How to build a SaaS CRO strategy

This guide is designed for Tech, SaaS, and AI companies using a free trial, freemium, or book-a-demo model.

It provides a step-by-step system to help you build your own CRO strategy — from setting goals to prioritizing tests and tracking results.

About the examples:‍

Throughout this article, we use a single fictional SaaS company focused on increasing "Book a Demo" conversions.

You can use these examples to guide and assist you, but the goal is to apply the frameworks to build a customized CRO strategy for your company.

Looking for a full video walkthrough? Watch this!

Want your own CRO Strategy Handbook? Access here

Approach

CRO should focus first on long-term improvements — strengthening the website’s Value Proposition, Clarity, Relevance, minimizing Anxiety, and minimizing Distraction — because these factors create compounding business impact over time.

Short-term tactical optimizations like adding Urgency elements (e.g., time-limited offers) or micro-UX tweaks (e.g., button color changes) are important, but they come second. They should only be prioritized once the core foundations are strong.

A real CRO system evolves the website alongside the product, ICP, and brand positioning — not just surface-level tweaks.

Key operating principles:

• Continuous: Testing and improvement should be an ongoing system, not a project.
• Isolate Variables: Single-element tests (e.g., just a headline) provide the clearest insight because you know exactly which change drove performance. However, testing one broader idea (e.g., rewriting a section’s headline and body copy to better target the ICP) can also be valuable. Sometimes it's more practical to change multiple related elements together to validate an idea faster, rather than splitting them into two separate tests. It’s a trade-off between speed and depth of insight — both approaches are valid depending on the situation.
• Marketing Insights: Test outcomes should feed back into improving your overall messaging, positioning, and sales strategies — not just optimize for surface-level UX lifts.

Goals

Goals Waterfall

First, list your business goals.

Then, list your marketing goals and map each one to the relevant business goal it supports.

Next, list your conversion goals and map each one to the relevant marketing goal it supports.

This creates a waterfall structure that ensures every conversion goal directly connects back to your marketing and business goals.

Conversion Goals

Goals Table

Create your Conversion Goals Table using the example below.

First, list your conversion goals.

Then, rank them in order of importance.

Finally, assign goal values.

If you have data, use it to assign goal values accurately (see example calculations below).

If you don’t have data, use your best estimates — and commit to updating the values later as real data becomes available.

The most important part is getting the order and relative importance right.

This keeps everyone aligned on what matters most when prioritizing website changes, tests, and improvements.

It makes sure everyone is working toward the same goals — with a clear hierarchy of importance for every decision.

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Goal Value Assumptions

• Traffic: 30,000 site visits/quarter
• Visitor-to-Demo Rate: 0.5%
• Demo-to-Sale Rate: 15%
• Average Deal Size: $30,000

Goal Value Calculations

Book a Demo

30,000 × 0.5% = 150 demos

150 × 15% = 22.5 sales

22.5 × $30,000 = $660,000

$660,000 ÷ 150 = $4,400 per demo

Build Your Quote

Estimated 35% of quote users book a demo

35% × $4,400 = $1,540

Download Datasheet

Estimated 15% of users go on to book a demo

15% × $4,400 = $660

Watch On Demand Demo

Estimated 5% conversion rate from users who watch ≥50% of the demo

5% × $4,400 = $220

Main Conversions vs Micro Conversions

• Main: The primary conversion target — in this case, Book a Demo.
• Micro-Step: A step that indicates progress toward the main goal (e.g., Build Your Quote).
• Micro-Indicator: A lighter signal of interest in converting in future (e.g., Watch On-Demand Demo).

Which Goal Should You Optimize For?

In conversion experiments, you should always optimize for the goal most directly tied to revenue. In this case, it's "Book a Demo."

Why?

If you optimize for micro-conversions (like datasheet downloads) and see an increase, but that increase causes a drop in higher-value actions (like quote submissions or demo bookings), you could end up with a net loss overall.

