eCommerce conversion rate optimization in the B2B environment: special features and approach

Conversion rate optimization (CRO) as a measure and sub-discipline of digital marketing has one goal: to increase the number of desired actions while maintaining the same quality and quantity of visitors. Which action(s) are suitable for this depends on the company goals and the marketing and sales strategy derived from them. In this article, you will learn which optimization goals and metrics make sense depending on the type of offer, what challenges B2B companies face compared to B2C companies and how you too can successfully optimize your platform or website.  

 B2B conversion rate optimization expert at work

1. the conversion rate: the differences in B2B compared to B2C:

Similarities:
First of all, the conversion rate for both B2C and B2B offers is one of the most important key figures for evaluating how well the website or platform manages to lead users to the desired action. The conversion rate(s) of the macro and micro goals should therefore have a fixed place in the marketing strategy. All of a company's efforts have one goal: to increase sales directly via transactions or to increase the number of (qualified) inquiries from target customers. A deep understanding of target groups, the development of personas and the alignment of content to these target groups (also by means of personalization) is also essential for both B2C and B2B offers. 


Differences:
The differences in the optimization of the conversion rate(s) can be mapped within the following dimensions:

1. Decision-making process and buying cycle 

B2B:
The buying cycle (eCommerce), or the decision-making process in general, is significantly more complex and longer in B2B. The process usually involves extensive research, requirements analyses and comparisons as well as approval procedures and several decision-makers or influencers. 

B2C: The purchase cycles in B2C are significantly shorter - “impulse purchases” or “spontaneous purchases” occur. This does not exclude the possibility that a purchase decision is well-founded and associated with appropriate research. However, since the purchase decision is made by one or usually a maximum of two people, the process is naturally shorter. 

[Translate to Englisch:]

 

 

2. number of purchasing decision-makers 

B2B: Several parties have an influence on the purchase decision. In B2B marketing, this is also referred to as a “buying center”. Those involved, such as budget managers, decision-makers and users, represent different interests.  

B2C: In most cases, the purchase decision in B2C is made by one person, but in the case of larger purchases such as furnishings (e.g. furniture) or a car, two people may also be involved in the decision. In individual cases, there may also be more, such as a group trip. 

3. motivation to buy 

B2B: The target group consists of companies or organizations that purchase products or services in order to achieve their corporate goals, increase efficiency or maximize sales. Decisions are strongly driven by profitability and long-term benefits for the company and represent an investment. 

B2C: The target groups are individuals or families who usually buy products or services for personal use or consumption. Decisions are emotionally driven and personal preferences play a greater role.  


4. sales strategy and customer relationship 

B2B: The focus is on building relationships with customers and providing personal advice. Sales processes are often consultation-intensive and characterized by individual offers of tailor-made solutions and negotiations. The customer relationship is intensively cultivated - with technical support or service contracts. 

B2C: Customer interactions are often less personal. This does not mean that the approach to the identified target groups/personas is not personal. However, mass market strategies tend to be used here. Branding and emotional marketing should influence purchasing decisions. Long-term customer relationships and customer loyalty and therefore customer service are also important in B2C - albeit more standardized and less personal. 


5. platform / conversion devices 

B2B: A study by Google from 2015 shows that 42% of users in the B2B purchasing process use mobile devices for their research. Compared to 2013, this is a 91% increase. In fact, 49% of B2B researchers use their mobile devices to research products while they work. They compare prices, find out about products, compare features and contact retailers. They also make purchases; mobile purchase rates have increased by 22% in the last two years (as of 2015). It can be assumed that this development is even more advanced today thanks to mobile applications. 

B2C: In B2C, mobile commerce has been around for some time. The motto is now “mobile first” and the customer journey takes place predominantly on mobile devices. B2C is still the pioneer here - but B2B companies are continuing to follow suit. However, the importance of mobile experiences is significantly higher in the B2C sector, as they are now “state of the art”.  

6. Product and pricing 

B2B: The products are often specialized and tailor-made solutions require individual pricing. Volume discounts, individual conditions depending on the purchase quantity and long-term contract commitments on both sides are also the rule. 

