To leverage the true power of web analytics in your business, you must have a well-rounded approach towards the implementation of web analytics in your organization. As a business owner striving to make the most out of digital data and metrics for increasing the bottom line, you must have a well-planned structure for web analytics implementation.
Nowadays, most digital marketers and e-commerce site owners are aware of web analytics. As a matter of fact, a vast majority of the organizations and digital marketers have been utilizing web analytics for the past many years.
If you too are making use of web analytics to increase your revenue, then you must find the answers to the following questions.
- Are you aware why you are tracking certain metrics?
- How aligned are your analytics reports to your business objectives?
- Does your web analytics tool produce insightful reports that help you increase your profits?
- Are you able to take well-informed business decisions after analyzing your analytics reports?
If you are uncertain about more than one of these above questions, then your approach towards web analytics is not holistic and ineffective. It has been found that most organizations use web analytics for merely generating reports. Only a very few organizations scrutinize those reports to take pivotal business decisions. Web analytics must be seen as a tool to responsibly carry out data-driven web marketing. A robust and all-embracing web analytics implementation will revolutionize the digital marketing approach in your organization.
In order to have an effective web analytics system in place, the organization must have a strong understanding of the following aspects: management/data governance, scope, goals, resources and their skills, methodology and process, and last but not the least, the tools and technology. Before I delve deeper into these aspects, let’s find out how most companies deal with web analytics.
Most of the times it so happens that the marketing team’s head comes to know about the awesome benefits of web analytics from the internet or through other sources. He/she then coerces the IT team to search and select a good web analytics tool. Then a whole lot of time and energy are spent in implementing the best web analytics tool in the market and tagging every online resource available to increase the scope of tracking web analytics data.
But when the tool actually goes live, no one is trained to comprehend what metrics relate to which business goals! No one is sure why they are collecting the analytics data at all! All that the IT team knows is that they have to generate hordes of analytics reports at the end of every week. But they aren’t sure what methodology they must follow while creating these reports for the marketing team. Metrics are pushed into the reports haphazardly without knowing its purpose. Worst of all, the team is untrained to rightly leverage the recommendations and insights offered by the tool, which indicates that the team is not equipped with a data governance model! With data spitting out as gibberish every week without knowing its real intent, the web analytics effort of the organization ends up in failure.
Hence, an efficient web analytics model must have a clear understanding of the following elements. But it is extremely crucial to take one small step at a time while trying to progress exceptionally fast in any of these elements.
- Data governance
Data Governance: Data governance is not just about setting accurate instructions about who owns the data. It’s also about laying out clear-cut instructions about metrics tracking, report generation, data analysis, and taking actions. Every data set must be assigned to a person or a core team so that they can be held responsible or accountable in case a glitch arises with that data asset.
Objectives: The organization must be crystal clear about the business objectives of each data set. For instance, how are you going to leverage your website to achieve your business goals? Will you be using it to generate leads? Or is it just a means to develop visitor interaction? Every metric that an organization is tracking must have a definite purpose. Each metric must be able to tell you if you are on the right path to accomplishing your goals or not. And most importantly, how closer you are to it!
If your objective is to boost the number of leads through your website, then the most appropriate metric that’ll help you accomplish that objective is Conversion Rate. Whereas if you are looking to boost visitor engagement, then some of the crucial metrics that you must track are Bounce Rate, Abandonment Rate (if you have an e-commerce site), Time on Site, Click-through Rate, Session Length, and Pages Per Visit etc.
If you have an e-commerce site, you must know how many of your users are abandoning the cart. Analyzing this metric will unravel the reasons behind shopping cart abandonment. But if you have a regular website, a user engagement may mean clicking a link or filling up an opt-in form or completing a survey on your website.
The Scope of your Digital Analytics: Several organizations go overboard with tracking numerous metrics immediately after they venture into web analytics. Define the objectives of your metrics first. Then set the scope of your web analytics with regard to the scope of your marketing campaign. Begin with one digital resource, say, your main website or your e-commerce site. Then add other resources one by one progressively to include all your digital assets in the end.
