline data into your web analytic program. You can also export the online data and create an Excel-based report that combines the online and offline data. Your UF can also be used to measure the percent of registered users who use the site to transact business. By monitoring the Utilization Factor over time, you can determine how well your efforts are to shift your transactions to the web. Specific actions can include training of your users on how to use your site to process transactions, or ongoing communications that remind your users to use the site.

5. Self Service Factor (SSF)

If your site is to be used to provide customer service, one of your goals could be to reduce the percent of customer service issues that are handled through the phone. Thus, the SSF would be calculated as the number of service issues that were resolved on the web divided by the total number of service issues (web + phone + chat + email). In order to do this, you would either need to import your offline data into your web analytics program, or export your online data into a spreadsheet to combine it with your offline data. If your company has a target goal for resolving service issues via the site, you can create a gauge that shows how well the actual percentage is compared to the goal, or color-code the result as red or green to show if the SSF is above or below the target. Part of your site’s optimization efforts would include analyzing the issues that are most often called in and updating the content on the website, or making the top 10 most frequent issues a sidebar on the customer service site.

In Part 2 of this article, I will show you how to use these five additional actionable metrics:

  • New Customer Index
  • Campaign Quality Index
  • Return Visitor Index
  • Branded Search Index
  • Site Search Impact

Is Your Web Analytics Program on Solid Footing? January 5, 2010

Posted by Joe Kamenar in web analytics.
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Web analytics can provide a company with insight into how well its web assets are doing to increase the company’s revenue, and to provide data to make business decisions regarding web strategy, web marketing and other business-related initiatives. In order to make the right decisions, the web analytics program needs to be built properly to provide the supporting data. If any of the pillars of your program are built incorrectly, your whole program can crash, leading to lost opportunities and wasted financial investments.

In this post, I will share with you the top ten fundamentals that you need to consider when building your analytics program, to enable it to support your company’s business decisions.

1. Determine Business Goals and KPIs

The first step in the process is to determine your company’s business goals, as they pertain to its web assets. What role does the site play in providing revenue or business leads? Will the site be used to provide various audience segments with the tools needed to conduct the company’s business? Will it be used to provide corporate branding information and build interest in your company’s product or service? Will it be used to provide employees with information? Will it be used to provide the first level of customer support, in an effort to reduce incoming calls to your call center? Will it be used to keep customers loyal to your product or service?

To properly understand your site’s business goals, you need to conduct interviews with all of the stakeholders who touch the website. This can involve staff from your marketing department, HR, , IT, sales, customer service among others. Find out what information is important to them and how your reports will help them do their job better. This can help you identify any data collection gaps you have.

Once the goals are identified, they need to be mapped to key performance indicators, or KPIs.  KPIs are metrics that are tied to your company’s goals and are measured over time. They should be able to reflect the effects of any future optimization efforts. They need to be agreed upon by those who are impacted by the website’s performance.

2. Understand the Fundamentals of Web Analytics

The next step is to understand the fundamentals of web analytics. It is important to know how unique visitors are measured, how a bounce rate is measured and what it means. You need to understand the difference between new visitors, return visitors, and repeat visitors, and how time on site is calculated. You need to understand the difference between dimensions and measures, and how your analytics tool uses each. You need to be able to build a conversion funnel, and identify the relevant steps in the process. You need to understand terms like CPC, CPA, CTR, ROAS, ROI and others.  Ideally, you also need to have an understanding of JavaScript, server-side includes, first and third party cookies, and HTML. Think of all of these topics as ingredients in your analytics program’s concrete. If any of the ingredients are missing, your platform may not be as strong as it should be.