B2C: Products are intended for end consumers and are easier to use. Prices are usually fixed and discounts are used to promote sales. Subscriptions can be used in both B2B and B2C - this is a common feature. 


7. Distribution channels 

B2B: Sales are often made directly via the manufacturer or specialized distributors or sales representatives. Although online platforms are becoming increasingly important, personal contact continues to play a major role (also in customer care).  

B2C: Sales are made both via physical retail outlets and eCommerce platforms. The spectrum for reaching end consumers is very broad. 

[Translate to Englisch:] Smart Commerce Produkte

2. differences in macro conversions by business model

To simplify matters, we can distinguish between two business models: 

  1. eCommerce companies  

  2. Service companies  


In addition, there is not always just one single metric to optimize, but two or three depending on the user segment. An example: A B2B eCommerce company requires customers to register before they can use the store. 

The main conversion of the user segment “non-registered users” is therefore the registration for the customer portal or the online store. In the registered user segment, on the other hand, the main conversion is clearly the transaction. The segments and sometimes different target groups also play a role here. eCommerce companies have the primary goal of increasing their transaction revenue. Therefore, the “purchase conversion rate” is not enough at this point. Key figures such as average order value (AOV), average revenue per user (ARPU) and customer lifetime value (LTV) are also relevant for sales. Since not every purchase is worth the same, simply looking at the conversion rate would be a fallacy.

The following chart shows that a higher conversion rate can also go hand in hand with lower sales in some cases. Although this is less common, it is negligent to ignore the above key figures.

For service companies, the main conversion is usually a contact request (e.g. contact form or callback request), appointment booking or, for SAAS companies, a demo booking. Here, the conversion rate of a landing page for a contact request is more meaningful on its own.

Parallel to eCommerce companies, CTAs can of course be tested on the homepage of important target pages for company websites.  

3. what B2B customers expect from B2B online stores

A study from 2022 by ECC Cologne makes it clear how trend-setting the B2C user experience is for B2B. 

86%

... of respondents (231 ≤ n ≤ 247; top 2 values - strongly agree & somewhat agree) stated that they expect a customer experience for professional online purchases that they are familiar with from private purchases. 

82%

... B2B buyers also expect the same services and functionalities as in B2C online stores. 

41%

... of respondents confirm that more than half of B2B online stores do not fully meet their expectations for a convenient shopping experience.

Although private purchasing behavior is not fully transferable to professional behavior, B2B stores need to make adjustments in order to meet their customers' requirements.

4. how does the approach to conversion rate optimization differ between B2B offers and B2C offers?

B2C offers often operate in mass markets and the acquired traffic is therefore significantly cheaper to buy than that of B2B target groups. This means that websites aimed at B2C target groups tend to have a higher volume of traffic. This also ensures that A/B tests can be used much more extensively.  

Conversion rate optimization is not just about reducing friction points. These are often identified problems that have a clear solution (such as bugs). These do not have to be tested before they can be implemented. It is much more effective to increase user motivation and develop innovative ideas. These ideas are formulated as hypotheses and then validated using A/B testing. The result is then either that the null hypothesis is confirmed or rejected. However, in order to carry out A/B tests, you need a sufficient sample size of users so that the results are valid.  

INFO: Since we want to influence the behavior of USERS, the number of users is considered the sample and not the visitors.  

This means that there must either be enough users OR the demonstrable effect (uplift) must be large enough for a statistically significant result to be achieved. This means for B2B companies with a moderate number of users on the website:

For this case, let's assume by way of example that a change is to be made to the product detail page. Let's assume that a B2B eCommerce website has a monthly traffic of 100,000 users. Of these, 60,000 users visit a product page. The total number of users to be tested is therefore 60,000. 

[Translate to Englisch:] Consultant berechnet die Conversion Rate
  1. Find out the conversion rate of your main A/B test objective. In our example, 6% of users add a product to the shopping cart from a product page. 

  2. Determine the number of users you potentially want to reach through the test. Since we want to test the PDP, we need to find out how many users have visited a product detail page in the last 30d. As described above, this is 60,000 users. 

