B2B eCommerce analytics turn data into business growth
B2B eCommerce analytics are no longer an add-on, but the engine of your business growth. In this guest article, Head of Data Intelligence Jarkko Niemelä (Quru Oy) explains 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.
B2B eCommerce analytics turn data into business growth
B2B eCommerce analytics are no longer an add-on, but the engine of your business growth. In this guest article, Head of Data Intelligence Jarkko Niemelä (Quru Oy) explains 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.
Jarkko Niemelä
Head of Data Intelligence
3
min read
18.8.2025
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.
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.
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.
Data analytics are critical for driving B2B eCommerce sales growth
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:
Customer understanding is based on facts, not assumptions
Do you, as a seller, truly know who your customers are and how they behave in your online store? Analytics often reveal surprising truths and completely new target groups.
Conversion growth is continuous and measurable
Instead of making large eCommerce redesigns blindly, small, measured improvements accumulate over time into significant results.
Marketing investments deliver better returns
As conversion improves, every euro spent on marketing generates more revenue. It’s pure mathematics.
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:
Customer understanding is based on facts, not assumptions
Do you, as a seller, truly know who your customers are and how they behave in your online store? Analytics often reveal surprising truths and completely new target groups.
Conversion growth is continuous and measurable
Instead of making large eCommerce redesigns blindly, small, measured improvements accumulate over time into significant results.
Marketing investments deliver better returns
As conversion improves, every euro spent on marketing generates more revenue. It’s pure mathematics.
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:
Customer understanding is based on facts, not assumptions
Do you, as a seller, truly know who your customers are and how they behave in your online store? Analytics often reveal surprising truths and completely new target groups.
Conversion growth is continuous and measurable
Instead of making large eCommerce redesigns blindly, small, measured improvements accumulate over time into significant results.
Marketing investments deliver better returns
As conversion improves, every euro spent on marketing generates more revenue. It’s pure mathematics.
Five analyses every B2B eCommerce business should do
1. Current state analysis: Map the starting point
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:
Every step of the funnel from landing page to checkout
Functionality of analytics and tracking
Compliance of GDPR and cookie tracking
Clarity of KPI definitions
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:
Which channels visitors come from
Critical pages along the purchase journey
Where customers abandon the process
How different segments behave
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.
3. Shopping cart analysis: Increase average order value
In B2C, shopping cart analysis is standard practice, but in B2B it’s still underutilized—even though the potential is huge.
What to analyze:
Which products are typically bought together
Probabilities of certain product combinations
Average cart size by segment
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.
4. Customer segmentation: Identify the real buyer groups
Do you think you truly know your customers? Many B2B companies are surprised when analytics reveal the actual customer segments.
What to analyze:
Behavior-based segments
Groups based on purchase history
Channel preferences
Value potential
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.
5. Conversion optimization and A/B testing: Build a culture of continuous improvement
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:
Headlines and product descriptions
Calls to action
Form length
Payment options
Site structure
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.
1. Current state analysis: Map the starting point
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:
Every step of the funnel from landing page to checkout
Functionality of analytics and tracking
Compliance of GDPR and cookie tracking
Clarity of KPI definitions
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:
Which channels visitors come from
Critical pages along the purchase journey
Where customers abandon the process
How different segments behave
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.
3. Shopping cart analysis: Increase average order value
In B2C, shopping cart analysis is standard practice, but in B2B it’s still underutilized—even though the potential is huge.
What to analyze:
Which products are typically bought together
Probabilities of certain product combinations
Average cart size by segment
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.
4. Customer segmentation: Identify the real buyer groups
Do you think you truly know your customers? Many B2B companies are surprised when analytics reveal the actual customer segments.
What to analyze:
Behavior-based segments
Groups based on purchase history
Channel preferences
Value potential
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.
5. Conversion optimization and A/B testing: Build a culture of continuous improvement
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:
Headlines and product descriptions
Calls to action
Form length
Payment options
Site structure
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.
1. Current state analysis: Map the starting point
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:
Every step of the funnel from landing page to checkout
Functionality of analytics and tracking
Compliance of GDPR and cookie tracking
Clarity of KPI definitions
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:
Which channels visitors come from
Critical pages along the purchase journey
Where customers abandon the process
How different segments behave
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.
3. Shopping cart analysis: Increase average order value
In B2C, shopping cart analysis is standard practice, but in B2B it’s still underutilized—even though the potential is huge.