3. Select the Proper Analytics Tool

The next step is to either select the proper analytics tool, or evaluate what you are using now to make sure it meets your needs. These days, you have the choice between log files and tagging, free analytics tools and paid tools, and software vs. hosted solutions. Here are some of the decisions you must make:

  • Log files vs. tagging – There are pros and cons to using either log files or JavaScript tags to collect your data. The discussion on this could become another blog topic entirely. Do your research and determine which option (or a combination of the two) best meets your needs.
  • Free vs. paid – Depending on your analytics budget, you may be able to afford an enterprise-level tool such as WebTrends or Omniture. Depending on the size and complexity of your site, these solutions can cost tens of thousands of dollars per year. If your budget is small, consider using Google Analytics. Over the past year, Google has made significant improvements to its Analytics tool, to the point that many larger companies are now using it.
  • Software vs. hosted – Some tools, like WebTrends, provide you with the option of installing the software on your own servers, or using a hosted, “on demand” service. Each has its tradeoffs, in terms of cost, ease of use, and data availability.
  • Data privacy vs. data collection restrictions – If you organization needs to keep its web data private, your web analytics tool choice would be limited to either log files or a server-based data tagging software package. If you need or wish to collect personally identifiable information (full names, email addresses, credit card information, addresses, phone numbers, etc…), you can not use Google Analytics as your tool, as its terms of service prohibits capturing and storing this information on their servers.
  • Self-service help vs. tech support – If you are using a free tool such as Google Analytics, your tech support may be limited to its online help center, plus forums, blogs and discussion groups. If your organization is not that tech-savvy, it may need to have an account rep or phone-based tech support that comes with a paid tool.
  • Standalone vs. third-party integration – Tools like Google Analytics do not integrate well with other third-party tools used for pay-per-click bid management or email marketing. Google Analytics works well with their own services, such as AdWords.  Enterprise-level tools such as Omniture and WebTrends have optional modules that integrate with other vendors’ products, giving you a more complete picture of the overall performance of your web marketing activities.
  • Reporting vs. data mining – Some organizations need the ability to dig deeper into the collected web data to identify trends, new segments or correlations, or to more advanced analysis such as calculating the lifetime value of a customer. If your needs go beyond simple reporting, you may need to use a more advanced tool.
  • IT capabilities – If your organization has neither the talent nor the budget to implement advanced tagging methods into your website, you may need to use Google Analytics in its simplest fashion – simply paste a block of code on each page and include their “js” file on your website. Implementing more robust data gathering mechanisms with any analytics tool can require significant IT capabilities.
  • What are your peers using? – If you want to keep up with what your peers or competitors are doing, it helps to know what tools they are using. Simple Firefox browser add-ons, such as WASP, will show you which analytic tools are being used on any website.

4. Use Your Tool Properly

Once you have chosen your analytics tool, you need to use it properly, just as a builder would do with his tools. If you don’t, you can get poor results, or draw inaccurate conclusions.  Depending on the capabilities of your analytics tool, you may want to look at options such as segmenting, event tracking, conversion funnels, custom variables, pre and post analysis filtering, setting up profiles, templates, reports, custom metrics, calculated metrics, and conversion funnels.

Next, you need to determine what you are going to track. You can start with the basics, such as visits, unique visitors, page views,  average time on site, average pages per visit, top entry and exit pages, top pages, and traffic sources, then move on to landing page bounce rates, referral sources, organic and paid search keywords, internal site search results, visitor segments, visitor information, path analysis, traffic variables, conversions, tracking registered user visits, tool usage, interaction with Flash or video, downloads of PDFs or podcasts, events, products viewed, shopping cart actions, form completions and more. Each tool handles these differently, so you need to read your instruction manual first.

5. Develop Actionable Campaign Tracking

In a previous post, I talked about tracking all of your campaign activity. A campaign is any method, whether paid or organic, that gets visitors to your site. Some of these activities include pay-per-click, banner ads, email, newsletters, blogs, articles, social media, classifieds, forums, referral partners and affiliates. In the other post, I provided recommendations on how to set up Google Analytics and Omniture to provide you with a methodology to create and track the performance of all of your campaigns. When done properly, you can determine how well these campaigns do in bring not only visitors to your site, but qualified visitors who become customers or leads for your company. Once you know the value of your campaign efforts, you can provide recommendations on which campaigns work and which ones do not, letting your organization optimize its marketing budget.

