Web Analytics

Website or Mobile application channels form the most significant share of users’ interaction with businesses. It is imperative then to put the increasing effort into understanding these interactions to serve the customers better.  The collection, measurement, and monitoring of the data generated by the customer’s interaction with the website or smartphone device are known as web analytics.

The objective here is to gather users’ attributes such as customer location, type of device used, products and content of interest, and much more. Web Analytics provides a deeper and broader understanding of both prospective and existing customers, enabling businesses to acquire and retain more customers. Thus, Web Analytics plays an increasingly significant role in shaping marketing and customer experience strategies in today’s world.

Key Data Collected for Web Analytics

So, what is the typical information you can expect if you adopt a Web Analytics solution for your website? Here’s a quick overview :

•Visitor’s Location, Language, IP address, Device Type (Laptop/ Mobile/ I pad), Browser Type (OS, Android), Screen Resolution, etc.

•New Visitor vs. Returning visitor – Whether the visitor is new or has already visited the site earlier.

•Data related to the user’s frequency, duration, and recency of visits

•Traffic Source – Was the user directed to the website through some digital marketing channel? E.g., Google Search, Facebook, LinkedIn, etc., or visiting the site through indirect search.

•Visitor Actions/ Events can also be recorded and analyzed. (E.g. Adding Product to Cart, Product Purchase, Product Comparison, etc.)

•Navigation of the Pages –The order followed by the users to navigate from one page to another.

•Errors Encountered– Errors encountered by the visitor while visiting a particular page

Methods of Data Collection for Web Analytics

There are multiple ways in which the web activities of a user can be captured. Mentioned below are some of those ways

Java script tagging 

Java script tagging is the most common method for collecting website interaction data. In this mechanism, a website is ‘tagged’ by inserting a snippet of JavaScript called the tag in the web page’s code. Using this tag, the analytical tool counts each time the user visits the website or clicks on a link. The tag can also gather other information like the user’s device, browser, and geographic location (via IP address), etc. Google Analytics is a prominent web analytics solution, and the page-tag provided by them is called analytics.js.
The tagging solution providers may also use cookies to track individual sessions and determine repeated visits from the same browser. (Cookies are a small piece of data that is stored in the user’s device. Service providers use these cookies to understand user’s preferences, which later helps them deliver a customized user experience.) Some users don’t entertain cookies or occasionally delete them, resulting in different visit counts than the actual.

Web Logs

By default, all the interaction and activity on a website gets captured in a web server log. The weblogs capture several user events such as the IP address of the user, multiple sessions on the website, duration of visits, pages visited, etc. Weblogs don’t require an additional monitoring code. Data-sensitive organizations such as banks, healthcare, or government organizations might prefer this process due to data security and privacy concerns.
This information is available in a free-flowing, semi-structured format. Therefore, this method involves a bit of processing work for parsing the weblogs to extract meaningful information.

Web Beacon

A web beacon is nothing but a tiny 1-by-1 “tracking pixel” that is inserted in an image/banner to track ad impressions and clicks. This method is mainly used for online advertising, especially while using banner advertisements. 

Each of these methods has its pros and cons.  E.g., even though the weblog method might be cumbersome, it might be the only method that can provide you historical data of the website. On the other hand, weblogs may incorrectly interpret a search engine’s crawler for actual users, leading to incorrect information about website visits. Depending on the customer’s needs, one method may be more suitable than the other.

Applications of Web Analytics 

The data collected by web analytics tools can give multiple valuable insights to track the organization’s performance. Some of the prominent KPIs are as follows:

Visitor Behavior/ Engagement Analysis

These KPIs help businesses analyze the behavior of their users, leading the organizations to understand their user’s experience. For example, the customer data may show:

•    common landing pages 
•    common exit pages 
•    frequently visited pages 
•    average time spent per visit
•    number of pages visited per visit
•    bounce rate etc.

Conversion Analysis 

These are by far the most important metrics to track the success of the website or digital campaigns. Conversion is nothing but a favorable action by the user such as adding a product to the cart, buying a product, downloading a white paper, applying for the service, or just clicking and visiting the website.

