How web analytics are used in the context of marketing

how does web analytics work and how can web analytics help a business
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DavyGodwin,United States,Professional
Published Date:03-08-2017
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Comment CHAPTER 1 Introducing Web Analytics This book is about Google Analytics, and at some level that means it is also about web analytics. It’s important to note that Google Analytics is not the same as web analytics. Web analytics is a business process used to continuously improve your online business. Google Analytics is a tool to quantitatively measure what happens on your website. Just because you have Google Analytics does not mean you are doing web analytics. Before we dive into Google Analytics, I believe it’s important to establish how Google Analytics should fit into your overall analytics strategy. Defining Web Analytics Rather than creating another definition of web analytics (there are a lot of them out there), I prefer to reference Avinash Kaushik’s concise yet thorough definition. In his book Web Analytics: An Hour a Day (Wiley), Kaushik defines web analytics as: The analysis of qualitative and quantitative data from your website and the competition, to drive a continual improvement of the online experience that your customers, and potential customers have, which translates into your desired outcomes (online and offline). This definition encapsulates three main tasks every business must tackle when doing web analytics: • Measuring quantitative and qualitative data • Continuously improving your website • Aligning your measurement strategy with your business strategy Let’s look at each part of the definition and break it down into more detail. Quantitative and Qualitative Data Web analytics is not possible without data. But many organizations fail to realize that they need many different types of data to understand the performance of their website. Tools like Google Analytics, Omniture, WebTrends, and Yahoo Web Analytics gen- erate quantitative, or clickstream, data. This data identifies where website traffic comes from and what it does on the site. It more or less tells what happened on a website. While clickstream data is critical, you must collect more than quantitative data—you must also collect qualitative data. While quantitative data describes what happens on your website, qualitative describes why it happens. Qualitative data comes from dif- ferent sources, like user interviews and usability tests. But the easiest way to get qual- itative data is through surveys. Asking website visitors simple questions like the ones below can lead to a greater understanding of what visitors want and whether you’re making it easy for them: Why did you come here today? Were you able to do what you wanted to do? If not, why? There are a number of free qualitative data tools, like 4Q and Kampyle, that are easy to implement and provide valuable feedback from your website visitors. In many cases, it’s easier to implement these tools than a clickstream data tool like Google Analytics. If you’re not collecting qualitative data, start now It’s not enough, however, to analyze clickstream data from your own website. You must also look at data from your competitors’ websites. We live in an amazing age in which competitive data is freely available to everyone. Competitive data provides valuable context for your own data. It describes your per- formance as compared to that of your competitors. and Google Trends can help you identify simple things like whether your competitors are getting more traffic than you. The Continuous Improvement Process The second part of Kaushik’s web analytics definition is, “to drive a continual im- provement of the online experience that your customers, and potential customers have.” All of the data and analysis must drive a continuous improvement process. This is the most critical part of web analytics. You must take action on the data. That’s the whole purpose of web analytics—to improve over time. Figure 1-1 shows a very basic repre- sentation of the web analytics process. 2 Chapter 1: Introducing Web Figure 1-1. The web analytics process: measure, analyze, and change Knowing how to change as a result of analysis is often difficult, though. Much of our data tells us that there is a problem, but it does not say how to fix it. So how does one go about fixing or optimizing a website based on data? You create different solutions to the problems and test them. Testing is the process of displaying the potential solution to website visitors, in real time, and measuring which one generates the best result. Many people are surprised to learn that testing a website is possible. There are a number of free tools, like Google’s Website Optimizer, that provide this service. Testing has always been part of marketing. Direct-mail marketers have been testing different offers and different ad variations for a long time. And those doing pay-per- click marketing have also been testing for many years, experimenting with different headlines and ad copy to optimize ad expenditures. However, website testing has failed to gain popularity. I believe the reason testing has been adopted so slowly is because of the many misconceptions about testing. Most people