6. Evaluate Your Data Quality

The expression “garbage in, garbage out” applies to your analytics program. If the quality of the data you are processing is suspect, the quality of the reports will not be any better. Some of the items you need to pay attention to include:

  • Filtering of internal and development partner traffic
  • Exclusion of images, spiders, bots and external site monitoring services from being counted as visits and page views
  • Merging together same pages with different URLs (case differences, “www.” vs. no “www”,”/ index.htm” vs. “/” at the end of a home page or path)
  • Removing query parameters from same page names
  • Test and verify your tagging structure and data collection to make sure you are capturing all the data you think you are.
  • Ensure that all your pages are tagged and that your custom tags are firing properly.
  • Testing all other JavaScript on your site. Any JavaScript errors that occur on a page before your analytics tag will prevent that tag from being executed.

7. Avoid Information Overload

Some organizations go a bit crazy when collecting web data. For example, I’ve seen a client set up a traffic variable that collects an internal search term and then combines it with the page where they went on the site. Yet no report was being used with this information (nor should it have been). Enabling all the parameters you have available can increase the overhead on your analytics tool, and can sometimes cause you to hit limits on the amount of data that can be processed. If any data that you are collecting (other than out-of-the-box) data does not serve a purpose in relating to your KPIs (business goals), then stop collecting it.

8. Set up an Optimization Process

Once you have your analytics program running smoothly, it is time to add an optimization process to it. This involves selecting any aspect of your metrics that can use improvement. For example, an easy win would be to reduce the bounce rate from targeted landing pages, or reducing the exit rate from pages that should lead to a call to action. Longer term, you will want to improve the performance of campaigns to lower your cost per lead or sale, to reduce the fallout rates in your conversion process, or to increase page views or reduce calls to your call center, and so on. Items that can be tested include landing pages, conversion funnel pages, forms, body copy, headlines, offers, colors, graphics, processes and segmentation.

The optimization process starts by implementing a tool that will let you conduct A/B split testing and multivariate testing. Since this is more advanced topic and requires strategic planning and execution to administer properly, you will either want to work with your optimization tool vendor or a company like Edgewater Technology to show you the way. To do this effectively, your organization will want to create a team that merges strategy, technology and creativity together. After you run a given test, analyze your results, make the recommended changes, and test again.

9. Understand How to Measure ROI on Activities

The end goal on any phase of testing is to increase your ROI for that cycle. But, how do you measure that? It helps to understand the ROI formula. Basically, it is the gain from an investment minus the cost of the investment, divided by the cost of the investment. Suppose for example, you have a baseline of an average of 10,000 orders per month from 434,000 visitors. That is a conversion rate of 2.30%. If your average revenue per sale is $50, your total revenue would be $500,000 from these visitors. If, through your optimization efforts, you raise the conversion rate to 3.1%, your resulting number of orders would be 13,454, for a revenue total of $672,700, or a difference of $172,700. If it cost your company $50,000 to make these improvements, your ROI would be ($172,000 – $50,000) / $50,000, or 245%. Note that this ROI was based only on the gross revenue, and does not factor in the cost of goods or services sold.

10. Implement an Analytics Roadmap

Just as a builder uses a blueprint to help guide his team, your web analytics program should also use a blueprint. At Edgewater Technology, we call this a “road map”. It is designed to help move your organization from simply collecting web data to building a comprehensive reporting platform that gives you a 360 degree view of your customer. In this road map, some very important questions are answered, including:

  • Where is your analytics program now?
  • Where do you want your analytics program to be?
  • How will you get there?
  • What are the goals of the various stakeholders?
  • What data to they want to see?
  • What data are you not collecting?
  • Do you need to integrate online data with offline data?
  • What challenges will you face in getting to your goal?
  • What specific tasks does your team need to do to get there?