Micro-goals are useful to track for context and diagnosis, but they should not be the primary optimization target.

Page Prioritization

Purpose

Prioritize which pages to test first based on Potential, Importance, and Ease — so you maximize ROI from testing efforts.

The PIE Framework

Use PIE to systematically score and prioritize pages:

• Potential – How much improvement is possible?
• Importance – How valuable is the traffic?
• Ease – How simple is implementation?

Each page gets a score from 1–5 for each factor, then summed for a total PIE score.

Process

1. Score each page
2. Rank pages by total PIE score
3. Build a prioritized testing roadmap
4. Start testing the highest-priority page first

Example

Test List & Prioritization

Purpose

The purpose of the Test List is to generate and capture specific optimization ideas for a given page — and to prioritize them based on likely impact.

This creates a structured pipeline of high-value actions that can be systematically executed.

It stops you guessing what to test and ensures a consistent, strategic focus that directly supports business goals.

Creating Hypotheses

Fuelling Test Ideas (Data Insights)

To generate strong test ideas, you first need quantitative and qualitative insights to pull from.

Use the following sources:‍

Quantitative:

• GA4 performance reports
• Funnel drop-off analysis
• Heatmaps (aggregate click behavior)

‍‍Qualitative:‍

• Hotjar session recordings
• On-site surveys
• Customer support feedback
• Sales call insights
• User interviews
  

Look for friction points, motivational gaps, usability barriers, and unclear messaging.

Once you've identified these issues, you can use the LIFT model to dive deeper into the theory of why they could be happening — and to create structured, actionable test ideas that unify theory with data.

Note: You should gather insights before running your first test, but continue gathering insights in parallel once testing begins. This ensures your Test List stays up-to-date — with new tests being added, priorities being updated, and outdated ideas being removed as new information emerges.

Cementing Test Ideas (LIFT Model)

Once you have insights, use the LIFT model to structure and strengthen your test ideas — unifying data with theory.

Every test idea should aim to either increase at least one conversion driver or decrease at least one conversion inhibitor.

Conversion Drivers:

• Value Proposition: Making the existing value proposition clearer, more outcome-driven, and more compelling to the visitor.
• Clarity: Making it clearer who you target, what you offer, and the benefits and outcomes you deliver.
• Relevance: Ensuring the page content directly matches the visitor’s intent — speaking to their role, goals, and context (e.g., Finance-specific messaging for Finance teams).
• Urgency: Speaking to the prospect’s internal urgency (existing motivation to act) or creating external urgency through time-sensitive offers, scarcity, or fear of loss.

Conversion Inhibitors:

• Anxiety: Adding evidence to back up bold claims; reinforcing credibility with social proof.
• Distraction: Removing animations, clutter, or elements that confuse or distract the visitor from the main goal.

Marble Jar Analogy

Think of each visitor as carrying a jar.

• Improve a conversion driver → add marbles
• Worsen a conversion inhibitor → remove marbles
• When the jar overflows → you get a conversion

Hypothesis Structure

Once you have a structured idea, you can create a testable hypothesis using one of the following formats:

• Long Format: Changing [the thing you want to change] into [what you’d change it to] will lift the conversion rate for [your conversion goal].
• Short Format: Changing [X] into [Y] will lift the conversion rate for [Goal]

A good hypothesis should:

• Be testable
• Solve a conversion problem
• Yield insight, even if it loses

Prioritizing Tests

Once you have your list of structured hypotheses, you need to prioritize which tests to run first.

Remember: You should always start with your highest-priority pages first — based on the PIE framework we covered earlier.

After identifying those pages, you generate test ideas specifically for them.

To prioritize individual test ideas, use the adapted ICE framework.

Scoring Formula:
(Impact × 0.5) + (Confidence × 0.3) – (Effort × 0.2)

Definitions:

• Impact: How much of a lift could this realistically create?
• Confidence: How well is the idea supported by insight, research, or past evidence?
• Effort: How complex is the test in terms of copy, design, or development? (Effort reduces the score.)

