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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.