To learn more about how Edgewater can help you build a strong web analytics foundation, be sure to visit our Web Analytics Services page to review our offerings.

Tracking Campaigns in Omniture Site Catalyst December 24, 2009

Posted by Joe Kamenar in campaign tracking, web analytics.
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Tracking campaigns with Omniture Site Catalyst

In a previous post, I discussed how to track marketing campaigns using Google Analytics. In this post, I will explain how to do it using Omniture Site Catalyst. Unlike Google, where you create a campaign tracking string based on five parameters and append it to your URL link, with Omniture, you simply create a campaign ID and append the ID to the URL. As an example, the URL http://mysite.com/landing_page.htm?cid=cl_phl_oct could represent a posting to the Philadelphia section of Craigslist in October. You could create a string of campaign codes and visually see each one in your Site Catalyst report, simply by setting the “s.campaigns” variable to the campaign ID. When you look t the report, you can add metrics such as visits, leads, orders, revenue, or other key performance indicators (KPIs).

The drawback to this is that if you have multiple types of campaigns, with multiple parameters, you would need to memorize each and every one to make sense of the report. Instead of doing this, you can instead “classify” the campaign variable. What this does is to associate meta data with it so that you can segment, filter, group or sort all your data to gain insight to what really works.

To do this, you need to go into the Admin function of Site Catalyst and then select the variable you want to classify. Typically, this would be the campaign variable. You can then set up classification categories based on your needs. You can set up classifications similar to what you would do with Google Analytics (source, medium, name, keyword, content), or you can be as specific as your business needs dictate. Omniture has a couple of excellent blog posts that show you how to set up classifications. One is specifically about campaign tracking, and the other discusses how to classify your campaigns using a tool called the “SiteCatalyst Attribute Importing and Naming Tool”, or SAINT. Using SAINT, you create a template in Excel that lists all of your campaign tracking codes and what they mean, as far as your classification list. This list needs to match the list you set up in the Admin console. Once you upload your template, you can then run reports that let you drill down to any of your campaign classifications, and see how well each aspect of your campaign performed.

To have all this make sense and provide meaningful and actionable data, you need to first determine your campaign goals, then create KPIs that can show management if these goals are being met. Your campaigns need to be identified and a tracking spreadsheet template created as per the SAINT requirements. All of your marketing URLs then need to be tagged with the unique tracking codes you have created. If you are doing email campaigns, you need to make sure that your campaign codes do not conflict with any tracking code that your email vendor uses. Fortunately, Omniture does provide integration capabilities with leading email marketing platforms.

One of Edgewater’s strengths is in providing your business with a complete web analytics roadmap, including looking at where you are now, determining where you need to be, and showing you how to get there. Your roadmap would include aspects such as identifying marketing opportunities, creating a classification template, building a set of KPIs and reports, developing tagging specifications, creating a test plan, and then analyzing your data to determine how to better optimize your web marketing efforts. Regardless of the analytics tool you use, Edgewater can show you how to use it better to take your web analytics to the next level.

Advanced Web Analytics Using Google Analytics December 15, 2009

Posted by Joe Kamenar in web analytics.
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In the past, Google Analytics was seen as simply a quick “DIY” analytics tool that gave some useful reports. All you did was just add some code to each page, include a JavaScript file on your site, and you were finished. The tool costs nothing to use as far as license fees, and the learning curve was simple. However, no “real company” would use Google Analytics (GA), as it did not provide any real insight that would let management make any data-based decisions. Most mid to large size companies would use enterprise-level tools, such as Omniture’s Site Catalyst, WebTrends, CoreMetrics, or other subscription-based tools. However, the cost of using these tools can add up to some serious coin, making it hard to justify an ROI on the results you would get.

