B2B eCommerce analytics are no longer an add-on, but the engine of your business growth. In this article, we explain why data-driven development is a necessity, which five analyses every online store should carry out, and how analytics directly impact sales, conversions, and marketing ROI.
Imagine your brick-and-mortar store had its entrance filled with rocks and gravel.
Customers stumble on their way in, some turn back at the door, and others walk around the store with gravel rubbing in their shoes the entire time.
But as the shop owner, you simply walk around the pile and think: “Well, the rocks are just there. Maybe they won’t affect sales.”
This is exactly how many B2B companies treat their online stores.
The digital sales channel exists, but its true performance is neither measured, analyzed, nor developed.
Meanwhile, according to Forrester research, as many as 75% of B2B buyers would prefer to shop through self-service, without any contact with a salesperson.
B2B eCommerce is no longer an optional add-on. For many companies, it has become the primary sales channel—and the preferred purchasing channel for customers.
Yet, online store development is still often guided by gut feeling rather than data-driven understanding of what works and what doesn’t.
Systematic data analytics change this in three ways:
A current state analysis is like a health check for your online store. It reviews the entire purchase journey from the customer’s perspective and identifies the most obvious areas for improvement.
What to analyze:
Why this matters: Without a clear picture of the current state, development work is a gamble. You may end up fixing things that aren’t broken, while real problems remain unnoticed.
Concrete outcome: A prioritized list of development areas that deliver the biggest impact. The current state analysis also guides other analyses and areas of improvement.
2. Customer journey analysis: Find the drop-off points
The customer journey analysis uses statistical methods to study how, and with what likelihood, visitors move from one step to the next in your online store. The goal is to identify possible “stumbling blocks” and bottlenecks where the number of visitors suddenly drops significantly.
What to analyze:
Why this matters: Even if your store has thousands of visitors, it doesn’t help if they all drop off at the same stage. Fixing just one bottleneck can significantly boost sales.
Concrete outcome: A clear picture of where in the journey the most potential customers are lost. Often, the fixes turn out to be surprisingly simple.
In B2C, shopping cart analysis is standard practice, but in B2B it’s still underutilized—even though the potential is huge.
What to analyze:
Why this matters: Shopping cart analysis reveals the likelihood of customers purchasing specific product combinations. With this knowledge, you can develop product bundling and upsell prompts, thereby increasing average order value.
Concrete outcome: Ready-made product bundles and cross-selling recommendations based on actual buying behavior.
Do you think you truly know your customers? Many B2B companies are surprised when analytics reveal the actual customer segments.
What to analyze:
Why this matters: Across multiple segmentation projects, we’ve observed a recurring phenomenon: online store owners often don’t fully realize what kinds of customer segments actually use their site. The end results of segmentation often highlight surprising insights that can be leveraged to improve sales and marketing.
Concrete outcome: A true understanding of customer groups enables more targeted marketing and sales. When you know who you’re serving, you can serve them better.
Once potential bottlenecks and friction points in the customer experience have been identified, they can be systematically addressed through conversion optimization and A/B testing. A/B testing is not a one-off experiment but an ongoing process.
Examples of what to test:
Why this matters: The value of A/B testing comes from the continuous process. When testing is systematic, every development decision is based on data rather than assumptions.
Concrete outcome: Every A/B test teaches you something about your customers. Over time, small wins accumulate into significant improvements in conversion.
Sometimes the answers only emerge when different data sources are combined in the analyses. eCommerce data can be enriched with external sources to better understand the impact of various factors—often outside the company itself—on sales.
Examples of data enrichment opportunities:
Generative AI and AI agents add a new dimension to data enrichment. They accelerate the analysis process and enable handling of more complex data combinations.
What’s critical, however, is understanding what you want to achieve with the data—and how to interpret the results correctly from a business perspective.
This is usually the point where a skeptic asks: “But how much does this really affect revenue?”
Based on our experience, well-executed corrective actions can increase an online store’s conversion rate by several tens of percent—especially when clear bottlenecks exist in the starting situation.
Think of it like this:
It’s also important to consider the multiplier effect: when your online store converts better, you can confidently invest more in marketing, which brings in more visitors—who then convert at an even higher rate.
Running an online store without analytics is like running a shop in the dark. Customers come and go, the cash register rings occasionally, but you can’t see how many stumble between the aisles or leave empty-handed.
If you decide to start, begin with one analysis: the current state analysis is often the best starting point because it gives you a complete overview of the situation. After that, you can prioritize which other analyses are worth investing in—or not.
Remember: your competitors are continuously developing their online stores. If you don’t measure and analyze, they will pass you. Data-driven development is no longer optional—it’s a necessity in today’s eCommerce competition.
Your customers vote with their feet. They will go where buying is easiest. Analytics help you make your online store that place.
1. Why is web analytics important for a B2B online store?
Without data, online store development is based on guesswork. Analytics reveals potential purchasing bottlenecks, builds understanding of customer behaviour, and clarifies marketing ROI.
2. What are the benefits of a current state analysis?
It’s a health check for your online store that identifies the most critical issues and shows where you should focus first. This helps you avoid making incorrect fixes and provides a clear roadmap for progress.
3. How often should online store analyses be done?
Key metrics should be monitored continuously. A broader analysis should be done at least once a year or whenever major updates to the online store are planned.
4. What’s the difference between customer journey analysis and conversion optimisation?
Customer journey analysis shows how customers navigate within the online store and where they might drop off the purchase path. Conversion optimisation tests and adjusts solutions to remove these bottlenecks, such as improving how delivery or payment options are presented.
5. Can analytics really impact revenue?
Yes. Even a small increase in the conversion rate can significantly boost sales with the same number of visitors. Additionally, marketing ROI and customer experience improve, which increases long-term sales.
6. How does generative AI relate to e-commerce analytics?
It speeds up the analysis process and connects complex data sources. AI can generate segment-specific reports or suggest product recommendations, but human business insight is still essential.