Let’s reframe the conversation so the word “advanced” means you can answer more questions. Take a B2B marketing team. They know website traffic increased last month. Great. But did more potential customers visit? What marketing activities attracted them?

This guide explains the five levels of advanced website analytics and how to work out where your team stands. We'll also cover three techniques that will help you make progress. You might be closer to the next level than you think.

What “advanced” actually means

Advanced website analytics means using website data to answer increasingly specific questions about your visitors and their behavior.

Think of website analytics as a ladder with five rungs. As you climb the ladder, the questions you answer get more helpful to your team. A standard web analytics setup can tell you how many people visited your site and where they came from. At the higher levels, you can investigate which channels attract visitors who engage with your content. Identifying the companies behind those visits requires an additional data source.

But beware. One trap most teams fall into is skipping levels. A marketing team might invest in sophisticated software while still relying on basic monthly comparisons. They'll have access to more information, but they won't necessarily know what to do with it. Instead, build better analytical habits. Once you've established your web analytics best practices, start asking more demanding questions of your existing data. You'll soon discover whether or not you need new advanced web analytics tools.

The five levels

Follow our website analytics maturity model to see what your team can currently measure, and what it would take to move further.

Level 1: Counting

At its most basic level, website analytics answers the question, “How much traffic did we get?” You can see the number of visitors your site received over a defined time period, and some limited information about what they did while they were there, such as how many pages they viewed.

All you need is a working tracking script and a regular reporting routine. Getting the setup right is important, so in addition to placing the script correctly, make sure everyone responsible for reporting understands how to monitor website traffic. Monitor your figures consistently and report them regularly. Your team should be able to produce the same figures whenever someone asks, without spending hours searching for information.

But counting has its limits. As good as it is to know how busy your website is, simple counting can’t tell you whether those visits were valuable to your business. In this way, the number of visitors your website gets is a bit of a vanity metric.

Level 2: Comparing

At Level 2, you can answer the question, “Is our website performing better or worse than before?” You have the traffic figures from Level 1, but now you can put them into context by comparing different periods. Compare last month’s or quarter’s visitor numbers with the previous one, or get a longer-term picture by comparing year-on-year figures. Either way, you can see whether traffic is increasing or falling, and by how much.

The important thing is to compare like with like. Use consistent definitions and choose periods that make sense for your business. Your web analytics report should make these comparisons easy to find and understand.

When you spot a dramatic change in your figures, get into the habit of investigating why. If traffic suddenly increases, try to find out whether it's an unusual jump or part of an established pattern.

But there's still a ceiling on what you can achieve here. You can see that website performance has changed, but you can't tell which part of your traffic was responsible.

Level 3: Segmenting

At Level 3, you can answer the question, “Which part of our website traffic has changed?” By dividing visitors into groups, you can find out what's happening beneath the overall figures.

For example, your website traffic might have increased by 20% last month. That’s promising news. But when you break the figures down by acquisition channel, you discover that organic traffic stayed the same while paid traffic increased sharply. You now have a much clearer picture of where that growth came from.

You can configure segments in Google Analytics 4 to examine visitors by channel or other relevant characteristics. The important habit is to look at these groups before making judgments about overall performance. That way, you can spot changes that a headline traffic figure might hide. Segmentation also gives your team a better starting point for investigating unusual results. If one channel suddenly performs differently, you know where to focus your attention.

But there's still a gap. Segmentation shows you which part of your traffic changed, without explaining which marketing activities caused that change.

Level 4: Attributing

At Level 4, you can answer the question, “Which of our marketing activities contributed to a conversion?” So, when someone fills out an inquiry form, you can investigate which campaign helped bring them to your website.

Using utm parameters lets you identify which campaigns brought visitors to your site and connect that activity with recorded conversions. Use Data Studio to create a report breaking down results by campaign.

You also need an attribution model. This is an agreed way of assigning credit to marketing activities that contributed to a conversion. With b2b multi touch attribution, different models can give different amounts of credit to the same customer journey.

There’s no universally agreed attribution model across B2B marketing, and models are agreements rather than objective truths. Choose a model based on what you want to measure, then apply it consistently.

Attribution has a blind spot. You analyze the journeys that lead to recorded conversions, but potential buyers who research your business without converting remain invisible.

Level 5: Identifying

At Level 5, you can answer the question, “Which companies are researching our business?” This includes potential customers who visit your website but haven't yet spoken to your sales reps.