Once you’ve scored each test idea, rank them from highest to lowest ICE Score.

Start by running the highest-scoring, highest-ROI experiments first.

Example

Managing the Test List

Your Test List is a living system.

Keep adding new ideas from insights and update prioritization as you gather more data.

Tracking & Analytics Setup

Purpose

Tracking enables you to measure conversion goals, diagnose friction points, and fuel new hypotheses based on real user behavior.

Setup

• Set up GA4 goals based on your main and micro-step conversion actions.
• Use GTM to fire event triggers (form submissions, button clicks, video views, scroll depth).
• Sync event naming consistently across GA4 and your A/B testing tool.

Example

A/B Testing

Testing Lifecycle

Each test should follow a clear lifecycle:

• Idea: Identify the opportunity.
• Hypothesis: Write a clear, LIFT-based hypothesis.
• In Test: Run and monitor the experiment.
• Complete: Analyze the outcome objectively.
• Next Step: Implement, iterate, or discard based on result.

You can extend this with labels like “Winner,” “Loser,” or “Inconclusive” if needed.

Primary vs Secondary Metrics

Each A/B test must define:

• Primary Metric: The main conversion action you are optimizing for (e.g., Book a Demo).
• Secondary Metrics: Useful supporting metrics for context (e.g., datasheet downloads, quote submissions).

Only the primary metric determines success.

Secondary metrics help diagnose partial wins or unexpected behaviors.

Ownership & Roles

Clearly define who is responsible for each part of the test:

• Owner: Drives the test, coordinates across teams
• Copy/Design: Prepares the creative/assets/copy for the test
• Dev/Setup: Implements test
• Analyst: Reviews data, interprets results

Sample Size, Duration & Significance

• Only run tests on pages with at least 500+ visitors per variant per month.
• Run the test until you reach ≥95% statistical significance for your primary metric.
• Most modern A/B testing platforms (e.g., VWO, Convert, AB Tasty) automatically calculate statistical significance for you.
• Always check your platform settings to ensure tests are not auto-stopping early based on lower confidence thresholds.
• Most tests take between 2–6 weeks depending on traffic and conversion rates.
• If the test does not reach ≥95% significance after a full business cycle (typically 4–6 weeks), and there is no clear trend toward a winner, mark the test as Inconclusive and plan a follow-up iteration.

Post-Test

After a test concludes, you need to take clear action based on the outcome.

• Winner: Roll out the winning variation live. Monitor performance after launch to confirm consistent results.
• Loser: Keep the control version live. Document what you learned from the losing variant and why it likely underperformed.
• Inconclusive: Plan a follow-up iteration. Either refine the hypothesis, adjust the test scope, or try a different angle based on available insights.

Document Findings

Always document the test outcome, including the winning or losing variant, the measured impact, and any key learnings.

Update your Test List to reflect the result and mark the test as completed.

Feed learnings back into your future test ideas — even a "loser" or "inconclusive" test builds insight for future experiments.

Tools

A/B Testing Tools

• VWO
• Convert
• AB Tasty
• Optimizely

Tracking & Analytics

• Google Tag Manager (GTM)
• Google Analytics 4 (GA4)

Tool Integration

GTM event triggers → GA4 conversion tracking → Experiment platform goal setup

Maintain naming consistency across platforms.

Closing Summary

You now have everything you need to build and run a structured CRO program.

Implement the system outlined above — setting clear goals, prioritizing pages, building a test list, tracking properly, and running structured experiments — and you will be ready to start testing.

Focus on long-term improvements first i.e., strengthening value proposition, clarity, relevance, and trust — not just chasing short-term wins.

Treat CRO as a continuous process: while tests are running, keep gathering insights, generating new test ideas, and updating your prioritization based on learnings.

Done correctly, this system will create compounding improvements across your website, marketing, and sales over time.

Looking for a full video walkthrough? Watch this!

Want your own CRO Strategy Handbook? Access here