Why Web Analytics Matters

Web analytics is not a new idea for companies. It has been a topic for discussion for organizations ever since the mid-90s. Beginning with usage patterns, organizations applied analytics and tracked key metrics in their business functions like sales and marketing. However, modern web analytics tools have stronger capabilities now and they are regulated more strictly. You can learn about the basics of web analytics from websites that showcase digital marketing courses in Singapore.

Strict data privacy laws like GDPR are forcing businesses to be more careful about the data of consumers. However, benefits and success stories of web analytics are so compelling that businesses are willing to invest more on web analytics. Because of artificial intelligence and machine learning, modern web analytics tools are able to let businesses automate the analysis process with auto-generated and on-demand insights.

What is web analytics?

Web analytics is the collection, reporting and analysis of website data through server logs or code embedded on webpages. The main purpose of website analytics is to benchmark website performance and keep track of user behavioral data by making and measuring Key Performance Indicators KPIs.

Collection of data

To start an analysis, you must have to collect the needed data. Most web analytics tools insert JavaScript code into HTML text of sites so they could capture data and store it in database tables. Data they capture could also include webpage clicks, the device user accessed, geographic location of the visitor and more.

Processing data into information

This step involves transforming data into metrics by making ratios from counts that you obtained during the first step. For example, bounce rate is dividing the early-leavers count by total number of visitors. Even if this metric is vital for understanding the success of the webpage, it has to be combined with other metrics and information to make actionable insights to develop a marketing or business strategy. For example, bounce rate can be due to a slow loading website, dull content, bugs on the website, etc. Additional information is needed to understand the root cause and make the necessary action.

Tracking KPIs

Companies track metrics important to their business strategy and are commonly called Key Performance Indicators (KPIs). They give history to key metrics so companies can measure how they are changing over time. For example, conversion rate as well as cost per conversion are typical KPIs.

Identifying actions to take

Reviewing all the analytics information as well as their business goals, businesses must decide what needs to be done. Continuous analytics enables companies to test results of their strategies and make changes accordingly. For example, A/B testing is used commonly to improve conversions by testing two different designs for a page.

What is the source data for web analytics?

The power of any analytics product is limited by the quality as well as the diversity of its data sources. Web analytics usually depends on the following data sources:

• Visitor data
• Data captured through javascript code snippets or cookies
• Direct HTTP request data: Data sent by a web client (browser) to request a resource such as an image on a webpage.
• Application-level data sent with HTTP requests: This data is produced and processed by applications like JavaScript, PHP and ASP.Net and includes how a visitor interacts with the web page. They are usually collected by internal logs instead of web analytics services.
• External data needed to analyze visitor data. External data is combined with onsite data to help understand website behavior data. The most common example is understanding the geolocation of users since IP addresses are associated with Geographic regions and internet service providers. This is a common feature offered by almost all web analytics software.
• CRM: If companies can connect visitors to leads in their CRM system, they can have an accurate view of where their revenue is coming from
• Search engines: Search engines are a major source of traffic and tools like Google Search Console or Bing Webmaster Tools can help companies better understand and optimize traffic from search engines.
• Other search engine related data: There are numerous data providers that cover different aspects of search engine traffic such as competitors’ rankings, search engine friendliness of the company’s websites, etc.
• Server logs: Can provide additional, aggregated information about visitors that do not allow their data to be tracked.

How does GDPR change data collection?

Countries are making data privacy laws to protect their citizens’ data from being abused. These laws include

• GDPR(General Data Protection Regulation) in Europe
• CCPA(California Consumer Privacy Act) in California, USA
• POPIA(Protection of Personal Information Act) in South Africa

Several countries either have published similar laws or are working on them. Most of these laws tend to be similar and we are going to focus on GDPR which has the largest geographic coverage.

In EU, GDPR is a regulation law on data protection and privacy. After GDPR, companies are required to acquire the user’s consent to record their data. That is why most EU websites nowadays have a cookie disclaimer that requests users to accept cookies. If users do not accept cookies, none of their personal data will be stored. And most users are most likely not to accept cookies unless they are forced to accept them and GDPR prohibits companies from forcing users to accept cookies. However, this is not the end of your company’s web analytics. There are 3 ways that you can mitigate the impact of GDPR:

• Users who consent to cookies can be analyzed to gain insights into the behavior of users. However, this provides only partial data, the cookie accepting users are likely to differ in their behavior when compared to cookie refusing users.
• Servers generate log files including non-individualized data like visitor numbers per page. These can be used for high-level analytics because they do not count as personal data.
• Data without personal information could be valuable as well. Vendors such as Salesviewer use visitor data without relying on cookies by focusing on attributes such as IP browser characteristics, etc. to build a device fingerprint. Comparing this with their database, they can identify user’s companies which they share with website data owners. Their legal advisors certified them to be compliant to GDPR as well as national data privacy laws since their data processing is limited.