Quick Tips on How to Make Conversion Rate Optimisation (CRO) Work for You

Introduction

Conversion Rate Optimisation (CRO) isn't about quick fixes or flashy tricks, it's your full-court press strategy for digital success. CRO is an iterative, continuous process that keeps evolving like a player developing their game. As long as you're committed to optimising your digital consumer journey, you can keep elevating your results to championship levels!

The CRO process breaks down into four key quarters:

1. Evaluate site performance
2. Test hypotheses
3. Analyse the results
4. Iterate and improve

Step 1: Evaluate site performance

With your Analytics tool locked in (whether Google Analytics 4 or another major player), and qualitative tools like Hotjar or Full Story on your squad, the first move is to analyse your current site data. We need to identify where users are getting blocked in their journey. Those friction points that stop them from converting. To break through these defensive walls, we need to understand your users, their behaviour patterns, and what they're really searching for on your site.

1.1 Understand the friction points on the site:

First, you need to identify the pages that represent the "weak links" in your digital lineup. These pages are often open floodgates of lost conversion opportunities, the equivalent of missed free throws in a tight game. The "Behaviour Flow" report in Google Analytics is your scouting report, showing you exactly where to focus your attention.

Behaviour flow visualises the path users follow from one page to another or between events. These reports help you identify your most engaging content, but more importantly, they spotlight problem areas and potential issues (drop-offs) where users are bouncing from your conversion funnel.

1.2 Identify the problem(s) with "weak" pages

Next, we need to drill down into what's disrupting the user journey on these problematic pages. What's throwing off their rhythm? This is where qualitative research comes in clutch:

Heatmaps

Heatmaps deliver a visual breakdown of click distribution on specific pages. Like a shot chart in basketball, they show where users are engaging most. Red zones (hot) highlight areas getting the most clicks and attention, while blue areas (cold) receive few or no clicks, just like tracking a player's hot and cold shooting zones.

Scroll maps

Scroll maps are another form of heatmap that visualize how far visitors scroll down your page. Using the same color principle, they show the most viewed sections (red) versus least viewed (blue). This tells you whether your key content is getting visibility or if users are checking out before seeing your best offers.

Session recordings

Session recording is your game film review. This tool provides granular detail on how users engage with your site by recording their activity. This play-by-play breakdown helps understand precisely what's going wrong on those "weak" pages.

Once you've analysed all available data, it's time to draw up some plays and create hypotheses to test!

Step 2: Test hypotheses

After identifying friction points through your qualitative and quantitative analysis, the best way to validate your hypotheses is through testing – this is your practice court before the big game. A/B testing is the experimental approach carried out on websites or other digital channels (Ads, Mobile apps) that validates hypotheses against a baseline. It shows what's actually working for your audience based on statistical significance, not just gut feelings. While there are other testing methods like Multivariate Testing (MVT), these require more traffic and are more complex to execute.

The major benefits of A/B testing include:

• Deep insights into user behavior with each test
• Eliminating the risk factor and subjectivity from decision-making by building a culture of experimentation
• Focusing on what delivers flawless results for consumers through continuous learning

This phase requires a diverse skill set, including web development expertise to build and run experiments effectively. Several tools dominate the market for these tests: AB Tasty, Optimizely, and VWO (paid options). Google Optimize also offers an accessible solution for testing hypotheses, though with more limited features.

Step 3: Analyse the results

Once your tests reach statistical significance, like hitting that sample size sweet spot, there are three potential outcomes:

• The hypothesis is validated: Just like when a play works perfectly in a game, it's time to implement the changes you tested. However, consider every aspect of implementation: development costs, technical constraints, and the resources required for the change.
• The hypothesis is not validated: The test didn't deliver the expected improvements – your play didn't work. In this case, learn what went wrong and understand the impact of the failed test. If necessary, adjust your strategy and retest based on what you have learned.
• Neutral result: The hypothesis neither improved nor harmed performance. Similar to a play that doesn't create an advantage, study the results, learn from them, and reiterate if necessary.

Step 4: Iterate

If your test delivered results worth celebrating, shift your focus to identifying new optimisation opportunities to explore. This must become part of your ongoing process, like how the best players always work on their game.

CRO is a data-driven approach that leaves no room for just "feeling it" or guessing. The fundamental principle is making decisions based on solid data, not hunches. By integrating CRO into your digital strategy, you'll boost ROI and lower acquisition costs. However, CRO demands discipline and perseverance, the key to unlocking championship-level success!