How many times a week do you check your website analytics ? If your answer is less than “quite a lot” then you could be missing out on useful data to power your marketing.

In this guide, we’ll run through what website analytics is, why you should invest time setting up and optimizing, and how you can use website analytics to increase both web traffic and conversion rates. Whether you’re a content marketer, product marketer, or any type of marketer, this guide will open your eyes to the gold mine that is website analytics.

What is web analytics?

Whether you have a whole bank of content or one or two blog posts, you need to know what is and isn’t performing.

Regardless of whether your web pages are fun, SEO optimized, or whether your internal teams think they are great, you need to know they are what your audience needs and if they are best optimized for organic search.

Web analytics is a collection of metrics, reports, and insights on any website that provides you with this exact data.

For example, you publish a blog post covering the 10 Best CRM Providers in the UK. After two weeks, you haven’t seen any leads generated, and your sales team is twiddling their thumbs.

Instead of spending time writing a new blog post without direction, you can use web analytics and heat maps to find out the user behavior like how many people have read your post on clikz , the time they spent reading, and even where they clicked away (and didn’t convert to a prospect).

With historic and real-time data on any of your web pages, you can make informed decisions about what is and isn’t working on your website.

Data collected through web analytics

may include traffic sources, referring sites, page views, paths taken and conversion rates. The compiled data often forms a part of customer relationship management analytics (CRM analytics) to facilitate and streamline better business decisions.

Web analytics enables a business to retain customers, attract more visitors and increase the dollar volume each customer spends.

Analytics can help in the following ways:

  • Determine the likelihood that a given customer will repurchase a product after purchasing it in the past.
  • Personalize the site to customers who visit it repeatedly.
  • Monitor the amount of money individual customers or specific groups of customers spend.
  • Observe the geographic regions from which the most and the least customers visit the site and purchase specific products.
  • Predict which products customers are most and least likely to buy in the future.

The objective of web analytics is to serve as a business metric for promoting specific products to the customers who are most likely to buy them and to determine which products a specific customer is most likely to purchase. This can help improve the ratio of revenue to marketing costs.

How does web analytics work?

When your website gets a unique visitor, your web analytics tool starts processing data about that visit. You receive data like your visitor’s IP address and can decipher geographical and ISP information. This can prove useful for retargeting efforts or making decisions on who your buyer persona is.

Website tracking is how websites collect, store, and share information about their visitors’ activities. Websites can track data like a visitor’s operating system, browser, screen resolution, device type, and many other data points that help with understanding more about your visitors. Other information comes from direct request data. This is the searching and fetching of what your user has typed to find your website.
Once you have a visitor on your site, analytics packages—like Google Analytics—start processing all on-site behavior.

The web analytics process involves the following steps:

  1. Setting goals. The first step in the web analytics process is for businesses to determine goals and the end results they are trying to achieve. These goals can include increased sales, customer satisfaction and brand awareness. Business goals can be both quantitative and qualitative.
  2. Collecting data. The second step in web analytics is the collection and storage of data. Businesses can collect data directly from a website or web analytics tool, such as Google Analytics. The data mainly comes from Hypertext Transfer Protocol requests — including data at the network and application levels — and can be combined with external data to interpret web usage. For example, a user’s Internet Protocol address is typically associated with many factors, including geographic location and clickthrough rates.
  3. Processing data. The next stage of the web analytics funnel involves businesses processing the collected data into actionable information.
  4. Identifying key performance indicators (KPIs). In web analytics, a KPI is a quantifiable measure to monitor and analyze user behavior on a website. Examples include bounce rates, unique users, user sessions and on-site search queries.
  5. Developing a strategy. This stage involves implementing insights to formulate strategies that align with an organization’s goals. For example, search queries conducted on-site can help an organization develop a content strategy based on what users are searching for on its website.
  6. Experimenting and testing. Businesses need to experiment with different strategies in order to find the one that yields the best results. For example, A/B testing is a simple strategy to help learn how an audience responds to different content. The process involves creating two or more versions of content and then displaying it to different audience segments to reveal which version of the content performs better.