think testing is too hard, too expensive, or takes too much time. But in reality, testing has been changing, just like web analytics. With free tools it’s becoming easier and easier to start testing different parts of a website. Measuring Outcomes The final part of Kaushik’s definition of web analytics is that it “translates into your desired outcomes (online and offline).” The entire goal of the web analytics process is to increase our desired business out- comes. We are no longer obsessed with just measuring how much traffic our online business generates. We also want to measure how well it performs in business terms. This means measuring metrics that relate directly to our overall business goals. Every website exists for a reason, and your measurement strategy must align with the business goals of the website. Defining Web Analytics For the most part, all websites exist for one of the four following reasons: • To sell a product • To generate a sales lead • To generate ad revenue • To provide support Some websites do other things as well, but for the most part, this is why websites exist. This is where you should start measuring your website. How does it affect the bottom line of your business? Once you define why you have a website, it becomes much easier to identify the metrics you should focus on. You don’t need a lot of metrics—just a handful (3‒5) should help you understand if your business is succeeding or failing. If you’re having trouble identifying key performance indicators (or KPIs) for your site, try The Big Book of Key Performance Indicators by Eric Peterson ( What Google Analytics Contributes Google Analytics provides a core set of tools that supports some of the primary tasks that web analysts perform. First and foremost, Google Analytics tracks many standard website metrics, like visits, unique visitors, pageviews, bounce rate, and abandonment rate. But, more importantly, it can track business outcomes, called goals. Remember, we want to move beyond tracking basic traffic to our websites and begin understanding if our websites are adding to the bottom line of our business. In addition to tracking goals, Google Analytics does a great job at tracking all different kinds of marketing initiatives. Many people believe that Google Analytics can only track AdWords, but it can track other types of paid searches, email marketing, display ad- vertising, social media, and any other type of ad you can think of. One of the key activities of any analyst is performing segmentation. Segmentation in- volves diving deeper into the data to understand how smaller buckets, or segments, of traffic perform and ultimately influence the overall performance of the website. A simple example of segmentation is viewing website traffic based on the physical location of the visitors. Google Analytics does this using the Map Overlay report, shown in Figure 1-2. This is a very basic segmentation. Each row of data shows all the values for a dimen- sion. A dimension is an attribute of a website visitor or the visits that they create. Some common dimensions are country, campaign name, and browser version. There are many, many different types of dimensions, and you can view the complete list at http: // 4 Chapter 1: Introducing Web Figure 1-2. The Map Overlay report shows traffic from individual countries In this case, the dimension is the country. The metrics for that dimension are shown in the columns of the report. Now notice the tabs at the top of the report. The Goal tab displays conversions for the same dimension of traffic. So, if you click the Goal Set 1 tab, Google Analytics will display conversions for each goal for each country. This is the way all Google Analytics reports work. Every row of data is a different value of the dimension of traffic. For example, in the Traffic Sources report, each row in the table is a different source of traffic (organic search, marketing campaigns, etc.). But the ability to segment data does not end there. Google Analytics also has a feature called Advanced Segmentation that can segment data on the fly based on attributes that you define. For example, you can build an advanced segment to view all traffic coming from Google AdWords that resulted in transactions greater than 1,000.00. You can do this using a simple drag-and-drop interface, shown in Figure 1-3. This is a complicated segmentation that you can build and apply in real time The result is the ability to view the segment we created above, along with other segments of website traffic. Figure 1-4 shows the High Value AdWords traffic along with the total traffic to the website. This ability to drill down and focus on various segments of traffic is key to all analysis. We want to identify the segments of traffic that are performing well and determine how to promote those segments. We also want to identify the segments of traffic that suck and figure out how to fix them. Advanced Segmentation is not the only tool that helps facilitate analysis. Google An- alytics also contains a custom reporting tool that can greatly simplify your daily reporting and even help simplify common segmentations. What Google Analytics Contributes Figure 1-3. The interface to build Advanced Segments Figure 1-4. Viewing a segment of traffic along with all traffic in Google Analytics The Custom Reporting interface is very similar to the Advanced Segmentation interface. You can drag and drop different pieces of information to create your own reports, as shown in Figure 1-5. 