  3. Find out how high the MDE (Minimal Detectable Effect) is - i.e. the minimum impact on the conversion rate caused by the variant. If the effect is lower than this value, the test result is not statistically significant. 


A “pre-test analysis”, such as this one, is suitable for this:  https://cxl.com/ab-test-calculator/.  

[Translate to Englisch:] Test Page Data

In this case, the number of weekly users is approx. 60,000 divided by 4, i.e. 15,000.

The number of weekly conversions, i.e. the add-to-cart events, is 6% of these 15,000, i.e. 900.

The number of variants remains at 2. With more variants, the MDE is significantly higher, so a much greater uplift must be achieved - or the traffic volume must be significantly higher.  

We leave the confidence interval at 95%. We leave the statistical power (test strength) at 80%. Put simply, the confidence interval describes the risk of detecting a change when in reality none is detectable (false positive or type 1 error). This risk should not exceed 5%. Statistical power is the probability that an effect will be detected if the effect actually exists (false negative or type II error). (Statistical) power is defined as the probability of correctly rejecting a false null hypothesis. 

Statistical test procedure Conversion rate optimization

Akobeng (2016), Acta pediatric

[Translate to Englisch:] Testpage Data Conversion Rate berechnen

We generally assume a test duration of approx. 4 weeks. This has proven to be best practice, as it covers several business cycles, i.e. weeks. This means that the conversion rate of the variant must be at least 8.12% better for the test result to be significant.

The conversion rate would therefore have to increase from 6% to 6.49%. Even if there is no rule of thumb here, this uplift is realistically achievable. An MDE of 20% is much more difficult to achieve. Such large changes, if any, are only seen with CTA elements and less with purchase conversion rates. Here, uplifts often range between >1 and 5% - so significantly more users (sample size) are needed to demonstrate a significant effect. 

5. Where do the insights for conversion rate optimization come from?

[Translate to Englisch:] Conversion Rate Insights Grafik

6. doesn't work - doesn't exist: 3 tips for optimizations with moderate traffic

Tip 1: If there is only moderate traffic, several elements that support the same hypothesis should be changed instead of just one small change. Normally, only one element is tested so that it is later clear that exactly this change led to effect X. If several elements are adapted and tested, it is more likely to generate a large effect and thus achieve valid results. However, it is then not clear exactly which change led to the result. This “trade-off” is accepted here.

Tip 2: Concentrate on elements that are very likely to have a major effect. Changing the color of a button is generally not one of them. An optimized display of product images or even a 3D view, on the other hand, can achieve significant effects. 

Tip 3: You can carry out user tests instead of A/B tests. A/B testing is based on a quantitative approach and on what the majority of your visitors prefer. User testing, on the contrary, provides you with qualitative information that allows you to see whether users find it easy to use your website. The advantage of this method is that you get concrete answers quickly. The disadvantage is that the results are more subjective because they are based on a small sample. 

[Translate to Englisch:] High Five im Team

7. conclusion

Adapting conversion rate optimization to the specific needs and differences between B2B and B2C markets requires a deep understanding of the respective target groups and buying processes. While B2C marketing often targets quick and emotional purchase decisions, B2B requires a more strategic approach that takes into account the longer decision paths and the importance of relationships. The challenge is to optimize the digital presence to meet the complex needs of B2B decision makers while providing a seamless and engaging user experience that B2C customers are accustomed to. In low-traffic environments, A/B testing becomes a challenge. Here, it is recommended to focus on larger and significant changes that promise to have a strong impact on user experience and conversion rate. In addition, companies with limited traffic can use alternative methods such as user tests or qualitative surveys to gain insights into user behavior and develop hypotheses for more extensive changes. 

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[Translate to Englisch:] Florian Fleischer, Digital Consultant, Smart Commerce SE

About the author:

Florian Fleischer is an experienced Digital Consultant at Smart Commerce. He has been working for the company for 2 years and is mainly involved in digital marketing consulting, CRO, SEO, SEA and web analytics. He has experience in the operational management of SEA campaigns and carries out CRO campaigns for clients such as fischerwerke and FÖRCH. 

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