How to Choose What to A/B Test: A Strategic Approach for Digital Marketers

The Testing Paradox: Why Choice Overwhelms Marketers

When you’re new to A/B testing, the possibilities can seem endless. Should you test your headline? Your form fields? Your images? Your call-to-action buttons? With so many options, analysis paralysis often sets in, and many marketers either test random elements or, worse, don’t test at all.

I faced this exact challenge when I started implementing A/B testing for clients. One e-commerce client wanted to test everything from product descriptions to checkout processes simultaneously. We needed a structured approach to focus our efforts where they mattered most.

The solution? A strategic framework that helps you identify high-impact testing opportunities aligned with your specific business goals.

a/b testing, deciding what to test

Follow the Data: Using Analytics to Identify Testing Opportunities

Your analytics platform is a treasure map pointing to valuable testing opportunities. Before brainstorming test ideas, dig into your data to find:

Conversion Bottlenecks

Look for pages with:

  • High traffic but low conversion rates
  • Significant drop-offs in your funnel
  • High exit rates at critical points

For example, we discovered a client’s product page received substantial traffic but had a conversion rate 40% below industry benchmarks. This immediately became a priority testing area.

User Behavior Signals

Heat maps, session recordings, and user testing can reveal:

  • Elements users interact with most frequently
  • Areas where users hesitate or seem confused
  • Content that users ignore entirely

When reviewing heat maps for a SaaS client, we noticed visitors repeatedly clicked on non-clickable features in their dashboard mockup. This led us to test making those elements interactive, resulting in a 28% increase in free trial sign-ups.

Customer Feedback Patterns

Pay attention to:

  • Common questions in customer support tickets
  • Feedback themes in surveys and reviews
  • Direct requests and suggestions from users

A financial services client kept receiving questions about their pricing structure. We tested three different ways of presenting the same pricing information, finding that a comparison table format increased conversion by 17% while reducing pricing-related support tickets by 32%.

Visualization of analytics data highlighting potential A/B testing opportunities

The PIE Prioritization Framework: Potential, Importance, Ease

With a list of potential testing opportunities, the next challenge is deciding where to start. The PIE framework helps you rank your ideas by considering three factors:

  1. Potential: How much improvement can this change create?
    • High traffic pages have greater potential impact
    • Elements directly tied to conversions (like CTAs) typically have higher potential
    • Pages with poor current performance have more room for improvement
  2. Importance: How valuable is this page or element to your business?
    • Revenue-generating pages usually have higher importance
    • Core funnel steps typically outrank secondary pages
    • Primary conversion paths take precedence over minor user journeys
  3. Ease: How difficult will this test be to implement?
    • Simple copy or image changes are typically easiest
    • Complex layout or functionality changes require more resources
    • Tests requiring developer time may need higher potential to justify

Score each potential test on these three dimensions (from 1-10), then calculate the average to prioritize your testing roadmap.

Test Where It Matters: Aligning Tests with Business Objectives

Your testing program should directly support your key business objectives. Map potential tests to specific goals:

Business ObjectivePotential A/B Test Elements
Increase lead generationLead forms, CTAs, landing page design, offer messaging
Improve e-commerce conversionProduct images, pricing display, checkout process, shipping options
Boost email engagementSubject lines, preview text, email layout, CTA placement
Reduce churnOnboarding sequence, dashboard design, feature highlights
Increase average order valueUpsell prompts, bundle offers, recommended products

This alignment ensures your testing program delivers meaningful business impact rather than just interesting data points.

Start with These High-Impact Elements

If you’re still unsure where to begin, these elements typically offer the highest return on testing investment:

  1. Headlines and primary messaging – These create first impressions and communicate your core value proposition
  2. Call-to-action buttons – The direct gateway to conversion
  3. Forms – Often a major source of friction in the conversion process
  4. Pricing presentation – How you display costs significantly impacts perceived value
  5. Hero images/videos – Dominant visual elements that quickly communicate benefits
Before and after examples of A/B tests showing significant improvements

Building Your Testing Roadmap

Rather than approaching A/B testing as a series of disconnected experiments, develop a testing roadmap that:

  • Follows a logical sequence (test major elements before minor ones)
  • Builds on previous learnings
  • Groups related tests when appropriate
  • Balances quick wins with more substantial changes

A well-structured roadmap prevents the common mistake of random testing and helps maintain momentum in your testing program.

Turning Test Selection into Organizational Learning

The best A/B testing programs don’t just optimize individual elements—they systematically build organizational knowledge about customer preferences. Document your testing hypotheses, results, and insights to develop a “testing playbook” specific to your audience.

Over time, patterns will emerge that help you predict what might work in future campaigns, giving you a significant competitive advantage in your market.

Want to learn more about maximizing the impact of your A/B tests? Check out our Ultimate Guide to A/B Testing for a comprehensive overview, or explore How To Analyze A/B Testing Results to ensure you’re drawing the right conclusions from your experiments.

Remember, the goal isn’t to run as many tests as possible—it’s to run the tests that matter most for your business and create meaningful improvements in your marketing performance.