Team: In order to draw useful business insights from the web analytics data, your organization must have a dedicated and trained digital marketing team. Usually, it is the IT team in a company that takes up the web analytics duties. Of course, you need their help to set up the tagging and tracking code, but they are rarely aware of your digital marketing goals. So you must have at least one team member from the IT team who clearly knows how to draw valuable insights from your metrics, what each metric stands for, why that are being tracked, and how do those metrics affect your goals. This element is extremely important to have an effective web analytics implementation.
Approach: This is where your digital marketing team’s experience plays a major role. Your web analytics approach totally depends on your organization type and the business objectives that you are planning to accomplish. Hence, there is no single “best” approach for this. You must develop a methodology that suits your organization and then fine tune it gradually to make it more aligned to your business objectives.
Tools: Last but not the least is choosing the most appropriate web analytics tool for your business. Although the core functionalities of most of the web analytics tools remain the same, there are some highly distinctive features that make certain tools far superior to the others.
We at RawSoft are quite confident that our flagship product, the FoxMetrics web analytics easily fits into that superior echelon! If you want to know more about this tool, here are some of those features that make FoxMetrics unique. The one striking aspect that makes FoxMetrics one-of-a-kind is its robust and intuitive data integration approach. Our suite of web analytics tools allows you to integrate the most secure and efficient data integration and ownership methodology into your web analytics implementation.
Best Practices for Web Analytics Implementation
Usually, the duty of web analytics implementation is comfortably delegated to the amicable IT guy in your organization and to your web analytics vendor. However, several vital business decisions need to be taken during the implementation process; and several of those have enormous data implications. So it is vital that web analytics experts, policy makers, and website owners are also included in the implementation procedure. It’s worth emphasizing here that just the IT personnel and web analytics vendor cannot successfully implement your web analytics solution.
Now let me acquaint you with some vital technical best practices of web analytics implementation at this juncture. Let’s check them out one by one.
All your web pages must be tagged
Here’s a short video that I found on YouTube that clearly explains how web analytics tagging and tracking really works!
To make sure that all your tags are intact, FoxMetrics web analytics suite includes a smart little program. This will check all your tags on a regular basis and report the bugs (if any) to the team/analyst or any other person that you assign.
Give the lowest precedence for tags
Several web analytics implementations place the tags all the way up at the top of the web page coding. Or they will place it in the <Header> HTML tag or just before the <Body> HTML tag. This is a bad analytics practice. Instead, the analytics tags must be placed just before or close to the closing </Body> HTML tag. By doing this, when a web page is loaded, the analytics tag will be loaded only in the end. By giving the lowest precedence for tags, you are allowing the web page and its content to load faster before the tags, in case the analytics server is sluggish or it has just stopped working.
Avoid misplaced tagging
Wrongly placed tags can greatly hamper the ability of your web analytics implementation to collect data efficiently. So make sure it is placed in harmony with the rest of the code. Never place it within important web page elements like the tables, frames, and other content holders.
Consider dynamic web page URLs (if any)
Modern web pages can be programmed to behave dynamically and display personalized content to the users. This is can be a challenging aspect in terms of a web analytics standpoint. If your web page doesn’t have a static unique identity, your web analytics tool must be set up to identify the page uniquely with the right combination of file name and parameters.
If you are using cookies on your website, always try to use first-party cookies. Try avoiding third-party cookies as much as possible. By the way, a cooking is nothing but a small snippet of code placed on your computer by a website when you open it in your browser. A cookie is usually used to collect three types of analytics data. The source attributes, user attributes, and page attributes.
The source attributes tell you how a user arrived at your site (for example, from search engines, other websites, ads etc.). The user attributes reveal the identity of the user, whether he is anonymous, possesses a login etc. And the page attributes will collect their behavioral details on your site (attributes like which pages they visited, the frequency of visits, navigational details and so on).
These points just make up few of the web analytics best practices! There are several others that I’m planning to discuss in a different post. These points may seem a bit technical if you are completely from a business background. But there’s no way you can get around these points to make your web analytics implementation a success. In fact, these points need careful analysis to make your web analytics activity efficient and robust.