6 Chapter 1: Introducing Web Figure 1-5. The Custom Reporting interface The rows of data in a custom report represent different dimensions of data. The col- umns in a custom report are the different metrics in Google Analytics: things like visits, pageviews, conversions, revenue, etc. For example, to create a report that shows the conversion rate for different marketing campaigns, drag the Campaign dimension to the Dimension section of the screen and drag the Conversion Rate metric to a metric column. Custom reports also provide the ability to drill down into each dimension and view subdimensions. Notice the subdimension sections of the interface in Figure 1-5. You can add more dimensions under your primary dimension. Using subdimensions, it’s easy, for example, to view the different types of visitors (new or returning) in your marketing campaigns and determine what time of day each visitor type converts—just keep dragging dimensions to the interface (Figure 1-6). These are just a few of the features that are standard in Google Analytics. They don’t take any extra configuration. Every user, from day one, can access these features and use them to analyze their own data. I encourage you to experiment with these features: you’ll be amazed at how much time they can save you. How Google Analytics Fits in the Analytics Ecosystem Obviously, Google Analytics is one of the most popular clickstream data tools that has ever been created. In the five years since its launch, it has been adopted by millions of businesses, both large and small. How Google Analytics Fits in the Analytics Ecosystem Figure 1-6. A custom report with many subdimensions Small and mid-sized businesses have access to a world-class analytics tool that can help drive their continuous improvement process. Larger organizations that have tradition- ally spent six figures on a web analytics tool are migrating to Google Analytics because it provides 90% of all the reporting and analysis functionality that their organizations need. They can save tremendous amounts of money and reallocate those funds to skil- led analysts who can help make the data actionable. As we discuss Google Analytics throughout this book, though, remember that it’s just a small piece of your web analytics strategy. It’s a tool (and a very good one in my opinion) that provides clickstream data. Google Analytics will help you identify what is working and what is not working with your online business, but remember, the world of web analytics is much bigger than Google Analytics 8 Chapter 1: Introducing Web CHAPTER 2 Creating an Implementation Plan Google Analytics is a business intelligence tool and, because every business has different data needs, your implementation may be very different from someone else’s. Do not believe that you can simply slap some tags on the site and collect valid data. It is very rare that an implementation involves only page tagging. There are many configuration steps required to generate accurate, actionable data. With that said, there are some standard things that everyone should do to get reliable data for analysis. Implementing Google Analytics does take some planning and fore- sight. The Google Analytics support documentation does contain a rough implemen- tation guide that includes the various steps to get Google Analytics installed and running. I have modified that process as follows: 1. Gather and document business requirements. 2. Analyze and document website architecture. 3. Create a Google Analytics account and configure profiles. 4. Configure the Google Analytics tracking code and tag website pages. 5. Tag marketing campaigns. 6. Create additional user accounts and configure the following reporting features: • Report access • Automated email report delivery • Reporting customizations (Custom Reports, Advanced Segments) 7. Perform the following optional configuration steps: • Enable e-commerce transaction tracking • Implement event tracking • Implement custom variables Gather Business Requirements You probably noticed that step 1 has very little to do with Google Analytics. As I men- tioned before, Google Analytics is just a tool that you can use to measure the perform- ance of your business. How you define and measure success for your business will be different than for other organizations. Take the time at the start of this process to understand your organization’s data needs. Sit down with the different stakeholders and interview them. Ask them what data they need to make better decisions and document the answers. The information you collect should be the driving force for your implementation. What you measure needs to align with your business objectives. Remember, you need to collect and define the KPIs for your organization. It’s also important to ask if there are any existing reports distributed internally. If so, you can use these as a template for your Google Analytics reports. Analyze and Document Website Architecture Once you have an understanding of what’s important to the business, it’s time to an- alyze your website. During this step, you should identify any aspect of the website architecture that