In the past year, GA has narrowed the gap in functionality between its older versions and paid services like Omniture and WebTrends. Now, more and more larger internet retailers and service providers are using Google Analytics, including Garmin.com, RitzCamera.com, FatBrainToys.com, several BCBS websites, UnitedRentals.com and many more. So, what kind of enterprise-level features does Google Analytics now provide that have caused companies to take a second look? In this article, I will show you some of the features that you can now get with Google Analytics.

Multiple Profiles

Within GA, you can set up multiple profiles for an account, and apply specific filtering to each profile to create specific views of visitor behavior. For example, you can have a profile that is only for paid search traffic, or for events, or for segments of the site that are for specific departments. It is recommended that you keep one unfiltered profile, to retain all non-filtered data, as once you filter the data, you can’t go back to the raw data. Specific filters can be done to create profiles that are for content groups, paid search, internal traffic, and so on. Within the unfiltered profile, advanced segmenting can be performed on historical data to drill down on specific types of visits or visitor behavior.

Conversion Funnels

A conversion funnel is simply the desired path you want a visitor to take to become either a customer, a lead, a registration, or whatever other goal you have in mind. It is a list of pages that represent the start of the path to the end. Within each stage, you can see what percent of visitors made it to the next step, and what percentage left the “funnel”. In the past, GA limited you to just 4 goal conversion funnels across your site. Now, you can have up to 5 goals in each of up to 4 profiles, for a total of 20 goals to analyze. Conversion funnels can help you pinpoint where your site is not delivering, as far as meeting your company goals.

Event Tracking

GA can now do event tracking, similar to SiteCatalyst. It is done a bit differently, but you can assign an event to any activity broken down to a category, action, label and value to any site interaction. An event can be used to track how videos and Flash objects are used on your site. You can see how many times an item is viewed, how far they get through it, and if your desired message is being viewed. Using events, you can see how specific actions impact conversions on your site. On a per-visit basis, a total of about 500 page views and event calls can be sent to GA by a visitor. Once you have these events captured, you can then segment on these events to look at things like conversion rate. For example, you can tag a “Get Quote” button, and then see what percent of those who clicked this button converted.  If you have a retail site, you can tag a “shipping cost” link, and then see what percentage of those who go to this link make the purchase. When used properly, events  can let you capture more than just page views and visits. It can truly let you see how visitors are using your site. Google is looking at creating event-based goal conversion funnels as well as page-based funnels. With an event-based funnel, you can track visitor actions to see how they get to your end goal. Just by using the event tracking properly on a site, you can now get more granular insight into visitor behavior.

There is no limit to the number of events as they are not assigned to a particular variable as in Omniture.. The total number of calls to GA on a per-visit basis is about 500. Also, with the event tracking, it gives you a total count of each item, and a unique, per-visit count.

As an example, suppose you run a truck rental site. You want to track specific events. The event tag looks like this:

_trackEvent (category, action, optional_label, optional_value)

Thinking along the lines of rental activities, you can set up the tagging like this:

  • Category: Itinerary, Pick-Up Location, Drop-Off Location, Contact Info, Trucks and Options, Quote and Payment, Review
  • Action: Get Quote, Search Pickup Locations, Search Dropoff Locations, Select Pickup Location, Select Dropoff Location, Add to Quote, Change Quote, Enter Payment Info

The label and value are optional. For the label field, if you are tracking Flash videos, you would do something like this:

  • Category – video
  • Action – press play (or reached a certain percentage of the file, or any other embedded action)
  • Label – [title of video]
  • Value – time to load, perceived dollar value, quality points, etc…)

When you think about the event method, you can use the optional label field to store something about the visitor as well. If you were to store a unique ID for the visitor, or segment type (see below), you can then do a query on the label field to see what actions were taken by a particular visitor or segment.