What to analyze:
Which products are typically bought together
Probabilities of certain product combinations
Average cart size by segment
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.
4. Customer segmentation: Identify the real buyer groups
Do you think you truly know your customers? Many B2B companies are surprised when analytics reveal the actual customer segments.
What to analyze:
Behavior-based segments
Groups based on purchase history
Channel preferences
Value potential
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.
5. Conversion optimization and A/B testing: Build a culture of continuous improvement
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:
Headlines and product descriptions
Calls to action
Form length
Payment options
Site structure
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.
Data enrichment: When basic analytics aren’t enough
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:
Weather data + sales data = A hardware store can forecast seasonal demand for decking materials and grilling products.
CRM + eCommerce = Companies can identify which customers are most likely to make repeat purchases—and why.
Financial data + buying behavior = A construction supplier can predict order volumes based on building permits and investment data.
Logistics data + conversions = Showing real-time handling and delivery times can significantly increase conversions.
Public procurement + prospecting = B2B companies can identify new customer opportunities by analyzing public procurement data.
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.
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:
Weather data + sales data = A hardware store can forecast seasonal demand for decking materials and grilling products.
CRM + eCommerce = Companies can identify which customers are most likely to make repeat purchases—and why.
Financial data + buying behavior = A construction supplier can predict order volumes based on building permits and investment data.
Logistics data + conversions = Showing real-time handling and delivery times can significantly increase conversions.
Public procurement + prospecting = B2B companies can identify new customer opportunities by analyzing public procurement data.
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.
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:
Weather data + sales data = A hardware store can forecast seasonal demand for decking materials and grilling products.
CRM + eCommerce = Companies can identify which customers are most likely to make repeat purchases—and why.
Financial data + buying behavior = A construction supplier can predict order volumes based on building permits and investment data.
Logistics data + conversions = Showing real-time handling and delivery times can significantly increase conversions.
Public procurement + prospecting = B2B companies can identify new customer opportunities by analyzing public procurement data.
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.
The business impact of analytics: What does this really mean in euros?
This is usually the point where a skeptic asks: “But how much does this really affect revenue?”
Based on Quru’s 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:
If your eCommerce conversion rate rises from 2% to 2.5%, that’s a 25% increase in sales.
If the number of visitors stays the same, it means 25% more orders.
At the same time, marketing ROI automatically improves, enabling even larger investments in that area.
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.
This is usually the point where a skeptic asks: “But how much does this really affect revenue?”
Based on Quru’s 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:
If your eCommerce conversion rate rises from 2% to 2.5%, that’s a 25% increase in sales.
If the number of visitors stays the same, it means 25% more orders.
At the same time, marketing ROI automatically improves, enabling even larger investments in that area.
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.
This is usually the point where a skeptic asks: “But how much does this really affect revenue?”
Based on Quru’s 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:
If your eCommerce conversion rate rises from 2% to 2.5%, that’s a 25% increase in sales.
If the number of visitors stays the same, it means 25% more orders.
At the same time, marketing ROI automatically improves, enabling even larger investments in that area.
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.
Analytics are an investment in the future
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.
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.
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.
FREQUENTLY ASKED QUESTIONS
1. Why is web analytics important for a B2B online store?
1. Why is web analytics important for a B2B online store?
1. Why is web analytics important for a B2B online store?
2. What are the benefits of a current state analysis?
2. What are the benefits of a current state analysis?
2. What are the benefits of a current state analysis?
3. How often should online store analyses be done?
3. How often should online store analyses be done?
3. How often should online store analyses be done?
4. What is the difference between customer journey analysis and conversion optimization?
4. What is the difference between customer journey analysis and conversion optimization?
4. What is the difference between customer journey analysis and conversion optimization?
5. Can analytics really impact revenue?
5. Can analytics really impact revenue?
5. Can analytics really impact revenue?
6. How does generative AI relate to online store analytics?
6. How does generative AI relate to online store analytics?
6. How does generative AI relate to online store analytics?
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GDPR
COMPLIANT
Future-proof eCommerce built in the EU
AI Commerce Cloud is developed and hosted within the EU, fully compliant with GDPR and all relevant regulations.
© 2025 AI Commerce Cloud. All rights reserved.
GDPR
COMPLIANT
Future-proof eCommerce built in the EU
AI Commerce Cloud is developed and hosted within the EU, fully compliant with GDPR and all relevant regulations.
© 2025 AI Commerce Cloud. All rights reserved.