may interfere with measuring your business objectives defined in the previous step. During this step you should ask questions like the following: • Does the website span multiple domains? • Does the website have multiple subdomains? • Is the website dynamic (does it have query-string parameters)? • Does the website use Frames or iFrames? • Does the website use any redirect? • Does the website contain any Ajax, Flash, or other elements you want to track? All of the items listed here can cause issues with Google Analytics. While they complicate the implementation process, they will not keep you from using Google Analytics, but it’s critical to identify them before starting the implementation. The amount of work it takes to complete this step depends on how large your organi- zation is and how many websites you have. Regardless of how big your company is, take the time to answer these questions through experimentation and interviews. Browse your own website or websites to determine if it uses any of the above configu- rations. Meet with IT people and ask them to explain as much as they can about how the website works. And document everything you learn. Having written documentation about the website architecture will make the entire process easier. 10 Chapter 2: Creating an Implementation Create an Account and Configure Your Profile Once you’ve got all of your business requirements, it’s time to start working in Google Analytics. Begin by creating an account. If you’ve already got a Google Analytics ac- count, there is no need to create another one. Once you have an account, configure your profile settings, such as Site Search, Filters, and Goals. Configure the Tracking Code and Tag Pages We’ll discuss how to configure the tracking code later, but, briefly, based on your website architecture, you may need to alter the tracking code to compensate for things like subdomains or multiple domains. Luckily, there is a code configuration tool that makes changing the JavaScript rather simple. Once you have created and configured the profiles and the tracking code, it’s time to tag the pages. Because most sites use some type of template system, like WordPress, Drupal, or some custom content management system, this makes tagging pages fairly easy. In most cases, you can place the page tag in your footer template, and in about three hours you should start to see data. If your website does not use a templating system, you will need to manually add the tag at the bottom of all the pages on your site. Tag Marketing Campaigns Tagging marketing campaigns is one of the most critical parts of configuring Google Analytics. This is the process of identifying your different marketing activities (like paid search, display advertising, and email marketing) to Google Analytics. You do this using a process called link tagging. If you do not tag your marketing campaigns, it will be impossible to measure the success of your online marketing initiatives. I will thoroughly describe how to tag your marketing campaigns in Chapter 9. Create Additional User Accounts and Configure Reporting Features Once analytics is up and running and you’ve started to collect data, it’s time to configure various features that provide access to data. This is the time to create user accounts so coworkers and others can access analytics. This is also the time to configure some of the reporting tools that Google Analytics provides. Features like automated report email messages and custom reports can greatly reduce the time it takes to generate any standard reports that an organization may need. Create Additional User Accounts and Configure Reporting Features Perform Optional Configuration Steps There are many Google Analytics features that generate additional data. E-commerce tracking, custom variables, and event tracking are optional features that all collect other types of data. While it is not necessary to implement these features, they often provide additional information that can provide you with more insight. For example, custom variables can collect demographic information about your site visitors, event tracking can measure how people interact with different types of content, and e-commerce tracking can collect revenue and transactional data in real time. Some organizations may make these features a high priority based on the metrics they provide. If you’re one of them, these implementation steps may not be optional for you. Schedule the implementation of these features based on your priority and implemen- tation resources. To some extent, the implementation process is iterative. Don’t expect to get it right the first time. Once you have installed the tracking code and you have some data in the reports, check the data. Does it make sense? Should you modify the data to manipulate how it looks? It may be that you need to add an additional filter or change a profile setting to improve the quality. Can you reconcile the data with a different tool? Granted, the data is unlikely to be exactly the same between tools, but is it fairly consistent? Do you see the same trends in the data? The key to a successful implementation is to take a structured approach, take your time, and document everything you do. 12 Chapter 2: Creating an Implementation Plan

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