Segmenting

Segmenting is a powerful tool that lets you see how specific audiences act on your site. We often talk about analytics in terms of averages – average time on site, average pages per visit, average revenue per sale, and so on, but in reality, there is no “average” visitor. They can be segmented into specific groups, and the behavior of each group analyzed to gain insight into how they can be better served. Segments can be based on visitor type (new vs. return), visit method (direct, paid search, organic search, referral), key words (branded, unbranded), and even a custom defined segment (more on that later). Within each segment, you can apply filtering to extract visits that meet you desired criteria. Filtering an include queries like matches exactly, does not match exactly, contains, does not contain, starts with, ends with, equals, greater than, less than, and others.

GA also lets you set up a custom segment variable, and then set it as you wish. Suppose you have a health insurance site that caters to various audiences, such as non-registered users, subscribers, brokers, employers, providers (doctors and hospitals), and employees. Depending on how they identify themselves as in logging in, which type of login they use, and so on, you can segment these individuals into their respective groups. You can then see how users in the particular segments behave on your site, and to see if your site is meeting the desired goals.

You can also do your conversion analysis or other analysis based on the values stored in each segment. The user defined segment cookie lasts two years, and can be overwritten on subsequent visits. The biggest problem that I see with this variable is that it is read at the beginning of the session, and any changes that are made during the visit are not used until the visitor later returns to the site. Thus, if someone comes to the site an anonymous, then later registers, any activity will be attributed to the anonymous segment. Only when the visitor returns does this change to “logged in” or “member”. Thus, the next time the visitor returns, he or she is tagged as a “member” or “logged in”, even if they do not log in on the next visit. Thus, while having this user-defined segment can be useful, it can also give misleading segment information.

Google is planning on expanding the number of user-defined variables shortly. Right now, if you want to store multiple types of data, you would create a string that can be parsed or joined in JavaScript, then store the entire string in the user-variable cookie. To access the data, in the profile you would then create a custom segment that extracts out the portion of the string that contains the section of interest. You can then correlate that with other items in the string to create a more narrow segment. I have seen some JavaScript code available that creates mini-functions that either add an item to the string or remove an item from the string.

Essentially, you can store anything in this variable, including a login ID. Google, of course, prohibits storing any personally identifiable information, and this includes things like an email address, SSN, full name, drivers license number, address, phone number, credit card number, etc…

Google now gives you 5 custom variables that you can use to do segmenting and analysis. Within each variable, you can store data that is either permanent, session-based or page based. With each variable, you can set a name-value pair that lets you create a segment that can be visitor-based, visit-based (expires after 30 minutes or when a browser closes or visitor exits the site), or page-based, such as defining content groups for each page. This new feature give you much more power to create reports that have meaning.

Traffic Sources

One of the most misleading stats I see in web analytics is in the organic search area. Often, the top search terms are the website’s URL. If you know the URL, why search for it? The answer is in the sneaky way that browsers’ home pages are loaded. If you have Internet Explorer and your default start-up page is MSN.com, the curser drops right into the search field. On FireFox, often the default load page is the Google page. Instead of moving the curser to the URL bar, many users simply type the name of the site they wish to go to in the search box, then they click on the top result, which is the site’s home page. If the top result is also a “paid search” link, and the visitor click on it, the search engine makes money, as do the browser folks. Thus, the organic or paid search results can get skewed.

To keep your stats in line, GA lets  you change the traffic source from “search engine” to “direct” or “referral site” to “direct” by adding some lines of code to the GA code that goes on your pages. Thus, those who come to your site by entering the URL in the search field will not be classified as search visits.

Custom Reports

GA also lets you create custom reports, where you can select your dimensions and drag it to the report, then select which metrics you want to show for that dimension.  With the dimension section, you can add sub-dimensions to the list, such as “Keywords -> Search Engines -> etc…”. You can then add a series of metrics to the report, letting you drill-down on each dimension to get more refined data. This feature is seen in the paid analytics tools, and lets an experienced analyst create multiple views of visitor behavior.

