5 web experiments for better B2B ecommerce performance

In B2B commerce, your product content carries a lot of weight. Manufacturers and distributors understand this, but figuring out what actually drives clicks, conversions, and orders (or re-orders)? That's where things get tricky.

Your product pages operate around the clock, serving as digital salespeople that deliver information 24/7. Every element—copy, photos, CTAs—needs to connect with each buyer's specific needs. With the extensive catalogs most M&D companies manage, A/B testing becomes the only reliable way to determine which content version delivers better results. The ROI of A/B testing can be significant, but the challenges are real, too.

Why is A/B testing so hard?

A/B testing frustrates teams for predictable reasons:

1. It’s slow: Creating variants, setting them up in your CMS, and gathering enough traffic for reliable results often takes weeks or months.
2. It’s resource heavy: You need copywriters, designers, and analysts just to run a handful of tests. Testing across all SKUs simultaneously isn't realistic, and prioritizing which products to test becomes its own challenge.
3. It’s hard to scale: Even when you have solid test data, manually testing every headline, description, or CTA across thousands of products simply doesn't work.

These constraints push A/B testing to the back burner. Digital teams end up relying on instinct or trying random approaches to see what happens.

But that’s where AI comes in.

A real-world example

Obviously, the proof is in the pudding! That’s why the Optimizely marketing team decided to build actual A/B tests using information from several of Optimizely's top Configured Commerce clients.

Our goal: Create five test concepts specifically designed for ecommerce, marketing, and catalog managers at manufacturing and distribution companies.

The result: Using Optimizely's free Website Analyzer tool and its Opal AI assistant, we built five comprehensive A/B tests in under an hour.

How Opal helps

AI-powered optimization streamlines the entire workflow when it comes to experimentation. Using the Optimizely Opal Web Analyzer, the URLs of three distributor clients were assessed to highlight underperforming elements. Based on the analyses, five common improvement areas emerged that could serve as the foundation for testing.

From there, we defined clear goals within each area to ensure measurable business outcomes. With that framework in place, we easily crafted targeted prompts for Opal. From there, the tool generated new headlines, descriptions, and calls to action—in seconds.

This approach reflects Optimizely’s broader perspective on AI-driven experimentation. For us, it’s not about replacing human judgment. It’s about accelerating the creative process, reducing friction in test development, and ensuring every experiment is tied to concrete ROI.

Without further ado, here are the five A/B test examples developed from our example, including the underlying problem and expected returns.

A/B testing for B2B eCommerce: 5 ways to get started

1. Navigation clarity: Guiding users to products

The problem

Large catalogs often bury products behind dropdowns or generic menus. When buyers can’t quickly drill down to the right category or solution, they abandon the search.

The return

Clear navigation reduces bounce rates and shortens time-to-product, directly lifting conversions. A well-structured menu can increase catalog engagement and improve lead quality.

Image source: Optimizely

The tests

• Visual prominence: Increase font size, contrast, or add background highlights to main navigation items.
• Dropdown cues: Add arrow icons or other signals showing when sub-menus are available.
• Sub-category display: Test multi-column layouts or descriptive text/icons that make categories easier to scan.

2. CTA prioritization: Directing user action

The problem

Pages overloaded with “Learn More” or “View Products” create decision paralysis. B2B buyers hesitate because no path feels clearly right and often abandon the page.

The return

Focused, benefit-driven CTAs increase click-through to revenue-generating actions (quote requests, spec downloads, cart adds). Stronger CTAs mean higher lead conversion and a more qualified pipeline.

The tests

• Descriptive language: Replace generic CTAs with context-specific wording (“Download Product Specs,” “Request Bulk Quote”).
• Visual hierarchy: Make the primary CTA button bigger, bolder, or more distinct in color than secondary actions.
• Quantity & placement: Reduce clutter by limiting CTAs per section, placing the main action where intent is highest.

3. Above-the-fold content: Capturing attention in seconds

The problem

Oversized hero images and vague taglines often dominate the screen. Buyers don’t see product categories, solutions, or value until they scroll. Unfortunately, many don’t have time to hunt for this information.

The return

Getting the right content above the fold boosts engagement instantly. Buyers know they’re in the right place, reducing drop-offs and increasing catalog exploration.

Image source: Optimizely

The tests

• Hero section optimization: Shrink hero images to expose more product or solution content immediately.
• Content prioritization: Surface top product categories or solution snippets on entry.
• Value proposition clarity: Test headlines/sub-heads that clearly state what problems you solve and for whom.

4. Page load speed: Creating a seamless user experience

The problem

Heavy pages and intrusive pop-ups slow down the buyer journey. In B2B commerce, slow load times signal inefficiency and hurt credibility.

The return

Faster load speeds lower abandonment rates, improve SEO rankings, and keep buyers engaged longer, which is critical for long, complex B2B buying cycles.

The tests

• Pop-up timing: Delay banners or make them non-blocking so users can see content first.
• Frequency control: Limit repeat pop-ups for returning visitors.
• Technical optimizations: Compress images, use lazy loading, and streamline server response times.

5. Incentives and personalization: Encouraging engagement and conversion

The problem

Without clear incentives or tailored experiences, new visitors often hesitate to engage or share information.

The return

Incentives reduce friction and accelerate order capture. Personalization keeps buyers on relevant paths, improving both initial conversion and long-term customer value.

Image source: Optimizely

The tests

• First-time incentives: Offer 10% off, free consultations, or complimentary samples on entry.
• Targeted personalization: Display content based on industry, behavior, or referral source.
• Lead magnet placement: Test different wording and placement for catalogs, whitepapers, or spec sheets exchanged for contact details.

Each set of tests focused on solving a problem initially identified by Opal’s Web Analyzer tool. After the tests are created, getting them up and running in Optimizely Web Experimentation is a snap.

Want to try the Opal Web Analyzer tool yourself? It’s free to use!

Remember, design A/B tests based on business goals

AI makes it easier to generate test options, but it’s vital to prioritize your testing efforts based on your most important business goals. Without this focus, you might prove that a certain headline gets more clicks without knowing if it actually impacts revenue.

Not sure which business goals matter most for your B2B commerce experience right now? Here are common goals, tests, and metrics that successful M&D leaders monitor:

Using Opal for your product catalog

As you can see from the examples above, you can create dozens of A/B tests in a fraction of the time with Opal. Additionally, manufacturers and distributors can configure brand rules once, ensuring every variant stays on-message and compliant. From there, deploying at scale doesn't require additional resources.

Instead of running one or two “hero” tests per quarter, M&D marketing teams can continuously experiment across their catalogs, without massive overtime.

Still not sure about A/B testing? See how DS Smith leverages Optimizely Web Experimentation to improve user experience and focus on data-driven decisions.

Wrapping up...

For manufacturers and distributors, product content isn't just marketing copy—it's a critical component of successful B2B commerce experiences and potentially the key to achieving your goals. A/B testing powered by AI tools like Optimizely Opal provides a fast, scalable way to maximize every aspect of your ecommerce platform.

In the end, it's not just about running more tests. It's about building content that aligns with your business goals, making faster decisions, and getting measurable results that drive growth.