In Part 1 of this topic, I covered four of the top ten fundamentals in building a strong web analytics platform. In this post, I will discuss the remaining six pillars.
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
- Testing and verifying your tagging structure and data collection to make sure you are capturing all the data you think you are. Make sure that all pages are tagged and that custom tags fire properly.
- Ensuring that all tag parameter variables are accounted for, even if you have no data for a particular parameter
- Ignoring currency formatting on e-commerce data that is passed in your tracking code
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?
- Is your collected data accurate?
- 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?
Once you have a road map, you will be able to break down all the required tasks and determine what level of effort is needed to implement your analytics program.
By understanding the fundamentals needed to build a strong web analytics platform, you will be able to provide reliable data that supports your company’s business goals and provides you with actionable insights that can be used to optimize all aspects of your web program.