Analyzing Web Session Data In B2B Marketing

Marketers have access to endless numbers of web metrics such as time on page, pageview counts, and bounce rates. But choosing metrics that should be reported on a regular basis can be difficult. This is often the case with web session data.

In this blog post we’ll discuss how B2B marketers can make the most out of web session data. We’ll cover what web session data is and using it to improve revenue generation in you digital marketing efforts.

What is Web Session Data?

Web session data measures the level of activity on a website. A web session can be defined in two ways, 1) it can be time-based, meaning a web session is counted when there is user-activity within a given time-period, or 2) it can be navigation-based, meaning a web session is counted when a series of navigations is made by the user.

Marketers use this data to understand how leads and prospects are using the website, where they come from, and what users are doing before and after an important action like a form fill. Web session data is structured like below.

Example of web session data table.jpg

This is only a snippet and Bizible’s session data comes with much more.

What’s most helpful to marketers is when they can generate useful metrics and connect this data to other dimensions, such as pageview,  lead, opportunity and revenue data.

Web session data includes pages viewed, forms filled out, and more. All activity is tracked, and timestamps are added for every page view.

At Bizible we use a standard thirty minute time window, meaning if there is no activity for thirty minutes we close the session (while still logging the session activity).

How do you interpret session activity duration?

This depends on context and your business. A lot of activity within a web session can signal that users can’t find something on your website. But if users are on a content heavy part of the site, like a blog, it can show that your content is interesting and getting a lot of engagement. Again, it depends on context.

If you’re just now starting to dive into web session data, start with setting a baseline. Start with understanding average activity, how much variation there typically is, and investigate where there is above, or below, average activity. For example, below are average session duration charts for a specific audience (leads) and specific set of pages.

web session data chart b2b marketing.jpg

(Click image to enlarge)

Above average activity can mean there’s a section of your web property where users can’t find what they’re looking for. On the other hand, if you’re entering a new market, launching a new product, driving more traffic to your sit, adding new content, or changing the type of content on your site, then you might expect changes in user activity. In this case, web session data is useful, too.

Define Relevant Web Session Metrics

Web session data has details on pages viewed, forms submitted during the session, and session duration. So you can create metrics like:

  • Average session duration
  • Average number of pages viewed before a form fill
  • The page(s) viewed before a form fill
  • Average number of pages viewed during a session

These might sound like trivial metrics, after all, how actionable is knowing average session duration? To make session data useful, consider the following strategies.

Segment Session Data

Average session duration and average number of pageviews per session across your website isn’t the most helpful metric. Segmenting sessions based on specific pages (e.g. content focused on specific verticals or product lines), specific audiences (leads and contacts in opportunities), or geographic locations (based on IP addresses) can be much more helpful.

For global companies with multiple product lines and web properties, segmenting session data for comparison and monitoring can help marketers better understand what to expect from certain audience segments. For example, you may expect certain levels of web activity during new product releases or define optimal session durations for different parts of your website.

Define Expected Rates

Metrics without context are just random numbers. Average number of pageviews per session doesn’t mean anything without context. To add context, marketers should understand expected rates and optimal rates.

Expected rates simply refers to what you expect the rates or numbers to be.

Creating baseline figures is a great way to set expected rates. For example, finding average rates and standard deviations (a measure of variation around the average) is a great way to set expectations.

For example, if user activity levels averages to 5 pageviews per session and 95 percent of sessions deviate by plus or minus 1 page, then you expect average pageviews to be between 4-6 pageviews. There’s only a 5 percent chance that average pageviews falls outside the range of 4-6 pageviews. When this happens, it will be unexpected and you can investigate.

If you’re trying to influence site activity, then you’ll want to know whether increases in site activity were likely due to typical fluctuations around the mean or a result of your marketing.

Define Optimal Rates

Optimal rates refers to a target amount of web activity. A simple example is defining an optimal session duration. If sessions are too long, it signals that visitors can’t find what they’re looking for on your website. If it’s too short, it can mean your content is low quality and people are not engaged.

Optimal rates are specific to your website and business. For example, long session durations are expected and optimal if you’re Netflix.

Combine Session Data with Other Data Sources

As marketer you aren’t just concerned with website activity from everyone. You care about customers and prospects. Web session data from Bizible is combined with user identifying information like email, account, opportunity stage, and revenue. And you can access it all with Bizible’s Data Warehouse.

Combining session data with additional dimensions helps marketers understand what high value audiences are doing on their site.


You’ve built demand generation programs that are repeatable and are running smoothly.

Web session metrics are useful for optimization and monitoring. Your demand generation engine is a lot like a car engine, and utilizing web session data is like using engineering technology to find the best mixture of air and fuel to make the engine perform as efficiently as possible.

Accessing session data and combining it with touchpoints and contact data can provide a deeper understanding of when prospects are active on your site, and what prospects are doing on your site. You can use session data to validate click data from ad platforms, too.

Web session data can be overwhelming. Hundreds of thousands of rows of data can be generated in a day, so it can often feel like looking for a needle in a haystack, that needle being an actionable piece of information.

Start with descriptive statistics and end with a research question where mining session data can help you better understand how web activity relates to revenue. After all, if your marketing efforts aren’t translating into growth and revenue, then you’re simply not making the best use of your budget.

Originally published by Andrew Nguyen on Bizible.