Search Filtering

Within searches, such as keywords, instead of getting a massive list, you can apply filtering, to only look at keywords or other items (like page views) based on a metric range.  You can “nest” conditions to include or exclude specific terms or metrics to generate a more refined search.

Motion Charts

A new feature titled “Motion Charts” lets you create a 4-dimension view of specific metrics, such as keywords. It lets you assign x and y axis values, then show additional metrics in the form of the size and color of a dot. You can place the chart in motion to show how the performance of any keyword changed over time. You can see the dots move up and down or left and right across your grid to see changes in two of the dimensions, along with seeing the size and the color of the dots change to see changes in the other two dimensions.

Internal Site Search

Internal site search is a very useful tool that lets you see how easy it is for visitors to find what they want on your site. It is important to see what visitors do when they find or do not find what they are looking for.  Internal site search can also be tracked to show additional metrics, such as average pages per visit, time on the site and conversions for those who find site results and those who do not.

API

The API tool lets you export out a complete report, based on specific queries that you make. The GA API tool seems fairly robust, as you can send URL based queries via the API and receive an XML file in return. There are a variety of third-party tools that have already been developed using the API that integrate GA data with Excel data and display it within PowerPoint, desktop applications, email marketing platforms, and mobile platforms.

Alerts

GA also provides analytics alerts that notify you when specific thresholds change, similar to the alerts that the paid tools provide. If your conversion rate drops below a specific threshold, or the number of orders you get exceeds a threshold, you can be notified right away, instead of waiting until you or your analyst does the report.

E-Commerce

Google Analytics collect two types of e-commerce data: transaction data and item data. Transaction data describes the overall transaction (transaction ID, total sale, tax, shipping, etc.) while item data describes the items purchased in the transaction (sku, description, category, etc.). Here’s a complete list of the data:

Transaction Data

  • Transaction ID: your internal transaction ID [required]
  • Affiliate or store name
  • Total
  • Tax
  • Shipping
  • City
  • State or region
  • Country

Item Data

  • Transaction ID: same as in transaction data [required]
  • SKU
  • Product name
  • Product category or product variation
  • Unit price [required]
  • Quantity [required]

When the e-commerce reports are enabled, you get additional reports, such as number of visits until purchase and the time to purchase. The Visits to Purchase (VTP) report shows how many visits a visitor generated before they converted. The Time to Purchase (TTP) report shows how many days it took from the first visit to make a purchase. If the TTP is “0”, it means it was on the same day, but not necessarily on the first visit.

For lead-generation sites that are NOT e-commerce sites, the e-commerce code can still be used to apply segmenting information and value information to leads or registrations that are submitted. By doing this, the e-commerce functionality can be enabled, letting the user see the VTP and TTP for a visitor who submits a lead or completes a registration form.

Third Party Integration

While Google supports its own A/B test tool, Google Website Optimizer, it does not integrate with third party tools from other vendors. Such tools can provide more advanced testing and behavioral targeting tools, email clients, multi-platform PPC management and so on.

Summary

Google Analytics can provide small to mid-size companies with the tools they need to create an actionable analytics plan and increase the value of the website. However, just like using paid tools such as Omniture, WebTrends or other more advanced packages, the tool is only as good as the mechanic who uses it. Companies like Edgewater Technology can help you develop a road map that looks at your company’s goals and creates an analytics strategy that helps you meet these goals. Edgewater can help you define key business metrics, create profiles and reports, define tagging specifications, tag your site, set up site optimization using the Google Website Optimizer, and train your team how to use these reports and continue to enhance your site.

With all the new tagging capabilities within Google Analytics, there is a fair amount of analytics enhancement can be done for those who are using this free tool. It can be a lot more involved than just placing the GA code on each page and the ga.js file on your site. By creating the right tagging specifications based on business strategy, Edgewater can help you get a better look at how visitors are using your site, and how you can better serve them.

To learn more, visit http://Edgewater.com or contact Joe Kamenar, Manager of Web Analytics, at 215-480-2737.