•    Some of the critical conversion Metrics are:
•    Conversion Rate
•    Leads Generated
•    Cost Per Acquisition

Other significant business initiatives that benefit from the use of clickstream data are:

•    Lead Generation
•    Campaign Performance Analysis
•    Marketing Attribution
•    Website Optimization
•    Abandoned Cart Analysis
•    Customer Journey 

Lead Generation

A constant generation of new leads is an essential aspect of driving sales. Analyzing web traffic can help better understand your prospective customers, their behavior and help create sales pipe. One can use multiple behavioral attributes to classify the customer into different lead buckets. For instance, a customer who visits your website and immediately logs off may be more likely an accidental user than a serious prospect. On the other hand, a user who spends more time going through testimonials may be a much stronger prospect to buy your product. These insights help differentiate users as ‘interested personas,’ ‘early prospects,’ or ‘hot leads,’ and help the marketing team devise a strategy to convert them into customers.

Campaign Performance Analysis

Measuring the performance of digital campaigns is an essential step in streamlining marketing activities. It helps understand the success rate of specific campaigns, channels, and content in engaging the target customer. This kind of analysis can help businesses assess the impact of their marketing effort and use it for planning and refining the digital marketing strategy. Some of the crucial questions this type of analysis can answer are:

•    Which campaigns resulted in the most traffic generation on the website?
•    Which keyword search resulted in a click and visit to your website?
•    What was the trend of response to your campaign immediately vs. after a few days?
•    What campaign is giving the highest return on ad spend (ROAS)?

Marketing Attribution Analytics

Digital marketing may result in multiple clicks on the website, which may eventually result in the conversion (a sale, an application, or any other desired action). However, it doesn’t readily explain which click contributed the most or least in the conversion. Some channels may be driving more clicks and more traffic to your website, but certain others could be more instrumental in driving the conversion or purchase. 
Marketing attribution takes marketing analytics a step further by using multiple algorithms in determining how different clicks have contributed to the conversion. This analysis can help you in adjusting your marketing strategy by shifting the ad spend across channels.

Website Optimization:

Optimizing your website is an essential step in enhancing the user experience. Broken links, slow response, complex navigation, etc., can put off a user and reduce your chances of building a business relationship with the user. Website optimization approach can be divided into two steps 

•    Pro-active experimentation
•    Root Cause Analysis
•    Proactive Experimentation

These are controlled trials to improve a website’s ability to drive more goals. A/B testing is one of the most common methods to conduct such experiments. It includes changing website page content or appearances –  e.g., colors, messages, banners, contact information, form length, information, etc. to determine which modifications will finally result in more conversions.
Root Cause Analysis
This involves first identifying the indicators of bad experience of your website, E.g., high log-off or Exit-Rate. Once the problem is identified, the next step is to determine why this is happening, e.g., the high exit rate could be because of a page loading issue, incorrect linkages, or some irrelevant content present on the page. 

Abandoned Cart Analysis:

An abandoned cart is when a user adds items to the cart but leaves the site/app without completing the transaction. This could be due to multiple reasons such as unclear call-to-actions, delay in loading the payment gateway, difficulties in navigating through payment, limited options of payment, delivery prices, and other similar issues. In some cases, it could be due to a complex combination of these issues.
Analyzing the web traffic data and understanding customer behavior before the abandonment can help understand the root cause of cart abandonment and take appropriate action to reduce abandonment when avoidable. The insights developed here can also be used in determining the best marketing promotions to entice these users to return and complete the purchase.

Customer Journey Analysis:

A customer journey is about understanding the sequential activities performed by the users across multiple channels. It is a series of actions taken by the user on the website. Understanding the order of activities may help know the root cause of certain behaviors such as page exit or abandoned cart by the customer. It can help in the following ways:

•    Proper identification of potential areas of friction where users are dropping off.
•    Analyzing the impact of marketing initiatives on the conversion process at every step of the user’s journey.
•    Discovery of the paths taken by the users before getting converted.

How to choose the right Web-Analytics tool for you

The proven benefits of implementing a web analytics tool make the decision to purchase one for your business an easy one. However, in an ever-changing competitive business environment with constantly varying needs, choosing the right Web Analytics tool for your business can be a daunting task. We understand it may neither be feasible nor economically sensible for your business to do a detailed study of each of the countless options available in the market today. We at Intellisqr can guide you through this journey to short-list, identify and select the most cost-effective and efficient tools to match your needs, keeping in mind your best interests.