This level works differently from the previous four. It requires an additional source of company identification data, rather than further analysis of your existing figures.

The additional layer uses company identification data, including methods like reverse IP lookup, to associate website visits with organizations. This is where website intelligence comes in. Leadfeeder Web Insights shows how many companies visit through each channel, campaign, or page, how many match your ideal customer profile (ICP), and their average Intent Score. Web Visitors lets you see those companies by name. To get started, install the tracking script and check the Traffic Sources report after a week to see which channels brought ICP-fit companies.

There is still a limit. Company identification tells you which organization visited your website, but it cannot identify the individual person browsing.

How to tell which level you are on

Answer these questions with a simple yes or no, based on what you can currently do with your website data. 

1. Can you report how much website traffic you received last month?

2. Can you compare that figure with an earlier period, using consistent definitions?

3. Do you routinely break down your traffic into segments to see which groups of visitors are responsible for changes?

4. Can you connect a conversion to the marketing activity that contributed to it, using an agreed attribution model?

5. Can you identify companies that visited your website without making an inquiry?

Your current level is the last question you answered yes to in an unbroken sequence starting at Level 1. The next step is always the level directly above. Remember not to skip steps. Skipping is a recipe for expensive software your team isn't ready to use.

If you're at Level 2, develop a web analytics strategy that helps you investigate changes systematically.

At Level 3, create a web analytics dashboard that displays your most relevant segments before the overall totals.

If you're an agency analyst, you can use this assessment to show clients what their current reporting tells them and what they'd gain by moving up a level.

Three techniques worth the effort

Advanced analytics techniques help you answer questions your regular reports struggle to answer. Three are worth the effort for a B2B team, and none needs a data team: cohort analysis, path analysis, and blending site behavior with CRM outcomes. They're especially useful in B2B marketing, where visitors may return several times before filling in a form.

1. Cohort analysis on first visit month

Cohort analysis is an advanced analytics technique that suits B2B marketers well. It lets you track groups of visitors over time, so you can see how their behavior changes during a longer buying cycle. Repeat visits indicate engagement, although they don't prove someone will eventually buy.

Start by grouping visitors according to the month they first arrived at your website. For example, everyone who visited for the first time in January belongs to the January cohort. Now look at what that group did in February, March, and the months that followed. Did they return to your website? Did they continue reading content relevant to their original interest?

This is particularly useful for seo web analytics, where someone might discover your business through an organic search long before they're ready to make an inquiry. Compare how much of each cohort returns over subsequent months. If a good proportion keeps coming back to relevant content, that suggests sustained interest. If activity drops sharply and stays low, those visitors may no longer be considering becoming customers.

2. Path analysis on the evaluation route

Path analysis helps you understand how visitors move between pages on your website, especially the areas that behave like buying signals. These typically include product information, pricing, integrations, technical documentation, and customer case studies. On a B2B site, this sequence is the closest thing you have to a funnel.

The order they view these pages also matters when it comes to evaluating website visitor intent. If a visitor checks out your product page and then goes immediately to your integrations page, they might be trying to see whether your tool will play nicely with their current tech stack. If a noticeable number of visitors leave after reading your pricing page, the information may not be clear enough, and a rewrite could improve results.

Don't assume every buyer follows the same route. There could be several people in an organization looking at your offering, each with a different priority. Look for patterns rather than anomalies to point you in the right direction.

3. Blending site behavior with CRM outcomes

You can also investigate which pieces of content companies engaged with before their deals progressed or closed.

To do this, you need website activity that can be associated with a known company, plus a matching company record in your CRM. A shared company identifier, known as a join key, lets you connect the two. In practice, the join key is usually the company's website domain. Your website data shows acme.com read the integrations page three times in March, and your CRM shows the Acme deal moved to proposal in April. Matched on the domain, you can ask which pages companies read in the 90 days before a deal moved forward, and how that differs from deals that stalled.

Look for patterns. Did companies that eventually bought your product repeatedly visit a particular page? Did they engage with content that other prospects rarely viewed? Use these answers to inform your content decisions. If successful deals often involve companies researching a specific product question, you can create more content that addresses it.

However, remember that correlation doesn't prove causation. Just because companies read a page before buying doesn't mean that page caused the sale.

If you're already at Level 4, your next step is website visitor identification, and you can get started with Leadfeeder by installing a tracking script during a 14-day free trial (terms and conditions apply).